Evidence map›Paper›PMID 42164270›Full record

ArticleFrontiers in cellular and infection microbiology2026

Development and validation of a nomogram based on immune-inflammation-nutrition indictors for predicting 28-day mortality in sepsis patients with severe fungal pneumonia.

Gongliang Du, Longyang Ma, Xingbo Dang, Wei Dai, Qi Xin

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Gongliang DuDepartment of Emergency Surgery, Shaanxi Provincial People's Hospital, Xi'an, China.
Longyang MaDepartment of Emergency Surgery, Shaanxi Provincial People's Hospital, Xi'an, China.
Xingbo DangDepartment of Emergency Surgery, Shaanxi Provincial People's Hospital, Xi'an, China.
Wei DaiDepartment of Emergency Surgery, Shaanxi Provincial People's Hospital, Xi'an, China.
Qi XinDepartment of Emergency Surgery, Shaanxi Provincial People's Hospital, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Severe fungal pneumonia with sepsis carries high mortality. Early and accurate prognosis is essential for improving outcomes. We developed and validated a nomogram based on immune-inflammation-nutrition indicators to predict 28-day mortality in these patients. Methods: We conducted a retrospective, exploratory cohort study analyzing 486 sepsis patients with severe fungal pneumonia, randomly splitting them into training (n=365) and validation (n=121) sets. Using LASSO regression and multivariate logistic regression, we identified independent predictors from clinical, laboratory, and immune-inflammation-nutrition data. We built a nomogram and evaluated its discrimination, calibration, and clinical utility with ROC curves, calibration plots, and decision curve analysis (DCA). Results: Eight independent predictors entered the nomogram: respiratory failure (RF), chronic obstructive pulmonary disease (COPD), prothrombin time (PT), glucose, blood urea nitrogen (BUN), white blood cell count (WBC), albumin-to-alkaline phosphatase ratio (AAPR), and lactate-albumin ratio (LAR). The nomogram achieved AUCs of 0.884 (training) and 0.834 (validation), outperforming the SOFA score (0.740 and 0.691). Furthermore, temporal validation using an independent later cohort achieved an AUC of 0.875. Calibration curves showed good agreement between predicted and observed outcomes. DCA confirmed clinical utility across a wide range of threshold probabilities. Conclusion: We developed and internally validated a practical nomogram that integrates clinical variables with immune-inflammation-nutrition indicators to predict 28-day mortality in sepsis patients with severe fungal pneumonia. This tool may help clinicians with early risk stratification and individualized treatment decisions.

Indexed as

InflammationLung Diseases, FungalMycosesNomogramsPneumoniaSepsisAgedFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesROC Curvefungal pneumoniaimmune-inflammation-nutrition indicatorsmortalitynomogramsepsis

Identifiers

PMID42164270
PMCPMC13183808

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.