Predictive value of triglyceride-glucose index for the occurrence of acute respiratory failure in asthmatic patients of MIMIC-IV database

This study aims to investigate the association between the triglyceride-glucose (TyG) index and the occurrence of acute respiratory failure in asthma patients. This retrospective observational cohort study utilized data from the Medical Information Mart for Intensive Care IV (MIMIC-IV 2.2) database. The primary outcome was the development of acute respiratory failure in asthma patients. Initially, the Boruta algorithm and SHapley Additive exPansions were applied to preliminarily determine the feature importance of the TyG index, and a risk prediction model was constructed to evaluate its predictive ability. Secondly, Logistic regression proportional hazards models were employed to assess the association between the TyG index and acute respiratory failure in asthma patients. Finally, subgroup analyses were conducted for sensitivity analyses to explore the robustness of the results. A total of 751 asthma patients were included in the study. When considering the TyG index as a continuous variable, logistic regression analysis revealed that in the unadjusted Model 1, the odds ratio (OR) was 2.381 (95% CI: 1.857-3.052; P < 0.001), in Model II, the OR was 2.456 (95% CI: 1.809-3.335; P < 0.001), and in the multivariable-adjusted model, the OR was 1.444 (95% CI: 1.029-2.028; P = 0.034). A consistent association was observed between the TyG index and the risk of acute respiratory failure in asthma patients. No significant interaction was found between the TyG index and various subgroups (P > 0.05). Furthermore, machine learning results indicated that an elevated TyG index was a significant feature predictive of respiratory failure in asthma patients. The baseline risk model achieved an AUC of 0.743 (95% CI: 0.679-0.808; P < 0.05), whereas the combination of the baseline risk model with the TyG index yielded an AUC of 0.757 (95% CI: 0.694-0.821; P < 0.05). The TyG index can serve as a predictive indicator for acute respiratory failure in asthma patients, albeit confirmation of these findings requires larger-scale prospective studies.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-11-19
DOI
https://doi.org/10.1038/s41598-024-74294-8
Citations
2
Primary Topic
Chronic Obstructive Pulmonary Disease (COPD) Research
Type
article
Field-Weighted Citation Impact
0.84
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive value of triglyceride-glucose index for the occurrence of acute respiratory failure in asthmatic patients of MIMIC-IV database

Feng Qi, Zhibao Lv, Chun Xiao Ba, Ying Qian Zhang
2 citations
Scientific Reports
Chronic Obstructive Pulmonary Disease (COPD) Research
0.84
article

Predictive value of triglyceride-glucose index for the occurrence of acute respiratory failure in asthmatic patients of MIMIC-IV database

Feng Qi, Zhibao Lv, Chun Xiao Ba, Ying Qian Zhang
article en
2 citations

Abstract

This study aims to investigate the association between the triglyceride-glucose (TyG) index and the occurrence of acute respiratory failure in asthma patients. This retrospective observational cohort study utilized data from the Medical Information Mart for Intensive Care IV (MIMIC-IV 2.2) database. The primary outcome was the development of acute respiratory failure in asthma patients. Initially, the Boruta algorithm and SHapley Additive exPansions were applied to preliminarily determine the feature importance of the TyG index, and a risk prediction model was constructed to evaluate its predictive ability. Secondly, Logistic regression proportional hazards models were employed to assess the association between the TyG index and acute respiratory failure in asthma patients. Finally, subgroup analyses were conducted for sensitivity analyses to explore the robustness of the results. A total of 751 asthma patients were included in the study. When considering the TyG index as a continuous variable, logistic regression analysis revealed that in the unadjusted Model 1, the odds ratio (OR) was 2.381 (95% CI: 1.857-3.052; P < 0.001), in Model II, the OR was 2.456 (95% CI: 1.809-3.335; P < 0.001), and in the multivariable-adjusted model, the OR was 1.444 (95% CI: 1.029-2.028; P = 0.034). A consistent association was observed between the TyG index and the risk of acute respiratory failure in asthma patients. No significant interaction was found between the TyG index and various subgroups (P > 0.05). Furthermore, machine learning results indicated that an elevated TyG index was a significant feature predictive of respiratory failure in asthma patients. The baseline risk model achieved an AUC of 0.743 (95% CI: 0.679-0.808; P < 0.05), whereas the combination of the baseline risk model with the TyG index yielded an AUC of 0.757 (95% CI: 0.694-0.821; P < 0.05). The TyG index can serve as a predictive indicator for acute respiratory failure in asthma patients, albeit confirmation of these findings requires larger-scale prospective studies.

Scientific ReportsVol. 14(1)
Hebei Medical University (CN), Hebei North University (CN), Hospital of Hebei Province (CN)
Zero hunger
Openalex Percentile: Top 23%
Chronic Obstructive Pulmonary Disease (COPD) Research
0.84
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.