ArticleTzu chi medical journal
Early prediction of survival at different time intervals in sepsis patients: A visualized prediction model with nomogram and observation study.
Article in Tzu chi medical journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction models for mortality in patients with sepsis: a systematic review and meta-analysis.Frontiers in medicine · 2026Pooled it
- Development and validation of a nomogram model for predicting 28-day mortality in patients with sepsis.Heliyon · 2024Article
- Risk factors for sepsis in patients with colorectal cancer complicated with gastrointestinal perforation and its impact on prognosis.Journal of gastrointestinal oncology · 2023Article
- Pre-hospital Prognostic Factors of 30-Day Survival in Sepsis Patients; a Retrospective Cohort Study.Archives of academic emergency medicine · 2023Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesSepsis is a major cause of death around the world. Complicated scoring systems require time to have data to predict short-term survival. Intensivists need a tool to predict survival in sepsis patients easily and quickly. MATERIALS AND
methodsThis retrospective study reviewed the medical records of adult patients admitted to the surgical intensive care units between January 2009 and December 2011 in National Taiwan University Hospital. For this study, 739 patients were enrolled. We recorded the demographic and clinical variables of patients diagnosed with sepsis. A Cox proportional hazard model was used to analyze the survival data and determine significant risk factors to develop a prediction model. This model was used to create a nomogram for predicting the survival rate of sepsis patients up to 3 months.
resultsThe observed 28-day, 60-day, and 90-day survival rates were 71.43%, 52.53%, and 46.88%, respectively. The principal risk factors for survival prediction included age; history of dementia; Glasgow Coma Scale score; and lactate, creatinine, and platelet levels. Our model showed more favorable prediction than did Acute Physiology and Chronic Health Evaluation II and Sequential Organ Failure Assessment at sepsis onset (concordance index: 0.65 vs. 0.54 and 0.59). This model was used to create the nomogram for predicting the mortality at the onset of sepsis.
conclusionWe suggest that developing a nomogram with several principal risk factors can provide a quick and easy tool to early predict the survival rate at different intervals in sepsis patients.
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