Evidence map›Paper›PMID 31144659›Full record

ArticleThe Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology2019

Model for end-stage liver disease and pneumonia: An improved scoring model for critically ill cirrhotic patients with pneumonia.

Feng Gao, Meng-Xing Cai, Miao-Tong Lin, Ling-Zhi Zhang, Qian-Zi Ruan, Feng Gao

Abstract readComparative Study
In one paragraph

Article in The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Feng GaoDepartment of Gastroenterology and Hepatology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Meng-Xing CaiDepartment of Cardiovascular Medicine, the Heart Center, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Miao-Tong LinDepartment of Emergency Medicine, Intensive Care, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Ling-Zhi ZhangDepartment of Electrocardiogram, the First People's Hospital of Wenling, Wenling, China.
Qian-Zi RuanDepartment of Bone and Joint Surgery, the First People's Hospital of Wenling, Wenling, China.
Feng GaoDepartment of Gastroenterology and Hepatology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

aimsCritically ill patients with cirrhosis with pneumonia are at an increased risk for mortality. Only a few accurate predictive models are existing specific to these patients. The aim of the present study was to compare the existing prognostic models and to develop an improved mortality risk model for patients with cirrhosis and pneumonia. MATERIALS AND

methodsA total of 231 patients were enrolled in our study (70% training and 30% validation cohorts). All participants were followed up for at least 21 days. Model for End-stage Liver Disease and Pneumonia (MELD-P) was derived by the Cox proportional hazards model. The performances of prognostic scoring systems were compared by calculation of the area under the receiver operating characteristic (AUROC) curve.

resultsMELD-P showed better discriminative capabilities than existing scoring systems. Four clinical variables, including loge bilirubin (hazard ratio (HR) 1.29, 95% confidence interval (CI) 1.01-1.73), loge international normalized ratio (HR 3.57, 95% CI 1.30-9.78), loge pulse oxygen saturation/fraction of inspired oxygen (HR 0.38, 95% CI 0.14-0.99), and vasopressors used (HR 3.72, 95% CI 1.85-7.49), were considered as independent prognostic values associated with 21-day mortality. MELD-P had AUROC curve values of 0.78 (95% CI 0.71-0.84) in predicting in-hospital mortality, 0.78 (95% CI 0.70-0.84) at 21-day, 0.88 (95% CI 0.82-0.93) at 14-day, and 0.87 (95% CI 0.81-0.92) at 7-day. A similar result was obtained in validation cohort.

conclusionMELD-P, as the first model specifically designed to evaluate the risk of mortality in critically ill patients with cirrhosis and pneumonia, performs well on the mortality assessment of short-term mortality.

Indexed as

AdultAgedArea Under CurveCritical IllnessEnd Stage Liver DiseaseFemaleHospital MortalityHumansInternational Normalized RatioKaplan-Meier EstimateLiver CirrhosisMaleMiddle AgedPneumoniaPrognosisProportional Hazards Models

Identifiers

PMID31144659
PMCPMC6565347

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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.