ArticleScientific reports2024
The value of five scoring systems in predicting the prognosis of patients with sepsis-associated acute respiratory failure.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed.
- Development and multi-center validation of a machine learning‑based prediction model for mortality in tumor-related sepsis.BMC infectious diseases · 2026Article
- A multicenter machine learning model for predicting ICU mortality in mechanically ventilated patients: development and external validation.BMC medical informatics and decision making · 2026Article
- Nonlinear correlation between lactate levels and 28-day all-cause mortality in patients with sepsis complicated by acute respiratory distress syndrome (ARDS): a retrospective study based on the MIMIC-IV database.BMC medical informatics and decision making · 2026Article
- Hemoglobin glycation index correlates with the prognoses of critically ill patients with hyperlipidemia: a retrospective cohort study from the MIMIC-IV database.BMC endocrine disorders · 2026Article
- Development of a mortality prediction nomogram for dementia patients using the MIMIC-IV database.Scientific reports · 2026Article
- The predictive value of serological markers for successful weaning and 30-day mortality in patients with severe intracerebral hemorrhage.BMC neurology · 2026Article
- Association between PaO2/FiO2 trajectories and survival outcomes in patients with sepsis-associated acute respiratory failure under invasive mechanical ventilation: a retrospective cohort analysis based on MIMIC-IV database.BMC pulmonary medicine · 2026Article
- Development and validation of predicting hospital mortality of acute ischemic stroke patients over 80 years in ICU: a retrospective study.BMC geriatrics · 2026Article
- Machine learning-driven sedation-analgesia optimization in mechanically ventilated sepsis patients: a retrospective MIMIC-IV analysis.Frontiers in pharmacology · 2026Article
- Early metoprolol use in ICU patients with congestive heart failure is associated with increased 30-day mortality: a causal machine learning study.Frontiers in pharmacology · 2026Article
- A machine learning model for predicting 28-day mortality in ICU patients with community-acquired pneumonia and acute kidney injury.Scientific reports · 2025Article
- Prognostic Value of SIRS, SOFA, qSOFA, and LqSOFA in Emergency Department Sepsis Patients and Correlation of Cytokine Patterns With In-Hospital Mortality.Journal of clinical medicine research · 2025Article
- Explainable AI unravels sepsis heterogeneity via coagulation-inflammation profiles for prognosis and stratification.Nature communications · 2025Observational
- Article
- Predictive value of seven scoring systems for 28-day mortality in ICU patients with Sleep apnea-hypopnea syndrome (SAHS) and clinical indicators.European journal of medical research · 2025Article
- Development and validation of an explainable machine learning model for predicting prognosis in sepsis patients with a history of cancer who were admitted to the intensive care unit.The Journal of international medical research · 2025Article
- Association Between the Glucose-to-Lymphocyte Ratio and 28-Day Mortality in Patients with Mechanical Ventilation.Balkan medical journal · 2025Article
- Comparison of Intensive Care Scoring Systems in Predicting Overall Mortality of Sepsis.Diagnostics (Basel, Switzerland) · 2025Article
- Machine learning-derived multivariate renal function trajectories in acute kidney injury in critically ill patients: a multicentre retrospective study.Clinical kidney journal · 2025Article
- Development and validation of a predictive model for hospital mortality in patients with community-acquired pneumonia admitted to the intensive care unit.The Journal of international medical research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Our study aimed to identify the optimal scoring system for predicting the prognosis of patients with sepsis-associated acute respiratory failure (SA-ARF). All data were taken from the fourth version of the Markets in Intensive Care Medicine (MIMIC-IV) database. Independent risk factors for death in hospitals were confirmed by regression analysis. The predictive value of the five scoring systems was evaluated by receiving operating characteristic (ROC) curves. Kaplan‒Meier curves showed the impact of acute physiology score III (APSIII) on survival and prognosis in patients with SA-ARF. Decision curve analysis (DCA) identified a scoring system with the highest net clinical benefit. ROC curve analysis showed that APS III (AUC: 0.755, 95% Cl 0.714-0.768) and Logical Organ Dysfunction System (LODS) (AUC: 0.731, 95% Cl 0.717-0.7745) were better than Simplified Acute Physiology Score II (SAPS II) (AUC: 0.727, 95% CI 0.713-0.741), Oxford Acute Severity of Illness Score (OASIS) (AUC: 0.706, 95% CI 0.691-0.720) and Sequential Organ Failure Assessment (SOFA) (AUC: 0.606, 95% CI 0.590-0.621) in assessing in-hospital mortality. Kaplan‒Meier survival analysis patients in the high-APS III score group had a considerably poorer median survival time. The DCA curve showed that APS III may provide better clinical benefits for patients. We demonstrated that the APS III score is an excellent predictor of in-hospital mortality.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.