Methods of predicting influenza A(H1N1) pneumonia at early clinical stage
返回论文页
|更新时间:2023-12-18
|
Methods of predicting influenza A(H1N1) pneumonia at early clinical stage
Journal of Chongqing Medical UniversityVol. 36, Issue 9, Pages: 1044-1047(2013)
作者机构:
1. 承德医学院附属医院呼吸科,承德,067000
2. 天津泰达医院ICU,天津,300457
3. 北京大学人民医院呼吸科,北京,100044
作者简介:
基金信息:
DOI:
CLC:
Published:2013,
扫 描 看 全 文
ZHAO Zhiwei, ZHANG Qing, XING Zhili, et al. Methods of predicting influenza A(H1N1) pneumonia at early clinical stage. [J]. Journal of Chongqing Medical University 36(9):1044-1047(2013)
DOI:
ZHAO Zhiwei, ZHANG Qing, XING Zhili, et al. Methods of predicting influenza A(H1N1) pneumonia at early clinical stage. [J]. Journal of Chongqing Medical University 36(9):1044-1047(2013)DOI:
Methods of predicting influenza A(H1N1) pneumonia at early clinical stage
Objective:To investigate the methods of predicting susceptibility of influenza A(H1N1) pneumonia at early clinical stage in outpatient department. Methods:Totally 206 patients diagnosed as novel influenza A(H1N1) in Chengde area between September and December of 2009 were concentrated in Chengde Hospital for Infectious Diseases for free treatment. The diagnosis was consistent with the Protocol for Diagnosis and Treatment of Influenza A(H1N1)(2009 3rd ed) issued by the General Office of Ministry of Health. A retrospective study on the 206 cases was conducted. Based on the final imaging findings,these patients were divided into pneumonia group(n=51) and non-pneumonia group(n=155). Clinical characteristics and auxiliary examination were compared between the two groups;univariate analysis and multivariate logistic regression analysis were used to identify independent predictors of pneumonia;goodness of fit test was performed on an established clinical predicting scoring system. Results:Multivariate logistic regression analysis of the statistically significant factors demonstrated that:expectoration as initial symptom(OR=3.537,95%CI=1.016 to 12.311),onset-to-treatment interval > 48 h(OR=19.525,95%CI=4.576 to 83.309),lactic dehydrogenase > 250 U/L(OR=16.717,95%CI=5.484 to 34.417),potassium ion<3.5 mmol/L(OR=7.332,95%CI=1.763 to 49.709),aspartate aminotransferase > 40 U/L(OR=3.809,95%CI=1.008 to 12.460) and presence of underlying diseases(OR=61.003,95%CI=5.484 to 34.417) were the independent risk factors of influenza A(H1N1) pneumonia(all P<0.05). Area under receiver operating characteristic curve was 0.965(95%CI=5.484 to 34.417,P<0.001). Prediction scoring system of pneumonia was established according to levels of six high risk factors:low risk(score 0-2),intermediate risk(score 3-4),high risk(score 5-6) and very high risk(score 7) and were categorized for predicting the occurrence of pneumonia illness. Goodness of fit test showed good results(R2=0.916,P=0.043). Conclusions:In the future,clinical physicians can predict the susceptibility of pneumonia in patients with influenza A(H1N1) by comprehensive scoring concerning initial symptom,onset-to-treat-ment interval time,level of serum potassium ion and aspartate aminotransferase and presence of underlying diseases.
关键词
甲型H1N1流感肺炎危险因素预测评分
Keywords
influenza A(H1N1)pneumoniarisk factorpre-dicting and scoring
A clinical study of cardiac autonomic neuropathy with retinopathy and nephropathy in patients with type 2 diabetes mellitus
Risk factors for cognitive dysfunction in patients with brain infarction and type 2 diabetes
An analysis of risk factors for preoperative hypofunction of the HPA and HPT axes in patients with pituitary adenoma and their postoperative outcomes
Risk factors for the recurrence of craniopharyngioma
Analysis of pathogenic bacteria distribution,risk factors and countermeasures of nosocomial infection in elderly patients in gastroenterology department
Related Author
Tian Lina
Niu Ben
Zhu Enxian
Xie Yajuan
Ma Fanyuan
Chen Chuixiong
Wu Liping
Zhang Hua
Related Institution
Department of Endocrinology,The First People’s Hospital of Yunnan Province/Affiliated Hospital of Kunming University of Science and Technology
The First College of Clinical Medicine,Yunnan University of Chinese Medicine
Teaching Office of Health Statistics, Department of Military Preventive Medicine,Air Force Medical University
Department of Geriatrics,Xijing Hospital,Air Force Medical University
Department of Geriatrics, Tangdu Hospital,Air Force Medical University