The Association between Hematocrit and All-Cause Mortality in Patients with Acute Congestive Heart Failure.

The blood urea nitrogen to serum albumin ratio (BAR) has been identified as a novel indicator of both inflammatory and nutritional status, exhibiting a correlation with adverse cardiovascular outcomes. To explore the association between the BAR and 28-day all-cause mortality in cardiac arrest patients who achieved return of spontaneous circulation (ROSC) and were admitted to the intensive care unit (ICU). Data for patients with cardiac arrest were obtained from the Medical Information Mart for Intensive Care IV database. The outcome was 28-day all-cause mortality. Multivariable-adjusted Cox regression analysis, curve fitting, and threshold effects analysis were used to assess the relationship between the BAR and 28-day all-cause mortality in patients with cardiac arrest in the intensive care unit. A total of 793 patients were included and divided into tertiles based on the BAR (Q1, Q2, Q3); 8-day all-cause mortality rates were 37.5%, 53.4%, and 63.8%, respectively (P < 0.001). A higher BAR at initial admission was significantly associated with an increased 28-day all-cause mortality risk. Results from the adjusted Models 2, 3, 4, and 5 were consistent with those of Model 1. Subgroup analysis revealed no interactions in age, sex, renal disease, liver disease, vasoactive drug use, ventilation, race, aids, malignant cancer, diabetes, peptic ulcer disease, rheumatic disease, chronic pulmonary disease, cerebrovascular disease, peripheral vascular disease, congestive heart failure and myocardial infarct between the BAR and 28-day all-cause mortality. Restricted cubic spline analysis revealed a nonlinear association between the BAR and 28-day all-cause mortality (P = 0.003). With BAR ≤ 17.981, each 1-unit increase in the BAR was associated with a 5.7% higher risk of death [95% CI (1.012-1.105), P < 0.05]. This study identified a non-linear relationship between the BAR and 28-day all-cause mortality in patients with cardiac arrest.

Previous studies have not thoroughly explored the impact of serum osmolality levels on early mortality in heart failure and reduced ejection fraction (HFrEF) patients. The purpose of this study was to investigate the relationship between serum osmolality levels and early all-cause mortality in patients with HFrEF. The open access MIMIC-IV database was the source of data for our study. We collected demographic data, vital signs, laboratory parameters, and comorbidities of the included patients and divided them into 3 groups based on their initial serum osmolality on admission, with the primary outcome being all-cause mortality within 28 days of admission. Smoothing Spline Fitting Curve, the Kaplan-Meier survival curve, and Threshold effect analysis were used to assess the relationship between serum osmolality and early mortality in HFrEF patients. A total of 6228 patients (55.31% male) were included. All-cause mortality within 28 days on admission was 18.88% in all patients. After adjusting for confounders, higher serum osmolality levels were independently associated with an increased risk of 28-days all-cause mortality compared with the reference group (Reference group Q2: 290-309 mmol/L, Q4: HR, 1.82 [95% CI 1.19-2.78] P<0.05, Q5: HR, 1.99 [95% CI 1.02-3.91] P<0.05). Smooth spline fitting revealed a U-shaped association between serum osmolality and 28-days all-cause mortality. Further threshold effect analysis results suggested that each unit increase in serum osmolality level was associated with a 2% increase in 28-days all-cause mortality when serum osmolality levels were ≥ 298.8 mmol/L (HR, 1.019 [95% CI 1.012-1.025] P<0.05). A U-shaped correlation between initial serum osmolality and 28-days all-cause mortality in HFrEF patients was identified, revealing higher osmolality levels significantly increase mortality risk. These results underscore serum osmolality's critical role in early mortality among HFrEF patients, highlighting the need for further, larger-scale studies for validation.

The early identification and appropriate management may provide clinically meaningful and substained benefits in patients with acute heart failure (AHF). This study aimed to develop an integrative nomogram with myocardial perfusion imaging (MPI) for predicting the risk of all-cause mortality in AHF patients. Prospective study of 147 patients with AHF who received gated MPI (59.0 [47.5, 68.0] years; 78.2% males) were enrolled and followed for the primary endpoint of all-cause mortality. We analysed the demographic information, laboratory tests, electrocardiogram, and transthoracic echocardiogram by the least absolute shrinkage and selection operator (LASSO) regression for selection of key features. A multivariate stepwise Cox analysis was performed to identify independent risk factors and construct a nomogram. The predictive values of the constructed model were compared by Kaplan-Meier curve, area under the curves (AUCs), calibration plots, continuous net reclassification improvement, integrated discrimination improvement, and decision curve analysis. The 1, 3, and 5year cumulative rates of death were 10%, 22%, and 29%, respectively. Diastolic blood pressure [hazard ratio (HR) 0.96, 95% confidence interval (CI) 0.93-0.99; P=0.017], valvular heart disease (HR 3.05, 95% CI 1.36-6.83; P=0.007), cardiac resynchronization therapy (HR 0.37, 95% CI 0.17-0.82; P=0.014), N-terminal pro-B-type natriuretic peptide (per 100pg/mL; HR 1.02, 95% CI 1.01-1.03; P<0.001), and rest scar burden (HR 1.03, 95% CI 1.01-1.06; P=0.008) were independent risk factors for patients with AHF. The cross-validated AUCs (95% CI) of nomogram constructed by diastolic blood pressure, valvular heart disease, cardiac resynchronization therapy, N-terminal pro-B-type natriuretic peptide, and rest scar burden were 0.88 (0.73-1.00), 0.83 (0.70-0.97), and 0.79 (0.62-0.95) at 1, 3, and 5years, respectively. Continuous net reclassification improvement and integrated discrimination improvement were also observed, and the decision curve analysis identified the greater net benefit of the nomogram across a wide range of threshold probabilities (0-100% at 1 and 3years; 0-61% and 62-100% at 5years) compared with dismissing the included factors or using either factor alone. A predictive nomogram for the risk of all-cause mortality in patients with AHF was developed and validated in this study. The nomogram incorporated the rest scar burden by MPI is highly predictive, and may help to better stratify clinical risk and guide treatment decisions in patients with AHF.

ObjectiveThe lactate/albumin ratio (LAR) has been used as a novel prognostic indicator for aneurysmal subarachnoid hemorrhage, traumatic brain injury, sepsis, heart failure, and acute respiratory failure. However, its potential in predicting all-cause mortality in patients with ischemic stroke (IS) has not been evaluated. Therefore, this study aimed to elucidate the correlation between LAR and 28-day all-cause mortality in IS patients without reperfusion therapy.MethodsThis retrospective cohort study used data from the Medical Information Mart for Intensive Care (MIMIC-IV) (v2.0) database. It included 568 IS adult patients admitted to the intensive care unit (ICU). The correlation between LAR and ICU 28-day all-cause mortality rate was analyzed using multiple COX regression analysis and Kaplan–Meier survival analysis. Restricted cubic spline (RCS) curves were used to assess the relationship between LAR and 28-day mortality. In addition, a subgroup analysis was performed to investigate the impact of other influencing factors on outcomes. The primary outcome was the ability of LAR to predict 28-day mortality in IS patients.ResultsAmong the 568 patients with IS, 370 survived (survival group) and 198 died (non-survival group) within 28 days of admission (mortality rate: 34.9%). A multivariate COX regression analysis indicated that LAR was an independent predictor of all-cause mortality within 28 days after admission for patients with IS (hazard ratio: 1.32; 95% confidence interval: 1.03–1.68; P = 0.025). We constructed a model that included LAR, age, race, sex, white blood cell count, Sequential Organ Failure Assessment (SOFA) score, and anion gap (AG) and established a prediction model with an area under the curve (AUC) value of 71.5% (95% confidence interval: 67.1%−75.8%). The optimal cutoff value of LAR that separated the survival group and the non-survival group based on the Youden index was 0.55. The Kaplan-Meier survival curves plotted using this critical value showed that patients with LAR ≥ 0.55 had a significantly higher 28-day all-cause mortality rate than patients with LAR < 0.55 (P = 0.0083).ConclusionLAR can serve as an independent predictor of all-cause mortality within 28 days after admission for patients with IS.

Background: The stress-induced hyperglycemic ratio (SHR) is an index that reflects the imbalance between acute stress-induced glucose fluctuations and baseline glucose metabolism levels. Currently, there are few studies on the SHR index and its prognostic significance in heart failure (HF) patients undergoing invasive mechanical ventilation. This study aimed to investigate the relationship of SHR with the risk of death in HF patients requiring invasive ventilation. Methods: Conduct a retrospective cohort study based on the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Include adult heart failure patients who received invasive ventilation and divide them into quartile groups according to the level of the Systemic Heart Rate (SHR). The primary endpoints of the observation are the 30-day all-cause mortality rate and the all-cause mortality rate in the Intensive Care Unit (ICU), while the secondary endpoints are the 365-day all-cause mortality rate and the all-cause mortality rate during hospitalization. The Kaplan-Meier curve is used to compare the survival outcomes between groups. A Cox proportional hazards regression model that adjusts for demographic characteristics, underlying diseases, and the severity of critical illnesses is employed to evaluate the relationship between SHR and the mortality rate. The Restricted Cubic Spline (RCS) is utilized to test the nonlinear association between the two, and subgroup analysis is carried out to verify the consistency of the results across different groups. Results: Among the 1,038 eligible patients, the mean age was 68.50 years (range: 59.46 - 77.48 years), and 639 (61.56%) of them were male. The Kaplan-Meier curve showed that the higher the SHR index, the higher the risk of all-cause mortality in patients at 30 days (log-rank test, p = 0.011) and in the ICU (log-rank test, p = 0.0029). An increase in SHR was independently associated with an increased risk of 30-day and ICU mortality. Compared with the second quartile group Q2, the 30-day mortality rate in the group with the highest SHR was significantly higher (HR = 1.59, 95% CI 1.08, 2.33), and the ICU mortality rate in the group with the highest SHR was significantly higher (HR = 1.86, 95% CI 1.10, 3.14). The restricted cubic spline analysis showed a non-linear dose-response relationship between SHR and 30-day all-cause mortality (p for non-linearity &lt; 0.05), and the risk of 30-day and ICU all-cause mortality gradually increased with the increase of the SHR index. The risks of 30-day and all-cause mortality in the ICU gradually increased. The results of the subgroup analysis confirmed that it remained stable in the subgroup of patients with Coronary Heart Disease (CHD). Conclusion: In critically ill heart failure (HF) patients receiving invasive ventilation, a higher stress hyperglycemia ratio (SHR) index is significantly associated with an increased risk of 30-day and all-cause mortality in the intensive care unit (ICU). Meanwhile, the SHR index is an independent predictor of mortality in critically ill HF patients who require invasive ventilation.

BackgroundIn this study, we evaluated the predictive utility of neutrophil percentage-to-albumin ratio (NPAR) for all-cause mortality in patients with chronic heart failure (CHF).MethodsPatients diagnosed as CHF enrolled in this retrospective cohort study were from Beijing Chaoyang Hospital, capital medical university. Admission NPAR was calculated as neutrophil percentage divided by serum albumin. The endpoints of this study were defined as 90-day, 1-year and 2-year all-cause mortality. Multivariable Cox proportional hazard regression model was performed to confirm the association between NPAR and all-cause mortality. Receiver operating characteristics (ROC) curves were used to evaluate the ability for NPAR to predict all-cause mortality.ResultsThe 90-day (P = 0.009), 1-year (P < 0.001) and 2-year (P < 0.001) all-cause mortality in 622 patients with CHF were increased as admission NPAR increased. Multivariable Cox regression analysis found the higher NPAR value was still independently associated with increased risk of 90-day (Group III versus Group I: HR, 95% CI: 2.21, 1.01–4.86, P trend = 0.038), 1-year (Group III versus Group I: HR, 95% CI:2.13, 1.30–3.49, P trend = 0.003), and 2-year all-cause mortality (Group III versus Group I: HR, 95% CI:2.06, 1.37–3.09, P trend = 0.001), after adjustments for several confounders. ROC curves revealed that NPAR had a better ability to predict all-cause mortality in patients with CHF, than either albumin or the neutrophil percentage alone.ConclusionsNPAR was independently correlated with 90-day, 1-year, and 2-year all-cause mortality in patients with CHF.

Hypertensive heart disease (HHD) complicated by heart failure is a significant cause of morbidity and mortality. The glucose-to-lymphocyte ratio (GLR) has been suggested as a potential marker of inflammation and stress. This study aimed to investigate the relationship between GLR and 28-day all-cause mortality in patients with HHD complicated by heart failure using the Medical Information Mart for Intensive Care, version IV database. We conducted a retrospective analysis of 6203 patients admitted to the intensive care unit (ICU) with HHD complicated by heart failure. Patients were excluded if they were not admitted to the ICU, had glucose deficiency, lymphocytopenia, or were identified as outliers. Patients were divided into quartiles based on GLR values. Cox regression models were used to evaluate the association between GLR and 28-day all-cause mortality. Subgroup analyses were performed to assess the impact of various clinical factors on this relationship. The study population had a mean age of 73.2 years, with 42.0% being male. The median GLR was 11.2 (interquartile range 6.4–20.0). In univariate Cox regression analysis, GLR was significantly associated with 28-day all-cause mortality (hazard ratio [HR] 1.0049, 95% confidence interval [CI] 1.0037–1.006, P < .001). Multivariate analysis confirmed this association, with the highest GLR quartile (Q4) showing a significantly higher risk of mortality compared to the lowest (Q1) (HR 2.57, 95% CI 2.18–3.03, P < .001). Threshold effect analysis identified a turning point at GLR 31.879, where the hazard ratio was 1.04 (95% CI 1.032–1.048, P < .001) for GLR below this value and 1.0023 (95% CI 0.9949–1.0097, P = .5481) for GLR above it. Kaplan–Meier survival analysis and forest plots further supported these findings. GLR is significantly associated with 28-day all-cause mortality in patients with HHD complicated by heart failure. Higher GLR values are associated with an increased risk of mortality. Our findings suggest that GLR could serve as a useful prognostic marker in this patient population.

OBJECTIVES:Geriatric nutritional risk index (GNRI) might predict the all-cause mortality in patients with heart failure (HF). We performed a meta-analysis to evaluate the correlation between GNRI and all-cause mortality in patients with HF.METHODS:We searched the PubMed, Medline, Cochrane Library, and Embase databases for clinical trials investigating the association between GNRI and all-cause mortality in patients with HF, having the primary endpoint as all-cause mortality.RESULTS:In total, nine studies involving 7,659 subjects were included in the systematic review and meta-analysis. The results indicated that major risk and moderate risk GNRI (GNRI<92) was associated with an increased risk of all-cause mortality in elderly patients with HF (hazard ratios [HR] 1.59, 95% confidence intervals [CI] 1.37-1.85). Low risk GNRI (GNRI<98) group predicted all-cause mortality in elderly HF patients (HR 1.56, 95%CI 1.12-2.18) when compared with the high GNRI value group. A subgroup analysis indicated that the relationship between GNRI and HF might differ based on the subtype of heart failure.CONCLUSIONS:GNRI is a simple and well-established nutritional assessment tool to predict all-cause mortality in patients with HF.

BackgroundChronic obstructive pulmonary disease (COPD) is one of the leading causes of death worldwide, and acute kidney injury (AKI) is one of the most common comorbidities in patients with COPD. However, the impact of AKI occurring within 2 days of COPD diagnosis is unclear. Therefore, this study aimed to assess the impact of a 2-day onset of AKI on COPD patient outcomes using the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database.MethodsThis retrospective study is based on version 2.2 of the MIMIC-IV database. We collected clinical data and 30-day all-cause mortality data for patients with COPD in the intensive care unit (ICU), who met the diagnostic criteria for COPD upon admission between 2008 and 2019. We used the International Classification of Diseases, 10th Revision (ICD-10) (codes J44, J440, J441, and J449) to identify COPD. Kaplan-Meier analysis was used to compare 30-day all-cause mortality in COPD patients with and without 2-day AKI. A Cox proportional hazards model was employed to investigate risk factors associated with 30-day all-cause mortality in COPD patients.ResultsThis study included 2,609 patients with COPD, of whom 1,514 (58.03%) developed AKI within 2 days, while 1,095 (41.97%) did not. Patients with COPD, those who developed AKI within 2 days were older than those who did not develop AKI within 2 days [median: 72.7 (65.1, 80.0) vs. 70.6 (63.2, 79.6), P=0.005] and had a higher Simplified Acute Physiology Score III (SAPSIII) score [median: 50.0 (37.0, 67.8) vs. 37.0 (28.0, 48.0), P<0.001], at the same time, the scores of Simplified Acute Physiology Score II (SAPSII), Sequential Organ Failure Assessment (SOFA) score, and Outcome and Assessment Information Set (OASIS) Charlson Comorbidity Index were also higher (all P<0.001). In our study, 30-day all-cause mortality [hazard ratio (HR) =2.07, 95% confidence interval (CI): 1.6–2.69, P<0.001] was higher in COPD patients with a 2-day onset of AKI than in patients without a 2-day onset of AKI. After adjusting for covariates, results showed that 2-day AKI was an independent risk factor for 30-day all-cause mortality in COPD patients (HR =11.02, 95% CI: 1.8–67.39, P=0.009).ConclusionsThe occurrence of 2-day AKI was an independent risk factor for 30-day all-cause mortality in patients with COPD. Clinically, these findings highlight the importance of providing early kidney protection for patients with COPD.

Identifying high-risk acute pancreatitis (AP) patients in the ICU is vital for improving prognosis. Thus, this study aims to explore the relationship between the coefficient of variation (CV) of blood glucose and the all-cause mortality of patients with AP in the ICU. A retrospective analysis was conducted on AP patients in the MIMIC-IV database. The CV was used to describe the glycemic variability (GV) and the optimal cut-off value was determined using the ROC curve. Subsequently, analyze the correlation between CV and all-cause mortality. A total of 907 patients with AP in the ICU were included in this study. The ROC curve determined the optimal CV cut-off value as 0.25. The KM survival curves and univariate and multivariate logistics regression analyses all showed that CV was associated with the 30-day, 60-day, and 90-day all-cause mortality (P < 0.05). The RCS curves showed a nonlinear correlation (P < 0.05). When CV is less than 0.421, 0.449, and 0.428, respectively, the risk of death at 30-day, 60-day, and 90-day increases as the CV value rises. Subgroup analysis showed an interaction between congestive heart failure and CV in 30-day and 60-day all-cause mortality, between age and CV in 60-day and 90-day all-cause mortality, and between chronic pulmonary disease and CV in 30-day all-cause mortality (P all < 0.05). The CV is associated with the all-cause mortality of AP patients in the ICU, especially when the CV value is between 0.25 and 0.45. When using CV, the effects of age, congestive heart failure, and chronic pulmonary disease should be considered.

Intracerebral hemorrhage (ICH) is associated with high mortality and morbidity rates. Although some studies have indicated a correlation between serum bilirubin levels and ICH severity, evidence of the relationship between serum total bilirubin (TBIL) and ICH outcomes remains lacking. A total of 914 patients from the Medical Information Mart for Intensive Care IV database met the eligibility criteria and were included in the study. The patients were categorized into two groups based on whether they survived for 28 days following admission to hospital. The association between serum TBIL levels and 28-day survival in patients with ICH was investigated using Spearman's correlation analysis and restricted cubic splines. The effect of serum TBIL levels on survival time and rate in the 28-day period was analyzed using Kaplan-Meier curves and restricted mean survival times. Univariate Cox regression, least absolute shrinkage and selection operator regression, and multivariate Cox regression were used to identify risk factors associated with 28-day all-cause mortality. Finally, subgroup analysis was performed to verify the stability of the association between serum TBIL levels and 28-day all-cause mortality in patients with ICH. A negative relationship was revealed between TBIL levels and survival (p < 0.001, correlation = -0.174). Restricted cubic spline analysis revealed a nonlinear link between mean serum TBIL levels and 28-day all-cause mortality (p for nonlinear = 0.001). Patients with ICH and higher serum TBIL levels had significantly reduced survival times and rates compared with those with lower serum TBIL levels (p < 0.001). Serum TBIL level was identified as a significant risk factor for 28-day all-cause mortality in patients with ICH (hazard ratio [95% confidence interval] = 1.121 [1.063-1.182], p < 0.001). Subgroup analyses revealed that the assessed variables had no influence on the association between serum TBIL levels and 28-day all-cause mortality. Higher serum TBIL levels are associated with a greater risk of mortality within 28 days in patients with ICH, whereas lower serum TBIL levels are associated with prolonged survival.

Background Heart failure patients may be particularly susceptible to non-optimal temperature exposures due to compromised physiological functions. However, the associations between short-term exposures to low and high temperatures and all-cause mortality in patients with heart failure remain unclear. Purpose We aimed to assess the associations between short-term exposures to low and high temperatures and all-cause mortality among patients with heart failure in Sweden. Methods This nationwide study analyzed all-cause mortality in 250,640 heart failure patients in Sweden between 2006 and 2021, using data from the Swedish National Patient Register and Cause of Death Register. Daily mean ambient temperatures (modeled a 1 × 1 km spatial resolution) were linked to patients’ residential Regional Statistical Areas (RegSO). We applied a time-stratified case-crossover design and used conditional logistic regression with a distributed lag non-linear model to investigate the associations between low and high temperature exposures during the 1-week period preceding a death event (lag 0-6 days) and all-cause and cardiovascular mortality in heart failure patients. Temporal variations in these associations were assessed by comparing data from 2006-2013 to that from 2014-2021. We also examined potential effect modification by comorbidities, medication use, and air pollution levels. Results The relationship between short-term exposure to daily air temperature and all-cause mortality in heart failure patients exhibited a U-shaped pattern (Figure 1). The odds ratios for all-cause mortality in heart failure patients were 1.130 (95% CI: 1.074-1.189) for low temperatures at the 2.5th percentile and 1.054 (95% CI: 1.017-1.093) for high temperatures at the 97.5th percentile, compared to the Minimum Mortality Temperature, corresponding to the 84th percentile of temperature distribution. Similar U-shaped patterns were observed for cardiovascular mortality. Notably, the slopes of the all-cause and cardiovascular mortality risk curves for high temperatures were steeper and exhibited a more rapid increase in 2014-2021. Heart failure patients comorbid with diabetes and those using diuretics were found to be more susceptible to low temperatures. Conversely, high temperatures showed a stronger association with all-cause mortality among individuals exposed to higher ozone levels. Conclusions Our nationwide study in Sweden indicates that short-term exposure to low and high temperatures is associated with an increased risk of all-cause and cardiovascular mortality in heart failure patients. Notably, the steepening slope of mortality risk associated with high temperatures over time suggests that the threat posed by heat to heart failure patients may be growing.Figure 1

ObjectiveSystemic inflammation is associated with a poor prognosis in acute heart failure (AHF). This study was to assess the long-term prognostic value of combining the accessible inflammatory markers in relation to all-cause mortality in patients with AHF.MethodsConsecutive patients with AHF who were hospitalized between March 2012 and April 2016 at the Department of Cardiology of the First Affiliated Hospital of Nanjing Medical University were enrolled in this prospective study. The LASSO regression model was used to select the most valuable inflammatory biomarkers to develop an inflammatory prognostic scoring (IPS) system. Kaplan-Meier method, multivariate COX regression and time-dependent ROC analysis were used to assess the relationship between inflammatory markers and AHF prognosis. A randomized survival forest model was used to estimate the relative importance of each inflammatory marker in the prognostic risks of AHF.ResultsA total of 538 patients with AHF were included in the analysis (mean age, 61.1 ± 16.0 years; 357 [66.4%] men). During a median follow-up of 34 months, there were 227 all-cause deaths (42.2%). C-reactive protein (CRP), red blood cell distribution width (RDW) and neutrophil-to-lymphocyte ratio (NLR) were incorporated into the IPS system (IPS = 0.301×CRP + 0.263×RDW + 0.091×NLR). A higher IPS meant a significantly worse long-term prognosis in Kaplan-Meier analysis, with 0.301 points as the optimal cut-off value (P log-rank <0.001). IPS remained an independent prognostic factor associated with an increased risk of all-cause mortality among patients with AHF in multivariate Cox regression models with a full adjustment of the other significant covariables. Random forest variable importance and minimal depth analysis further validated that the IPS system was the most predictive for all-cause mortality in patients with AHF.ConclusionsInflammatory biomarkers were associated with the risk of all-cause mortality in patients with AHF, while IPS significantly improved the predictive power of the model and could be used as a practical tool for individualized risk stratification of patients with AHF.

Acute pulmonary edema is a severe clinical condition with high mortality. The anion gap, reflecting metabolic acid-base disturbances, is often elevated in critically ill patients. However, its relationship with outcomes in acute pulmonary edema remains unclear. To explore the association between admission anion gap levels and 28-day all-cause mortality in patients with acute pulmonary edema. This retrospective cohort study utilized data from the MIMIC-IV database (2008-2019) and included adult patients with acute pulmonary edema. Patients were categorized into quartiles based on anion gap levels. Cox regression models analyzed the relationship between anion gap and mortality, with restricted cubic spline (RCS) curves, Kaplan-Meier analysis, and subgroup analyses. A total of 1094 patients were included. Univariate Cox regression showed a positive correlation between anion gap levels and 28-day mortality (HR = 1.13, 95%CI: 1.09-1.17, P < 0.001). Multivariate analysis confirmed anion gap as an independent predictor (HR = 1.11, 95%CI: 1.07-1.15, P < 0.001). The RCS curve indicated a nonlinear relationship, and Kaplan-Meier analysis showed lower survival in higher anion gap groups (P < 0.001). Subgroup analysis revealed significant interactions between age and renal disease status, indicating that anion gap levels had a stronger association with mortality in younger patients and those without renal disease. Admission anion gap levels predict 28-day all-cause mortality in acute pulmonary edema patients, particularly in younger patients and those without renal disease. Clinically, anion gap monitoring should be emphasized, and individualized prognostic and treatment strategies should be developed with factors like age and renal status to improve outcomes.

Intra-aortic balloon pump implantation in early-stage cardiogenic shock reduces 30-day mortality in patients with ventricular septal defect following myocardial infarction.