Related Experiment Video
Updated: Jul 11, 2025
A Preclinical Model of Exertional Heat Stroke in Mice
Published on: July 1, 2021
A nomogram based on lymphocyte percentage for predicting hospital mortality in exertional heatstroke patients: a
Jiale Yang1,2, Fanghe Gong3, Xuezhi Shi2
1Guangzhou University of Chinese Medicine, Guangzhou 510006, China.
Background:
Exertional heatstroke (EHS) is a life-threatening disease without ideal prognostic markers for predicting hospital mortality.
Methods:
This is a single-center retrospective study. Clinical data from EHS patients admitted to the Intensive Care Unit (ICU) of the General Hospital of Southern Theatre Command between January 1, 2008, and December 31, 2020, were recorded and analyzed. Univariate and multivariate logistic regression were used to identify the factors for mortality. The prediction model was developed with the prognostic markers, and a nomogram was established.
Results:
The study ultimately enrolled 156 patients, and 15 (9.6%) of patients died before discharge. The lymphocyte count (Lym) and percentage (Lym%) were significantly lower in non-survivors (P<0.05). The univariate and multivariate logistic regression analyses indicated that Lym% at the third day of admission (Lym% D3) (OR=0.609, 95%CI: 0.454-0.816) and hematocrit (HCT) (OR=0.908, 95%CI: 0.834-0.988) were independent protective factors for hospital mortality. A nomogram incorporating Lym% D3 with HCT was developed and demonstrated good discrimination and calibration ability. The comparison between the prediction model and scoring systems revealed that the prediction model had the largest area under the curve (AUC) (0.948, 95%CI: 0.900-0.977), with 100.00% sensitivity and 83.69% specificity, and a greater clinical net benefit.
Conclusion:
Severe EHS patients had a higher risk of experiencing prolonged lymphopenia. A nomogram based on Lym% D3 and HCT was developed to facilitate early identification and timely treatment of patients with potentially unfavorable prognoses.
