Evidence map›Paper›PMID 38274425›Full record

ArticleFrontiers in psychiatry2023

The risk factors and predictive modeling of mortality in patients with mental disorders combined with severe pneumonia.

Yaolin Li, Weiguo Zhou, Huiqin Wang, Jing Yang, Xiayahu Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 43% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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 at 4 institutions in 1 country.

Yaolin LiDepartment of Respiratory and Critical Care Medicine, The Third People's Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University, Chengdu, China.
Weiguo ZhouDepartment of Critical Care Medicine, Chengdu Fourth People's Hospital, Chengdu, China.
Huiqin WangThe Affiliated Women's and Children's Hospital, School of Medicine, UESTC, Chengdu, China.
Jing YangDepartment of Critical Care Medicine, Chengdu Fourth People's Hospital, Chengdu, China.
Xiayahu LiDepartment of Critical Care Medicine, Chengdu Second's People Hospital, Chengdu, China.
Fourth People's Hospital of Sichuan Province · CNChengdu Second People's Hospital · CNSouthwest Jiaotong University · CNUniversity of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: We explored clinical characteristics and risk factors for mortality in patients with mental disorders combined with severe pneumonia and developed predictive models. Methods: We retrospectively analyzed the data of 161 patients with mental disorders combined with severe pneumonia in the intensive care unit (ICU) of a psychiatric hospital from May 2020 to February 2023, and divided them into two groups according to whether they died or not, and analyzed their basic characteristics, laboratory results and treatments, etc. We analyzed the risk factors of patients' deaths using logistics regression, established a prediction model, and drew a dynamic nomogram based on the results of the regression analysis. Based on the results of regression analysis, a prediction model was established and a dynamic nomogram was drawn. Results: The non-survivor group and the survivor group of patients with mental disorders combined with severe pneumonia were statistically different in terms of age, type of primary mental illness, whether or not they were intubated, whether or not they had been bedridden for a long period in the past, and the Montreal Cognitive Assessment (MoCA) scale, procalcitonin (PCT), albumin (ALB), hemoglobin (Hb), etc. Logistics regression analysis revealed the following: MoCA scale (OR = 0.932, 95% CI:0.872-0.997), age (OR = 1.077, 95%CI:1.029-1.128), PCT (OR = 1.078, 95% CI:10.006-10.155), ALB (OR = 0.971, 95%CI:0.893-1.056), Hb (OR = 0.971, 95% CI: 0.942-0.986) were statistically significant. The ROC curve showed that the model predicted patient death with an area under the curve (AUC) of 0.827 with a sensitivity of 73.4% and a specificity of 80.4%. Conclusion: Low MoCA score, age, PCT, and low Hb are independent risk factors for death in patients with mental disorders with severe pneumonia, and the prediction model constructed using these factors showed good predictive efficacy.

Indexed as

mental disorderpredictive modelingrisk factorssevere pneumoniaThe Montreal Cognitive Assessment

Identifiers

PMID38274425
PMCPMC10808291
OpenAlexW4390807185

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.