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. 2024 Dec 26;19(12):e0316254.
doi: 10.1371/journal.pone.0316254. eCollection 2024.

Nomogram model for predicting secondary infection in critically ill patients with heatstroke: A pilot study from China

Guodong Lin  1   2 , Hailun Peng  3 , Bingling Yin  4 , Chongxiao Xu  5 , Yueli Zhao  2 , Anwei Liu  2 , Haiyang Guo  4 , Zhiguo Pan  1   4   6
Affiliations

Nomogram model for predicting secondary infection in critically ill patients with heatstroke: A pilot study from China

Guodong Lin et al. PLoS One. .

Abstract

Objective: In this retrospective analysis, we explored the clinical characteristics and risk factors of secondary infections in patients with severe heatstroke with the aim to gain epidemiological insights and identify risk factors for secondary infections.

Method: The study included 129 patients with severe heatstroke admitted to the General Hospital of the Southern Theater Command of the PLA between January 1, 2011, and December 31, 2021. Patients were divided into an infection group (n = 24) and a non-infection group (n = 105) based on infection occurrence within 48 h of intensive care unit (ICU) admission. Clinical indicators, infection indicators, and clinical outcomes within 24 h of ICU admission were collected and compared between the groups. Independent risk factors for infection in patients with severe heatstroke were analyzed using univariate and multivariate analyses. A nomogram model was constructed, evaluated, and validated.

Result: Among the 129 patients with heatstroke, 24 developed secondary infections. Infections occurred between days 3 and 10 post-ICU admission, primarily affecting the lungs. Multivariate analysis identified vasopressor use, serum creatinine level, and gastrointestinal dysfunction at admission as independent risk factors, while elevated lymphocyte count (odds ratio [OR] = 0.167; 95% confidence interval [CI] 0.049-0.572; P = 0.004) was protective against severe heatstroke. Infected patients required longer durations of mechanical ventilation (OR = 2.764; 95% CI, 1.735-4.405; P = 0.044) and total hospital stay than those in the non-infection group. The nomogram model demonstrated clinical feasibility.

Conclusion: Increased lymphocyte count is an independent protective factor against infections in patients with severe heatstroke. Vasopressor use, gastrointestinal dysfunction, and elevated serum creatinine levels are independent risk factors. These indicators can aid clinicians in assessing infection risk in patients with severe heatstroke.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Flowchart of patients with severe heatstroke grouped according to whether they had secondary infections.
Fig 2
Fig 2. Distribution of infected sites in the infection group of ICU patients with heatstroke.
Fig 3
Fig 3. Distribution of secondary infection cases and time of infection in ICU heatstroke.
Fig 4
Fig 4. Pathogen distribution in the infection group of ICU patients with heatstroke.
Fig 5
Fig 5. ROC curve for the prediction model, vasopressors use, serum creatinine levels, and gastrointestinal dysfunction in predicting secondary infection in patients with heatstroke.
Fig 6
Fig 6. Nomogram for predicting secondary infection in patients with heatstroke.
Fig 7
Fig 7. Calibration curve of the nomogram for predicting secondary infection in patients with heatstroke.
Fig 8
Fig 8. Decision curve analysis (DCA) comparison of the prediction model and serum creatinine.
Fig 9
Fig 9. Clinical impact curve (CIC) of the serum creatinine.
Fig 10
Fig 10. Clinical impact curve (CIC) of the prediction model.
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