新生儿重症监护病房中重症肺炎多种菌感染相关因素分析

目的分析新生儿重症监护病房(NICU)中重症肺炎新生儿多种菌感染危险因素。方法回顾分析2014年1月至2019年5月收入NICU的1 057例重症细菌肺炎新生儿的临床资料,分析其多种菌感染的危险因素。结果单因素分析显示,胎龄(37周)、出生体质量(2 500 g)、发病日龄(7 d)、羊水污染(Ⅱ、Ⅲ度)、感染类型(医院感染)、住院时间(≥14天)、机械通气、Apagar评分(7分)、胎膜早破、抗菌药物使用天数(≥10天)、更换抗菌药物(≥3种)、联合使用抗菌药物(≥3种)12个因素是NICU中重症肺炎新生儿多种菌感染的危险因素,差异有统计学意义(P均0.05)。多因素分析显示,更换抗菌药物(≥3种)、Apagar评分(7分)、感染类型(医院感染)、机械通气、羊水污染(Ⅱ、Ⅲ度)是NICU中重症肺炎新生儿多种菌感染的独立危险因素(P0.05)。结论临床应针对主要危险因素采取综合防控措施,减少NICU新生儿重症肺炎多种菌感染。     

Comparison of diagnostic usefulness of predictive models in preliminary differentiation of adnexal masses

The purpose of this study was to compare prognostic models evaluating the probability of an ovarian cancer occurrence based on a number of clinical and ultrasonographic data in women with adnexal masses. A total of 686 women with adnexal masses underwent the examinations between 1994 and 2002. The recorded parameters included: age, menopausal status, body mass index, the grayscale and Doppler ultrasonographic examination, and selected markers concentration levels. In order to find the best combination of features, which significantly influences the probability of malignancy, stepwise logistic regression analysis, as well as artificial neural network, was used. The diagnostic efficiency of received models was estimated and compared using receiver-operating characteristics (ROC) curve. The results indicate that 431 and 255 patients had a benign and malignant ovarian tumor, respectively. Application of stepwise logistic regression analysis revealed statistically significant importance of eight features. The sensitivity and specificity for the received model were 65.71% and 77.59%, respectively. Three-layer perceptron network shows 13 features as significant predictors of malignancy. The network gave a sensitivity of 85.7% and specificity of 93.1%. Comparison of area under ROC curve for received models was 0.9679 vs 0.9716. Prognostic values of the analyzed neural model are not optimal but seem to surpass logistic regression model in terms of the predictive possibilities.     

Preventing heart disease: is treating the high risk sufficient?

Monte Carlo simulation was used to assess the effects of several intervention strategies on coronary heart disease mortality rates in a Finnish and a North American cohort. Lowering total serum cholesterol by 4%, smoking by 15%, and diastolic blood pressure by 3% for the whole cohort would be expected to reduce the incidence of non-fatal myocardial infarction by at least 13% and coronary heart disease deaths by at least 18%. Lowering serum cholesterol by 34%, diastolic blood pressure to 90 mmHg, and reducing smoking by 20% in the subset of the population with all three risk factors in the highest quartile would result in a 6-8% reduction in non-fatal myocardial infarction and a 2-9% reduction in deaths from coronary heart disease in these cohorts. These data demonstrate that in populations with a relatively high incidence of heart disease, treating the entire population will produce larger effects than focusing only on high-risk populations.     

慢性乙型肝炎肝郁脾虚证的logistic回归及判别分析

目的归纳慢性乙型肝炎肝郁脾虚证的辨证要点。方法对慢性乙型肝炎肝郁脾虚证、肝郁证、脾虚证的症状及舌、脉进行logistic回归及判别分析。结果肝郁脾虚证logistic回归提取的症状为腹胀、倦怠乏力、腹痛、食欲不振、紧脉、便溏、胁肋疼痛、胁肋不适；判别方程包含的症状则为腹痛、腹胀、倦怠乏力、便溏、黄苔。结论肝郁脾虚证的辨证要点包括胁肋疼痛或不适、腹胀、腹痛、乏力、食欲不振、便溏。利用logistic回归和判别分析归纳本证诊断要点是可行的。     

肥胖与胆石病的多因素条件Logistic回归分析

目的探讨肥胖与结石病发病的关系。方法采用调查表的方式对1997年住院手术确诊为结石病的病人进行回顾性调查，内容包括：年龄、性别、体重、身高、是否吃早餐。对调查表进行多因素logstic统计分析。结果分析结果表明我们调查了我院102例结石病患者和101名正常人发现肥胖、女性、不经常吃早餐、饮用高硬度的水均是结石病的危险因紊，对那些长时间不吃早餐的人更容易患结石病，（相对危险度OR〉40．139）。结论我们建议今后应注意膳食营养的均衡，保持标准体重，饮用卫生水。     

安氏Ⅲ类错畸形病因的logistic分析

目的研究引起安氏Ⅲ类错牙合畸形的病因。方法对50例安氏Ⅲ类错牙合患者和50例正常牙合人作病因问卷调查,将结果用logistic法分析,提取有效病因。结果共有慢性扁桃体炎、遗传因素、咬上唇3项病因进入方程。结论按贡献大小,长期慢性扁桃体炎、经常咬上唇和遗传因素是导致安氏Ⅲ类错牙合畸形的危险因素。     

高血压病危险因素研究

本文对高血压病病人及对照的生活习惯、个人嗜好、精神因素等15个因素进行了1:1配比病例对照研究及 Logistic 回归分析,同时调查厂遗传因素和高血压病的关系。结果表明:超体重、发病前二年受应激事件刺激、母亲高血压史为高血压病的危险因素。高血压病遗传度35.58%,提示遗传因素在该病的发生过程中不起主要作用。     

A preliminary statistical model for identifying repeaters of parasuicide

This paper presents a statistical model constructed using logisticregression to identify those at high-risk of repeating parasuicide. Thesubjects in the study are Cork city residents who exhibited parasuicidalbehaviour between 1 January and 30 June 1995. Repetition of the behaviourwithin six months of the index episode distinguishes repeaters fromnon-repeaters. The model was designed so that it could be used bynon-clinicians and hence does not require information relating topsychiatric diagnosis or use of psychiatric services. The proportion ofsubjects correctly classified remained stable across a range of cut-pointprobabilities (mean = 86%, range: 83.9–87.5%). Using acut-point of 0.2, 96% of repeaters and 81% of non-repeaters were correctly classified. Using 0.45 led to the correct identification of81% of repeaters and 90% of non-repeaters. If these highlevels of sensitivity and specificity are maintained in validation tests onfuture cohorts in Cork city then the model could form the basis of anintervention programme designed to prevent the repetition of parasuicide.     

用Logistic曲线求月经初潮均龄

介绍用Logistic 曲线来计算初潮均龄及95%可信区间,该方法只需原始数据即可进行计算,不必将来潮率以概率单位置换,从而避免了年龄与发生率的S 形曲线与正态分布函数相符这一要求。经验证和比较,认为本方法计算简便,误差小,是一种值得采用的方法。