洪涝灾害对灾民腹泻影响因素的Logistic回归分析

１９９６年８月３日至４日，河北省８个市９１个县１５１７万人口遭受洪涝灾害，对其中２０个县４０个乡８０个自然村２０８０户，７９０８名灾民进行腹泻调查，发现腹泻９３９例，人群罹患率为１１．８７％。对全部调查对象进行腹泻影响因素调查，并对共用Ｌｏｇｉｓｔｉｃ回归分析，结果发现灾区为平原、村进水或被水围、水源不以自来水为主、洪水时未组织有效地井水消毒和户内饮水消毒以及消毒不及时，当时降雨量、家庭有腹泻病人     

急性白血病早期死亡高危因素的Logistic回归分析

为了解急性白血病（ＡＬ）早期死亡的高危因素，对近１０ａ上海地区２７家医院共３４７例ＡＬ住院患者早期死亡的高危因素进行了Ｌｏｇｉｓｔｉｃ回归分析。结果表明：出血、感染和多脏器衰竭是ＡＬ死亡的主要原因。全反式维甲酸的应用降低了急性早幼粒细胞白血病早期病死率，早期死亡的高危因素为：年龄≥６０岁或≤１岁，发病时伴有出血，弥散性毛细血管内凝血，肝脏明显肿大，ＦＡＢ分类属于急性骨髓细胞白血病，外周血细胞＞１００×１０９／Ｌ，ＢＰＣ＜５０×１０９／Ｌ，伴发病发热和感染。提示：为了降低ＡＬ的早期病死率，必须针对上述高危因素采取相应防治措施     

Evaluation of three risk scores to predict postoperative nausea and vomiting

BACKGROUND: So far there are three different scores to predict postoperative vomiting (PV: Apfel et al., 1998) or postoperative nausea and vomiting (PONV: Koivuranta et al., 1997; Palazzo and Evans, 1993). All three scores used logistic regression analysis to identify and create weights for the risk factors for PV or PONV. In short, these were sex, age, history of previous PONV, motion sickness, duration of anaesthesia, and use of postoperative opioids. However, an external evaluation and a comparison of these scores has not been performed so far. METHODS: Patients undergoing a variety of surgical procedures under general anaesthesia were studied prospectively. Preoperatively, they completed a questionnaire concerning potential risk factors for the occurrence of PV or PONV implemented in the three risk scores. Balanced anaesthesia (induction agent, nondepolarising neuromuscular blocker, opioid, and inhalation agent in nitrous oxide/oxygen) was performed. No intravenous anaesthesia or any antiemetic prophylaxis was applied. Postoperatively, the patients were observed in the recovery room for the occurrence of PV and PONV and were visited twice on the ward within the 24-h observation period. Both the patients and the nursing staff were asked whether PV or PONV was present. The severity of PONV was categorised using a standardised scoring algorithm. A total of 1,444 patients was finally included into the analysis. Using information of the predicted risk for the individual patients and the actual occurrence of PV or PONV, Receiver Operator Characteristics (ROC-curves) were drawn. The area under each ROC-curve was calculated as a means of the predictive properties of each score and was compared for statistical differences. RESULTS: For prediction of PONV (any severity) the AUC-values (AUC=area under the curve) and the corresponding 95%-confidence intervals were: Apfel: 0.70 (0.67-0.72); Koivuranta: 0.71 (0.69-0.73); Palazzo: 0.68 (0.65-0.70). For prediction of PV: Apfel: 0.73 (0.71-0.75); Koivuranta: 0.73 (0.70-0.75); Palazzo: 0.68 (0.65-0.70). Thus, all three scores appeared to have a moderate accuracy as measured by the AUC. The score of Koivuranta predicts PONV (P=0.007) and also PV (P=0.002) significantly better than Palazzo's score. Furthermore, for predicting of PV the score of Apfel was also superior to Palazzo's score (P=0.005). All three scores predict PV with the same accuracy as PONV. CONCLUSION: The occurrence of PV and PONV in patients undergoing surgery under balanced anaesthesia can be predicted with moderate but acceptable accuracy using one of the available risk scores, regardless of local surgical or anaesthesiological circumstances. For clinical practice, we recommend the score published by Koivuranta, since its calculation is very simple.     

Age and Outcome After Severe Head Injury

The authors analyzed the relationship between patient age and the final outcome in a series of 810 patients aged 14 years or older who were consecutively admitted between 1987 and 1996 after suffering a severe closed head injury. The most relevant clinico-radiological variables were prospectively collected in a Data Bank. Stratified and logistic regression analyses were performed in order to assess the influence of age on adverse outcome and the interaction between patient age and other prognostic indicators. Our results reaffirm that the adverse outcome rate increases steadily with age in severe head injured patients and that age effect on outcome is independent of other prognostic variables. The odds of having an adverse outcome increases significantly over 35 years of age being 10 times higher in patients older than 65 years as compared to those aged 15-25 years (reference age group). The adverse influence of an advanced age on the final outcome has not yet been satisfactorily explained but an older brain may have an impaired ability to recover after a pathological insult as compared to a younger one.     

原发性中枢神经系统淋巴瘤患者预后因素的 Weibull回归模型分析

目的:研究原发性中枢神经系统淋巴瘤患者术后的生存期,寻找影响患者生存期的主要因素.方法:通过回顾性调查收集我院1995～2002年期间接受手术治疗的22例中枢神经系统淋巴瘤患者的病例资料,用Kaplan-Meier方法估计患者的生存率曲线和平均生存期,采用Weibull回归对患者生存的影响因素进行模型拟合.结果:原发性中枢神经系统淋巴瘤患者的中位生存时间为18个月(95%CI:14～22月).Weibull回归模型分析显示:患者的年龄、肿瘤发生的部位、病程、手术后治疗方法是影响患者生存期的主要因素;患者的性别以及肿瘤的病理特点与患者的生存期没有关系.结论:Weibull回归模型对患者的生存期及其影响因素具有较好的拟合优度.     

宁波市鄞县农村2型糖尿病危险因素病例对照研究

目的探索农村2型糖尿病的危险因素,为预防控制提供依据.方法采用成组病例对照研究方法,选择2型糖尿病病例238例,对照3866例,运用多因素Logistic回归分析.结果年龄、性别、超重(肥胖)、既往高血压病史、直系亲属糖尿病史、水果摄入多等进入主效应模型,OR值分别为1.22、1.36、2.18、1.56、2.51和0.64.结论超重(肥胖)、既往高血压史、直系亲属糖尿病史是主要的危险因素,水果摄入多是保护因素.     

学生心理障碍影响因素Logistic回归分析

目的:探讨学生心理障碍的影响因素,为今后的干预提供科学依据。方法:应用SCL-90自评量表测评分析,采用1:2配比病例对照研究,对学生进行心理调查及艾森克人格(EPQ)问卷。结果:心理障碍组学生SCL-90各因子均分离于正常组,经Logistic回归分析,单因素分析选出9项因子(P<0.05),多因素分析有4项因素进入回归模型。结论:学生心理障碍与学生同家庭成员关系,父亲理解的程度,对学习的要求程度以及人格特征和个性特质有关。     

Is normal β-hCG regression curve helpful in the diagnosis of persistent trophoblastic disease?

OBJECTIVE: The aim of this study was to evaluate the probable usefulness of normal beta-human chorionic gonadotropin (beta-hCG) regression curve in the diagnosis of persistent trophoblastic disease (PTD). METHODS: A log-value regression curve was developed from the means and 95% confidence limits of serial weekly serum beta-hCG titers of 43 patients with uneventful complete hydatidiform moles and 14 patients, who were previously confirmed as PTD. RESULTS: All 14 PTD patients (100%) had abnormal values, beyond normal range, within 4 weeks. beta-hCG was in its upper values, compared to normal regression curve at 2.29 +/- 0.19 weeks. This was earlier than plateau or rise detection at 4.21 +/- 0.33 weeks (P < 0.001). Within 3 weeks of evacuation, 13 of 14 (92.86%) PTD patients' beta-hCG values exceeded the normal range, whereas only six of 14 (42%) showed a rise or plateau. CONCLUSION: Our finding indicates that the normal beta-hCG regression curve may be useful for quicker detection of PTD than the plateau or rise of level.     

肝癌发病时期趋势和年龄效应分析

目的 反映启东地区肝癌发病的时期变化趋势和年龄作用方式。方法 应用年龄-时期-队列模型对启东地区25年肝癌发病监测资料分区进行模型拟合和效应分析。结果 海东区和吕四区在局部时间上有所上升；汇龙区、江海区、王鲍区、启西区20世纪50年代以后出生的人群发病危险性有显著减缓或下降的趋势。结论 肝癌发病危险性在时期趋势上没有整体下降，20世纪50年代以后出生的人群发病危险性有下降趋势。     

威布尔回归分析在哮喘患者中的应用

目的 分析哮喘患者季节史、发作频度和发作严重度、控制治疗情况等因素与病程长短的关系,以发现其密切相关的影响因素.方法 利用SAS6.12软件对87例哮喘患者基本资料进行威布尔回归模型拟合并作假设检验.结果 通过参数估计,得出x5哮喘患者发作频度,x6哮喘患者急性发作严重度,x7哮喘患者控制治疗情况与哮喘患者病程长短有关系,且其回归系数B5,B6,B7的估计值有统计学意义(P＜0.05),形态参数γ=0.3391,其标准误为0.0364.据此可得出Weibull回归下哮喘病人的死亡风险函数,生存函数及概率密度函数为:h(y)=0.3391y-0.6609exp(1.9559-0.2501x5-0.4899x6 0.4618x7),s(Y)=exp(-Y0.3391exp(1.9559-0.2501x5-0.4899x6 0.4618x7)),f(Y)=h(Y)s(Y).结论 Weibull回归模型不仅可用于定量评价病人生存情况及其因素间的关系,而且还可用于预测预报病人的预后情况.