ABSTRACT
Objective
To investigate the predictive value of the arterial blood lactate to serum albumin ratio (LAR) on in-hospital mortality of patients with community-acquired pneumonia (CAP) admitted to the Intensive Care Unit (ICU).
Methods
Clinical datasets of 1720 CAP patients admitted to ICU from MIMIC-IV database were retrospectively analyzed. Patients were randomly assigned to the training cohort (n=1204) and the validation cohort (n=516) in a ratio of 7:3. X-tile software was used to find the optimal cut-off value for LAR. The receiver operating curve (ROC) analysis was conducted to compare the performance between LAR and other indicators. Univariate and multivariate Cox regression analyses were applied to select prognostic factors associated with in-hospital mortality. Based on the observed prognostic factors, a nomogram model was created in training cohort, and the validation cohort was utilized to further validate the nomogram.
Results
The optimal cut-off value for LAR in CAP patients admitted to ICU was 1.6 (the units of lactate and albumin were, respectively, ‘mmol/L’ and ‘g/dL’). The ROC analysis showed that the discrimination abilities of LAR were superior to other indicators except Sequential Organ Failure Assessment score and Simplified acute physiology score (SAPSII), which had the same abilities. Age, mean arterial pressure, SpO2, heart rate, SAPSII score, neutrophil-to-lymphocyte ratio, and LAR were found to be independent predictors of poor overall survival in the training cohort by multivariate Cox regression analysis and were incorporated into the nomogram for in-hospital mortality as independent factors. The nomogram model, exhibiting medium discrimination, had a C-index of 0.746 (95% CI = 0.715–0.777) in the training cohort and 0.716 (95% CI = 0.667–0.765) in the validation cohort.
Conclusion
LAR could predict in-hospital mortality of patients with CAP admitted to ICU independently as a readily accessible biomarker. The nomogram that included LAR with other independent factors performed well in predicting in-hospital mortality.
Disclosure of financial/other conflicts of interest
The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose
Data availability statement
The data used in this study are available by reasonable request to the corresponding author, as well as in PhysioNet (https://physionet.org/content/mimiciv/1.0/).
Author contributions
Chaoqun Xu, Haoran Liu and Hao Zhang contributed to hypothesis development and manuscript preparation; Yang Yi, Nan Li, and Ruxin Cheng were responsible for collecting blood samples and clinical data of participants; Quan Li and Qi Li conceived, designed, and performed the experiments; Jun Zeng, Xiangdong Zhou, and Chuanzhu Lv critically revised the paper. All authors approved the final version of the manuscript. All authors have participated in the work and have reviewed and agree with the content of the article.