Weiqiang Wang, Jincheng Cheng, Kai Wang, Jun Zhang
{"title":"Predictive Value of Major Inflammatory Markers in Complete Blood Count for Short-Term Prognosis in Patients with Acute Carbon-monoxide Poisoning","authors":"Weiqiang Wang, Jincheng Cheng, Kai Wang, Jun Zhang","doi":"10.21767/2172-0479.100154","DOIUrl":null,"url":null,"abstract":"Background: Acute carbon monoxide poisoning (ACOP) has high morbidity and mortality. The best inflammatory markers or indices can be identified by retrospective analysis the associations of inflammatory indices in completed blood count and short-term prognosis in ACOP patients and the indices can be used to guide in clinical diagnosis and treatment. Method: There were 256 ACOP patients who admitted into No. 123 Hospital from Jan 2008 to Dec 2017 were enrolled into this study. According to the health condition of ACOP patients after 2 months, the patients were divided into poor (n=21) and good (n=235) prognosis groups. The inflammatory indices, age, Glasgow coma scale (GCS) and other parameters were compared between the groups. Receiver operating characteristic (ROC) curves were used to evaluate the predictive values of various indicators towards prognosis of patients with ACOP. Results: The count of white blood cells, neutrophil, red blood cell distribution width, age and hypertension morbidity rate were significantly higher in poor prognosis group than that of the good prognosis group while the GCS was significant lower in the poor prognosis group compared to the good prognosis group. Multifactor analysis showed that neutrophil, age and GCS were risk factors for poor prognosis in patients with ACOP. Thus the results of combination of neutrophil count with age and GSC can be best in predicting the prognosis of ACOP. Conclusion: Neutrophil count is the indicator in predicting the short-term prognosis of ACOP and its predictive value can be increased by combining the parameters like age and GCS.","PeriodicalId":89642,"journal":{"name":"Translational biomedicine","volume":"09 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational biomedicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21767/2172-0479.100154","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Acute carbon monoxide poisoning (ACOP) has high morbidity and mortality. The best inflammatory markers or indices can be identified by retrospective analysis the associations of inflammatory indices in completed blood count and short-term prognosis in ACOP patients and the indices can be used to guide in clinical diagnosis and treatment. Method: There were 256 ACOP patients who admitted into No. 123 Hospital from Jan 2008 to Dec 2017 were enrolled into this study. According to the health condition of ACOP patients after 2 months, the patients were divided into poor (n=21) and good (n=235) prognosis groups. The inflammatory indices, age, Glasgow coma scale (GCS) and other parameters were compared between the groups. Receiver operating characteristic (ROC) curves were used to evaluate the predictive values of various indicators towards prognosis of patients with ACOP. Results: The count of white blood cells, neutrophil, red blood cell distribution width, age and hypertension morbidity rate were significantly higher in poor prognosis group than that of the good prognosis group while the GCS was significant lower in the poor prognosis group compared to the good prognosis group. Multifactor analysis showed that neutrophil, age and GCS were risk factors for poor prognosis in patients with ACOP. Thus the results of combination of neutrophil count with age and GSC can be best in predicting the prognosis of ACOP. Conclusion: Neutrophil count is the indicator in predicting the short-term prognosis of ACOP and its predictive value can be increased by combining the parameters like age and GCS.