Predictive analysis of all-cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertension
ObjectiveTo investigate the risk factors for all-cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertension and construct a predictive model.MethodsWe retrospectively analyzed the clinical data of inpatients with previously untreated pulmonary tuberculosis co...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-08-01
|
| Series: | Frontiers in Cellular and Infection Microbiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fcimb.2025.1574824/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849390736704798720 |
|---|---|
| author | Anhua Cao You Nie Zhun Zhong Yi Pei Yi Pei Ping Deng Hebin Xie Yiping Leng Yiping Leng |
| author_facet | Anhua Cao You Nie Zhun Zhong Yi Pei Yi Pei Ping Deng Hebin Xie Yiping Leng Yiping Leng |
| author_sort | Anhua Cao |
| collection | DOAJ |
| description | ObjectiveTo investigate the risk factors for all-cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertension and construct a predictive model.MethodsWe retrospectively analyzed the clinical data of inpatients with previously untreated pulmonary tuberculosis complicated by hypertension from 2019 to 2021 in Changsha Central Hospital. Patients’ survival status and cardiovascular events were collected through telephone follow-up. LASSO regression was utilized to screen predictive variables, and binary logistic regression identified mortality risk factors. A predictive nomogram model was developed using R software, and its precision and reliability were verified.ResultsAmong the 1,014 patients, there were 100 (9.86%) deaths and 82 (8.09%) cardiovascular events. LASSO regression screened out 13 predictive variables. Multivariate logistic regression analysis revealed that smoking history, sputum bacteriology, pleural effusion, coronary heart disease, and chronic kidney disease were independent risk factors. Based on the training set data, a nomogram prognostic model was developed, showing an AUC of 0.712 (95% CI: 0.777-0.847), with 50.0% sensitivity and 84.3% specificity. The model’s fit was confirmed through internal and external validations.ConclusionThe prediction model constructed in this study has high predictive ability and satisfactory clinical efficacy, and can provide an effective individualized prediction tool for assessing all-cause mortality risk in patients with previously untreated pulmonary tuberculosis complicated by hypertension. |
| format | Article |
| id | doaj-art-ec586682d3214e5bbbec5d68d2ac4e5c |
| institution | Kabale University |
| issn | 2235-2988 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cellular and Infection Microbiology |
| spelling | doaj-art-ec586682d3214e5bbbec5d68d2ac4e5c2025-08-20T03:41:22ZengFrontiers Media S.A.Frontiers in Cellular and Infection Microbiology2235-29882025-08-011510.3389/fcimb.2025.15748241574824Predictive analysis of all-cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertensionAnhua Cao0You Nie1Zhun Zhong2Yi Pei3Yi Pei4Ping Deng5Hebin Xie6Yiping Leng7Yiping Leng8The Affiliated Changsha Central Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Changsha, Hunan, ChinaThe Affiliated Changsha Central Hospital, Department of Laboratory Medicine, Hengyang Medical School, University of South China, Changsha, Hunan, ChinaThe Affiliated Changsha Central Hospital, Center of Tuberculosis Diagnosis and Treatment, Hengyang Medical School, University of South China, Changsha, Hunan, ChinaThe Affiliated Changsha Central Hospital, Center of Tuberculosis Diagnosis and Treatment, Hengyang Medical School, University of South China, Changsha, Hunan, ChinaThe Affiliated Changsha Central Hospital, Technology Demonstration Base for Tuberculosis Diagnosis and Treatment in Hunan Province, University of South China, Changsha, Changsha, Hunan, ChinaThe Affiliated Changsha Central Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Changsha, Hunan, ChinaThe Affiliated Changsha Central Hospital, Department of Science and Education, Hengyang Medical School, University of South China, Changsha, Hunan, ChinaThe Affiliated Changsha Central Hospital, Changsha Tuberculosis Research Institute, Hengyang Medical School, University of South China, Changsha, Hunan, ChinaThe Affiliated Changsha Central Hospital, Changsha Technology Innovation Center for Tuberculosis Diagnosis and Treatment, University of South China, Changsha, Hunan, ChinaObjectiveTo investigate the risk factors for all-cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertension and construct a predictive model.MethodsWe retrospectively analyzed the clinical data of inpatients with previously untreated pulmonary tuberculosis complicated by hypertension from 2019 to 2021 in Changsha Central Hospital. Patients’ survival status and cardiovascular events were collected through telephone follow-up. LASSO regression was utilized to screen predictive variables, and binary logistic regression identified mortality risk factors. A predictive nomogram model was developed using R software, and its precision and reliability were verified.ResultsAmong the 1,014 patients, there were 100 (9.86%) deaths and 82 (8.09%) cardiovascular events. LASSO regression screened out 13 predictive variables. Multivariate logistic regression analysis revealed that smoking history, sputum bacteriology, pleural effusion, coronary heart disease, and chronic kidney disease were independent risk factors. Based on the training set data, a nomogram prognostic model was developed, showing an AUC of 0.712 (95% CI: 0.777-0.847), with 50.0% sensitivity and 84.3% specificity. The model’s fit was confirmed through internal and external validations.ConclusionThe prediction model constructed in this study has high predictive ability and satisfactory clinical efficacy, and can provide an effective individualized prediction tool for assessing all-cause mortality risk in patients with previously untreated pulmonary tuberculosis complicated by hypertension.https://www.frontiersin.org/articles/10.3389/fcimb.2025.1574824/fullpreviously untreated pulmonary tuberculosishypertensionmortality raterisk factorsprediction model |
| spellingShingle | Anhua Cao You Nie Zhun Zhong Yi Pei Yi Pei Ping Deng Hebin Xie Yiping Leng Yiping Leng Predictive analysis of all-cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertension Frontiers in Cellular and Infection Microbiology previously untreated pulmonary tuberculosis hypertension mortality rate risk factors prediction model |
| title | Predictive analysis of all-cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertension |
| title_full | Predictive analysis of all-cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertension |
| title_fullStr | Predictive analysis of all-cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertension |
| title_full_unstemmed | Predictive analysis of all-cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertension |
| title_short | Predictive analysis of all-cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertension |
| title_sort | predictive analysis of all cause mortality of previously untreated pulmonary tuberculosis patients complicated by hypertension |
| topic | previously untreated pulmonary tuberculosis hypertension mortality rate risk factors prediction model |
| url | https://www.frontiersin.org/articles/10.3389/fcimb.2025.1574824/full |
| work_keys_str_mv | AT anhuacao predictiveanalysisofallcausemortalityofpreviouslyuntreatedpulmonarytuberculosispatientscomplicatedbyhypertension AT younie predictiveanalysisofallcausemortalityofpreviouslyuntreatedpulmonarytuberculosispatientscomplicatedbyhypertension AT zhunzhong predictiveanalysisofallcausemortalityofpreviouslyuntreatedpulmonarytuberculosispatientscomplicatedbyhypertension AT yipei predictiveanalysisofallcausemortalityofpreviouslyuntreatedpulmonarytuberculosispatientscomplicatedbyhypertension AT yipei predictiveanalysisofallcausemortalityofpreviouslyuntreatedpulmonarytuberculosispatientscomplicatedbyhypertension AT pingdeng predictiveanalysisofallcausemortalityofpreviouslyuntreatedpulmonarytuberculosispatientscomplicatedbyhypertension AT hebinxie predictiveanalysisofallcausemortalityofpreviouslyuntreatedpulmonarytuberculosispatientscomplicatedbyhypertension AT yipingleng predictiveanalysisofallcausemortalityofpreviouslyuntreatedpulmonarytuberculosispatientscomplicatedbyhypertension AT yipingleng predictiveanalysisofallcausemortalityofpreviouslyuntreatedpulmonarytuberculosispatientscomplicatedbyhypertension |