ArticleCritical care medicine2016
A Severe Sepsis Mortality Prediction Model and Score for Use With Administrative Data.
Article in Critical care medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 2 of them syntheses that pooled it.
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
46 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Prediction models for mortality in patients with sepsis: a systematic review and meta-analysis.Frontiers in medicine · 2026Pooled it
- Machine learning for the prediction of sepsis-related death: a systematic review and meta-analysis.BMC medical informatics and decision making · 2023Pooled it
- A comparison of machine learning models versus clinical evaluation for mortality prediction in patients with sepsis.PloS one · 2021Trial
- The German Quality Network Sepsis: study protocol for the evaluation of a quality collaborative on decreasing sepsis-related mortality in a quasi-experimental difference-in-differences design.Implementation science : IS · 2018Trial
- Stable Nationwide Sepsis-Related Mortality Does Not Extend to Individuals with Alcohol-Associated Liver Disease.Digestive diseases and sciences · 2026Article
- Machine learning-based prognostic model for 30-day mortality prediction in Sepsis-3.BMC medical informatics and decision making · 2024Article
- Trajectories of State-Level Sepsis-Related Mortality by Race and Ethnicity Group in the United States.Journal of clinical medicine · 2024Article
- Article
- Prediction of mortality in patients with secondary pulmonary embolism based on primary admission indication: A short communication.Biomolecules & biomedicine · 2024Article
- The value of the INFECTIONS scoring system in identifying bacterial infections among patients presenting at the emergency department of a middle-income country: A pilot study.Chinese journal of traumatology = Zhonghua chuang shang za zhi · 2024Article
- Construction and evaluation of shortZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2024Article
- Neighborhood socioeconomic deprivation, healthcare access, and 30-day mortality and readmission after sepsis or critical illness: findings from a nationwide study.Critical care (London, England) · 2023Article
- Association of severe mental illness and septic shock case fatality rate in patients admitted to the intensive care unit: A national population-based cohort study.PLoS medicine · 2023Article
- Can markers of disease severity improve the predictive power of claims-based multimorbidity indices?Journal of the American Geriatrics Society · 2023Article
- Ecological effects of selective oral decontamination on multidrug-resistance bacteria acquired in the intensive care unit: a case-control study over 5 years.Intensive care medicine · 2022Article
- Explainable Artificial Intelligence Helps in Understanding the Effect of Fibronectin on Survival of Sepsis.Cells · 2022Article
- Predictive Validity of the Sequential Organ Failure Assessment Score versus Claims-based Scores among Critically Ill Patients.Annals of the American Thoracic Society · 2022Article
- Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach.Journal of medical Internet research · 2022Article
- Impact of history of mental disorders on short-term mortality among hospitalized patients with sepsis: A population-based cohort study.PloS one · 2022Article
- Development and validation of risk-adjusted quality indicators for the long-term outcome of acute sepsis care in German hospitals based on health claims data.Frontiers in medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
objectiveAdministrative data are used for research, quality improvement, and health policy in severe sepsis. However, there is not a sepsis-specific tool applicable to administrative data with which to adjust for illness severity. Our objective was to develop, internally validate, and externally validate a severe sepsis mortality prediction model and associated mortality prediction score.
designRetrospective cohort study using 2012 administrative data from five U.S. states. Three cohorts of patients with severe sepsis were created: 1) International Classification of Diseases, 9th Revision, Clinical Modification codes for severe sepsis/septic shock, 2) Martin approach, and 3) Angus approach. The model was developed and internally validated in International Classification of Diseases, 9th Revision, Clinical Modification, cohort and externally validated in other cohorts. Integer point values for each predictor variable were generated to create a sepsis severity score.
settingAcute care, nonfederal hospitals in New York, Maryland, Florida, Michigan, and Washington. SUBJECTS: Patients in one of three severe sepsis cohorts: 1) explicitly coded (n = 108,448), 2) Martin cohort (n = 139,094), and 3) Angus cohort (n = 523,637)
interventionsNone. MEASUREMENTS AND MAIN
resultsMaximum likelihood estimation logistic regression to develop a predictive model for in-hospital mortality. Model calibration and discrimination assessed via Hosmer-Lemeshow goodness-of-fit and C-statistics, respectively. Primary cohort subset into risk deciles and observed versus predicted mortality plotted. Goodness-of-fit demonstrated p value of more than 0.05 for each cohort demonstrating sound calibration. C-statistic ranged from low of 0.709 (sepsis severity score) to high of 0.838 (Angus cohort), suggesting good to excellent model discrimination. Comparison of observed versus expected mortality was robust although accuracy decreased in highest risk decile.
conclusionsOur sepsis severity model and score is a tool that provides reliable risk adjustment for administrative data.
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.