---
title: "Infection Does Not Impair Decongestion or Short-Term Kidney Outcomes in Cardiorenal Syndrome Type 1"
id: "plos-one-11-impact-of-infection-on-decongestion-and-kidney-outcomes-in-patients-with"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-11-impact-of-infection-on-decongestion-and-kidney-outcomes-in-patients-with"
content_type: "clinical_feed_article"
specialty: "Cardiology"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355608"
published_at: "2026-08-07T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Infection Does Not Impair Decongestion or Short-Term Kidney Outcomes in Cardiorenal Syndrome Type 1
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-one-11-impact-of-infection-on-decongestion-and-kidney-outcomes-in-patients-with
- **Specialty:** [Cardiology](https://medichelpline.com/clinical-feed/cardiology.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355608)
- **Published At:** 2026-08-07T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- This prospective cohort enrolled 256 patients with **cardiorenal syndrome type 1 (CRS1)** hospitalized at a tertiary center between 2022 and 2024. - Infection was present in 72 patients (28.1%), defined as clinical suspicion of bacterial infection plus antibiotic therapy. - Patients with infection had higher baseline congestion markers: median BNP 25,264 pg/mL versus 13,405 pg/mL (p = 0.012) and lower PaO2 (45 vs. 65.5 mmHg, p = 0.019). - Total furosemide exposure during hospitalization was similar between groups (600 mg vs. 580 mg, p = 0.62). - Primary outcome: successful decongestion assessed by symptoms, biomarkers (BNP/CA-125) and POCUS. Successful decongestion occurred in 61.4% of infected patients vs. 59.8% of non-infected patients (p = 0.83). - Infection was not independently associated with successful decongestion (adjusted odds ratio [aOR] 1.28, 95% CI 0.65–2.51). - Secondary outcomes: major adverse kidney events (MAKE) at 10 and 30 days (death, new kidney replacement therapy, or ≥25% eGFR decline). Infection was not independently associated with MAKE-30 (aOR 1.26, 95% CI 0.57–2.79). - Authors conclude that although infection is linked to more severe baseline congestion in CRS1, achieving **decongestion** is feasible and infection did not increase short-term MAKE in this cohort. - Data and study materials are publicly available in a Zenodo repository (DOI: 10.5281/zenodo.20821008). - Funding was provided by the Secretaria de Salud Jalisco and CONAHCYT; authors declared no competing interests.
## Clinical Analysis & Structured Key Points
Impact of infection on decongestion and kidney outcomes in patients with cardiorenal syndrome type 1 | PLOS One Browse Subject Areas ? Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click here . Article Authors Metrics Comments Media Coverage Reader Comments Figures Figures Abstract Background Infections are frequent precipitants of acute decompensated heart failure (ADHF) and may alter decongestive trajectories in patients with cardiorenal syndrome type 1 (CRS1), it may reduce diuretic efficacy and increase the risk of kidney injury. However, the impact of infection on decongestion and kidney outcomes in CRS1 remains unclear. Methods We conducted a prospective cohort study including 256 patients with CRS1 hospitalized at a tertiary center (2022–2024). Patients were stratified by the presence of infection, defined as clinical suspicion plus antibiotic therapy. The primary outcome was successful decongestion, assessed by symptoms, biomarkers (BNP/CA-125), and POCUS findings. Secondary outcomes included major adverse kidney events at 10 and 30 days (MAKE: death, kidney replacement therapy [KRT], or ≥25% eGFR decline). Results Seventy-two patients (28.1%) had infection, presenting with higher BNP (13,405 vs. 25,264 pg/mL, p = 0.012) and lower PaO 2 (45 vs. 65.5 mmHg, p = 0.019). Furosemide exposure was comparable (600 vs. 580 mg, p = 0.62). Successful decongestion occurred in 61.4% of patients with infection vs. 59.8% without infection (p = 0.83). Infection was not independently associated with decongestion (aOR 1.28, 95% CI 0.65–2.51) or MAKE-30 (aOR 1.26, 95% CI 0.57–2.79). Conclusions In CRS1, infection was associated with more severe baseline congestion but did not compromise decongestion rates or increase short-term MAKE. These findings support the notion that achieving decongestion is feasible in patients with ADHF due to infection without an incremental risk of MAKE. Citation: Chávez-Iñiguez JS, Zaragoza JJ, Del Toro RE-, Fong-Maravilla I, Navarro-Blackaller G, Medina-González R, et al. (2026) Impact of infection on decongestion and kidney outcomes in patients with cardiorenal syndrome type 1. PLoS One 21(8): e0355608. https://doi.org/10.1371/journal.pone.0355608 Editor: Antonio Bellasi, Repubblica e Cantone Ticino Ente Ospedaliero Cantonale, SWITZERLAND Received: May 3, 2026; Accepted: July 23, 2026; Published: August 7, 2026 Copyright: © 2026 Chávez-Iñiguez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: Data Availability Statement: The datasets generated and analyzed during the current study are publicly available in the Zenodo repository under the record “SX CARDIORRENAL INFECTADOS FINAL” (DOI: 10.5281/zenodo.20821008 ). The data can be accessed without restriction and are available for verification and reuse. Funding: Funding Sources: This study was funded by a grant from the Secretaria de Salud Jalisco y el Consejo Nacional de Ciencia, Humanidades y Tecnología CONAHCYT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. Introduction Acute decompensated heart failure (ADHF) is a frequent cause of hospitalization and death among patients with cardiorenal syndromes (CRS) [ 1 ]. Common triggers include ischemic events, poor treatment adherence, lack of therapeutic optimization, arrhythmias, and infections among others [ 2 – 5 ]. Each of these precipitating factors may initiate distinct pathophysiological mechanisms, yet the majority of them ultimately converge in congestion and clinical deterioration [ 6 ]. Infections are a common cause of ADHF although the exact mechanisms remain unclear, involve multiple synergistic pathophysiological pathways, including endothelial dysfunction, systemic inflammation, neurohormonal activation, and hemodynamic alterations, ultimately resulting in sodium and water retention with subsequent congestion [ 2 – 5 ]. Despite the heterogeneous mechanisms underlying ADHF, the systematic approach to decongestion does not differentiate between etiological phenotypes of decompensation. It is possible that, due to its distinct pathophysiology, the trajectory and response to decongestion in patients with infection differ from those with other causes of ADHF, such as atrial fibrillation or treatment nonadherence. Current international guidelines recommend decongestion of ADHF patients primarily through the use of diuretics [ 7 ], which should be titrated according to clinical response until effective decongestion is achieved [ 8 ]. However, nearly 25% of patients develop diuretic resistance, necessitating dose escalation or the addition of alternative strategies to optimize decongestion [ 9 ]. Diuretics may be less effective in patients with active infection, since systemic inflammation, endothelial dysfunction, and sepsis-related hemodynamic alterations can impair renal perfusion and reduce natriuretic response. Furthermore, infection-induced activation of neurohormonal pathways and cytokine release may promote sodium and water retention, thereby increasing the risk of diuretic resistance and attenuating the efficacy of standard decongestive strategies [ 10 , 11 ]. Identifying differential responses to treatment in CRS patients with congestion according to the presence of infection would be of clinical value, as it may allow the early recognition of distinct phenotypes and the anticipation of tailored therapeutic strategies. To address this knowledge gap, we aimed to investigate the rate of successful decongestion CRS patients according to the presence of infection, as well as their risk of developing major adverse kidney events (MAKE) during follow-up. Methods Study design and patient population The present study was an investigator-initiated prospective cohort conducted at the Hospital Civil de Guadalajara Fray Antonio Alcalde, Guadalajara, Mexico. Potential participants were identified during routine hospital rounds of patients with acute kidney injury (AKI), and eligibility was confirmed through concurrent review of clinical records. Patients diagnosed with cardiorenal syndrome type 1 (CRS1) were included in the study, CRS1 was defined according to the 2008 classification system by Ronco et al, and both AKI and ADHF criteria needed to be present at baseline [ 12 ]. Cardiology and nephrology teams confirmed the presence of CRS1. ADHF was clinically defined [ 13 ], AKI was made using the serum creatinine (sCr) by KDIGO criteria [ 14 ]. The eGFR was calculated according to the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [ 15 ]. Infection was defined as the presence of a clinical suspicion of bacterial infection (pulmonary, abdominal, urinary, soft tissue, or other sites) combined with the prescription of antibiotics. MAKE outcomes were defined as death, a new requirement for KRT, or worsening kidney function by a ≥ 25% decline in the eGFR from baseline, [ 16 ] and they were evaluated during the first 10 days (MAKE10) and at 30 days (MAKE 30). We followed the 31st Acute Disease Quality Initiative group recommendations on the design of studies to explore treatments for patients with AKI and selected the sub-phenotype of patients with CRS and infection [ 17 ]. In addition, to better capture the interaction between kidney trajectory and decongestion, the cohort was stratified based on two key clinical parameters: presence or absence of infection as the main cause of decompensation of ADHF, and achievement or failure of clinical decongestion, evaluated through a composite assessment including symptom resolution, improvement in biomarkers (such as BNP or CA-125), and POCUS findings (e.g., lung ultrasound, IVC status, and VExUS score). Successful decongestion was defined as at least 1 of the following metrics: resolution of dyspnea and peripheral edema, > 30% reduction in BNP levels, and absence of B-lines or VExUS ≥ 2. The diuretics management was at the discretion of both teams according to institutional standards. Inclusions criteria were: (1) clinical diagnosis of ADHF; (2) AKI as per KDIGO criteria on admission [ 14 ]; (3) availability of baseline sCr in the 6 months prior to hospitalization; and (4) at least one follow-up sCr measurement within 30 days. Patients were excluded if they had had AKI within the past three months, were <18 years old, had CKD grade 5, chronic dialysis, kidney transplant, hospital stay <48 hours, or had missing data that would render analysis incomplete. The main exposure was the presence of infection and its association with effective decongestion and MAKE. Data collection Clinical characteristics, demographic information, and laboratory data were collected via automated retrieval from the institutional electronic medical records system (10 October 2025). We also considered other potential contributing factors to AKI, including nephrotoxic drugs such as aminoglycosides, non-steroidal anti-inflammatory drugs, and vancomycin. The indications for KRT included persistent congestion that was resistant to diuretics, severe hyperkalemia, severe metabolic acidosis, and uremic manifestations, such as encephalopathy, pericarditis, and seizures [ 18 ] . This was an exploratory analysis; hence, no formal sample size calculation was performed. However, the number of events was deemed sufficient for the planned multivariable analyses (≥10 events per variable). This study was approved by the Hospital Civil de Guadalajara Fray Antonio Alcalde Institutional Review Board (IRB HCG/CEI-0550/15) and was conducted according to the Declaration of Helsinki. Patient consent was not required in accordance with national guidelines, and the IRB approved a waiver of informed consent in accordance with local regulations. The study protocol was designed to align with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [ 19 ] and the REporting of studies Conducted using Observational Routinely collected health Data (RECORD) statement [ 20 ]. Study objectives The primary outcome was successful decongestion in CRS1 patients stratified by the presence of infection. Secondary outcomes were MAKE-30 and their separate subcomponents as Mortality, KRT and Worsening Kidney Function also stratified by the presence of infection. Statistical analysis Baseline demographic, clinical, and laboratory characteristics were summarized for the total cohort and stratified by the presence or absence of infection. Continuous variables were assessed for normality and presented as median and interquartile range (IQR) as all variables followed a non-normal distribution. Comparisons between groups were made using the Mann-Whitney U test. Categorical variables were presented as frequencies and percentages (%), and comparisons were performed using the Chi-squared test or Fisher’s exact test, as appropriate. To assess the independent association between infection (exposure) and the study outcomes, we performed multivariable logistic regression analysis. The primary outcome was successful decongestion, and the main secondary outcome was the incidence of MAKE-30. Infection was analyzed as an independent variable and was coded as a binary. For each outcome, we developed a primary multivariable model adjusted for a set of clinically relevant confounders selected a priori: age, sex, history of congestive heart failure, history of CKD, and baseline creatinine. To assess the robustness of our findings, we conducted a sensitivity analysis by developing a second, more comprehensive model. This sensitivity model included the variables from the primary model plus additional baseline covariates that were significantly different between groups in the descriptive analysis (p < 0.1), namely respiratory rate, leukocyte count, and glucose. The results of the logistic regression models are presented as adjusted Odds Ratios (aOR) with their corresponding 95% confidence intervals (95% CI). Complete-case analysis was performed for all multivariable models. Patients with missing values in any covariate included in a given model were excluded from that specific analysis. The reduction in sample size of the decongestion model was mainly attributable to missing biomarker and imaging variables that were obtained according to clinical availability rather than systematically in all participants. For the MAKE-30 analyses, only patients with complete 30-day follow-up and complete outcome ascertainment were included to avoid misclassification of the composite endpoint. Because missingness primarily reflected incomplete follow-up rather than isolated missing baseline covariates, multiple imputation was not considered methodologically appropriate. Finally, the time to MAKE was visualized using Kaplan-Meier curves, and the difference between the infection and no-infection groups was formally compared using the log-rank test. Patients with missing time-to-event data were excluded from this specific analysis. All statistical analyses were performed using Stata version 16.0 (StataCorp, College Station, TX, USA). A two-sided p-value < 0.05 was considered statistically significant for all analyses. Results From February 2022 to November 2024, a total of 328 patients with CRS were assessed by the nephrology service. Sixty-four subjects were excluded ( Fig 1 ), and the final cohort included 256 CRS patients. Of these 72 (28.1%) were diagnosed with a concurrent infection, while 184 (71.9%) constituted the non-infected control group as shown in the flow chart of Fig 1 . Download: PNG larger image TIFF original image Fig 1. Flowchart of study population. https://doi.org/10.1371/journal.pone.0355608.g001 Demographic and clinical characteristics of CRS patients according to the infection status group are presented in Table 1 . Median age was similar between groups (65 vs. 64.5 years, p = 0.51), and males represented 55.6% of the infection group ( p = 0.99). Likewise, the prevalence of diabetes, systemic hypertension, CKD, and congestive heart failure did not differ significantly, indicating that both groups were similar at baseline. As expected, infected patients showed higher antibiotic exposure (100% vs. 39.9%, p < 0.001), and non-steroidal anti-inflammatory drugs (NSAID) use was more frequent (19.4% vs. 9.8%, p = 0.037). Conversely, SGLT2 inhibitor use was significantly less common among those with infection (41.3% vs. 64.3%, p = 0.002), which may reflect treatment discontinuation during acute illness or differential prescribing practices. Markers of anemia and inflammation were also more pronounced in the infection group, with lower hemoglobin (9.77 vs. 11.1 g/dL, p = 0.022) and hematocrit (30.1% vs. 34.2%, p = 0.011). Importantly, markers of congestion were significantly worse in patients with infection, as they had markedly higher BNP concentrations (Q1 25,264 vs. Q3 13,405 pg/mL, p = 0.012) and significantly lower arterial oxygen tension (pO 2 45 vs. 65.5 mmHg, p = 0.019), likely indicating more severe pulmonary congestion and impaired gas exchange. The cumulative furosemide dose was similar between groups, with a median of 580 mg (IQR 330–920) in patients without infection and 600 mg (IQR 350–940) in those with infection, with no statistically significant difference. The proportion of patients requiring KRT specifically for volume overload was comparable (20.8% vs. 17.4%, p = 0.52). Download: PNG larger image TIFF original image Table 1. Baseline demographic and clinical characteristics of patients according to the presence of infection. https://doi.org/10.1371/journal.pone.0355608.t001 Primary outcome: Successful decongestion in CRS patients according to the presence of infection Successful decongestion was achieved in 107 patients without infection (59.8%) and in 43 patients with infection (61.4%), with no significant difference between groups (p = 0.83). The frequency of decongestion according to the site of infection is described in the S1 Fig . The multivariable decongestion model included 198 patients with complete covariate information, whereas the adjusted MAKE-30 model included 134 patients with complete 30-day follow-up and complete outcome ascertainment. The primary analysis demonstrated that infection was not independently associated with lower odds of achieving decongestion (adjusted OR 1.28, 95% CI 0.65–2.51, p = 0.48) Table 2 . Similarly, in the sensitivity model incorporating additional clinical and biochemical parameters such baseline respiratory rate, leukocyte count, and glucose, the association remained non-significant (adjusted OR 1.61, 95% CI 0.74–3.50, p = 0.23). A visual summary of the adjusted OR for successful decongestion is presented in the forest plot in Fig 2 . Download: PNG larger image TIFF original image Table 2. Multivariate model and sensitivity analysis for primary and secondary outcomes. https://doi.org/10.1371/journal.pone.0355608.t002 Download: PNG larger image TIFF original image Fig 2. Forest plot of adjusted odds ratios for the primary and secondary outcomes. https://doi.org/10.1371/journal.pone.0355608.g002 Secondary outcomes The secondary objectives are presented in Table 2 and 3 . MAKE-10 occurred in 151 patients without infection (82.1%) and in 65 patients with infection (90.3%), with no statistically significant difference between groups (p = 0.13). MAKE-30 occurred in 59 patients without infection (43.1%) and in 23 patients with infection (50.0%), with no significant difference between groups (p = 0.45). In the primary model, infection did not increase the risk of MAKE-30 (adjusted OR 1.26, 95% CI 0.57–2.79, p = 0.57), and this finding was consistent in the sensitivity model (adjusted OR 1.11, 95% CI 0.45–2.74, p = 0.82). Similarly, demographic characteristics such as age and sex were not associated with MAKE-30, nor were comorbid conditions including CHF and CKD. Additional relevant clinical and laboratory parameters, including respiratory rate, leukocyte count, and glucose, also failed to demonstrate independent predictive value, Table 2 . Fig 3 shows the Kaplan–Meier curves for MAKE-free survival according to infection status, demonstrating no significant difference between groups throughout follow-up (log-rank p = 0.88). The analysis of MAKE subcomponents revealed that infection was not independently associated with short-term mortality, initiation of KRT, or worsening kidney function in CRS patients. At 10 days, adjusted odds ratios for infection showed no significant association with mortality (aOR 1.27, 95% CI 0.41–3.96, p = 0.687), KRT initiation (aOR 1.49, 95% CI 0.53–4.21, p = 0.453), or worsening kidney function (aOR 1.17, 95% CI 0.60–2.29, p = 0.647). These findings were consistent at 30 days, where infection again failed to reach significance across mortality (aOR 1.23, 95% CI 0.40–3.79, p = 0.713), KRT initiation (aOR 1.57, 95% CI 0.47–5.27, p = 0.463), and worsening kidney function (aOR 1.30, 95% CI 0.58–2.92, p = 0.524); See Table 3 and Fig 4 . Other covariates, including age, sex, congestive heart failure, CKD, and baseline creatinine, did not demonstrate significant associations with any MAKE subcomponent, although trends were observed. Download: PNG larger image TIFF original image Table 3. Multivaritae analysis for MAKE componentes. https://doi.org/10.1371/journal.pone.0355608.t003 Download: PNG larger image TIFF original image Fig 3. Kaplan–Meier analysis of MAKE-free survival according to infection status. Kaplan–Meier curves demonstrating the probability of remaining free from MAKE during follow-up in patients with and without infection. The curves remained largely overlapping t
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