{"title":"与严重急性复合组织损伤住院死亡率相关的危险因素及预测预后","authors":"A.M. NAIMOV, A.A. RAZZOKOV, F.M. PARPIEV","doi":"10.25005/2074-0581-2023-25-3-334-345","DOIUrl":null,"url":null,"abstract":"Objective: To develop a reliable risk score prediction model to accurately predict the likelihood of lethal outcomes (LO) in severe acute composite tissue injuries (CTI) cases. Methods: We conducted an analysis of data from 3,186 patients with CTIs who were aged between 18 and 74. Of these patients, 2,432 were men (76.3%), and 754 were women (23.7%). The age distribution of patients was as follows: 2290 (71.9%) were between 18-44 years old, 638 (20.0%) were between 45-59 years old, and 258 (8.1%) were between 60-74 years old. The patients with CTIs were split into two groups based on their diagnosis and treatment. The study group consisted of 1669 patients (52.4%) who received optimized approaches considering the likelihood of developing LO. The control group included 1517 patients (47.6%) diagnosed and treated using traditional methods. LO were noted in 514 (16.1%) cases. To determine the risk factors (RFs) associated with LO, we analyzed the distribution of frequency variables between lethal and non-lethal outcomes. Results: The probability of developing LO in CTI was analyzed for statistical significance based on several RFs such as the patient's age, the presence of concomitant sub- and decompensated comorbid diseases, type and location of injury, severity of injuries, patient's state, and clinical forms of fat embolism syndrome (FES). Considering the identified RFs, a highly effective risk assessment scoring model for predicting the likelihood of developing LO in acute CTIs has been developed. Implementing optimized approaches and predicting the probability of developing LO significantly reduced fatality rates compared to traditional methods of diagnosis and treatment (13.5% and 18.5%, respectively, p<0.05). Conclusion: Based on the testing results of the proposed scale with the significant decrease in LO observed in the study group, we highly recommend implementing these approaches in clinical practice.","PeriodicalId":91037,"journal":{"name":"Paemi Sino","volume":"283 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"RISK FACTORS ASSOCIATED WITH IN-HOSPITAL MORTALITY AND PREDICTING OUTCOMES IN SEVERE ACUTE COMPOSITE TISSUE INJURIES\",\"authors\":\"A.M. NAIMOV, A.A. RAZZOKOV, F.M. PARPIEV\",\"doi\":\"10.25005/2074-0581-2023-25-3-334-345\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objective: To develop a reliable risk score prediction model to accurately predict the likelihood of lethal outcomes (LO) in severe acute composite tissue injuries (CTI) cases. Methods: We conducted an analysis of data from 3,186 patients with CTIs who were aged between 18 and 74. Of these patients, 2,432 were men (76.3%), and 754 were women (23.7%). The age distribution of patients was as follows: 2290 (71.9%) were between 18-44 years old, 638 (20.0%) were between 45-59 years old, and 258 (8.1%) were between 60-74 years old. The patients with CTIs were split into two groups based on their diagnosis and treatment. The study group consisted of 1669 patients (52.4%) who received optimized approaches considering the likelihood of developing LO. The control group included 1517 patients (47.6%) diagnosed and treated using traditional methods. LO were noted in 514 (16.1%) cases. To determine the risk factors (RFs) associated with LO, we analyzed the distribution of frequency variables between lethal and non-lethal outcomes. Results: The probability of developing LO in CTI was analyzed for statistical significance based on several RFs such as the patient's age, the presence of concomitant sub- and decompensated comorbid diseases, type and location of injury, severity of injuries, patient's state, and clinical forms of fat embolism syndrome (FES). Considering the identified RFs, a highly effective risk assessment scoring model for predicting the likelihood of developing LO in acute CTIs has been developed. Implementing optimized approaches and predicting the probability of developing LO significantly reduced fatality rates compared to traditional methods of diagnosis and treatment (13.5% and 18.5%, respectively, p<0.05). Conclusion: Based on the testing results of the proposed scale with the significant decrease in LO observed in the study group, we highly recommend implementing these approaches in clinical practice.\",\"PeriodicalId\":91037,\"journal\":{\"name\":\"Paemi Sino\",\"volume\":\"283 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Paemi Sino\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25005/2074-0581-2023-25-3-334-345\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Paemi Sino","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25005/2074-0581-2023-25-3-334-345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
RISK FACTORS ASSOCIATED WITH IN-HOSPITAL MORTALITY AND PREDICTING OUTCOMES IN SEVERE ACUTE COMPOSITE TISSUE INJURIES
Objective: To develop a reliable risk score prediction model to accurately predict the likelihood of lethal outcomes (LO) in severe acute composite tissue injuries (CTI) cases. Methods: We conducted an analysis of data from 3,186 patients with CTIs who were aged between 18 and 74. Of these patients, 2,432 were men (76.3%), and 754 were women (23.7%). The age distribution of patients was as follows: 2290 (71.9%) were between 18-44 years old, 638 (20.0%) were between 45-59 years old, and 258 (8.1%) were between 60-74 years old. The patients with CTIs were split into two groups based on their diagnosis and treatment. The study group consisted of 1669 patients (52.4%) who received optimized approaches considering the likelihood of developing LO. The control group included 1517 patients (47.6%) diagnosed and treated using traditional methods. LO were noted in 514 (16.1%) cases. To determine the risk factors (RFs) associated with LO, we analyzed the distribution of frequency variables between lethal and non-lethal outcomes. Results: The probability of developing LO in CTI was analyzed for statistical significance based on several RFs such as the patient's age, the presence of concomitant sub- and decompensated comorbid diseases, type and location of injury, severity of injuries, patient's state, and clinical forms of fat embolism syndrome (FES). Considering the identified RFs, a highly effective risk assessment scoring model for predicting the likelihood of developing LO in acute CTIs has been developed. Implementing optimized approaches and predicting the probability of developing LO significantly reduced fatality rates compared to traditional methods of diagnosis and treatment (13.5% and 18.5%, respectively, p<0.05). Conclusion: Based on the testing results of the proposed scale with the significant decrease in LO observed in the study group, we highly recommend implementing these approaches in clinical practice.