Cardiac arrest in the emergency department (ED) is a rare event. Prior studies have used dedicated cardiac arrest registries, but few have leveraged "big data" from electronic healthcare vendors to analyze trends in the care of patients excluded from registries.

This was a retrospective cohort study of adult patients in the ED with cardiac arrest from Epic Cosmos, a database with 277 million patients. Patients with ICD-10 codes corresponding to cardiac arrest in the ED were included. Outcomes included the incidence of cardiac arrest, mortality, code length, and extracorporeal membrane oxygenation (ECMO). Data were compared using odds ratio with 95 % confidence intervals (CI).

Among 196,834,283 ED visits from 1/1/2016 to 12/31/2023, there were 429,917 (0.22 %) cardiac arrests and 197,233 (45.88 %) patients who died in the ED. The incidence of cardiac arrest (0.26 %) and death in the ED (55.70 %) peaked in 2020. Cardiac arrest was more common in male and older patients, between 00:00-05:59, on weekends, and in the South (p < 0.001). The median code length was 10-20 min. Only 0.29 % of cardiac arrest patients received ECMO. Compared to 2016, the odds of a code length > 90 min and ECMO in 2023 were 1.43 (95 % CI 1.32-1.54) and 3.58 (95 % CI 2.41-5.31) times greater, respectively.

Although cardiac arrest in the ED is a rare event, almost half of patients die in the ED. The use of ECMO after cardiac arrest is increasing but remains low. Further research is needed to mitigate these differences in care.

In 2022, the U.S. Centers for Disease Control and Prevention reported increases in antimicrobial resistance (AMR) across U.S. hospitals during the COVID-19 pandemic. The key drivers and lasting effects of this phenomenon remain unexplored.

To determine the incidence of AMR infections in U.S. hospitals during and beyond the pandemic and identify factors contributing to AMR.

Retrospective cohort study.

243 U.S. hospitals.

Adult hospitalizations, excluding inpatient transfers.

Prepandemic (January 2018 to December 2019), peak pandemic (March 2020 to February 2022), and waning pandemic (March to December 2022).

Incidence of methicillin-resistant Staphylococcus aureus; vancomycin-resistant Enterococci; extended-spectrum cephalosporin-resistant Enterobacterales; and carbapenem-resistant Enterobacterales, Acinetobacter baumannii, and Pseudomonas aeruginosa infections was evaluated among 120 continuously reporting hospitals. Infections detected more than 3 days after admission were classified as hospital-onset. Antibiotic exposure was estimated using a duration- and spectrum-weighted index. A competing risks analysis was done in 243 hospitals to identify risk factors for resistance.

During the peak of the COVID-19 pandemic, AMR infections increased from 182 to 193 per 10 000 hospitalizations (6.5% [95% CI, 5.1% to 8.0%]). Hospital-onset AMR infections increased from 28.9 to 38.0 per 10 000 hospitalizations (31.5% [CI, 27.3% to 35.8%]). Factors associated with hospital-onset AMR included illness severity (intensive care unit admission, mechanical ventilation, vasopressors, COVID-19 diagnosis), comorbidities (Elixhauser Comorbidity Index), and prior exposure to antibiotics, but not hospital factors. Prevalence of AMR returned to prepandemic levels as the pandemic waned (182 to 182 per 10 000 hospitalizations; 0.4% [CI, -1.4% to 2.2%]), however, hospital-onset AMR remained above baseline (28.9 to 32.3 per 10 000 hospitalizations; 11.6% [CI, 6.8% to 16.7%]).

Residual confounding; unknown appropriateness of antibiotics.

Sustained increases in hospital-onset AMR infections occurred in U.S. hospitals during the pandemic and were strongly associated with antibiotic exposure.

National Institutes of Health Clinical Center; National Heart, Lung, and Blood Institute; and National Institute of Allergy and Infectious Diseases Intramural Research Programs.

Nationwide data are unavailable regarding changes in intensive care unit (ICU) outcomes and use of life support over the past 10 years, limiting understanding of practice changes.

To portray the epidemiology of US critical care before, during, and after the COVID-19 pandemic.

Retrospective cohort study of adult patients admitted to an ICU for any reason, using data from the 54 US health systems continuously contributing to the Epic Cosmos database from 2014-2023.

Patient demographics, COVID-19 status, and pandemic era.

In-hospital mortality unadjusted and adjusted for patient demographics, comorbidities, and illness severity; ICU length of stay; and receipt of life-support interventions, including mechanical ventilation and vasopressor medications.

Of 3 453 687 admissions including ICU care, median age was 65 (IQR, 53-75) years. Patients were 55.3% male; 17.3% Black and 6.1% Hispanic or Latino; and overall in-hospital mortality was 10.9%. The adjusted in-hospital mortality was elevated during the pandemic in COVID-negative (adjusted odds ratio [aOR], 1.3 [95% CI, 1.2-1.3]) and COVID-positive (aOR, 4.3 [95% CI, 3.8-4.8]) patients and returned to baseline by mid-2022. The median ICU length of stay was 2.1 (IQR, 1.1-4.2) days, with increases during the pandemic among COVID-positive patients (difference for COVID-positive vs COVID-negative patients, 2.0 days [95% CI, 2.0-2.1]). Rates of invasive mechanical ventilation were 23.2% (95% CI, 23.1%-23.2%) before the pandemic, increased to 25.8% (95% CI, 25.8%-25.9%) during the pandemic, and declined below prepandemic baseline thereafter (22.0% [95% CI, 21.9%-22.2%]). The use of vasopressors increased from 7.2% to 21.6% of ICU stays.

Pandemic-era increases in length of stay and adjusted in-hospital mortality among US ICU patients returned to recent historical baselines. Fewer patients are now receiving mechanical ventilation than prior to the pandemic, while more patients are administered vasopressor medications.

Urinary tract cancers (UTCs), including bladder cancer, remain a significant public health challenge, particularly among individuals aged 75 and older. Despite declining bladder cancer-specific mortality rates between 2015 and 2020, the broader trends in UTC mortality and associated demographic disparities remain underexplored.

We analyzed mortality data from 1999 to 2022 using the CDC WONDER database. UTC deaths were identified using ICD- 10 codes C64 to C68. Age-adjusted mortality rates (AAMRs) per 100,000 population were calculated, stratified by sex, race/ethnicity, and census regions. Joinpoint regression identified annual percent changes (APCs) to assess temporal trends.

From 1999 to 2022, 477,157 UTC deaths were recorded, 66% of which occurred among individuals aged 75 and older. The AAMR increased from 97.1 in 1999 to 103.5 in 2022, with a rise between 1999 and 2007 (APC: 0.63%), a decline from 2007 to 2019 (APC: - 0.33%), and a resurgence from 2019 to 2022 (APC: 2.42%). Older males exhibited higher AAMRs than females (178.7 vs. 53.6 in 2022), and Whites had the highest AAMR (108.5) among racial groups. The Western region recorded the highest AAMR (84.3) during the study period.

The resurgence in UTC mortality post- 2019 highlights emerging challenges, particularly among older males, Whites, and residents of the Western region. Targeted interventions, including improved screening and equitable healthcare access, are essential to mitigate these disparities and improve outcomes.

To examine differences between patients treated in integrated systems of care and patients treated outside of such systems during the COVID pandemic in the use of primary and preventive care, emergency services, inpatient services, and mortality.

Data are used from all enrollees in traditional Medicare aged 66 and older.

Difference-in-differences estimates are calculated from the pre-COVID time period (January 2019-February 2020) to the initial COVID time period (March-May 2020) and the ongoing COVID time period (June 2020-December 2021) for patients treated by primary care physicians working in a health system versus not, and by the type of health system.

Medicare claims data are used to measure monthly claims for office and telehealth visits, mammography, colon cancer screening, inpatient/emergency department visits, and death. Patients are assigned to primary care physicians using common algorithms. Physician membership in a health system is determined from a previously generated dataset.

Relative to the pre-COVID period, patients treated in health systems fared no better in maintaining primary care access than patients treated outside of such systems (DID estimate on receipt of office care or telehealth visit = -4%; p < 0.001). In the ongoing COVID time period, non-COVID mortality rose by less in health systems (DID estimate = -0.9%; p < 0.001) and health system patients experienced a greater decline in the use of the emergency department (DID estimate = -1.2%; p < 0.001) and emergency/urgent inpatient care for non-COVID conditions less (DID estimate = -0.7%; p < 0.001).

Health systems were associated with reduced occurrence of death and adverse medical events, although the effect magnitudes are modest. This reduction appears unrelated to the use of primary care and should be considered in the context of our evolving understanding of the advantages and disadvantages of health systems.

Pulmonary alveolar proteinosis (PAP) is a rare lung syndrome characterized by the accumulation of surfactant in the alveoli. Using a longitudinal claims database, we compared measures of clinical and economic burden between a sample of diagnosed PAP patients and non-PAP matched controls.

PAP patients were identified leveraging IPM.ai's longitudinal U.S. claims database spanning January 1, 2009, through May 1, 2022. PAP patients were selected based on the presence of ICD-10: J84.01 or ICD-9: 516.0 in their claims history and were indexed for observation. An age, gender, and geographically matched control cohort was created (ratio of 1:4) for comparison. A third cohort, consisting of likely undiagnosed PAP patients, was identified using a machine learning model. The PAP and control cohorts were tracked longitudinally, depending on individual index dates, from January 1, 2018, through May 1, 2023. Inclusion criteria required evidence of continual claims activity 12 months prior to and after the index date, which reduced the total number of diagnosed PAP and control patients in the analysis. Demographics, comorbidities, procedures, medication use, annual healthcare resource utilization (HCRU), and costs were calculated for eligible PAP and control patients and were compared 12 months prior to, and 12 months after each patient's index date.

After inclusion criteria were applied, 2312 confirmed PAP patients and 9247 matched controls were included in the analysis. Compared with matched controls, PAP patients had significantly higher rates of diagnosed conditions at baseline as defined by the Charlson Comorbidity Index (CCI). During the follow-up period, PAP patients had higher rates of diagnosed conditions, procedures, medication use, and cost-of-care compared with controls. PAP patients also had higher rates of emergency room visits (35% vs. 14%; P < 0.001), outpatient visits (87% vs. 56%; P < 0.001), inpatient visits (20% vs. 5%; P < 0.001) and had longer lengths of stay for inpatient hospitalizations (2.8 days vs. 0.56 days; P < 0.001), respectively.

This study represents the largest dataset of PAP patients and matched controls to be analyzed to date. Findings indicate that PAP patients have higher rates of diagnosed conditions, procedures, medication use, HCRU, and costs compared with non-PAP patients.

Optimizing outcomes of hospitalized patients anchors on standardizing processes in medical management, interventions to reduce the risk of decompensation, and prompt intervention when a patient decompensates.

A quality improvement initiative (optimized sepsis and respiratory compromise management, reducing health care-associated infection and medication risk, swift management of the deteriorating patient, feedback on performance, and accountability) was implemented in a multistate health system. The primary outcome was risk-adjusted in-hospital mortality. Secondary outcomes included health care-associated infections, patient-days with hypoglycemic and severe hyperglycemic episodes, and hospital onset (HO) acute kidney injury (AKI).

A total of 2,015,408 patients were admitted to 88 hospitals over the 36-month study period. Overall mortality improved from the baseline observed/expected (O/E) of 0.97 in 2021 to 0.74 in 2023 (-23.4%; 4,186 fewer deaths, p < 0.001). Controlling for baseline (2021) mortality O/E ratios, the mean mortality O/E ratio for 2023 was 0.74 for system and 0.84 for peers, representing a difference of -0.10 (p < 0.001, 95% confidence interval [CI] 0.12 - -0.07], with 1,807 fewer deaths). The standardized infection ratio declined for central line-associated blood stream infections by 24.8% (0.58; 88 fewer events), catheter-associated urinary tract infections by 30.6% (0.44; 98 fewer events), HO methicillin-resistant Staphylococcus aureus bacteremia by 29.0% (0.72; 67 fewer events), and HO Clostridioides difficile infection by 35.1% (0.36; 311 fewer events) in 2023 compared to 2021. HO AKI episodes dropped by 6.2% (8.6%; 1,725 fewer events), and patient-days with hypoglycemia and severe hyperglycemia decreased by 5.8% (4.0%; 4,840 fewer events) and 22.8% (5.2%; 30,065 fewer events), respectively.

This systemwide initiative focusing on standardizing processes, feedback on performance, and accountability was associated with sustainable improvements in mortality and a reduction in infectious and safety events.

Despite unintended consequences and ongoing need for revision, the 2018 adult heart transplant policy revision continues to have a favorable impact as evidenced by increased transplant rates, decreased waitlist mortality, and more rapid transplant in higher acuity patients. In 2023, the total number of heart transplants in the United States increased 101.1% since 2012, reaching a record 4,599, of which 4,092 were performed in adults. Between 2022 and 2023 alone, 424 more adult heart transplants were performed, the largest annual increase this decade. Concurrently, the prevalence of heart donors after circulatory death increased to 14.0% in 2023. Candidates listed at adult statuses 1 and 2 underwent transplant more quickly (2,225.8 and 1,088.1 transplants per 100 patient-years, respectively). In 2023, adult waitlist mortality reached a low: 8.5 deaths per 100 patient-years. Multiorgan transplants (heart-liver and heart-kidney) in adults continue to increase, achieving comparable survival to that of heart transplant alone. Adults with congenital heart disease had the lowest pretransplant mortality of all diagnoses but also the lowest posttransplant survival, 76.1% at 5 years, emphasizing the need for consensus on best practices. In pediatric heart transplant, heart transplants increased 36.3% and new listings increased 34.0%, but the transplant rate decreased 14.9% resulting in increased waiting times. High-urgency listings increased, with 83.6% of heart transplants performed for status 1A. Pediatric waitlist mortality has declined 53.4% since 2012, but remains substantial: 11.7 deaths per 100 patient-years. In 2023, 5-year posttransplant survival was 80.3% in adult recipients and 84.4% in pediatric recipients.

Vertebral fractures are associated with enduring back pain, diminished quality of life, as well as increased morbidity and mortality. Existing epidemiological data for cervical and thoracic vertebral fractures are limited by insufficiently powered studies and a failure to evaluate the mechanism of injury.

What are the temporal trends in incidence, patient characteristics, and injury mechanisms of cervical and thoracic vertebral fractures in the United States from 2003 to 2021?

The United States National Electronic Injury Surveillance System-All Injury Program (NEISS-AIP) database collects data on all nonfatal injuries treated in US hospital emergency departments and is well suited to capture epidemiological trends in vertebral fractures. As such, the NEISS-AIP was queried from 2003 to 2021 for cervical and thoracic fractures. The initial search by upper trunk fractures yielded 156,669 injuries; 6% (9900) of injuries, with a weighted frequency of 638,999 patients, met the inclusion criteria. The mean age was 62 ± 25 years and 52% (334,746 of 638,999) of patients were females. Descriptive statistics were obtained. Segmented regression analysis, accounting for the year before or after 2019 when the NEISS sampling methodology was changed, was performed to assess yearly injury trends. Multivariable logistic regression models with age and sex as covariates were performed to predict injury location, mechanism, and disposition.

The incidence of cervical and thoracic fractures increased from 2.0 (95% CI 1.4 to 2.7) and 3.6 (95% CI 2.4 to 4.7) per 10,000 person-years in 2003 to 14.5 (95% CI 10.9 to 18.2) and 19.9 (95% CI 14.5 to 25.3) in 2021, respectively. Incidence rates of cervical and thoracic fractures increased for all age groups from 2003 to 2021, with peak incidence and the highest rate of change in individuals 80 years or older. Most injuries occurred at home (median 69%), which were more likely to impact older individuals (median [range] age 75 [2 to 106] years) and females (median 61% of home injuries); injuries at recreation/sports facilities impacted younger individuals (median 32 [3 to 96] years) and male patients (median 76% of sports facility injuries). Falls were the most common injury mechanism across all years, with females more likely to be impacted than males. The proportion of admissions increased from 33% in 2003 to 50% in 2021, while the proportion of treated and released patients decreased from 53% to 35% in the same period.

This epidemiological study identified a disproportionate increase in cervical and thoracic fracture incidence rates in patients older than 50 years from 2003 to 2021. Furthermore, high hospital admission rates were also noted resulting from these fractures. These findings indicate that current osteoporosis screening guidelines may be insufficient to capture the true population at risk of osteoporotic fractures, and they highlight the need to initiate screening at an earlier age.

Level III, prognostic study.

Increasing nosocomial infections during the COVID-19 pandemic have been reported. However, data describing peripheral venous catheter associated bloodstream infections (PVC-BSI) are limited.

To describe the epidemiology and risk factors for PVC-BSI during the COVID-19 pandemic.

We conducted retrospective cohort study of prospectively collected PVC-BSI data in a 2100 bed hospital network in Switzerland. Adult patients with a PVC inserted between January 1, 2020 and December 31, 2021 were included. Risk factors for PVC-BSI were identified through descriptive analysis of patient and catheter characteristics, and univariable marginal Cox models.

206,804 PVCs and 37 PVC-BSI were analysed. Most PVC-BSI were attributed to catheters inserted in the Emergency department (76%) or surgical wards (22%). PVC-BSI increased in 2021 compared to 2020 (hazard ratio 2021 vs. 2020 = 2.73; 95% confidence interval 1.19-6.29), with a numerically higher rate of Staphylococcus aureus (1/10, 10%, vs. 5/27, 19%) and polymicrobial infection (0/10, 0% vs. 4/27, 15%). PVC insertions, patient characteristics, and catheter characteristics remained similar across the study period. PVC-BSI risk was associated with admission to the intensive care unit (ICU), and use of wide gauge catheter ( < = 16G).

Increased PVC-BSI during the COVID-19 pandemic was not explained by catheter or patient factors alone, and may result from system-wide changes. PVC-BSI events are primarily attributed to acute care settings, including the emergency department, surgical wards, and the ICU.

Geriatric trauma patients experience disproportionate adverse outcomes compared to younger patients with similar injuries and represent an important target for quality improvement. Our institution created a Geriatric Trauma Intensive Care Unit (ICU) Admission Guideline to identify high-risk patients and elevate their initial level of care. The goal of implementation was reducing unplanned ICU admissions (UIAs), a recognized surrogate marker for adverse outcomes.

The Geriatric Trauma ICU Admission Guideline was implemented on July 1, 2020, at a large academic level-1 trauma center. Using trauma registry data, we retrospectively analyzed geriatric patients who met the criteria for ICU admission 2 y preimplementation and postimplementation. The main outcome was UIAs in the target geriatric population. Secondary outcomes included hospital length of stay, ICU length of stay, ventilator days, mortality, and 30-d readmissions. Characteristics between groups were compared with t-test, Mann-Whitney U test, or chi-square test. Risk-adjusted logistic and negative binomial regressions were used for the categorical and continuous outcomes, respectively.

A total of 1075 patients were identified with 476 in the preimplementation and 599 in the postimplementation group. The groups were similar across most demographic and physiologic characteristics, with the exception of a higher incidence of hypertension in the preimplementation group (77.7% versus 71.6%, P = 0.02) and COVID in the postimplementation group (3.8% versus 0.4%, P < 0.001). While mechanism of injury was similar, there was a higher incidence of traumatic brain injury in the preimplementation group (35.1% versus 26.2%, P = 0.002). In the postimplementation group, there was a higher incidence ≥3 rib fractures (68% versus 61.3%, P = 0.02) and an expected increase in initial ICU level of care (69.5% versus 37.1%, P < 0.001). The odds of a UIA after guideline implementation were reduced by half (adjusted odds ratio 0.52, 95% confidence interval 0.3-0.92). There was not a significant difference in the secondary outcomes of mortality, 30-d readmission, hospital-free days, ICU-free days, or ventilator-free days.

Implementation of the Geriatric Trauma ICU Admission Guideline was associated with a reduction in UIAs by half in the target population. There was not a significant change in hospital-free days, ICU-free days, ventilator-free days, mortality, 30-d readmission, or venous thromboembolism. Further research is needed to better refine admission guidelines, examine the association of preventative admission on delirium, and determination of criteria that would allow safe, earlier downgrade.

COVID-19 pandemic surges strained hospitals globally. We performed a systematic review to examine measures of pandemic caseload surge and its impact on mortality of hospitalized patients.

PubMed, Embase, and Web of Science.

English-language studies published between December 1, 2019, and November 22, 2023, which reported the association between pandemic "surge"-related measures and mortality in hospitalized patients.

Three authors independently screened studies, extracted data, and assessed individual study risk of bias. We assessed measures of surge qualitatively across included studies. Given multidomain heterogeneity, we semiquantitatively aggregated surge-mortality associations.

Of 17,831 citations, we included 39 studies, 17 of which specifically described surge effects in ICU settings. The majority of studies were from high-income countries ( n = 35 studies) and included patients with COVID-19 ( n = 31). There were 37 different surge metrics which were mapped into four broad themes, incorporating caseloads either directly as unadjusted counts ( n = 11), nested in occupancy ( n = 14), including additional factors (e.g., resource needs, speed of occupancy; n = 10), or using indirect proxies (e.g., altered staffing ratios, alternative care settings; n = 4). Notwithstanding metric heterogeneity, 32 of 39 studies (82%) reported detrimental adjusted odds/hazard ratio for caseload surge-mortality outcomes, reporting point estimates of up to four-fold increased risk of mortality. This signal persisted among study subgroups categorized by publication year, patient types, clinical settings, and country income status.

Pandemic caseload surge was associated with lower survival across most studies regardless of jurisdiction, timing, and population. Markedly variable surge strain measures precluded meta-analysis and findings have uncertain generalizability to lower-middle-income countries (LMICs). These findings underscore the need for establishing a consensus surge metric that is sensitive to capturing harms in everyday fluctuations and future pandemics and is scalable to LMICs.

Prior research on racial/ethnic disparities in COVID-19 mortality has often not considered to what extent they reflect COVID-19-specific factors, versus preexisting health differences. This study examines how racial/ethnic disparities in COVID-19 mortality vary with age, sex, and time period over April-December 2020 in the United States, using mortality from other natural causes as a proxy for underlying health. We study a novel measure, the COVID excess mortality percentage (CEMP), defined as the COVID-19 mortality rate divided by the non-COVID natural mortality rate, converted to a percentage, where the CEMP denominator controls (albeit imperfectly) for differences in population health. Disparities measured using CEMP deviate substantially from those in prior research. In particular, we find very high disparities (up to 12:1) in CEMP rates for Hispanics versus Whites, particularly for nonelderly men. Asians also have elevated CEMP rates versus Whites, which were obscured in prior work by lower overall Asian mortality. Native Americans and Blacks have significant disparities compared with White populations, but CEMP ratios to Whites are lower than ratios reported in other work. This is because the higher COVID-19 mortality for Blacks and Native Americans comes partly from higher general mortality risk and partly from COVID-specific risk.

Sepsis occurs in 12-27% of patients with haematological malignancy within a year of diagnosis. Sepsis mortality has improved in non-cancer patients in the last two decades, but longitudinal trends in patients with haematological malignancy are not well characterised. We aimed to compare outcomes, including temporal changes, in patients with and without a haematological malignancy admitted to ICU with a primary diagnosis of sepsis in Australia and New Zealand over the past two decades.

We performed a retrospective cohort study of 282,627 patients with a primary intensive care unit (ICU) admission diagnosis of sepsis including 17,313 patients with haematological malignancy, admitted to 216 intensive care units (ICUs) in Australia or New Zealand between January 2000 and December 2022. Annual crude and adjusted in-hospital mortality were reported. Risk factors for in-hospital mortality were determined using a mixed methods logistic regression model and were used to calculate annual changes in mortality.

In-hospital sepsis mortality decreased in patients with haematological malignancy, from 55.6% (95% CI 46.5-64.6%) in 2000 to 23.1% (95% CI 20.8-25.5%) in 2021. In patients without haematological malignancy mortality decreased from 33.1% (95% CI 31.3-35.1%) to 14.4% (95% CI 13.8-14.8%). This decrease remained significant after adjusting for mortality predictors including age, SOFA score and comorbidities, as estimated by adjusted annual odds of in-hospital death. The reduction in odds of death was of greater magnitude in patients with haematological malignancy than those without (OR 0.954, 95% CI 0.947-0.961 vs. OR 0.968, 95% CI 0.966-0.971, p < 0.001). However, absolute risk of in-hospital mortality remained higher in patients with haematological malignancy. Older age, higher SOFA score, presence of comorbidities, and mechanical ventilation were associated with increased mortality. Leukopenia (white cell count < 1.0 × 109 cells/L) was not associated with increased mortality in patients with haematological malignancy (p = 0.60).

Sepsis mortality has improved in patients with haematological malignancy admitted to ICU. However, mortality remains higher in patients with haematological malignancy than those without.

Little is known as to whether the effects of physician sex on patients' clinical outcomes vary by patient sex.

To examine whether the association between physician sex and hospital outcomes varied between female and male patients hospitalized with medical conditions.

Retrospective observational study.

Medicare claims data.

20% random sample of Medicare fee-for-service beneficiaries hospitalized with medical conditions during 2016 to 2019 and treated by hospitalists.

The primary outcomes were patients' 30-day mortality and readmission rates, adjusted for patient and physician characteristics and hospital-level averages of exposures (effectively comparing physicians within the same hospital).

Of 458 108 female and 318 819 male patients, 142 465 (31.1%) and 97 500 (30.6%) were treated by female physicians, respectively. Both female and male patients had a lower patient mortality when treated by female physicians; however, the benefit of receiving care from female physicians was larger for female patients than for male patients (difference-in-differences, -0.16 percentage points [pp] [95% CI, -0.42 to 0.10 pp]). For female patients, the difference between female and male physicians was large and clinically meaningful (adjusted mortality rates, 8.15% vs. 8.38%; average marginal effect [AME], -0.24 pp [CI, -0.41 to -0.07 pp]). For male patients, an important difference between female and male physicians could be ruled out (10.15% vs. 10.23%; AME, -0.08 pp [CI, -0.29 to 0.14 pp]). The pattern was similar for patients' readmission rates.

The findings may not be generalizable to younger populations.

The findings indicate that patients have lower mortality and readmission rates when treated by female physicians, and the benefit of receiving treatments from female physicians is larger for female patients than for male patients.

Gregory Annenberg Weingarten, GRoW @ Annenberg.

Unprecedented increases in hospital occupancy rates during COVID-19 surges in 2020 caused concern over hospital care quality for patients without COVID-19.

To examine changes in hospital nonsurgical care quality for patients without COVID-19 during periods of high and low COVID-19 admissions.

This cross-sectional study used data from the 2019 and 2020 Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project State Inpatient Databases. Data were obtained for all nonfederal, acute care hospitals in 36 states with admissions in 2019 and 2020, and patients without a diagnosis of COVID-19 or pneumonia who were at risk for selected quality indicators were included. The data analysis was performed between January 1, 2023, and March 15, 2024.

Each hospital and week in 2020 was categorized based on the number of COVID-19 admissions per 100 beds: less than 1.0, 1.0 to 4.9, 5.0 to 9.9, 10.0 to 14.9, and 15.0 or greater.

The main outcomes were rates of adverse outcomes for selected quality indicators, including pressure ulcers and in-hospital mortality for acute myocardial infarction, heart failure, acute stroke, gastrointestinal hemorrhage, hip fracture, and percutaneous coronary intervention. Changes in 2020 compared with 2019 were calculated for each level of the weekly COVID-19 admission rate, adjusting for case-mix and hospital-month fixed effects. Changes during weeks with high COVID-19 admissions (≥15 per 100 beds) were compared with changes during weeks with low COVID-19 admissions (<1 per 100 beds).

The analysis included 19 111 629 discharges (50.3% female; mean [SD] age, 63.0 [18.0] years) from 3283 hospitals in 36 states. In weeks 18 to 48 of 2020, 35 851 hospital-weeks (36.7%) had low COVID-19 admission rates, and 8094 (8.3%) had high rates. Quality indicators for patients without COVID-19 significantly worsened in 2020 during weeks with high vs low COVID-19 admissions. Pressure ulcer rates increased by 0.09 per 1000 admissions (95% CI, 0.01-0.17 per 1000 admissions; relative change, 24.3%), heart failure mortality increased by 0.40 per 100 admissions (95% CI, 0.18-0.63 per 100 admissions; relative change, 21.1%), hip fracture mortality increased by 0.40 per 100 admissions (95% CI, 0.04-0.77 per 100 admissions; relative change, 29.4%), and a weighted mean of mortality for the selected indicators increased by 0.30 per 100 admissions (95% CI, 0.14-0.45 per 100 admissions; relative change, 10.6%).

In this cross-sectional study, COVID-19 surges were associated with declines in hospital quality, highlighting the importance of identifying and implementing strategies to maintain care quality during periods of high hospital use.

This study aimed to assess the impact of the pandemic on hospitalization and mortality rates among patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). We conducted a systematic search across three medical databases for studies comparing the AECOPD mortality and hospitalization rates during the COVID-19 pandemic with those before the pandemic, up until December 2023. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Meta-analysis of Observational Studies in Epidemiology guidelines, we performed a meta-analysis with a random-effects model to pool odds ratios (ORs), 95% confidence intervals (CIs), and heterogeneity (I2). From 4689 records, 21 studies met our inclusion criteria. Our analysis revealed a significant increase in in-hospital mortality during the pandemic (pooled OR = 1.27, 95% CI = 1.17-1.39, I2 = 50%). Subgroup analysis highlighted a more pronounced mortality risk in single-center studies and smaller populations. Conversely, hospitalization rates for AECOPD significantly declined during the pandemic (pooled OR = 0.39, 95% CI = 0.18-0.85, I2 = 99%). The study demonstrates that during the COVID-19 pandemic, there was a substantial decrease in hospital admissions for AECOPD and an increase in in-hospital deaths. This shows that better healthcare plans and pandemic preparedness are needed to help people with chronic conditions.

COVID-19 pandemic-related disruptions to the health care system may have resulted in increased mortality for patients with time-sensitive conditions.

To examine whether in-hospital mortality in hospitalizations not related to COVID-19 (non-COVID-19 stays) for time-sensitive conditions changed during the pandemic and how it varied by hospital urban vs rural location.

This cohort study was an interrupted time-series analysis to assess in-hospital mortality during the COVID-19 pandemic (March 8, 2020, to December 31, 2021) compared with the prepandemic period (January 1, 2017, to March 7, 2020) overall, by month, and by community COVID-19 transmission level for adult discharges from 3813 US hospitals in the State Inpatient Databases for the Healthcare Cost and Utilization Project.

The COVID-19 pandemic.

The main outcome measure was in-hospital mortality among non-COVID-19 stays for 6 time-sensitive medical conditions: acute myocardial infarction, hip fracture, gastrointestinal hemorrhage, pneumonia, sepsis, and stroke. Entropy weights were used to align patient characteristics in the 2 time periods by age, sex, and comorbidities.

There were 18 601 925 hospitalizations; 50.3% of patients were male, 38.5% were aged 18 to 64 years, 45.0% were aged 65 to 84 years, and 16.4% were 85 years or older for the selected time-sensitive medical conditions from 2017 through 2021. The odds of in-hospital mortality for sepsis increased 27% from the prepandemic to the pandemic periods at urban hospitals (odds ratio [OR], 1.27; 95% CI, 1.25-1.29) and 35% at rural hospitals (OR, 1.35; 95% CI, 1.30-1.40). In-hospital mortality for pneumonia had similar increases at urban (OR, 1.48; 95% CI, 1.42-1.54) and rural (OR, 1.46; 95% CI, 1.36-1.57) hospitals. Increases in mortality for these 2 conditions showed a dose-response association with the community COVID-19 level (low vs high COVID-19 burden) for both rural (sepsis: 22% vs 54%; pneumonia: 30% vs 66%) and urban (sepsis: 16% vs 28%; pneumonia: 34% vs 61%) hospitals. The odds of mortality for acute myocardial infarction increased 9% (OR, 1.09; 95% CI, 1.06-1.12) at urban hospitals and was responsive to the community COVID-19 level. There were significant increases in mortality for hip fracture at rural hospitals (OR, 1.32; 95% CI, 1.14-1.53) and for gastrointestinal hemorrhage at urban hospitals (OR, 1.15; 95% CI, 1.09-1.21). No significant change was found in mortality for stroke overall.

In this cohort study, in-hospital mortality for time-sensitive conditions increased during the COVID-19 pandemic. Mobilizing strategies tailored to the different needs of urban and rural hospitals may help reduce the likelihood of excess deaths during future public health crises.

Health care avoidance in the COVID-19 pandemic has been widely reported. Yet few studies have investigated the dynamics of hospital avoidance behavior during pandemic waves and inferred its impact on excess non-COVID-19 deaths.

This study aimed to measure the impact of hospital avoidance on excess non-COVID-19 deaths in public hospitals in Hong Kong.

This was a retrospective cohort study involving 11,966,786 patients examined between January 1, 2016, and December 31, 2021, in Hong Kong. All data were linked to service, treatment, and outcomes. To estimate excess mortality, the 2-stage least squares method was used with daily tallies of emergency department (ED) visits and 28-day mortality. Records for older people were categorized by long-term care (LTC) home status, and comorbidities were used to explain the demographic and clinical attributes of excess 28-day mortality. The primary outcome was actual excess death in 2020 and 2021. The 2-stage least squares method was used to estimate the daily excess 28-day mortality by daily reduced visits.

Compared with the prepandemic (2016-2019) average, there was a reduction in total ED visits in 2020 of 25.4% (548,116/2,142,609). During the same period, the 28-day mortality of non-COVID-19 ED deaths increased by 7.82% (2689/34,370) compared with 2016-2019. The actual excess deaths in 2020 and 2021 were 3143 and 4013, respectively. The estimated total excess non-COVID-19 28-day deaths among older people in 2020 to 2021 were 1958 (95% CI 1100-2820; no time lag). Deaths on arrival (DOAs) or deaths before arrival (DBAs) increased by 33.6% (1457/4336) in 2020, while non-DOA/DBAs increased only by a moderate 4.97% (1202/24,204). In both types of deaths, the increases were higher during wave periods than in nonwave periods. Moreover, non-LTC patients saw a greater reduction in ED visits than LTC patients across all waves, by more than 10% (non-LTC: 93,896/363,879, 25.8%; LTC: 7,956/67,090, 11.9%). Most of the comorbidity subsets demonstrated an annualized reduction in visits in 2020. Renal diseases and severe liver diseases saw notable increases in deaths.

We demonstrated a statistical method to estimate hospital avoidance behavior during a pandemic and quantified the consequent excess 28-day mortality with a focus on older people, who had high frequencies of ED visits and deaths. This study serves as an informed alert and possible investigational guideline for health care professionals for hospital avoidance behavior and its consequences.

Transferring patients to other hospitals because of inpatient saturation or need for higher levels of care was often challenging during the early waves of the COVID-19 pandemic. Understanding how transfer patterns evolved over time and amid hospital overcrowding could inform future care delivery and load balancing efforts.

To evaluate trends in outgoing transfers at overall and caseload-strained hospitals during the COVID-19 pandemic vs prepandemic times.

This retrospective cohort study used data for adult patients at continuously reporting US hospitals in the PINC-AI Healthcare Database. Data analysis was performed from February to July 2023.

Pandemic wave, defined as wave 1 (March 1, 2020, to May 31, 2020), wave 2 (June 1, 2020, to September 30, 2020), wave 3 (October 1, 2020, to June 19, 2021), Delta (June 20, 2021, to December 18, 2021), and Omicron (December 19, 2021, to February 28, 2022).

Weekly trends in cumulative mean daily acute care transfers from all hospitals were assessed by COVID-19 status, hospital urbanicity, and census index (calculated as daily inpatient census divided by nominal bed capacity). At each hospital, the mean difference in transfer counts was calculated using pairwise comparisons of pandemic (vs prepandemic) weeks in the same census index decile and averaged across decile hospitals in each wave. For top decile (ie, high-surge) hospitals, fold changes (and 95% CI) in transfers were adjusted for hospital-level factors and seasonality.

At 681 hospitals (205 rural [30.1%] and 476 urban [69.9%]; 360 [52.9%] small with <200 beds and 321 [47.1%] large with ≥200 beds), the mean (SD) weekly outgoing transfers per hospital remained lower than the prepandemic mean of 12.1 (10.4) transfers per week for most of the pandemic, ranging from 8.5 (8.3) transfers per week during wave 1 to 11.9 (10.7) transfers per week during the Delta wave. Despite more COVID-19 transfers, overall transfers at study hospitals cumulatively decreased during each high national surge period. At 99 high-surge hospitals, compared with a prepandemic baseline, outgoing acute care transfers decreased in wave 1 (fold change -15.0%; 95% CI, -22.3% to -7.0%; P < .001), returned to baseline during wave 2 (2.2%; 95% CI, -4.3% to 9.2%; P = .52), and displayed a sustained increase in subsequent waves: 19.8% (95% CI, 14.3% to 25.4%; P < .001) in wave 3, 19.2% (95% CI, 13.4% to 25.4%; P < .001) in the Delta wave, and 15.4% (95% CI, 7.8% to 23.5%; P < .001) in the Omicron wave. Observed increases were predominantly limited to small urban hospitals, where transfers peaked (48.0%; 95% CI, 36.3% to 60.8%; P < .001) in wave 3, whereas large urban and small rural hospitals displayed little to no increases in transfers from baseline throughout the pandemic.

Throughout the COVID-19 pandemic, study hospitals reported paradoxical decreases in overall patient transfers during each high-surge period. Caseload-strained rural (vs urban) hospitals with fewer than 200 beds were unable to proportionally increase transfers. Prevailing vulnerabilities in flexing transfer capabilities for care or capacity reasons warrant urgent attention.

During a COVID-19 pandemic, it is imperative to investigate the outcomes of all non-COVID-19 diseases. This study determines hospital admissions and mortality rates related to non-COVID-19 diseases during the COVID-19 pandemic among 41 million Iranians.

This nationwide retrospective study used data from the Iran Health Insurance Organization. From September 23, 2019, to Feb 19, 2022, there were four study periods: pre-pandemic (Sept 23-Feb 19, 2020), first peak (Mar 20-Apr 19, 2020), first year (Feb 20, 2020-Feb 18, 2021), and the second year (Feb 19, 2021-Feb 19, 2022) following the pandemic. Cause-specific hospital admission and in-hospital mortality are the main outcomes analyzed based on age and sex. Negative binomial regression was used to estimate the monthly adjusted Incidence Rate Ratio (IRR) to compare hospital admission rates in aggregated data. A logistic regression was used to estimate the monthly adjusted in-hospital mortality Odds Ratio (OR) for different pandemic periods.

During the study there were 6,522,114 non-COVID-19 hospital admissions and 139,679 deaths. Prior to the COVID-19 outbreak, the standardized hospital admission rate per million person-month was 7115.19, which decreased to 2856.35 during the first peak (IRR 0.40, [0.25-0.64]). In-hospital mortality also increased from 20.20 to 31.99 (OR 2.05, [1.97-2.13]). All age and sex groups had decreased admission rates, except for females at productive ages. Two years after the COVID-19 outbreak, the non-COVID-19 hospital admission rate (IRR 1.25, [1.13-1.40]) and mortality rate (OR 1.05, [1.04-1.07]) increased compared to the rates before the pandemic. The respiratory disease admission rate decreased in the first (IRR 0.23, [0.17-0.31]) and second years (IRR 0.35, [0.26-0.47] compared to the rate before the pandemic. There was a significant reduction in hospitalizations for pneumonia (IRR 0.30, [0.21-0.42]), influenza (IRR 0.04, [0.03-0.06]) and COPD (IRR 0.39, [0.23-0.65]) during the second year. There was a significant and continuous rise in the hematological admission rate during the study, reaching 186.99 per million person-month in the second year, reflecting an IRR of 2.84 [2.42-3.33] compared to the pre-pandemic period. The mortality rates of mental disorders (OR 2.15, [1.65-2.78]) and musculoskeletal (OR 1.48, [1.20-1.82), nervous system (OR 1.42, [1.26-1.60]), metabolic (OR 1.99, [1.80-2.19]) and circulatory diseases (OR 1.35, [1.31-1.39]) increased in the second year compare to pre-pandemic. Myocardial infarction (OR 1.33, [1.19-1.49]), heart failure (OR 1.59, [1.35-1.87]) and stroke (OR 1.35, [1.24-1.47]) showed an increase in mortality rates without changes in hospitalization.

In the era of COVID-19, the changes seem to have had a long-term effect on non-COVID-19 diseases. Countries should prepare for similar crises in the future to ensure medical services are not suspended.

COVID-19 mortality rates increase rapidly with age, are higher among men than women, and vary across racial/ethnic groups, but this is also true for other natural causes of death. Prior research on COVID-19 mortality rates and racial/ethnic disparities in those rates has not considered to what extent disparities reflect COVID-19-specific factors, versus preexisting health differences. This study examines both questions. We study the COVID-19-related increase in mortality risk and racial/ethnic disparities in COVID-19 mortality, and how both vary with age, gender, and time period. We use a novel measure validated in prior work, the COVID Excess Mortality Percentage (CEMP), defined as the COVID-19 mortality rate (Covid-MR), divided by the non-COVID natural mortality rate during the same time period (non-Covid NMR), converted to a percentage. The CEMP denominator uses Non-COVID NMR to adjust COVID-19 mortality risk for underlying population health. The CEMP measure generates insights which differ from those using two common measures-the COVID-MR and the all-cause excess mortality rate. By studying both CEMP and COVID-MRMR, we can separate the effects of background health from Covid-specific factors affecting COVID-19 mortality. We study how CEMP and COVID-MR vary by age, gender, race/ethnicity, and time period, using data on all adult decedents from natural causes in Indiana and Wisconsin over April 2020-June 2022 and Illinois over April 2020-December 2021. CEMP levels for racial and ethnic minority groups can be very high relative to White levels, especially for Hispanics in 2020 and the first-half of 2021. For example, during 2020, CEMP for Hispanics aged 18-59 was 68.9% versus 7.2% for non-Hispanic Whites; a ratio of 9.57:1. CEMP disparities are substantial but less extreme for other demographic groups. Disparities were generally lower after age 60 and declined over our sample period. Differences in socio-economic status and education explain only a small part of these disparities.

The COVID-19 pandemic has substantially affected people and healthcare systems. One of the main challenges was the reduction and change in the pattern of non-COVID-19 diseases and conditions. Moreover, due to the mental burden of the pandemic, the trend of poisonings and abuses changed. In this study, we aimed to assess the trends of poisonings from different agents before and during the COVID-19 pandemic using the interrupted time series method. This study was conducted at one of the main Tehran referral centers for poisoning, Baharloo Hospital. Pre-COVID-19 period was defined as April 2018 to January 2020 while the COVID-19 time was from February 2020 to March 2022. The total number of monthly poisoning cases in addition to eight categories of drugs/substances/agents were identified, including drugs (such as psychiatric drugs, cardiovascular drugs, and analgesics), opioids, stimulants, methanol, ethanol, cannabis, pesticides, and carbon monoxide. Interrupted time series analysis was performed to compare the pre-pandemic trend of total monthly cases from each category in addition to the proportion (%) of each one. In total, 13,020 cases were poisoned during the study period, among which 6088 belonged to the pre-pandemic period and 6932 were admitted during the COVID-19 era. There was no significant difference in terms of demographic characteristics of patients before and during the pandemic (p-value > 0.05). At the beginning of the pandemic, there was a sudden fall in the number of poisoning patients (- 77.2 cases/month, p-value = 0.003), however, there was a significant increasing trend during the COVID time (3.9 cases/month, p-value = 0.006). Most of the categories had a sharp decrease at the beginning of the pandemic except for methanol and ethanol which had increases, although not significant. Cannabis also had a significant change in slope (- 0.6 cases/month, p-value = 0.016), in addition to the sudden decrease at the beginning of the pandemic (- 10 cases/month, p-value = 0.007). Regarding the proportion of each category from total monthly poisoning cases, methanol, and ethanol had immediate rises of 4.2% per month and 10.1% per month, respectively (both significant). The pandemic had significant effects on the pattern of poisonings from different agents in Iran, the most important of which were alcohol (ethanol and methanol). These differences had policy implications that can be helpful for policymakers and healthcare systems in combating similar situations in the future.

During the COVID-19 pandemic, many non-COVID-19 emergency department (ED) visits were indirectly affected. ED visits and mortality were assessed during different pandemic time periods compared with pre-pandemic.

The study used data from 41 million Iran Health Insurance Organization members. The outcomes were non-COVID-19 ED visits and associated mortality in 956 hospitals. An analysis of ED visits was conducted both for all-cause and cause-specific conditions: cardiovascular diseases (CVD), mental and substance use disorders, unintentional injuries, and self-harm. In addition, total in-hospital ED mortality was analyzed. A negative binomial regression and a Poisson regression with a log link were used to estimate the incidence rate ratio (IRR) of visits and mortality relative risk (RR).

1,789,831 ED visits and 12,377 deaths were reported during the study. Pre-pandemic (Sep 2019 to Feb 2020), there were 2,767 non-COVID-19 visits rate per million person-month, which decreased to 1,884 during the first COVID-19 wave with a national lockdown from Feb 20 to Apr 19, 2020 (IRR 0.68, [0.56-0.84]). The non-COVID-19 ED mortality risk was 8.17 per 1,000 visit-month during the pre-pandemic period, rising to 12.80 during the first wave of COVID-19 (RR 1.57, [1.49-165]). Non-COVID-19 ED visit rates decreased during the first pandemic year from Sep 2020 to Feb 2021 (IRR 0.73, [0.63-0.86]), but increased after COVID-19 vaccination two years later from Sep 2021 to Feb 2022 (IRR 1.11, [0.96-0.17]). The total ED mortality risk for non-COVID-19 was significantly higher after the COVID-19 outbreak in the first (RR 1.66, [1.59-1.72]) and second years (RR 1.27, [1.22-1.32]) of the pandemic. The visit incidence rate for mental health and substance use disorders declined from 8.18 per million person-month to 4.57 (IRR 0.53, [0.32 to 0.90]) in the first wave. In the second year, unintentional injury visits increased significantly compared with pre-pandemic (IRR 1.63, [1.30-2.03]). As compared to before the pandemic, there was no significant change in CVD and self-harm visit rates during the pandemic. Cardiac arrest was the leading cause of death in Iran hospitals' EDs.

In the first year of the COVID-19 pandemic, non-COVID-19 hospital ED visits declined and mortality risk increased. Despite two years since the COVID-19 outbreak, non-COVID-19 ED mortality risk remains high.

In the first year of the COVID-19 pandemic, health systems implemented programmes to manage outpatients with COVID-19. The goal was to expedite patients' referral to acute care and prevent overcrowding of medical centres. We sought to evaluate the impact of such a programme, the COVID-19 Home Care Team (CHCT) programme.

Retrospective cohort.

Kaiser Permanente Northern California.

Adult members before COVID-19 vaccine availability (1 February 2020-31 January 2021) with positive SARS-CoV-2 tests.

Virtual programme to track and treat patients with 'CHCT programme'.

The outcomes were (1) COVID-19-related emergency department visit, (2) COVID-19-related hospitalisation and (3) inpatient mortality or 30-day hospice referral.

We estimated the average effect comparing patients who were and were not treated by CHCT. We estimated propensity scores using an ensemble super learner (random forest, XGBoost, generalised additive model and multivariate adaptive regression splines) and augmented inverse probability weighting.

There were 98 585 patients with COVID-19. The majority were followed by CHCT (n=80 067, 81.2%). Patients followed by CHCT were older (mean age 43.9 vs 41.6 years, p<0.001) and more comorbid with COmorbidity Point Score, V.2, score ≥65 (1.7% vs 1.1%, p<0.001). Unadjusted analyses showed more COVID-19-related emergency department visits (9.5% vs 8.5%, p<0.001) and hospitalisations (3.9% vs 3.2%, p<0.001) in patients followed by CHCT but lower inpatient death or 30-day hospice referral (0.3% vs 0.5%, p<0.001). After weighting, there were higher rates of COVID-19-related emergency department visits (estimated intervention effect -0.8%, 95% CI -1.4% to -0.3%) and hospitalisation (-0.5%, 95% CI -0.9% to -0.1%) but lower inpatient mortality or 30-day hospice referral (-0.5%, 95% CI -0.7% to -0.3%) in patients followed by CHCT.

Despite CHCT following older patients with higher comorbidity burden, there appeared to be a protective effect. Patients followed by CHCT were more likely to present to acute care and less likely to die inpatient.

The COVID-19 pandemic in Brazil has brought many challenges, particularly regarding the management of hospital capacity, and a new demand for healthcare that added to the preexisting demands, such as neoplasms, cardiovascular diseases and births. In this paper, we estimate the impact of the pandemic on the number of deaths and hospitalizations for other diseases. We construct a monthly panel data of deaths and hospitalizations for various causes by the municipality of residence and relate them to COVID-19 hospitalizations using regression models that control for municipalities fixed-effects and interactions between State and month fixed-effects. The standard errors are clustered at the municipality level. Our estimates imply that 100 more hospitalizations by COVID-19 is associated with a drop of 49 non-COVID-19 hospitalizations and an additional four deaths for other reasons (all measured per 100,000 pop.). The impact of intensive care units COVID-19 hospitalizations on mortality is larger. The groups most affected are the African Brazilians, less-educated and the elderly. Additional deaths occurred both at households and at hospitals. The main causes of additional deaths were diseases related to the circulatory and endocrine system. The decline in hospitalizations for other causes seems to be related to the overcrowding of hospitals in periods of surge in the COVID-19, alongside with the fall in the demand for care by the citizens who were afraid of COVID-19 infection. These mechanisms affected more strongly the vulnerable groups of the population. Our results highlight the importance of promoting the awareness of heightened risk of non-communicable chronic diseases during a health emergency context. This should be done preferably through already established channels with community outreach, such as the Family Health Program in Brazil.

New HIV diagnoses in Italy decreased drastically in 2020 due to COVID-19 related effects: 50% fewer diagnoses were reported by the National HIV Surveillance System. COVID-19 pandemic impact on HIV surveillance is unclear. We estimated the expected number of new HIV diagnoses in 2020 in order to isolate the impact of the COVID-19 pandemic.

We analyzed 29 697 new HIV infections diagnosed from 2012 to 2020, reported to the National HIV Surveillance System. We assessed temporal trends of new HIV diagnoses applying negative binomial mixed effects models. We estimated the COVID-19 impact as the difference between the model-estimated slopes from 2012 to 2019 and the change reported in the diagnoses. The expected number of new HIV diagnoses in 2020 was also estimated and compared with the reported count.

Based on the historical trend, we expected a 15% (95% CI: 5-25%) decline of new HIV diagnoses in 2020. We reported, however, a 49% decrease, yielding to a 34% net decrease in the number of new diagnoses. The strongest impact was estimated in northern regions (-40%) and MSM (-38%). We estimated 761 (95% prediction interval: 350-1277) missed diagnoses during 2020, the majority of them occurring in the North (465 cases), among MSM (416) and heterosexual males (217).

In 2020, when excluding 15% decrease of new diagnoses attributable to the expected reduction, an additional 34% decrease was observed, representing a large decline in new HIV diagnoses associated with the COVID-19 pandemic.

COVID-19 had severe direct and indirect effects on health and well-being in Latin America. To understand the extent to which disruptions among non-COVID-19-related health services affected population health, we used administrative data from the period 2015-21 to examine public hospital discharges and mortality for conditions amenable to health care in four Latin American countries: Brazil, Ecuador, Mexico, and Peru. Between March 2020 and December 2021, hospitalization rates for these conditions declined by 28 percent and mortality rates increased by 15 percent relative to prepandemic years. Noncommunicable diseases accounted for 89 percent of this rise in mortality. The poorest states in each country experienced relatively larger increases in mortality. Our results, which focus on the health effects of service disruption, suggest that maintaining health care services in this region during the pandemic could have avoided at least 96,000 deaths. Policies should focus on maintaining essential health care services during emergencies, particularly for patients with noncommunicable diseases, and on minimizing negative consequences by ensuring coordinated and continuous care; leveraging alternative modalities of care, such as telemedicine; broadening the role of nonphysician health care workers; and expanding options for medication delivery.

More than one-third of individuals experience post-acute sequelae of SARS-CoV-2 infection (PASC, which includes long-COVID). The objective is to identify risk factors associated with PASC/long-COVID diagnosis.

This was a retrospective case-control study including 31 health systems in the United States from the National COVID Cohort Collaborative (N3C). 8,325 individuals with PASC (defined by the presence of the International Classification of Diseases, version 10 code U09.9 or a long-COVID clinic visit) matched to 41,625 controls within the same health system and COVID index date within ± 45 days of the corresponding case's earliest COVID index date. Measurements of risk factors included demographics, comorbidities, treatment and acute characteristics related to COVID-19. Multivariable logistic regression, random forest, and XGBoost were used to determine the associations between risk factors and PASC.

Among 8,325 individuals with PASC, the majority were > 50 years of age (56.6%), female (62.8%), and non-Hispanic White (68.6%). In logistic regression, middle-age categories (40 to 69 years; OR ranging from 2.32 to 2.58), female sex (OR 1.4, 95% CI 1.33-1.48), hospitalization associated with COVID-19 (OR 3.8, 95% CI 3.05-4.73), long (8-30 days, OR 1.69, 95% CI 1.31-2.17) or extended hospital stay (30 + days, OR 3.38, 95% CI 2.45-4.67), receipt of mechanical ventilation (OR 1.44, 95% CI 1.18-1.74), and several comorbidities including depression (OR 1.50, 95% CI 1.40-1.60), chronic lung disease (OR 1.63, 95% CI 1.53-1.74), and obesity (OR 1.23, 95% CI 1.16-1.3) were associated with increased likelihood of PASC diagnosis or care at a long-COVID clinic. Characteristics associated with a lower likelihood of PASC diagnosis or care at a long-COVID clinic included younger age (18 to 29 years), male sex, non-Hispanic Black race, and comorbidities such as substance abuse, cardiomyopathy, psychosis, and dementia. More doctors per capita in the county of residence was associated with an increased likelihood of PASC diagnosis or care at a long-COVID clinic. Our findings were consistent in sensitivity analyses using a variety of analytic techniques and approaches to select controls.

This national study identified important risk factors for PASC diagnosis such as middle age, severe COVID-19 disease, and specific comorbidities. Further clinical and epidemiological research is needed to better understand underlying mechanisms and the potential role of vaccines and therapeutics in altering PASC course.

In April 2022, an outbreak of the SARS-CoV-2 virus Omicron variant in Shanghai precipitated an extensive lockdown. We assessed changes in healthcare utilization during this outbreak and investigated the relationship between the stringency of mitigation strategies and disruptions in healthcare utilization.

Using provincial-level data from routine health information systems covering all hospitals across Mainland China, we conducted an interrupted time series analysis to examine changes in healthcare utilization during the Shanghai outbreak. Linear regression was used to evaluate the direction and magnitude of the association between the relative changes in the move-out movement index, a proxy for the stringency in population-level mitigation strategies, and the estimated relative changes in healthcare utilization.

Overall, there were 22.9 billion outpatient visits and 1.2 billion discharged inpatients during the study period from January 2016 to May 2022, including 9.1 billion (39.7%) and 0.46 billion (38.2%) in the post-COVID-19 period (January 2020-May 2022), respectively. From March through May 2022, the outbreak resulted in an accumulative loss of 23.5 million (47%) outpatient visits and 0.6 million (55%) discharged inpatients in Shanghai, and a loss of 150.3 million (14%) outpatient visits and 3.6 million (7%) discharged inpatients in other regions. We find that for every 10-percentage point reduction in the relative change of move-out index, a 2.7 (95% CI: 2.0-3.4) percentage point decline in the relative change of outpatient visits, and a 4.3 (95% CI: 3.5-5.2) percentage points decline in the relative change of inpatient discharges.

The Shanghai COVID-19 Omicron outbreak associates with a substantial reduction in outpatient visits and inpatient discharges within Shanghai and other regions in China. The stringency of the COVID-19 lockdown policies associates with more profound reductions in healthcare utilization.

To examine the impact of COVID-19 on clinical health outcomes and health-related social needs among Medicaid-Medicare dual-eligible beneficiaries.

Scoping review.

Dual eligibles during COVID-19.

We performed a comprehensive scoping review including observational studies, clinical trials, and original empirical research studies of PubMed and CINAHL. We generated a list of terms related to programs that both serve dual eligibles and address our desired outcomes. With the assistance of a medical librarian, we identified relevant abstracts published during COVID-19 meeting our inclusion criteria. We performed full-text reviews of relevant abstracts and selected the final studies. We extracted the study population, design, and major findings, then conducted thematic analysis.

1100 articles were identified, with 439 deemed relevant. On full text-review, 15 articles met inclusion criteria representing more than 86 million Medicare beneficiaries. No studies were specific only to dual eligibles. Topic areas included in this review include COVID-19 case counts (2 articles), mortality (8 articles), hospitalizations (7 articles), food insecurity (1 article), self-reported mental health (1 article), and social connectedness (2 articles). Dual eligibles had disparate COVID-19-related outcomes from Medicare-only enrollees in 12 of 15 studies. Studies show higher mortality for dual eligibles overall, but this was not true for dual eligibles in nursing homes and assisted living communities. Dual eligibles were more likely to experience food insecurity. More favorably, dual eligibles reported greater social connectedness.

Dual eligibles had different outcomes from Medicare-only recipients in multiple health outcomes and health-related social needs during COVID-19, but studies are limited, particularly in terms of health-related social needs. Future work focusing on outcomes only among dual-eligible beneficiaries, integrated care programs, and fiscal alignment between Medicare and Medicaid plans may help stakeholders address health needs specific to dual eligibles.

The 2018 adult heart allocation policy sought to improve waitlist risk stratification, reduce waitlist mortality, and increase organ access. This system prioritized patients at greatest risk for waitlist mortality, especially individuals requiring temporary mechanical circulatory support (tMCS). Posttransplant complications are significantly higher in patients on tMCS before transplantation, and early posttransplant complications impact long-term mortality. We sought to determine if policy change affected early posttransplant complication rates of rejection, infection, and hospitalization.

We included all adult, heart-only, single-organ heart transplant recipients from the UNOS registry with pre-policy (PRE) individuals transplanted between November 1, 2016, and October 31, 2017, and post-policy (POST) between November 1, 2018, and October 31, 2019. We used a multivariable logistic regression analysis to assess the effect of policy change on posttransplant rejection, infection, and hospitalization. Two COVID-19 eras (2019-2020, 2020-2021) were included in our analysis.

The majority of baseline characteristics were comparable between PRE and POST era recipients. The odds of treated rejection (p = 0.8), hospitalization (p = 0.69), and hospitalization due to rejection (p = 0.76) and infection (p = 0.66) were similar between PRE and POST eras; there was a trend towards reduced odds of rejection (p = 0.08). In both COVID eras, there was a clear reduction in rejection and treated rejection with no effect on hospitalization for rejection or infection. Odds of all-cause hospitalization was increased in both COVID eras.

The UNOS policy change improves access to heart transplantation for higher acuity patients without increasing early posttransplant rates of treated rejection or hospitalization for rejection or infection, factors which portend risk for long-term posttransplant mortality.

Although the ongoing epidemics of Coronavirus disease 2019 (COVID-19) may have affected the mortality trend of the nation, the national level assessment of excess mortality (changes in overall mortality in the entire population) is still scarce in Korea. Therefore, this study evaluated the excess mortality during the COVID-19 pandemic in Korea using the certified mortality data.

Monthly mortality and population data from January 2013 to June 2022 was obtained from the National Health Insurance Service database and Statistics Korea. A quasi-Poisson interrupted time-series model adjusted for age structure, population, seasonality, and long-term trends was used to estimate the counterfactual projections (expected) of mortality during the COVID-19 pandemic (March 2020 to June 2022). The absolute difference (observed-expected) and ratio (observed / expected) of mortality were calculated. Stratified analysis based on pandemic years (years 2020, 2021, and 2022), sex, and age groups (aged 0-4, 5-19, 20-64, and ≥ 65 years) were conducted.

An 8.7% increase in mortality was observed during the COVID-19 pandemic [absolute difference: 61,277 persons; ratio (95% confidence interval (CI)): 1.087 (1.066, 1.107)]. The gap between observed and estimated mortality became wider with continuation of the pandemic [ratio (95% CI), year 2020: 1.021 (1.003, 1.040); year 2021: 1.060 (1.039, 1.080), year 2022: 1.244 (1.219, 1.270)]. Although excess mortality across sex was similar, the adult [aged 20-64, ratio (95% CI): 1.059 (1.043, 1.076)] and elderly [aged 65-, ratio (95% CI): 1.098 (1.062, 1.135)] population showed increased excess mortality during the pandemic.

Despite Korea's successful quarantine policy response, the continued epidemic has led to an excess mortality. The estimated mortality exceeded the number of deaths from COVID-19 infection. Excess mortality should be monitored to estimate the overall impact of the pandemic on a nation.

The COVID-19 virus caused a global pandemic leading to a swift policy response. While this response was designed to prevent the spread of the virus and support those with COVID-19, there is growing evidence regarding measurable impacts on non-COVID-19 patients. The paper uses a large dataset from administrative records of the Brazilian public health system (SUS) to estimate pandemic spillover effects in critically ill health care delivery, i.e. the additional mortality risk that COVID-19 ICU hospitalizations generate on non-COVID-19 patients receiving intensive care. The data contain the universe of ICU hospitalizations in SUS from February 26, 2020 to December 31, 2021. Spillover estimates are obtained from high-dimensional fixed effects regression models that control for a number of unobservable confounders. Our findings indicate that, on average, the pandemic increased the mortality risk of non-COVID-19 ICU patients by 1.296 percentage points, 95% CI 1.145-1.448. The spillover mortality risk is larger for non-COVID patients receiving intensive care due to diseases of the respiratory system, diseases of the skin and subcutaneous tissue, and infectious and parasitic diseases. As of July 2023, the WHO reports more than 6.9 million global deaths due to COVID-19 infection. However, our estimates of spillover effects suggest that the pandemic's total death toll is much higher.

An unprecedented global pandemic caused by a novel coronavirus named SARS-CoV-2 has created a severe healthcare threat and become one of the biggest challenges to human health and the global economy. As of July 2023, over 767 million confirmed cases of COVID-19 have been diagnosed, including more than 6.95 million deaths. The S protein of this novel coronavirus binds to the ACE2 receptor to enter the host cells with the help of another transmembrane protease TMPRSS2. Infected subjects that can mount an appropriate host immune response can quickly inhibit the spread of infection into the lower respiratory system and the disease may remain asymptomatic or a mild infection. The inability to mount a strong initial response can allow the virus to replicate unchecked and manifest as severe acute pneumonia or prolonged disease that may manifest as systemic disease manifested as viremia, excessive inflammation, multiple organ failure, and secondary bacterial infection among others, leading to delayed recovery, hospitalization, and even life-threatening consequences. The clinical management should be targeted to specific pathogenic mechanisms present at the specific phase of the disease. Here we summarize distinct phases of COVID-19 pathogenesis and appropriate therapeutic paradigms associated with the specific phase of COVID-19.

According to the US Renal Data System (USRDS), patients with end-stage kidney disease (ESKD) on maintenance dialysis had higher mortality during early COVID-19 pandemic. Less is known about the effect of the pandemic on the delivery of outpatient maintenance hemodialysis and its impact on death. We examined the effect of pandemic-related disruption on the delivery of dialysis treatment and mortality in patients with ESKD receiving maintenance hemodialysis in the Veterans Health Administration (VHA) facilities, the largest integrated national healthcare system in the USA.

Using national VHA electronic health records data, we identified 7,302 Veterans with ESKD who received outpatient maintenance hemodialysis in VHA healthcare facilities during the COVID-19 pandemic (February 1, 2020, to December 31, 2021). We estimated the average change in the number of hemodialysis treatments received and deaths per 1,000 patients per month during the pandemic by conducting interrupted time-series analyses. We used seasonal autoregressive moving average (SARMA) models, in which February 2020 was used as the conditional intercept and months thereafter as conditional slope. The models were adjusted for seasonal variations and trends in rates during the pre-pandemic period (January 1, 2007, to January 31, 2020).

The number (95% CI) of hemodialysis treatments received per 1,000 patients per month during the pre-pandemic and pandemic periods were 12,670 (12,525-12,796) and 12,865 (12,729-13,002), respectively. Respective all-cause mortality rates (95% CI) were 17.1 (16.7-17.5) and 19.6 (18.5-20.7) per 1,000 patients per month. Findings from SARMA models demonstrate that there was no reduction in the dialysis treatments delivered during the pandemic (rate ratio: 0.999; 95% CI: 0.998-1.001), but there was a 2.3% (95% CI: 1.5-3.1%) increase in mortality. During the pandemic, the non-COVID hospitalization rate was 146 (95% CI: 143-149) per 1,000 patients per month, which was lower than the pre-pandemic rate of 175 (95% CI: 173-176). In contrast, there was evidence of higher use of telephone encounters during the pandemic (3,023; 95% CI: 2,957-3,089), compared with the pre-pandemic rate (1,282; 95% CI: 1,241-1,324).

We found no evidence that there was a disruption in the delivery of outpatient maintenance hemodialysis treatment in VHA facilities during the COVID-19 pandemic and that the modest rise in deaths during the pandemic is unlikely to be due to missed dialysis.

There is limited information regarding COVID-19 in long-term blood or marrow transplant (BMT) survivors. We leveraged the BMT Survivor Study (BMTSS) to address this gap. BMTSS included patients who underwent BMT at 1 of 3 sites in the United States between 1974 and 2014 and survived ≥2 years after BMT. A sibling cohort serves as a non-BMT comparison group. Participants (2430 BMT survivors; 780 non-BMT participants) completed the BMTSS survey between October 2020 and November 2021 about COVID-19 testing, risk mitigation behaviors, morbidity, and health care use. Median age at BMT was 46 years (range, 0-78 years) and median follow-up since BMT was 14 years (6-46 years); 76% were non-Hispanic White, 54% had received allogeneic BMT. The risk of COVID-19 infection was comparable for BMT survivors vs non-BMT participants (15-month cumulative incidence, 6.5% vs 8.1%; adjusted odd ratio [aOR] = 0.93; 95% confidence interval [CI], 0.65-1.33; P = .68). Among survivors, being unemployed (aOR 1.90; 95% CI, 1.12-3.23; P = .02; reference: retired) increased the odds of infection; always wearing a mask in public was protective (aOR = 0.49; 95% CI, 0.31-0.77; P = .002; reference: not always masking). When compared with COVID-positive non-BMT participants, COVID-positive BMT survivors had higher odds of hospitalization (aOR = 2.23; 95% CI, 0.99-5.05; P = .05); however, the odds of emergency department visits were comparable (aOR = 1.60; 95% CI = 0.71-3.58; P = .25). COVID-19 infection status did not increase the odds of hospitalization among BMT survivors (aOR = 1.32; 95% CI = 0.89-1.95; P = .17) but did increase the odds of emergency department visits (aOR = 2.63; 95% CI, 1.74-3.98; P <.0001). These findings inform health care providers about the management of care for long-term BMT survivors during the ongoing pandemic.