What does this research mean for the field?

A nomogram integrating immune-inflammatory-nutritional indicators predicts 28-day mortality in sepsis patients with ARDS with an AUC of 0.873, outperforming the SOFA score. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To develop a nomogram that integrates immune-inflammatory-nutritional indicators to predict 28-day mortality in sepsis patients with ARDS.

February 28, 2026SHILAP Revista de lepidopterologíaOpen Access

A risk prediction model based on immune-inflammatory-nutritional indicators for predicting 28-day mortality in sepsis patients with acute respiratory distress syndrome

View Full Paper

Ask AI

Bookmark

Authors

QXQi Xin XDXingbo Dang GDGongliang Du

Discussion

Member takes

Overview

A nomogram predicts 28-day mortality in sepsis patients with ARDS, suggesting improved clinical decision-making.

Key Points

To develop a nomogram that integrates immune-inflammatory-nutritional indicators to predict 28-day mortality in sepsis patients with ARDS.
Analyzed clinical data from 635 sepsis patients with ARDS, split into training (477) and validation (158) sets.
Utilized univariate analysis and LASSO regression to identify predictors of mortality.
Constructed a multivariate logistic regression model for independent predictors and developed a nomogram.
Assessed model performance using AUC, calibration plots, and decision curve analysis.
Identified independent predictors including AAPR, ALBI, NLR, PLR, PNI, SII, and LAR for mortality risk.
Achieved AUC of 0.873 in training set and 0.837 in validation set, outperforming the SOFA score (AUC 0.689).
Demonstrated excellent consistency via calibration plots and confirmed clinical utility through decision curve analysis.

Cite This Study

Xin et al. (2026) studied this question.

synapsesocial.com/papers/69a285aa0a974eb0d3c00a0a https://doi.org/10.3389/fnut.2026.1764044

View Full Paper

Ask AI

Bookmark

February 28, 2026SHILAP Revista de lepidopterologíaOpen Access

A risk prediction model based on immune-inflammatory-nutritional indicators for predicting 28-day mortality in sepsis patients with acute respiratory distress syndrome

View Full Paper

Ask AI

Bookmark

Authors

QXQi Xin XDXingbo Dang GDGongliang Du

Discussion

Member takes

Overview

A nomogram predicts 28-day mortality in sepsis patients with ARDS, suggesting improved clinical decision-making.

Key Points

To develop a nomogram that integrates immune-inflammatory-nutritional indicators to predict 28-day mortality in sepsis patients with ARDS.
Analyzed clinical data from 635 sepsis patients with ARDS, split into training (477) and validation (158) sets.
Utilized univariate analysis and LASSO regression to identify predictors of mortality.
Constructed a multivariate logistic regression model for independent predictors and developed a nomogram.
Assessed model performance using AUC, calibration plots, and decision curve analysis.
Identified independent predictors including AAPR, ALBI, NLR, PLR, PNI, SII, and LAR for mortality risk.
Achieved AUC of 0.873 in training set and 0.837 in validation set, outperforming the SOFA score (AUC 0.689).
Demonstrated excellent consistency via calibration plots and confirmed clinical utility through decision curve analysis.

Cite This Study

Xin et al. (2026) studied this question.

synapsesocial.com/papers/69a285aa0a974eb0d3c00a0a https://doi.org/10.3389/fnut.2026.1764044

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

View Full Paper

Ask AI

Bookmark