Van Nynatten LR, Nabieva K, Barber G, Moroniti JJ, Iansavitchene A, Prager R, Slessarev M, Basmaji J, Leligdowicz A. Characterizing the molecular landscape of venous congestion. World J Crit Care Med 2026; 15(3): 122062 [DOI: 10.5492/wjccm.122062]
Corresponding Author of This Article
Aleksandra Leligdowicz, MD, PhD, Department of Critical Care Medicine, Western University, Robarts Research Institute, 100 Perth Dr, Room 4220, Ontario N6A5A5, Canada. aleks.leligdowicz@lhsc.on.ca
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Van Nynatten LR, Nabieva K, Barber G, Moroniti JJ, Iansavitchene A, Prager R, Slessarev M, Basmaji J, Leligdowicz A. Characterizing the molecular landscape of venous congestion. World J Crit Care Med 2026; 15(3): 122062 [DOI: 10.5492/wjccm.122062]
Logan R Van Nynatten, Karina Nabieva, Gemma Barber, Jonathan J Moroniti, Alla Iansavitchene, Ross Prager, Marat Slessarev, John Basmaji, Aleksandra Leligdowicz, Department of Critical Care Medicine, Western University, Ontario N6A5A5, Canada
Author contributions: Leligdowicz A, Van Nynatten LR, Basmaji J, Slessarev M, Prager R and Iansavitchene A contributed to study conception and design; Iansavitchene A, Barber G and Moroniti JJ contributed to data extraction; Van Nynatten LR and Nabieva K contributed to data extraction, data interpretation, data analysis, data presentation and manuscript preparation; Van Nynatten LR and Leligdowicz A wrote the manuscript; all authors participated in manuscript preparation and data review.
AI contribution statement: AI was not used in the extraction of data or preparation of the manuscript. No AI tool was involved in the generation of research data, interpretation of results, or formulation of conclusions.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Corresponding author: Aleksandra Leligdowicz, MD, PhD, Department of Critical Care Medicine, Western University, Robarts Research Institute, 100 Perth Dr, Room 4220, Ontario N6A5A5, Canada. aleks.leligdowicz@lhsc.on.ca
Received: April 8, 2026 Revised: June 16, 2026 Accepted: July 16, 2026 Published online: September 9, 2026 Processing time: 141 Days and 12.1 Hours
Abstract
BACKGROUND
Venous congestion is a pathologic state caused by reduced arteriovenous gradients that promote injurious tissue edema. Venous congestion can be due to etiologies such as decompensated cardiac disease, renal failure, or iatrogenic fluid administration. However, the underlying pathobiology of venous congestion is poorly investigated, particularly in critical illness. We conducted a scoping review to identify candidate circulating proteins potentially associated with venous congestion pathobiology.
AIM
To identify circulating proteins associated with the pathobiology of venous congestion.
METHODS
The MEDLINE and EMBASE databases were searched for articles relevant to venous congestion. Studies were included if they: (1) Investigated human adult subjects ≥ 18 years of age; (2) Measured plasma or serum proteins in disease states with reported measures of venous congestion; and (3) Reported clinical or ultrasound measures of assessing venous congestion. Preferred Reporting Items for Systematic Reviews and Meta-analysis extension for scoping reviews guidelines were used.
RESULTS
A total of 3860 abstracts were eligible for screening, of which 171 manuscripts underwent full-text review, and 145 texts met inclusion criteria. The median number of circulating proteins measured was 2 (interquartile range: 1-3). Most studies (116, 80%) reported measures of venous congestion in the context of cardiac disease. Five studies (3%) were performed in a critical care setting. Significant variability was noted in the reported measures of venous congestion, with physical examination often used to presume the presence of venous congestion (45% of studies). Less than 30% of studies had the objective of investigating circulating proteins, and less than 15% of studies aimed to characterize biology of venous congestion. The candidate circulating plasma proteins measured included proteins related to myocardial function, endothelial function, and inflammation.
CONCLUSION
We present the first scoping review identifying circulating proteins with a possible role in mediating venous congestion at a molecular level. To date, no robust studies have comprehensively investigated the biology of venous congestion. These data provide a foundation for further studies of the biological mechanisms of venous congestion. Understanding these mechanisms may assist in the measurement of responses to volume resuscitation, stratification in clinical trials focusing on appropriate volume administration and removal, and the identification of novel therapies that target pathways implicated in this deleterious condition.
Core Tip: Clinicians can increasingly identify venous congestion, but they still do not understand its pathobiology. Although congestion is recognized across multiple disease states, the existing literature is largely confined to isolated protein measurements in congested cardiac populations, leaving its broader molecular biology poorly understood. This review reveals a substantial translational gap between physiologic recognition and biological understanding of venous congestion, highlighting the need for high-dimensional molecular studies to define its mechanisms and therapeutic targets.
Citation: Van Nynatten LR, Nabieva K, Barber G, Moroniti JJ, Iansavitchene A, Prager R, Slessarev M, Basmaji J, Leligdowicz A. Characterizing the molecular landscape of venous congestion. World J Crit Care Med 2026; 15(3): 122062
Systemic venous congestion is a well-documented yet poorly understood pathophysiologic state caused by increased venous pressure that mediates pathogenic retrograde venous flow[1-3]. This results in reduced arteriovenous gradients across vital organs as venous pressure increases[1]. Several pathologies cause venous congestion, including acute or chronic congestive heart failure[4], pulmonary hypertension[5], vascular thrombosis[6] and acute or chronic kidney disease[7]. In addition, iatrogenic administration of excessive intravenous fluids in acute shock, including sepsis or trauma[8], may promote venous congestion, especially in patients with known pathologies associated with this state. Venous congestion may manifest clinically as pleural effusions, ascites, subcutaneous tissue edema and jugular venous distension. Importantly, venous congestion is a distinct entity from volume status[9]. Volume status is a broader term describing the overall amount of fluid within the body, including intravascular and extravascular compartments.
No standardized method exists for quantifying venous congestion. However, elevated right-sided cardiovascular pressures, leading to deleterious retrograde venous pressure characterizing venous congestion can be quantified using tools such as point-of-care ultrasound[1-3]. Venous congestion is commonly reported via venous excess ultrasound (VExUS) scores[1-3]. At the time of intensive care unit (ICU) admission, mild, moderate or severe venous congestion as measured via doppler ultrasound (VExUS score) is present in 37%, 16% and 6% of patients, respectively[10], implying that over one-half of ICU patients have some degree of venous congestion. However, the assessment of venous congestion using ultrasound is not routinely employed to quantify venous congestion in critical illness, requires technical skill, and has not yet been validated for all disease states[11,12].
The impact of venous congestion on patient outcomes, especially in critical illness, has only recently been recognized[2,3,13]. When present, venous congestion impairs organ perfusion[1,14], resulting in the accumulation of fluid within the vasculature, interstitial edema, and dysfunction of vital organs such as the heart, lungs, kidneys, liver and bowel[1,15]. For instance, in post-cardiac surgical patients, venous congestion increases the risk of renal injury and increases the need for renal replacement therapy[1,2,13,16]. Venous congestion may mediate end-organ dysfunction, while aggressive early “decongestion” using volume removal with diuretics or renal replacement therapy, and right heart optimization with inotropy may offer clinical benefit[17,18]. However, the relationship between venous congestion and volume status is an ongoing area of research[9].
When venous congestion becomes clinically evident, it is often accompanied by advanced organ failure. Therefore, early recognition of this state may be paramount to prevent organ dysfunction, morbidity, and death. The biological mechanisms leading to this state are largely unknown. Therefore, characterizing the pathobiology of this condition may identify circulating protein biomarkers that can detect venous congestion before clinical manifestations. Moreover, although various states can cause venous congestion, it still remains unknown whether all states of venous congestion should be treated in a similar manner. Characterizing circulating markers in different etiologies of congestion may inform whether underlying causes of venous congestion are prognostically unique.
This scoping review presents the current evidence on circulating blood proteins quantified in studies that concomitantly reported measures of venous congestion. This may yield insight into the molecular pathobiology of this condition. Understanding biological determinants of venous congestion could enable its early recognition, act as an adjuvant to the use of the ultrasound methods to visualize this state, and provide potential novel treatment options that focus on the molecular mechanisms that contribute to its progression.
MATERIALS AND METHODS
Search strategy
The study protocol for the scoping review was registered on Open Science Framework. Ethics approval was not required. We reported our findings based on the Preferred Reporting Items for Systematic Reviews and Meta-analysis extension for scoping reviews guideline.
An information scientist assisted with the search strategy criteria (Supplementary Table 1). We included articles that reported plausible measures of venous congestion (clinical or ultrasound) and measured circulating proteins in plasma or serum. MEDLINE and EMBASE databases were searched for articles published in English from January 2013 to present. The search included articles investigating biomarkers in the context of diagnosis, prognosis, and/or hospitalization. Conference abstracts presented at the American Thoracic Society, European Society of Intensive Care Medicine and the American Heart Association from January 2018 to present were also reviewed.
Study selection
Inclusion criteria: (1) Investigated human subjects ≥ 18 years old; (2) Measured circulating plasma or serum proteins; and (3) Utilized and reported clinical or ultrasound measures of venous congestion. Clinical diagnoses suggestive of venous congestion included states such as cardiorenal and cardiointestinal syndromes, advanced heart failure with congestion, pulmonary hypertension with right-sided circulatory dysfunction (edema, increased jugular venous pressure), or renal failure with physical exam findings of venous congestion (elevated jugular venous pressure, ascites, edema, pleural effusion). Studies that reported physical exam features of possible venous congestion (elevated jugular venous pressure, ascites, peripheral edema, auscultatory crackles, etc.) were also included. Hemodynamic measures included central venous pressure and ultrasonographic measures of venous congestion (i.e. inferior vena cava dilation, hepatic vein or portal vein pulsatility, or renal venous stasis index).
Exclusion criteria: (1) Investigated non-human subjects or human subjects < 18 years old; (2) Did not measure plasma or serum proteins/biomarkers or measured transcriptomics (RNA) or epigenetics (DNA); (3) Measured proteins in disease states without reporting measures of venous congestion (i.e., stable heart failure, cirrhosis, or chronic kidney disease without physical exam findings or ultrasound parameters identifying venous congestion); and (4) Were narrative or systematic reviews, opinion pieces, case reports, educational studies or editorial letters.
The Covidence systematic review software (Veritas Health Innovation, Australia) was utilized for abstract and full-text screening of articles from EMBASE and MEDLINE meeting inclusion criteria. Abstracts were screened in duplicate by two independent authors. Eligible abstracts underwent full-text review by authors in duplicate. Any discrepancies or disagreements were subject to consensus discussion. Conference abstracts were screened using the same methods.
Data extraction
Article data were extracted in duplicate, and discrepancies were resolved through consensus discussion. Data of interest included: Study authors, year of publication, study type, study design (prospective, retrospective), research objectives, location (inpatient, outpatient), number of subjects, study subgroups, the use of a validation cohort, method of protein quantification, timing of biomarker measurement during hospitalization, how congestion was measured, biomarkers quantified, outcome used in biomarker associations (i.e., presence of congestion, renal injury, disease severity, mortality, prognosis, etc.), and study conclusions. In keeping with PRISMA-SCR guidelines[19], studies were not assessed for applicability or risk of bias. Given the extent of studies identified, and difficulty to separate or group such exploratory studies into discrete categories, all studies are reported in Supplementary Table 1.
Outcomes and analysis
The primary objective was to review the literature describing the circulating human plasma or serum proteins measured in disease states with reported measures of venous congestion. The secondary objective was to hypothesize potential molecular pathways implicated in venous congestion. A qualitative discussion was performed for primary and secondary questions. Descriptive statistics, count data and percentages were used to convey relevant demographic or biomarker information. Data extraction was done in Microsoft Excel (Washington, United States). Data analysis and presentation were performed in GraphPad Prism (Version 8.4.0; GraphPad Software, San Diego, CA, United States) and bioRender. The Human Protein Atlas was used to characterize the cellular and tissue expression patterns of identified proteins (methodology reported in Supplementary Table 1).
The RNA data was used to cluster genes according to their expression across single cell types. Clusters contain genes that have similar expression patterns, and each cluster has been manually annotated to describe common features in terms of function and specificity.
RESULTS
Study characteristics
A total of 3860 abstracts were identified, with 171 undergoing full-text review, of which 145 reported clinical or ultrasound measures of potential venous congestion and quantified circulating proteins (Figure 1 and Supplementary Table 1). Most identified studies were prospective (88 studies, 61%), some were retrospective (46 studies, 32%), and a minority were designed as cross-sectional (five studies, 3.4%), case-control (two studies, 1.4%), or contained data from mixed study designs (five studies, 3.4%). Retrospective studies largely consisted of secondary analyses of clinical trials whereby plasma biomarkers were quantified in a subset of patients with available biological samples to explore a biological association with the outcome of interest. Prospective studies were often observational and characterized the prognostic value of clinical parameters with disease severity or determined associations between clinical outcomes and protein markers.
Figure 1 Preferred reporting items for systematic reviews and meta-analysis extension for scoping reviews flow diagram.
Most studies (57, 39%) investigated inpatients admitted under unspecified services, 36 (25%) were in the outpatient setting, 17 studies (12%) included both inpatient and outpatient settings, 10 studies (7%) were in cardiology units, and only five studies (3.4%) were in ICU (Table 1). The study sizes varied from less than 100 (44, 30%), to 100-1000 (79, 55%), to over 1000 (22, 15%) participants, with a median of 164 subjects [interquartile range (IQR): 84-442]. Baseline characteristics of these studies are reported in Table 1.
Table 1 Characteristics of included studies, n (%)/median (interquartile range).
The majority of studies (116, 80%) reported measures of venous congestion in relation to cardiac dysfunction, largely heart failure (Table 2 and Supplementary Table 1). Other disease states included pulmonary disease (7 studies, 5%), gastrointestinal disease (10 studies, 7%), renal disease (8 studies, 5.5%), or peripheral congestion (4 studies, 2.8%). Supplementary Figure 1 delineates the disease state and method of measuring venous congestion.
Table 2 Disease state under study and method of congestion measurement, n (%).
Venous congestion was identified via clinical assessment (physical exam) in 65 studies (45%), and approximately 30% of the studies graded congestion using a physical exam-based method of adjudicating or scoring congestion. Clinical congestion adjudication or scoring predominantly measured jugular venous pressure, auscultating for pulmonary crackles or S3 gallop, and identifying abdominal ascites or peripheral edema, whereby those patients with increasing numbers of such findings were presumed to be congested. None of the studies distinguished congestion from volume status. Cardiac ultrasound (often assessing RV function or filling pressures) was used in 56 studies (38.6%), lung ultrasound (often assessing for B-lines or pleural fluid) was used in 24 studies (16.6%), hepatic ultrasound (often assessing doppler waveforms) was used in 9 studies (6.2%), and renal ultrasound (often assessing doppler waveforms) was used in 5 studies (3.4%). These findings are summarized in Table 2.
Protein quantification
The median number of proteins quantified was 2 (IQR: 1-3). Most studies quantified a single protein (68 studies, 47%) or 2-10 proteins (68 studies, 47%). Seven studies quantified 11-100 proteins, and only two studies quantified more than 100 proteins. Of studies that reported the protein quantification method, 51% relied on standard immunoassays (such as enzyme linked immunosorbent assays, radioimmunoassays, or chemiluminescence assays). Six studies used high-throughput O-link proximity extension analysis for biomarker quantification. 44% of studies did not report the protein quantification method. These data are summarized in Table 1 and Supplementary Table 1.
Only 43 studies (30%) had the primary objective of characterizing the relationship between circulating protein markers and the disease state under study. The remainder of the studies reported proteins in association with a clinical question of interest however their primary objective was not the characterization of biology. Only 10 studies used a validation cohort to confirm the findings of the derivation cohort. Less than 15% of studies measured proteins to elucidate the biology of clinical congestion status.
Venous congestion in critical illness
Only five studies characterized venous congestion in the ICU. None of these studies used high-throughput protein quantification assays, and only two studies investigated biomarkers in relation to clinical congestion. Four studies measured a single protein (NTproBNP or FABP2) and one study measured two proteins (hs-cTnT and NGAL). As such, only four circulating proteins have been studied in association with venous congestion in critical illness. All studies reported ultrasound parameters to characterize congestion.
Associations between protein markers and venous congestion
Eighty circulating markers potentially associated with venous congestion were identified (Supplementary Table 2), of which 75 distinct proteins were identified, as some studies measured different forms of the same protein (i.e., NTproBNP and BNP). Proteins reported by five or more studies are shown in Figure 2. Cardiac disease was the most frequent disease state in which circulating proteins were quantified (Figure 2 and Supplementary Figure 2). NTproBNP or BNP were the most frequently reported proteins (Figure 2 and Supplementary Table 2). CA-125, Troponin, C-reactive protein, Endothelin-1 (ET-1), bioADM, CD146, fibroblast growth factor, ST2, vascular endothelial growth factor, interleukin-6, tumor necrosis factor-alpha, alkaline phosphatase, aspartate aminotransferase, Cystatin C, FABP, GDF15, GGT, MRproANP, P4NP7S, Herceptin2/4, hepatocyte growth factor, IGFBP7, Kallikrin, NGAL, TNFR1, SCF/KITLF, and VCAM-1 each had two or more studies reporting results on their concentration and study outcomes (Supplementary Table 2). Detailed study characteristics for the candidate markers are presented in Supplementary Table 1. These data suggest that myocardial function, endothelial function and inflammation may be associated with venous congestion.
Figure 2 Top circulating markers in studies with measures of venous congestion.
Circulating markers reported by > 3% of studies (5 or more studies) are shown. Cardiovascular and endothelial signaling proteins were the most frequently reported proteins. The bar graph demonstrates the number of studies (Y-axis) that reported clinical associations or findings with the identified proteins (X-axis). The proportion (%) of the 145 studies that report each protein is included above the green bars. The pie charts represent the disease states in which the proteins were quantified (cardiac: Dark blue; pulmonary: Light blue; renal: Beige; hepatic/abdominal: White; peripheral congestion: Grey). A complete list of all reported circulating markers with associations with results or outcomes in studies with measures of venous congestion is shown in Supplementary Table 2. BNP: B-type natriuretic peptide; ET-1: Endothelin 1; VEGF: Vascular endothelial growth factor; CRP: C-reactive protein; IL-6: Interleukin-6; TNF: Tumor necrosis factor; FGF: Fibroblast growth factor.
Molecular mechanisms of circulating proteins in venous congestion
The Human Protein Atlas[20] was searched to characterize cell-type specific expression patterns and to identify molecular mechanisms that may be implicated in venous congestion pathobiology (Figure 3). Tissue profile, subcellular localization, predicted location, clustering and functional data are described in Supplementary Table 2. Details of data extraction from the Human Protein Atlas are discussed in the Supplementary Table 1. The tissue expression of the proteins identified in this study was variable. Although most proteins were ubiquitously expressed throughout different organ systems, gastrointestinal and hematologic/immune systems (24% and 16%, respectively) were the most common sites that express the 75 proteins identified in our scoping review. Many proteins had multiple sites of tissue expression or subcellular localization. Of the 75 circulating proteins, 70% were classified as secreted, 40% as intracellular, and 29% as anchored to cell membranes. The presence of intracellular and membrane-anchored proteins in the circulation may suggest a pathologic state and provide insight into the pathobiology of venous congestion. Figure 4 provides a conceptual schematic of venous congestion pathobiology, including markers that were identified in this study.
Figure 3 Tissue expression, cellular localization, and predicted location of all identified circulating proteins.
The Human Protein Atlas was used to characterize protein expression across tissues and cells for those circulating proteins that had associations with study results or outcomes in studies with measures of venous congestion (those markers from Supplementary Table 2). Data are presented as a percentage (%) of the 75 unique proteins. Some proteins had multiple localizations. A: Characterization of organ-specific expression; B: Subcellular location based on immunohistochemistry staining; C: Protein localization (secreted, membrane-attached, or intracellular).
Figure 4 Conceptual model of multisystem molecular dysregulation in venous congestion.
Multiple pathobiologic mechanisms of venous congestion may be associated with the identified candidate circulating protein biomarkers. In venous congestion, elevated filling pressures in the heart may lead to myocardial stress (↑B-type natriuretic peptide, troponin, interleukin 1 receptor-like 1). This may contribute to endothelial dysfunction (↑endothelin 1, vascular endothelial growth factor, CD146, CA125, angiopoietin, vascular cell adhesion molecule 1), promoting vascular permeability and inflammation. Tissue edema (↑adiponectin, 7S domain of collagen type IV and hyaluronic acid) and systemic inflammatory processes (↑adrenomedullin, C-reactive protein, interleukin-6, tumor necrosis factor, fibroblast growth factor) may exacerbate organ dysfunction and, left unresolved, can lead to multiorgan failure involving the lungs, brain, liver, and kidneys (↑aspartate aminotransferase, alkaline phosphatase, gamma glutamyltransferase, Cystatin C, neutrophil gelatinase associated lipocalin, and hepatocyte growth factor). This interconnected network highlights the complex nature of venous congestion and its systemic effects that are yet to be investigated in critical illness. BNP: B-type natriuretic peptide; ST2: Interleukin 1 receptor-like 1; ET-1: Endothelin 1; VEGF: Vascular endothelial growth factor; CA125: Cancer antigen 125; ANGPT: Angiopoietin; VCAM: Vascular cell adhesion molecule 1; ADM: Adrenomedullin; CRP: C-reactive protein; IL-6: Interleukin-6; TNF: Tumor necrosis factor; FGF: Fibroblast growth factor; AST: Aspartate aminotransferase; ALP: Alkaline phosphatase; GGT: Gamma glutamyltransferase; NGAL: Neutrophil gelatinase associated lipocalin; HGF: Hepatocyte growth factor; P4NP7S: 7S domain of collagen type IV; HA: Hyaluronic acid.
DISCUSSION
This is the first scoping review of the current understanding of circulating proteins associated with the biological mechanisms of venous congestion. We demonstrate a paucity of studies investigating venous congestion, especially in critical illness. Most studies investigate a small number of proteins, and few studies have used high-throughput proteomics technologies. Importantly, a significant proportion of studies rely on physical examination to identify congestion, failing to differentiate between volume status and venous congestion. Moreover, most data is exploratory and observational in nature, emphasizing the need for hypothesis-driven studies that characterize venous congestion pathobiology.
Our inference of venous congestion pathobiology can mainly be extrapolated from studies conducted in the context of cardiac disease, as 80% of the studies identified by this scoping review focused on this patient population. Despite the increasing clinical relevance of states of venous congestion[10,12,21], we identified a relative paucity of studies that investigate the biology of this state. As most studies have focused on heart failure, limited data are available on other relevant congestion states, such as iatrogenic volume resuscitation in the context of shock, congestive nephropathy, congestive hepatopathy or cardiointestinal syndrome. Moreover, in critical illness, the implications of venous congestion have only recently begun to be characterized[2,3,13]. Seventy-five proteins were characterized in association with studies that have reported measures of venous congestion. However, their causal relationship with venous congestion remains uncertain, and it is unknown whether the pathobiology of decompensated heart failure is distinct from venous congestion that is not primarily due to heart failure.
With the increased use of point-of-care ultrasound in the intensive care setting[22], measurement of venous congestion is of increasing interest in critical illness[10,21,23,24]. A recent meta-analysis of 31 studies and over 30000 patients investigating the impact of a cumulative positive fluid balance during ICU stay on patient outcomes suggests that fluid overload is associated with increased mortality, acute kidney injury and respiratory failure[17]. In contrast, a fluid-restrictive strategy in acute respiratory distress syndrome is associated with an improved oxygenation index, lung injury scores, decreased duration of mechanical ventilation and more ICU-free days[18]. Although venous congestion is distinct from volume status, those patients that are hypervolemic often experience venous congestion. As such, clinicians focus on prevention of venous congestion by limiting fluid administration and/or reversal of this state by volume removal. Moreover, venous congestion is a mediator of congestive heart failure[25] and contributes to its progression[4,26]. In a cohort of patients with New York Heart Association class IV heart failure, lack of clinical congestion was an independent predictor of survival[27]. In advanced heart failure, venous congestion contributes to extra-cardiac organ injury, specifically worsening renal function and mortality[16,28]. However, the relative contribution of venous congestion to organ dysfunction and its biological mechanisms remain unknown.
Despite the relevance of venous congestion in critical illness, we identified only five studies which focused on the translational biology of venous congestion in ICU, and only two were dedicated biomarker studies, with the main study objective being the characterization of circulating proteins that may be implicated in venous congestion. To date, high-dimensional protein quantification has never been used to characterize circulating proteins associated with venous congestion in critical illness. All studies in the intensive care setting reported ultrasound parameters to measure congestion. This emphasizes the increasing use of ultrasonography to identify venous congestion in the ICU. Future studies elucidating the biology of venous congestion in critical illness should use high-throughput protein quantification methods complemented by ultrasound data to characterize the pathobiology of venous congestion.
Seventy-five distinct proteins were associated with clinical parameters, results or outcomes of interest in studies that reported measures of venous congestion. These proteins can be grouped into pathways related to myocardial function, endothelial function, and inflammation. The most frequently measured proteins were the natriuretic peptides NTproBNP and BNP, particularly in congestive heart failure. Brain natriuretic peptide, or BNP, is released from cardiac myocytes in response to ventricular stretch, hypoxia and neurohormonal activation[29]. Upon release, the natriuretic peptide is cleaved into the prohormone NT-proBNP and the biologically active BNP[29]. Natriuretic peptides downregulate sympathetic drive and renin-angiotensin-aldosterone signalling, facilitating diuresis and improving peripheral vascular resistance, thereby optimizing cardiac preload and afterload[30-32]. Natriuretic peptides also serve as clinical prognostic biomarkers for heart failure and diastolic dysfunction[33]. As such, NTproBNP or BNP are circulating protein markers implicated in venous congestion, including in the ICU setting[34-36].
Proteins representative of inflammation, endothelial and connective tissue injury have also been quantified in disease states associated with venous congestion. These include adrenomedullin, CA-125, CD-146 and ET-1, and are specifically relevant to congestion in heart failure[37]. Adrenomedullin is a protein ubiquitously expressed in endothelial and vascular smooth muscle cells[38]. It is synthesized as a prohormone that undergoes cleavage to form proAM, mid-regional proadrenomedullin, and C-terminal proAM (adrenotensin). Adrenomedullin mediates vasodilation, vascular tone and integrity via formation of nitric oxide[39], and has been implicated in cardiovascular disease and sepsis pathophysiology[40]. CA-125 is a glycoprotein expressed on surfaces of epithelial cells in tissues such as pericardium, pleura, peritoneum, and reproductive organs[41], and is a validated biomarker of ovarian cancer[42]. CA-125 is released from serosal surfaces in states of increased hydrostatic pressure and inflammation[37,43]. CD146 is a glycoprotein expressed on pericytes, smooth muscle and endothelial cells in blood vessels of all sizes[37]. It is implicated in vascular permeability, angiogenesis, structure and regeneration[44]. It is overexpressed in states of inflammation and endothelial dysfunction, and is implicated in renal disease, congestion, pregnancy loss, and malignancy[45-49]. ET-1 is the most abundant protein of the endothelin protein family expressed in endothelial cells after being processed from its preproendothelin precursor[50]. ET-1 is a potent vasoconstrictor implicated in neurohormonal activation, inflammation and sepsis[50,51]. It is associated with increased pulmonary arterial and wedge pressures, and endothelin inhibitors are an approved treatment for pulmonary hypertension[52]. ET-1, together with the vasodilator nitric oxide, regulates vascular function through ETA and ETB receptors, with shear stress, cytokines and free radicals stimulating its secretion[53]. Cumulatively, these proteins have biological plausibility and their association with the pathobiology of venous congestion warrants validation in larger observational cohorts, especially in the ICU setting.
Notably, natriuretic peptides and CA-125 may reflect distinct and complementary dimensions of congestion. BNP and NT-proBNP are released from cardiomyocytes in response to ventricular wall stress and elevated filling pressures, and thus predominantly index intravascular pressure and left-sided cardiac dysfunction[29]. CA-125, by contrast, is released from serosal mesothelial cells in response to extravascular fluid accumulation and inflammation, and is more closely associated with systemic congestion, pleural effusion, and right-sided cardiac dysfunction[37,43]. Consistent with these complementary biologies, the combination of CA-125 and NT-proBNP improves risk discrimination in acute heart failure beyond either marker alone, and patients with simultaneous elevation of both markers exhibit the highest risk of cardiovascular mortality, all-cause mortality, and heart failure rehospitalization[54-57]. Whether this dual-compartment approach extends to venous congestion in critical illness (where neither marker has been studied in combination) remains an open question well suited to the high-throughput, multi-marker strategies advocated by this review. These findings are summarized in Table 3.
To investigate if portal vein flow pulsatility identifes patients with congestion at risk for delirium
Post-cardiac surgery
US: Portal vein flow pulsatility
NTproBNP
Portal vein pulsatility was associated with cognitive dysfunction, asterixis, and delirium. ↑ NTproBNP levels were associated with cognitive dysfunction
To compare IVC diameter and pro-BNP for IV fluid administration in critically ill patients on intermittent positive pressure ventilation
Congestive heart failure
Echo: IVC diameter
NTproBNP
↑ IVC size associated with NTproBNP in patients with heart failure, and may be beneficial in discriminating between congestion and non-congestion in heart failure
↑ FABP was associated with worse clinical outcomes (death, transplant or LVAD placement); No association between FABP and right sided filling pressures or with echocardiographic parameters suggesting venous congestion
To investigate arterial and venous renal doppler in acute decompensated precapillary pulmonary hypertension
Pulmonary hypertension/acute right heart failure
US: IRVF, RVSI, RRI, Echo: Routine parameters, TAPSE, tv s’, E/A, VTI, RHC: CVP, mPAP, PAWP, RAP, CI
NTproBNP
↑ RRI was associated with age, hypertension, congestion (RAP and renal pulse pressure), cardiac function (TAPSE, VTI), systemic pressure and NTproBNP. ↑ RVSI was associated with congestion (high CVP, RAP, renal pulse pressure), right cardiac function (TAPSE), severe TR and systemic pressures
To assess the utility of NTproBNP, NGAL, and hs-cTNT for prediction and detection of congestive AKI
Cardiac surgery/congestive nephropathy
Echo: RV FAC, RHC: CVP, CI, PCWP
hs-cTnT, NTproBNP, NGAL
Baseline and postoperative NTproBNP, postoperative hs-cTnT, and change in hs-cTnT predicted AKI caused by congestion. Congestive AKI was associated with duration of mechanical ventilation and hospital/ICU length of stay
In addition, over 50% of the proteins identified by this scoping review were described by single reports. As such, it is impossible to make definitive conclusions about the association between these proteins and the pathobiology of venous congestion. Moreover, there were no mechanistic studies that characterize molecular mechanisms related to these proteins. This highlights an opportunity to use high-throughput techniques to measure a greater breadth of proteins representative of immune signaling, endothelial and connective tissue injury and other relevant pathways that may characterize the biology of venous congestion.
Several limitations must be considered when interpreting this scoping review. First, a minority (< 15%) of studies identified by the scoping review aimed to identify circulating protein biomarkers to characterize the pathophysiology of venous congestion. Most studies aimed to characterize either treatment efficacy or prognosticate the disease state by measuring circulating proteins, but did not specifically attempt to characterize venous congestion biology. Second, most studies were exploratory and observational in nature, lacking a robust study design to characterize biomarkers of venous congestion. Almost half of the studies did not report their methodology for protein quantification. Third, although all studies included clinical or ultrasound measurements of congestion, there is no consensus on how to identify venous congestion. Hence, the magnitude of the contribution of proteins potentially involved in the pathobiology of venous congestion is uncertain. Several studies relied on physical exam features and as such, could not make a distinction between volume status and venous congestion. Therefore, it is impossible to ascertain whether circulating proteins in these studies represent changes in volume status or venous congestion or whether they reflect other pathophysiology relevant to the underlying disease. Fourth, most studies investigated patients with cardiac pathology, and as such, the understanding of the pathobiology of venous congestion is skewed toward the pathophysiology of heart failure, which may be distinct from other etiologies of venous congestion.
CONCLUSION
There is a paucity of robust studies that characterize the biological mechanisms of venous congestion. Natriuretic peptides are most consistently characterized in states of venous congestion. The roles of other molecular pathways are unknown, and the biological mechanisms of venous congestion remain poorly characterized. Understanding these mechanisms may assist clinicians in measuring responses to volume resuscitation, stratifying patient clinical trials, and identifying novel drugs that target pathways implicated in this deleterious condition in critically ill patients.
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