COVID-19 disease has been a deadly pandemic in different waves in the Democratic Republic of Congo. However, knowledge of the clinical characteristics of COVID-19 patients and the factors associated with death during different waves is important.

We conducted a retrospective cohort of 410 patients hospitalized during 4 waves of COVID-19, from March 20, 2020, to January 2, 2022, at the Ngaliema clinic in DR Congo. We included any patient hospitalized for COVID-19 with biological confirmation by RT-PCR. Factors associated with death were investigated using logistic regression.

During the 4 waves of the COVID-19 pandemic at Clinique Ngaliema, complaints on admission were most often fever, cough and physical asthenia. Death was most common in the elderly, hypertensive and diabetic patients, those with elevated CRP and hyper leukocytosis. Mortality was highest in the 1st wave (28%), followed by the 3rd wave (27%), then the 2nd (22%) and 4th waves (21%). Factors associated with death were hyper leukocytosis (ORa: 2.76; CI 95%: 1.25-6.1), severe disease stage (ORa 21.24; CI 95%: 1.87-24). Vitamin C 500 mg twice a day use was protective (ORa: 0.24; CI 95%: 0.08-0.72).

COVID-19 disease poses a real public health problem, with non-negligible mortality. Factors associated with death were degree of disease severity, hyper leukocytosis and non-use of vitamin C. Taking these factors into account will help clinicians and decision-makers to anticipate future waves of the pandemic.

Despite availability of preventive vaccine and global control of the SARS-CoV-19 transmission, continuous emergence of new strains coupled with the increase spread of Mpox poses significant public health threats. Identification of simple factors for stratification and prognostics of hospitalized patients is crucial for management of these patients in limited resource settings. The aim of this study was to assess the biological profile of severe hospitalized COVID-19 patients in Cameroon and identify risk factors for mortality.

A prospective, cross-sectional, analytical study was conducted of a cohort of COVID-19 patients admitted and managed at the Adlucem hospital in Banka-Bafang, Haut-Nkam Department, West Cameroon Region, from 2021 to 2022. The clinical characteristics and biological parameters of patients with COVID-19 were evaluated.

Of the 259 cases of COVID-19 included in the study, 68 cases (26.3%) died. The majority of patients who died were over 70 years of age. Key factors predictive of mortality in these patients were leukocytosis (OR = 2.035; 95%CI: 1.161-3.567; p = 0.013), thrombocytosis (OR = 4.286; 95%CI: 1.152-15.950; p = 0.030), hypokalemia (OR = 2.400; 95%CI: 1.143-5.042; p = 0.021), hyponatremia (OR = 2.292; 95%CI: 1.185-4.431; p = 0.014) and hypochloremia (OR = 2.644; 95%CI: 1.188-5.882; p = 0.017).

Age, electrolyte imbalance and thrombocytosis were predictive of death in COVID-19 patients in this cohort. Thus, a biological work-up should be considered for risk stratification to ensure efficient management of COVID-19 patients on a case-by-case basis in resource limited settings like Cameroon.

Not applicable.

Coronavirus disease 2019 (COVID-19) a global problem, has affected all aspects of health, that is, physical, social, and mental. Our study aimed to describe various social-demographic factors and existing comorbidities that affected mortality in COVID-19 admitted patients.

This was a hospital-based retrospective study. The study included medical records of COVID-19 patients admitted from April 2021 to August 2021. Data was entered in Microsoft Excel 2013 and analyzed in STATA version 18.0. The Chi-square test, unpaired t-test, and Cox proportional hazard model were employed for analysis.

Of the total 1156 admitted patients, 103 hospitalized patients progressed to death (8.91%). Factors found to be significant with non-survivorship were age, residence, admission status, and coexisting comorbidities. In hazard analysis, geriatric patients had 4.358 times more hazard of death. Patients with diabetes and hypertension had two times higher hazard of death than patients without these comorbidities.

Mortality of patients was substantially higher in patients' ages above 60 years and patients with comorbidities. Therefore, close monitoring and priority treatment should be provided to elderly patients and patients with comorbidities.

To explore the risk factors of proteinuria in Omicron variant patients and to construct and verify the risk predictive model.

1091 Omicron patients who were hospitalized from August 2022 to November 2022 at Tianjin First Central Hospital were defined as the derivation cohort. 306 Omicron patients who were hospitalized from January 2022 to March 2022 at the same hospital were defined as the validation cohort. The risk factors of proteinuria in derivation cohort were screened by univariate and multivariate logistic regression analysis, and proteinuria predicting scoring system was constructed and the receiver operating characteristic(ROC)curve was drawn to test the prediction ability. The proteinuria risk model was externally validated in validation cohort.

7 factors including comorbidities, blood urea nitrogen (BUN), serum sodium (Na), uric acid (UA), C reactive protein (CRP) and vaccine dosages were included to construct a risk predictive model. The score ranged from -5 to 16. The area under the ROC curve(AUC) of the model was 0.8326(95% CI 0.7816 to 0.8835, p < 0.0001). Similarly to that observed in derivation cohort, the AUC is 0.833(95% CI 0.7808 to 0.9002, p < 0.0001), which verified good prediction ability and diagnostic accuracy in validation cohort.

The risk model of proteinuria after Omicron infection had better assessing efficiency which could provide reference for clinical prediction of the risk of proteinuria in Omicron patients.

Severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) infection is well established as a systemic disease including kidney damage. The entry point into the renal cell remains the angiotensin-converting enzyme 2 (ACE-2) receptor and the spectrum of renal lesions is broad, with a clear predominance of structural and functional tubular lesions. The most common form of glomerular injury is collapsing glomerulopathy (CG), which is strongly associated with apolipoprotein L1(APOL-1) risk variants. These acute lesions, which are secondary to the direct or indirect effects of SARS-CoV-2, can progress to chronicity and are specific to long COVID-19 in the absence of any other cause. Residual inflammation associated with SARS-CoV-2 infection, in addition to acute kidney injury (AKI) as a transitional state with or without severe histological lesions, may be responsible for greater kidney function decline in mild-to-moderate COVID-19. This review discusses the evidence for renal histological markers of chronicity in COVID-19 patients and triggers of low-grade inflammation that may explain the decline in kidney function in the post-COVID-19 period.

There have been differential mortality rates from COVID-19 in different parts of the world. It is not clear whether the clinical presentation does also differ, thus the need for this study in a sub-Saharan African setting. The aim of this study was to describe the clinical manifestations and outcomes of patients diagnosed with COVID-19 in selected tertiary hospitals in Tanzania.

This was a retrospective analysis of hospitalised adults confirmed SAR-COV-2 infection in five tertiary-level hospitals in Tanzania. Data collected and analysed included sociodemographic, radiological and clinical characteristics of the patients as well as the outcome of the admission (discharge vs death).

Out of 1387 COVID-19 patients, 52% were males. The median age was 60 years ((IQR)=(19-102)). The most common symptoms were dyspnoea (943,68%), cough (889, 64%), fever (597,43%) and fatigue (570, 41%). In-hospital mortality was (476, 34%). Mortality significantly increased with increasing age, being the most in age >90 years (aHR (95% CI)=4.4 (2.52 to 28.82), p=0.02). Other predictors of mortality were not possessing a health insurance, (aHR (95% CI)=3.7 (1.09 to 14.25), p=0.04); chest pain, (aHR (95% CI)=2.27 (1.36 to 4.13), p=0.03); HIV positivity, (aHR (95% CI)=3.9 (1.46 to 8.15), p=0.03); neutrophilia, (aHR (95% CI)=1.12 (1.01 to 2.65), p=0.03); no use of ivermectin, (aHR (95% CI)=1.21 (1.04 to 1.57), p=0.04) and non-use of steroids, (aHR (95% CI)=1.36 (1.18 to 2.78), p=0.04). The retrospective nature of this study which based on documented patients' records, with a large number of patients left out of the analysis due to missed data, this might in a way affect the results of the present study.

In-hospital mortality was 34%. The independent predictors of mortality were advanced age, HIV infection, no possession of a health insurance, chest pain, neutrophilia and no use of steroids or ivermectin.

During the COVID-19 pandemic, a considerable proportion of patients developed a severe condition that included respiratory failure, shock, or multiple organ dysfunction. Acute Kidney Injury (AKI) has been recognized as a possible cause of severe COVID-19 development. Given this, this study investigates the occurrence and consequences of AKI in Mexican patients to contribute to better knowledge and management of this problem. Methods: Using a retrospective observational cohort methodology, we investigated 313 cases from a cohort of 1019 patients diagnosed with COVID-19 at the IMSS Zacatecas General Hospital of Zone No. 1 in 2020. The prevalence of AKI was determined using the AKIN criteria based on serum creatinine levels and a detailed review of demographic characteristics, medical history, comorbidities, and clinical development. Results: The data showed a 25.30% prevalence of AKI among patients infected with severe COVID-19. Remarkably, these patients with AKI exhibited an advanced age (>65 years), arterial hypertension, a higher number of white blood cells during admission and the hospital stay, and elevated levels of C-reactive protein, serum creatinine, and blood urea nitrogen (BUN). Clinically, patients with AKI had signs of prostration, pneumonia, and the requirement for ventilatory assistance when compared to those without AKI. Finally, those diagnosed with AKI and COVID-19 had a 74% death rate. Relative risk analyses indicated that age (>65 years), arterial hypertension, high creatinine levels, endotracheal intubation, and pneumonia are associated with the development of AKI. On the other hand, among the protective factors against AKI, high hemoglobin levels and the consumption of statins during COVID-19 were found. Conclusions: The findings of this study underscore the significance of promptly identifying and effectively managing AKI to potentially alleviate the negative consequences of this complication within the Mexican population during COVID-19.

We included all patients with respiratory symptoms (dyspnea, fever, and cough) and/or respiratory failure admitted to the SOS Médecins de nuit SARL hospital, DR Congo, during the 2nd and 3rd waves of the COVID-19 pandemic. The diagnosis of COVID-19 was established based on RT-PCR anti-SARS-CoV-2 tests (G1 (RT-PCR positive) vs. G2 (RT-PCR negative)), and all patients had a chest CT on the day of admission. We retrieved the digital files of patients, precisely the clinical, biological, and chest CT parameters of the day of admission as well as the vital outcome (survival or death). Chest CT were read by a very high-definition console using Advantage Windows software and exported to the hospital network using the RadiAnt DICOM viewer. To determine the threshold for the percentage of lung lesions associated with all-cause mortality, we used ROC curves. Factors associated with death, including chest CT parameters, were investigated using logistic regression analysis.

The study included 200 patients (average age 56.2 ± 15.2 years; 19% diabetics and 4.5% obese), and COVID-19 was confirmed among 56% of them (G1). Chest CT showed that ground glass (72.3 vs. 39.8%), crazy paving (69.6 vs. 17.0%), and consolidation (83.9 vs. 22.7%), with bilateral and peripheral locations (68.8 vs. 30.7%), were more frequent in G1 vs. G2 (p < 0.001). No case of pulmonary embolism and fibrosis had been documented. The lung lesions affecting 30% of the parenchyma were informative in predicting death (area under the ROC curve at 0.705, p = 0.017). In multivariate analysis, a percentage of lesions affecting 50% of the lung parenchyma increased the risk of dying by 7.194 (1.656-31.250).

The chest CT demonstrated certain characteristic lesions more frequently in patients in whom the diagnosis of COVID-19 was confirmed. The extent of lesions affecting at least half of the lung parenchyma from the first day of admission to hospital increases the risk of death by a factor of 7.

We investigated the clinical profile, complications, and outcomes of inpatients with COVID-19 at Parirenyatwa Hospital, Harare, across the first two waves of SARS-CoV-2 infection, and factors associated with mortality.

We conducted a prospective cohort study on all patients admitted to the COVID-19 unit. Data were extracted from medical records and negative binomial regression with robust standard errors was used to assess the association between sociodemographic and clinical characteristics and mortality. Cox Regression was used for sensitivity analysis.

Of 563 people admitted with COVID-19 between 2 July 2020 and 19 March 2021, 214 (38.0%) died, 340 were discharged and 9 transferred. The median age was 56 (IQR 44-68) years and 53.8% were male. Overall, 38.8% experienced a complication, the most common being acute kidney injury (17.9%) and hyperglycaemia (13.1%). The most common comorbidity was hypertension (41.3%) followed by diabetes (28.6%), HIV (12.1%), cardiovascular disease (10.9%) and chronic kidney disease (7.8%). Among participants who stayed in the ward for more than 1 night, mortality was higher in patients with comorbidity compared to those without any comorbidity (38.7% vs 25.5%, risk ratio (RR) = 1.52 (95% CI 1.11, 2.07), p = 0.008). After adjusting for oxygen saturation, comorbidities, sex and pregnancy, mortality was higher in the second wave than in the first (adjusted RR 1.23, 95% CI 1.00-1.51, p = 0.05). In the second wave 57/161 (35.4%) deaths were attributed to lack of resources, mainly human resources.

The mortality rate was high and clinical COVID-19 care needs to pay careful attention to patient monitoring for complications and management of comorbidities. This will require addressing the critical health workforce shortage issues. Prevention of COVID-19 including vaccination particularly among individuals with comorbidities remains a high priority.

Determining the risk factors for severe disease and death among hospitalized Covid-19 patients is critical to optimize health outcomes and health services efficiency, especially in resource-constrained and humanitarian settings. This study aimed to identify the predictors of mortality of Covid-19 patients in North Kivu province in the Democratic Republic of Congo.A retrospective cohort study was conducted in 6 Covid-19 treatment centers in the city of Butembo from 1 January to 31 December 2021. The time to event (death), the outcome variable, was visualized by Kaplan-Meier curves and the log-rank test was used to confirm differences in trends. Cox regression was used for all the predictors in the bivariate analysis and multivariate analysis was done using predictors found statistically significant in the bivariate analysis. The following variables were considered for inclusion to the Cox regression model: Age, Sex, Disease length, Treatment site, History of at least one co-morbidity, Body mass index, Stage according to SpO2 and the NEWS-modified score.Among the 303 participants (mean age of 53 years), the fatality rate was 33.8 deaths per 1000 patient-days. Four predictors were independently associated with inpatient death: age category (≥ 60 years) (adjusted HR: 9.90; 95% CI: 2.68-36.27), presence of at least one comorbidity (adjusted HR: 11.39; 95% CI: 3.19-40.71); duration of illness of > 5 days before hospitalization (adjusted HR:1.70, 95% CI: 1.04-2.79) and peripheral capillary oxygen saturation (SpO2) < 90% (adjusted HR = 14.02, 95% CI: 2.23-88.32). In addition to advanced age, comorbidity, and length of disease before hospitalization, ambient air SpO2 measured by healthcare providers using low-tech, affordable and relatively accessible pulse oximetry could inform the care pathways of Covid-19 inpatients in resource-challenged health systems in humanitarian settings.

Acute kidney injury (AKI) is a complication of severe coronavirus disease 2019 (COVID-19). Kidney damage associated with COVID-19 could take specific features due to environmental and socio-cultural factors. This study evaluates the incidence of AKI, the associated factors, and mortality in COVID-19 patients in a Sub-Saharan African intensive care unit.

In a prospective cohort study conducted in the intensive care unit (ICU) of the Centre Médical de Kinshasa (CMK), consecutive patients admitted for COVID-19 were screened for the presence of AKI between 27 March, 2020 and 27 January 2022. AKI was defined according to Kidney Disease Improving Global Outcomes (KDIGO) guidelines. The primary outcome was occurrence of AKI. The secondary outcome was 48 days' mortality and recovery of the renal function at intensive care unit (ICU) discharge. Survival (time-to death) curves were built using the Kaplan Meier methods. Multivariate analyses were performed by logistic regression to identify factors associated with AKI and Cox regression to explore the association between AKI and in-hospital mortality. The significance level of the p-value was set at 0.05.

The median(IQR) sequential organ failure assessment score (SOFA) score and mean age of patients (215) including in our cohort were respectively 3(2-4) and 58.9 ± 14.9 years. The incidence of AKI was 28.4% with stages 1, 2, or 3 AKI accounted for 39.3%, 11.5%, and 49.2%, respectively. Hemodialysis was required in 16 out 215 (7.4%) patients. Dyspnea (adjusted odds ratio (aOR):2.27 [1.1--4.57] p = 0.021), SOFA ≥5 (aOR:3.11[1.29-7.53] p = 0.012), AST/ALT ratio (aOR: 1.53 [1.09-1.79] p = 0.015), N/L ratio (aOR:2.09 [1.09-3.20] p = 0.016), mechanical ventilation (aOR: 3.20 [1.66-10.51] p = 0.005) and Amikacin (aOR: 2.91 [1.37-6.18] p = 0.006) were the main factors associated with AKI. Patients with AKI had a mortality rate of 52.5% and 67.2% of the survivors did not recover kidney function at the end of hospitalization. Adjusted Cox regression analysis revealed that COVID-19-associated AKI was independently associated with in-hospital death (HR:2.96 [1.93-4.65] p = 0.013) compared to non-AKI patients.

AKI was present in three out of ten COVID-19 patients. The most significant factors associated with AKI were dyspnea, SOFA ≥ 5, AST/ALT and N/L ratio, mechanical ventilation and Amikacin. AKI has been associated with an almost threefold increase in overall mortality and seven out of ten survivors did not recover kidney function after AKI.

The COVID-19 pandemic continues to grow around the world and has caused enormous mortality and morbidity. The severity and mortality of coronavirus disease are associated with various comorbidities. The infection fatality rate was reported to be inconsistent with different studies. Therefore, the aim of this study was to assess the magnitude and factors associated with mortality among patients admitted to Eka Kotebe General Hospital, Addis Ababa, Ethiopia. An institutional-based cross-sectional study was conducted at Eka Kotebe General Hospital among patients who were admitted for COVID-19 from January 15, 2021, to June 30, 2021. A total of 393 records of patients were selected by simple random sampling. Data was extracted from compiled data forms where available information was already tabulated. Data was entered and analyzed using SPSS version 25. The determinant factors associated with mortality among COVID-19 patients were identified using bivariate and multivariable logistic regression analysis. A statistical association was declared with multivariable logistic regression using a 95% confidence interval and a P-value of less than 0.05. The proportion of COVID-19 mortality among patients admitted to Eka Kotebe General Hospital was 8.1% (95% CI (5.4-10.8%)). Age >50 years [AOR = 7.91; 95% CI (2.34-25.70)], being male [AOR = 2.09; 95% CI (1.20-3.65)], having diabetes mellitus [AOR = 2.64; 95% CI (1.30-5.35)], having hypertension [AOR = 2.67; 95% CI (1.22-5.88)] and having chronic kidney disease [AOR = 12.04; 95% CI (4.03-14.22)] were determinant factors of COVID-19 mortality. The current study findings revealed that COVID-19 mortality was high among hospitalized COVID-19 patients. Furthermore, age, gender, diabetes mellitus, hypertension, and chronic kidney disease were discovered to be independent predictors of COVID-19 mortality. Therefore, older COVID-19 patients and those with established comorbidities such as hypertension, diabetes, and end-stage renal disease should receive comprehensive preventative efforts, including vaccination.

Globally, patients with diabetes suffer from increased disease severity and mortality due to coronavirus disease 2019 (COVID-19). Old age, high body mass index (BMI), comorbidities, and complications of diabetes are recognized as major risk factors for infection severity and mortality.

To investigate the risk and predictors of higher severity and mortality among in-hospital patients with COVID-19 and type 2 diabetes (T2D) during the first wave of the pandemic in Dubai (March-September 2020).

In this cross-sectional nested case-control study, a total of 1083 patients with COVID-19 were recruited. This study included 890 men and 193 women. Of these, 427 had T2D and 656 were non-diabetic. The clinical, radiographic, and laboratory data of the patients with and without T2D were compared. Independent predictors of mortality in COVID-19 non-survivors were identified in patients with and without T2D.

T2D patients with COVID-19 were older and had higher BMI than those without T2D. They had higher rates of comorbidities such as hypertension, ischemic heart disease, heart failure, and more life-threatening complications. All laboratory parameters of disease severity were significantly higher than in those without T2D. Therefore, these patients had a longer hospital stay and a significantly higher mortality rate. They died from COVID-19 at a rate three times higher than patients without. Most laboratory and radiographic severity indices in non-survivors were high in patients with and without T2D. In the univariate analysis of the predictors of mortality among all COVID-19 non-survivors, significant associations were identified with old age, increased white blood cell count, lym-phopenia, and elevated serum troponin levels. In multivariate analysis, only lymphopenia was identified as an independent predictor of mortality among T2D non-survivors.

Patients with COVID-19 and T2D were older with higher BMI, more comorbidities, higher disease severity indices, more severe proinflammatory state with cardiac involvement, and died from COVID-19 at three times the rate of patients without T2D. The identified mortality predictors will help healthcare workers prioritize the management of patients with COVID-19.

The mortality of COVID-19 patients has left the world devastated. Many scoring systems have been developed to predict the mortality of COVID-19 patients, but several scoring components cannot be carried out in limited health facilities. Herein, the authors attempted to create a new and easy scoring system involving mean arterial pressure (MAP), PF Ratio, or SF ratio-respiration rate (SF Ratio-R), and lymphocyte absolute, which were abbreviated as MPL or MSLR functioning, as a predictive scoring system for mortality within 30 days for COVID-19 patients. Of 132 patients with COVID-19 hospitalized between March and November 2021, we followed up on 96 patients. We present bivariate and multivariate analyses as well as the area under the curve (AUC) and Kaplan-Meier charts. From 96 patients, we obtained an MPL score of 3 points: MAP < 75 mmHg, PF Ratio < 200, and lymphocyte absolute < 1500/µL, whereas the MSLR score was 6 points: MAP < 75 mmHg, SF Ratio < 200, lymphocyte absolute < 1500/µL, and respiration rate 24/min. The MPL cut-off point is 2, while the MSLR is 4. MPL and MSLR have the same sensitivity (79.1%) and specificity (75.5%). The AUC value of MPL vs. MSLR was 0.802 vs. 0.807. The MPL ≥ 2 and MSLR ≥ 4 revealed similar predictions for survival within 30 days (p < 0.05). Conclusion: MPL and MSLR scores are potential predictors of mortality in COVID-19 patients within 30 days in a resource-limited country.

This meta-analysis aimed to establish a clinical evidence base for respiratory rate (RR) as a single predictor of early-onset COVID-19. The review also looked to determine the practical implementation of mobile respiratory rate measuring devices where information was available.

We focused on domestic settings with older adults. Relevant studies were identified through MEDLINE, Embase, and CENTRAL databases. A snowballing method was also used. Articles published from the beginning of the COVID-19 pandemic (2019) until Feb 2022 were selected. Databases were searched for terms related to COVID-19 and respiratory rate measurements in domestic patients.

A total of 2,889 articles were screened for relevant content, of which 60 full-text publications were included. We compared the Odds Ratios and statistically significant results of both vital signs.

Multinational studies across dozens of countries have shown respiratory rate to have predictive accuracy in detecting COVID-19 deterioration. However, considerable variability is present in the data, making it harder to be sure about the effects. There is no meaningful difference in data quality in terms of variability (95% CI intervals) between vital signs as predictors of decline in COVID-19 patients. Contextual and economic factors will likely determine the choice of measurement used.

Little information is available on COVID-19 in Africa and virtually none is from humanitarian and more resource-constrained settings. This study characterizes hospitalized patients in the African humanitarian contexts of Juba, South Sudan and North and South Kivu in Eastern Democratic Republic of the Congo. This observational cohort was conducted between December 2020 and June 2021. Patients presenting for care at five facilities or referred from home-based care by mobile medical teams were eligible for enrollment and followed until death or recovery. Disease progression was characterized for hospitalized patients using survival analysis and mixed effects regression model to estimate survival odds for patient characteristics and treatments received. 144 COVID-19 cases enrolled as hospitalized patients were followed to recovery/death. The observed mortality proportion among hospitalized patients was 16.7% (CI: 11.2-23.3%); mortality was three times higher in South Sudan, where patients presented later after symptom onset and in worse conditions. Age and diabetes history were the only patient characteristics associated with decreased survival; clinical status indicators associated with decreased survival included fever, low oxygen level, elevated respiratory and pulse rates. The only therapy associated with survival was non-invasive oxygen; invasive oxygen therapies and other specialized treatments were rarely received. Improving availability of oxygen monitoring and proven COVID-19 therapies in humanitarian and resource-poor settings is critical for health equity. Customizing training to reflect availability of specific medications, therapies and operational constraints is particularly important given the range of challenges faced by providers in these settings.