A model based on meta-analysis to evaluate poor prognosis of patients with severe fever with thrombocytopenia syndrome
BackgroundEarly identification of risk factors associated with poor prognosis in Severe fever with thrombocytopenia syndrome (SFTS) patients is crucial to improving patient survival.MethodRetrieve literature related to fatal risk factors in SFTS patients in the database, extract the risk factors and...
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Frontiers Media S.A.
2024-01-01
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| Series: | Frontiers in Microbiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmicb.2023.1307960/full |
| _version_ | 1797361768776859648 |
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| author | Zishuai Liu Zhouling Jiang Ligang Zhang Xiaoyu Xue Chenxi Zhao Yanli Xu Wei Zhang Ling Lin Zhihai Chen |
| author_facet | Zishuai Liu Zhouling Jiang Ligang Zhang Xiaoyu Xue Chenxi Zhao Yanli Xu Wei Zhang Ling Lin Zhihai Chen |
| author_sort | Zishuai Liu |
| collection | DOAJ |
| description | BackgroundEarly identification of risk factors associated with poor prognosis in Severe fever with thrombocytopenia syndrome (SFTS) patients is crucial to improving patient survival.MethodRetrieve literature related to fatal risk factors in SFTS patients in the database, extract the risk factors and corresponding RRs and 95% CIs, and merge them. Statistically significant factors were included in the model, and stratified and assigned a corresponding score. Finally, a validation cohort from Yantai Qishan Hospital in 2021 was used to verify its predictive ability.ResultA total of 24 articles were included in the meta-analysis. The model includes six risk factors: age, hemorrhagic manifestations, encephalopathy, Scr and BUN. The analysis of lasso regression and multivariate logistic regression shows that model score is an independent risk factor (OR = 1.032, 95% CI 1.002–1.063, p = 0.034). The model had an area under the curve (AUC) of 0.779 (95% CI 0.669–0.889, P<0.001). The validation cohort was divided into four risk groups with cut-off values. Compared with the low-medium risk group, the mortality rate of high-risk and very high-risk patients was more significant (RR =5.677, 95% CI 4.961–6.496, P<0.001).ConclusionThe prediction model for the fatal outcome of SFTS patients has shown positive outcomes.Systematic review registration:https://www.crd.york.ac.uk/prospero/ (CRD42023453157). |
| first_indexed | 2024-03-08T15:59:14Z |
| format | Article |
| id | doaj.art-160ce819db234955af15f3740a3b840e |
| institution | Directory Open Access Journal |
| issn | 1664-302X |
| language | English |
| last_indexed | 2024-03-08T15:59:14Z |
| publishDate | 2024-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Microbiology |
| spelling | doaj.art-160ce819db234955af15f3740a3b840e2024-01-08T11:42:56ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2024-01-011410.3389/fmicb.2023.13079601307960A model based on meta-analysis to evaluate poor prognosis of patients with severe fever with thrombocytopenia syndromeZishuai Liu0Zhouling Jiang1Ligang Zhang2Xiaoyu Xue3Chenxi Zhao4Yanli Xu5Wei Zhang6Ling Lin7Zhihai Chen8Department of Infectious Disease, Beijing Ditan Hospital, Capital Medical University, Beijing, ChinaDepartment of Infectious Disease, Beijing Ditan Hospital, Capital Medical University, Beijing, ChinaDepartment of Infectious Diseases, Yantai Qishan Hospital, Yantai, ChinaDepartment of Infectious Disease, Beijing Ditan Hospital, Capital Medical University, Beijing, ChinaDepartment of Infectious Disease, Beijing Ditan Hospital, Capital Medical University, Beijing, ChinaDepartment of Infectious Diseases, Yantai Qishan Hospital, Yantai, ChinaDepartment of Infectious Disease, Beijing Ditan Hospital, Capital Medical University, Beijing, ChinaDepartment of Infectious Diseases, Yantai Qishan Hospital, Yantai, ChinaDepartment of Infectious Disease, Beijing Ditan Hospital, Capital Medical University, Beijing, ChinaBackgroundEarly identification of risk factors associated with poor prognosis in Severe fever with thrombocytopenia syndrome (SFTS) patients is crucial to improving patient survival.MethodRetrieve literature related to fatal risk factors in SFTS patients in the database, extract the risk factors and corresponding RRs and 95% CIs, and merge them. Statistically significant factors were included in the model, and stratified and assigned a corresponding score. Finally, a validation cohort from Yantai Qishan Hospital in 2021 was used to verify its predictive ability.ResultA total of 24 articles were included in the meta-analysis. The model includes six risk factors: age, hemorrhagic manifestations, encephalopathy, Scr and BUN. The analysis of lasso regression and multivariate logistic regression shows that model score is an independent risk factor (OR = 1.032, 95% CI 1.002–1.063, p = 0.034). The model had an area under the curve (AUC) of 0.779 (95% CI 0.669–0.889, P<0.001). The validation cohort was divided into four risk groups with cut-off values. Compared with the low-medium risk group, the mortality rate of high-risk and very high-risk patients was more significant (RR =5.677, 95% CI 4.961–6.496, P<0.001).ConclusionThe prediction model for the fatal outcome of SFTS patients has shown positive outcomes.Systematic review registration:https://www.crd.york.ac.uk/prospero/ (CRD42023453157).https://www.frontiersin.org/articles/10.3389/fmicb.2023.1307960/fullSFTSrisk factorsmeta-analysisprediction modelcohort study |
| spellingShingle | Zishuai Liu Zhouling Jiang Ligang Zhang Xiaoyu Xue Chenxi Zhao Yanli Xu Wei Zhang Ling Lin Zhihai Chen A model based on meta-analysis to evaluate poor prognosis of patients with severe fever with thrombocytopenia syndrome Frontiers in Microbiology SFTS risk factors meta-analysis prediction model cohort study |
| title | A model based on meta-analysis to evaluate poor prognosis of patients with severe fever with thrombocytopenia syndrome |
| title_full | A model based on meta-analysis to evaluate poor prognosis of patients with severe fever with thrombocytopenia syndrome |
| title_fullStr | A model based on meta-analysis to evaluate poor prognosis of patients with severe fever with thrombocytopenia syndrome |
| title_full_unstemmed | A model based on meta-analysis to evaluate poor prognosis of patients with severe fever with thrombocytopenia syndrome |
| title_short | A model based on meta-analysis to evaluate poor prognosis of patients with severe fever with thrombocytopenia syndrome |
| title_sort | model based on meta analysis to evaluate poor prognosis of patients with severe fever with thrombocytopenia syndrome |
| topic | SFTS risk factors meta-analysis prediction model cohort study |
| url | https://www.frontiersin.org/articles/10.3389/fmicb.2023.1307960/full |
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