Nomogram model for predicting secondary infection in critically ill patients with heatstroke: A pilot study from China.
<h4>Objective</h4>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.<h4>Method</h4&...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2024-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0316254 |
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| author | Guodong Lin Hailun Peng Bingling Yin Chongxiao Xu Yueli Zhao Anwei Liu Haiyang Guo Zhiguo Pan |
| author_facet | Guodong Lin Hailun Peng Bingling Yin Chongxiao Xu Yueli Zhao Anwei Liu Haiyang Guo Zhiguo Pan |
| author_sort | Guodong Lin |
| collection | DOAJ |
| description | <h4>Objective</h4>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.<h4>Method</h4>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.<h4>Result</h4>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.<h4>Conclusion</h4>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. |
| format | Article |
| id | doaj-art-563c592f54d44fd8b06907c987b64c4c |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-563c592f54d44fd8b06907c987b64c4c2025-01-08T05:32:28ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-011912e031625410.1371/journal.pone.0316254Nomogram model for predicting secondary infection in critically ill patients with heatstroke: A pilot study from China.Guodong LinHailun PengBingling YinChongxiao XuYueli ZhaoAnwei LiuHaiyang GuoZhiguo Pan<h4>Objective</h4>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.<h4>Method</h4>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.<h4>Result</h4>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.<h4>Conclusion</h4>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.https://doi.org/10.1371/journal.pone.0316254 |
| spellingShingle | Guodong Lin Hailun Peng Bingling Yin Chongxiao Xu Yueli Zhao Anwei Liu Haiyang Guo Zhiguo Pan Nomogram model for predicting secondary infection in critically ill patients with heatstroke: A pilot study from China. PLoS ONE |
| title | Nomogram model for predicting secondary infection in critically ill patients with heatstroke: A pilot study from China. |
| title_full | Nomogram model for predicting secondary infection in critically ill patients with heatstroke: A pilot study from China. |
| title_fullStr | Nomogram model for predicting secondary infection in critically ill patients with heatstroke: A pilot study from China. |
| title_full_unstemmed | Nomogram model for predicting secondary infection in critically ill patients with heatstroke: A pilot study from China. |
| title_short | Nomogram model for predicting secondary infection in critically ill patients with heatstroke: A pilot study from China. |
| title_sort | nomogram model for predicting secondary infection in critically ill patients with heatstroke a pilot study from china |
| url | https://doi.org/10.1371/journal.pone.0316254 |
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