重症新型冠状病毒肺炎患者死亡风险因素研究

目的 分析重症新冠病毒肺炎住院期间死亡患者临床及实验室特点,研究死亡相关危险因素,为进一步制定新冠病毒肺炎防治策略及优化医疗资源配置提供理论依据。 方法 回顾性收集武汉市两家三甲医院重症新冠病毒肺炎患者一般临床资料、实验室检查指标,通过多因素logistic回归分析死亡相关危险因素。 结果 1002例重症新冠病毒肺炎患者中,死亡142例,健康出院860例,高血压（36.7%）及糖尿病（15.3%）是最常合并的基础疾病。多因素logistic回归分析提示:高龄（OR=1.07,95%CI: 1.04～1.09）、 中性粒细胞/淋巴细胞比值（NLR）（OR=1.10,95%CI: 1.06～1.13）、降钙素原（PCT）大于0.5ng/ml（OR=2.17,95%CI: 1.09～4.31）、乳酸脱氢酶（LDH）大于300U/L（OR=2.20,95%CI: 1.23～3.91）、高敏肌钙蛋白I大于0.1ng/ml（OR=2.30,95%CI: 1.12～5.11）及C-反应蛋白（CRP）大于30mg/L（OR=3.33,95%CI: 1.95～5.71）均是重症新冠病毒肺炎死亡的独立危险因素。结论 高龄、NLR、PCT大于0.5ng/ml、LDH大于300U/L、高敏肌钙蛋白I大于0.1ng/ml及CRP大于30mg/L等入院指标为重症患者早期死亡危险因素,密切关注这些危险因素可帮助临床医务人员进行疾病死亡风险评估及判断预后。     

成都市新型冠状病毒肺炎患者的临床特征分析

目的 总结新型冠状病毒肺炎（COVID - 19）患者的临床特征。方法 回顾分析成都市公共卫生临床医疗中心收治的101例COVID - 19确诊病例的流行特点、临床特征、治疗及预后。采用Excel录入数据,SPSS 22.0对资料进行统计分析。结果 86.1%患者有明确流行病学接触史。主要临床症状表现为发热（75.2%）,咳嗽（70.3%）,咳痰（42.6%）,乏力/肌肉酸痛（24%）。89.1%患者白细胞计数正常或降低,65.3%患者C反应蛋白升高,68.3%患者血清淀粉样蛋白升高,51.5%患者空腹静脉血糖升高,54.5%患者CD4+T淋巴细胞计数下降。胸部CT典型表现为磨玻璃样病灶,77.2%患者为双侧肺部均受累。101例患者中,轻型及普通型66例,重型及危重型35例。97.0%患者需要不同支持力度的氧疗,96.0%患者接受了抗病毒治疗、16.8%患者接受了抗细菌治疗,5.9%患者激素治疗。5.9%发生不同程度的急性呼吸窘迫综合征,16.8%发生继发感染,5.0%发生休克,2.0%发生急性肾损伤。截至2020年3月24日0:00治愈出院98例,死亡3例。结论 COVID - 19患者多数症状轻微,预后好;重型及危重型主要发生在高龄、合并高血压、糖尿病、慢性肾功能衰竭等基础疾病的患者,危重型患者可并发急性呼吸窘迫综合征,甚至多器官功能障碍危及生命,应早期识别及时治疗。     

慢性心力衰竭患者营养不良风险列线图预测模型的构建与验证

目的 分析慢性心力衰竭患者营养不良的危险因素,构建营养不良风险列线图预测模型。方法 选取2020年9月至2021年10月于唐山市某三甲医院心内科住院治疗的320例慢性心力衰竭患者为研究对象,采集患者一般资料、疾病相关资料,采用单因素分析和多因素logistic回归分析慢性心力衰竭患者营养不良的危险因素,建立营养不良风险的列线图预测模型,采用受试者工作特征曲线和校准曲线评价列线图模型的诊断效能和校准度、临床决策曲线评估临床收益性。结果 多因素logistic回归分析显示,年龄≥65岁(OR=2.472,95%CI:1.189～5.139)、水肿(OR=2.228, 95%CI:1.190～4.171)、贫血(OR=3.266, 95%CI:1.566～6.810)、血清尿素氮≥8.85 mmol/L(OR=3.241,95%CI:1.639～6.411)、血清总蛋白<60g/L(OR=9.166,95%CI:4.083～20.576)是慢性心力衰竭患者营养不良的独立危险因素。列线图预测模型的受试者工作特征曲线下面积为0.833,灵敏度为74.04%,特异度为84.72%,H-L检验...     

构建个体化预测医务人员职业暴露风险的列线图模型

目的探究医护人员职业暴露的影响因素,构建个体化预测职业暴露风险的列线图模型。方法调查2016年7月—2017年7月医院医护人员职业暴露发生情况,使用二分类Logistic回归方法探索医务人员职业暴露风险的危险因素,应用R软件构建预测职业暴露风险的列线图模型。结果 962名医务人员中发生职业暴露有142例,职业暴露发生率为14. 76%; Logistic回归分析发现:夜班间隔时间、日均工作时间、防护用品满意度及职业防护培训是医护人员发生职业暴露的独立危险因素(P <0. 05),根据多因素分析结果绘制出职业暴露风险列线图。结论不参加单位职业防护培训、夜班间隔时间≤5 d是医护人员发生职业暴露的高危因素;基于以上危险因素建立个体化预测医务人员职业暴露风险的列线图模型,对医疗机构制定有针对性的职业暴露防控方案具有指导意义。     

28例新型冠状病毒肺炎死亡病例分析

 目的 探讨新型冠状病毒肺炎（COVID-19）死亡病例的临床特征与死因,提高对COVID-19的认知。方法 收集和分析2020年2月1日—3月21日武汉大学人民医院东院区重症监护病房（ICU）内确诊COVID-19死亡病例的临床资料。结果 共纳入COVID-19死亡病例28例,平均年龄（69.14±14.70）岁,男女比例2.5：1;19例（67.86%）伴基础疾病,以高血压、糖尿病居多,入院当日序贯器官衰竭估计评分（SOFA）平均分为6.00（4.00~9.00）,与同期存活病例比较差异有统计学意义（Z=-3.86,P<0.05）。经受试者工作特征曲线分析,其曲线下面积为0.90（0.79~1.00）。发病至确诊平均时间为6.50（3.00~12.00）d,发病主要累及呼吸与循环系统,均有呼吸困难。发病至死亡平均时间为21.50（15.25~29.00）d,均有重度急性呼吸窘迫综合征（ARDS）,19例（67.86%）发生多脏器功能障碍综合征（MODS）。6例（21.43%）合并其他感染,主要为革兰阴性杆菌。结论 ARDS及MODS为COVID-19重要死因,合并细菌感染也是死亡促进因素,应通过临床表现、SOFA评分等及时筛查危重型病例并及时优化治疗。     

妊娠期糖尿病并发子痫前期的风险预测列线图模型建立和验证

目的 建立妊娠期糖尿病(GDM)患者并发子痫前期的风险预测列线图模型，验证其预测效果。方法 选取2021年1—7月在温州市人民医院产检并分娩的352例GDM患者作为研究对象，按照是否发生子痫前期分为子痫前期组(42例)和无子痫前期组(310例)。收集患者相关临床资料，分析GDM患者发生子痫前期的影响因素，将确定的危险因素纳入R3.5.3软件，绘制预测GDM患者发生子痫前期的列线图预测模型。然后利用受试者工作特征(ROC)曲线检验列线图模型的预测效能，并检验模型的拟合优度。另再纳入2021年8—12月在温州市人民医院产检并分娩的129例GDM患者验证模型的预测效能。结果 352例GDM患者中，发生子痫前期42例，未发生子痫前期310例。单因素分析结果显示：子痫前期组患者孕前体质量指数(BMI)、空腹血糖(FPG)、糖化血红蛋白(HbA1c)、三酰甘油(TG)、总胆固醇(TC)、尿酸(UA)、同型半胱氨酸(Hcy)及双胎妊娠比例分别为(24.56±3.82)kg/m²、(5.19±0.65)mmol/L、(5.65±0.49)%、(3.82±2.01)mmol/L、(...     

脑卒中手术患者医院感染风险预测列线图模型的构建

目的构建脑卒中手术患者医院感染风险预测列线图模型,为早期筛查医院感染高风险人群和制定预防策略提供一定的参考和依据。方法回顾性收集2016-2018年山东大学齐鲁医院脑卒中手术患者的临床相关资料,将患者按照7∶3的比例随机分为建模组(571例)和验证组(245例)。采用单因素和多因素Logistic回归探讨医院感染的独立危险因素,基于危险因素的回归系数构建脑卒中手术患者医院感染风险预测列线图模型。分别在建模组(内部验证)和验证组(外部验证)中采用受试者工作特征(ROC)曲线下面积(AUC)和校准曲线评估预测模型的区分度和校准度。结果共纳入816例脑卒中手术患者,医院感染213例,医院感染发生率为26.10%。Logistic回归分析显示,脑卒中类型、留置胃管、静脉血栓、手术风险分级(NNIS)、美国国立卫生研究院卒中量表(NIHSS)评分以及住院时间是脑卒中手术患者医院感染的独立危险因素(P<0.05)。依此构建的列线图模型在建模组和验证组中的ROC曲线下面积分别为0.849和0.858,具有良好的区分度;两组校准曲线显示列线图模型的预测值和实际观察值结果一致性良好(P=0.731、P=0.224)。结论本研究构建的个体化风险预测列线图模型有助于提高对脑卒中术后医院感染高危人群的筛查和早期诊断,尽早制定干预策略,以降低感染发生率。     

个性化预测新生儿坏死性小肠结肠炎发病风险的列线图模型构建

目的 探究个性化预测新生儿坏死性小肠结肠炎(NEC)发病风险的列线图模型构建,为新生儿NEC的防治提供科学依据.方法 回顾性分析2017年10月 2019年12月海南现代妇女儿童医院与外院联合收集的1173例新生儿临床资料,根据是否发生NEC分为NEC组(n=46)与非NEC组(n=1127),采用Logistic回归...     

新型冠状病毒肺炎死亡病例危险因素分析

目的 以荆州市数据为例,探讨新型冠状病毒肺炎(coronavirus disease 2019,COVID-19)死亡病例相关危险因素,为临床治疗及评估预后提供相关依据。 方法 回顾性分析荆州市1 580例COVID-19病例,根据患者结局分为存活组(1 528例)和死亡组(52例)。收集并比较两组的基本信息、临床资料、暴露史等相关数据。差异有统计学意义的指标进一步进行二元logistic回归分析。比较两组部分血常规指标,对差异有统计学意义指标通过受试者工作特征曲线分析其在评估患者预后中的临床价值。 结果 单因素分析结果显示,两组在年龄(χ²=78.603,P＜0.001)、临床严重程度(χ²=173.994,P＜0.001)、疾病史(χ²=29.644,P＜0.001)、高血压史(χ²=31.143,P＜0.001)、糖尿病史(χ²=6.218,P=0.013)、心脑血管疾病史(χ²=12.737,P＜0.001)、入院时是否有气促症状(χ²=5.889,P=0.015)上比较差异有统计学意义。logistic回归分析结果显示,≥60岁(OR=8.913,95%CI:4.481~17.730)、高血压史(OR=2.004,95%CI:1.084~3.708)及入院时有气促症状(OR=2.302,95%CI:1.016~5.216)对COVID-19患者死亡具有显著影响(P＜0.05)。死亡组相较于存活组,淋巴细胞数、淋巴细胞百分比更低,而中性粒细胞百分比更高(P＜0.05),ROC曲线结果显示,淋巴细胞数、淋巴细胞百分比和中性粒细胞百分比在评估COVID-19患者预后中的曲线下面积分别为0.752、0.745、0.760。 结论 ≥60岁、高血压史以及入院时具有气促症状是影响COVID-19患者死亡的危险因素。淋巴细胞数、淋巴细胞百分比和中性粒细胞百分比水平变化可辅助评估COVID-19患者的预后。     

8例新型冠状病毒肺炎死亡病例临床特征分析

目的 探讨8例新型冠状病毒肺炎(简称新冠肺炎)死亡病例的死亡原因及可能危险因素。 方法 回顾性分析自2020年1月23日—2月25日在武汉市第五医院住院期间死亡的8例新冠肺炎病例的临床特征。 结果 8例新冠肺炎病例的死亡年龄在65~75岁之间,平均年龄(70.63±3.99)岁,平均病程 (12±2.83)d;8例病例均有明确基础疾病,其中最常见为高血压,其次为脑梗死、糖尿病、冠心病、肺部基础疾病;除肺脏损害外,其他器官损害主要有心脏,其次为肾脏、肝脏,凝血系统功能紊乱,其中4例(4/8)病例D2聚体明显升高;白细胞计数升高6例(6/8)、中性粒细胞计数升高6例(6/8)、C反应蛋白(C-reactive protein, CRP)升高8例(8/8)、降钙素原(procalcitonin, PCT)升高8例(8/8)、淋巴细胞计数下降4例(4/8)、淋巴细胞百分比下降8例(8/8)。病例死亡前一次白细胞计数(8/8)、中性粒细胞计数(8/8)、CRP(8/8)、降钙素原(8/8)、D2聚体(8/8)水平较入院时升高,血氧分压(8/8)、淋巴细胞计数(7/8)、淋巴细胞比率(8/8)较入院时降低,差异有统计学意义(P<0.05)。胸部CT显示肺部影像学较入院时病灶增多、范围增大。 结论 高龄及合并有基础疾病是新冠肺炎抢救困难甚至死亡的重要危险因素,细菌感染可能对疾病进展起着重要促进作用,血氧分压、胸部CT、白细胞计数、中性粒细胞计数、淋巴细胞计数、淋巴细胞百分比、CRP、降钙素原、D2聚体可能是疾病进展、预后不良的重要参考指标。     

Epidemiological,imaging, laboratory,and clinical characteristics and factors related to mortality in patients with COVID-19: a single-center study

ObjectivesCoronavirus disease 2019 (COVID-19) is a novel pandemic. Considerable differences in disease severity and the mortality rate have been observed in different parts of the world. The present study investigated the characteristics and outcomes of patients hospitalized with COVID-19 in Iran.MethodsWe established a retrospective cohort to study hospitalized COVID-19 patients in Iran. Epidemiological, imaging, laboratory, and clinical characteristics and outcomes were recorded from medical documents. The chi-square test, t-test, and logistic regression models were used to analyze the data. A p<0.05 was considered to indicate statistical significance.ResultsIn total, 364 cases (207 males and 157 females) were analyzed. The most common symptoms were cough, fever, and dyspnea. Multifocal bilateral ground-glass opacities with peripheral distribution were the predominant imaging finding. The mean age of patients was 54.28±18.81 years. The mean age of patients who died was 71.50±14.60 years. The mortality rate was 17.6%. The total proportion of patients with a comorbidity was 47.5%, and 84.4% of patients who died had a comorbidity. Sex, history of diabetes mellitus, and dyslipidemia were not significantly associated with mortality (p>0.05). However, mortality showed significant relationships with body mass index; age; history of hypertension, chronic kidney disease (CKD), ischemic heart disease, cerebrovascular accident (CVA), pulmonary disease, and cancer; and abnormal high-resolution computed tomography (HRCT) findings (p<0.05 for all). Cancer had the highest odds ratio.ConclusionComorbidities (especially cancer, CKD, and CVA), severe obesity, old age, and abnormal HRCT findings affected the health outcomes of patients hospitalized with COVID-19.     

Development of a predictive prognostic rule for early assessment of COVID-19 patients in primary care settings

ObjectiveTo investigate possible early prognostic factors among middle-aged and older adult and explore prognostic rules stratifying risk of patients.DesignCommunity-based retrospective cohort.SettingPrimary Health Care Tarragona region.Participants282 community-dwelling symptomatic patients ≥50 years with laboratory-confirmed COVID-19 (hospitalised and/or outpatient) during March-June 2020 in Tarragona (Southern Catalonia, Spain).Main outcome measurementsRelationship between demographics, pre-existing comorbidities and early symptomatology (first 5-days) and risk of suffering critical outcome (ICU-admission/death) across clinical course was evaluated by logistic regression analyses, and simple predictive models were developed.ResultsOf the 282 cases (mean age: 65.9 years; 140 men), 154 (54.6%) were hospitalised (30 ICU-admitted) and 45 (16%) deceased. Median time follow-up in clinical course was 31 days (range: 30–150) for survivors and 14 days (range: 1–81) for deceased patients. In crude analyses, increasing age, male sex, some comorbidities (renal, respiratory or cardiac disease, diabetes and hypertension) and symptoms (confusion, dyspnoea) were associated with an increased risk to suffer critical outcome, whereas other symptoms (rinorrhea, myalgias, headache, anosmia/disgeusia) were related with reduced risk. After multivariable-adjustment only age/years (OR: 1.04; 95% CI: 1.01–1.07; p = 0.004), confusion (OR: 5.33; 95% CI: 1.54–18.48; p = 0.008), dyspnoea (OR: 5.41; 95% CI: 2.74–10.69; p < 0.001) and myalgias (OR: 0.30; 95% CI: 0.10–0.93; p = 0.038) remained significantly associated with increased or reduced risk. A proposed CD65-M prognostic rule (acronym of above mentioned 4 variables) showed a good correlation with the risk of suffering critical outcome (area under ROC curve: 0.828; 95% CI: 0.774–0.882).ConclusionClinical course of COVID-19 is early unpredictable, but simple clinical tools as the proposed CD65-M rule (pending external validation) may be helpful assessing these patients in primary care settings.     

新型冠状病毒肺炎患者重症转归风险预测

目的 建立新型冠状病毒肺炎（COVID-19）患者转归为重症的预测模型,为早期、动态地监测患者转归提供更加全面、准确、及时的指标。方法 基于患者的入院检测指标和轻、重症分型,以及检测指标的动态改变（即入院后两次检测指标测量值差）等输入变量,使用XGBoost方法建立预测模型,评估患者在入院之后转归为重症的风险。然后将入选的患者从入院随访至出院,观察其病情转归情况,对模型预测结果进行验证。结果 在100例COVID-19患者的训练集中,筛选出具有较高评分的预测变量并建立模型,计算出预测变量取值的高风险范围：血氧饱和度<94%、外周血白细胞计数>8.0×10⁹个、SBP变化<-2.5 mmHg（1 mmHg=0.133 kPa）、心率>90次/min、有多发小斑片影、年龄>30岁、心率变化<12.5次/min。训练集的模型预测结果的敏感率为61.7%,漏诊率为38.3%;使用模型对测试集进行预测的敏感性为75.0%,漏诊率为25.0%。结论 与传统的预测判断方法（即采用入院时第一次检测的指标和重症入选条件进行评估患者是否为轻、重症）相比,模型的预测考虑到了COVID-19患者的基线生理指标与病情变化指标,因此能够全面、准确地预测患者重症转归的风险,减少重症患者的漏诊率。     

Impact of obesity on hospitalizations and mortality,due to COVID-19: A systematic review

The aim of the current review was to assess whether there was an association between obesity and higher levels of hospitalization, poor outcomes and mortality due to the disease of novel coronavirus (COVID-19). Methodology: A systematic review of articles on the novel coronavirus, containing information on obesity and its association with COVID-19 morbidity and mortality. In the bibliographic research, four databases were used, with the terms ['COVID-19′] AND ['hospitalization'] AND ['obesity'] AND ['mortality']. Studies published from 12/01/2019 until 05/01/2020 were included. The research contains inclusive criteria targeting studies of humans adults infected by Sars-Cov-2, with or without comorbidities. This research was selected from publications in Spanish and English languages. Results: 96 articles were identified, 15 being presented in two databases. Twenty articles were included, with a population total estimated from 1 to 7671 patients, with a prevalence of obesity ranging from 13.3% to 68.6%. The association of obesity and mortality has been observed in at least 4 studies, that 85.3% of the population was hospitalized. Among 19 of the 20 studies, more severe forms of the disease were observed and in 14 of them, higher rates of complications among obese people infected with the new coronavirus. Limitation differences in the definition of obesity was observed among publications, of which obesity was considered from a body mass index >25 kg/m². Conclusions: In the current review, obesity and overweight were represented an unfavorable factor for infection of novel coronavirus, where the higher the BMI the worse the outcomes. This occurred by worsening the infection itself, as well as increasing the prevalence of hospitalizations, worst outcomes and greater lethality; especially when co-occurring with other chronic conditions and in the elderly as well. Given this evidence, greater attention is suggested to the obese and overweight population in the face of the current pandemic.     

Tocilizumab therapy reduced intensive care unit admissions and/or mortality in COVID-19 patients

IntroductionNo therapy has yet proven effective in COVID-19. Tocilizumab (TCZ) in patients with severe COVID-19 could be an effective treatment.MethodWe conducted a retrospective case-control study in the Nord Franche-Comté Hospital, France. We compared the outcome of patients treated with TCZ and patients without TCZ considering a combined primary endpoint: death and/or ICU admissions.ResultsPatients with TCZ (n = 20) had a higher Charlson comorbidity index (5.3 [±2.4] vs 3.4 [±2.6], P = 0.014), presented with more severe forms (higher level of oxygen therapy at 13 L/min vs 6 L/min, P < 0.001), and had poorer biological findings (severe lymphopenia: 676/mm³ vs 914/mm³, P = 0.037 and higher CRP level: 158 mg/L vs 105 mg/L, P = 0.017) than patients without TCZ (n = 25). However, death and/or ICU admissions were higher in patients without TCZ than in the TCZ group (72% vs 25%, P = 0.002).ConclusionDespite the small sample size and retrospective nature of the work, this result strongly suggests that TCZ may reduce the number of ICU admissions and/or mortality in patients with severe SARS-CoV-2 pneumonia.     

Association between metabolic syndrome and mortality in patients with COVID-19: A nationwide cohort study

ObjectivesWe investigated the association between metabolic syndrome (MetS) and mortality among coronavirus disease 2019 (COVID-19) patients in Korea.MethodsWe analyzed 3876 individuals aged ≥ 20 years who were confirmed with COVID-19 from January 1 to June 4, 2020 based on the Korea National Health Insurance Service (NHIS)-COVID-19 database and had undergone health examination by NHIS between 2015 and 2017. Multivariable Cox proportional hazard regression analyses were performed.ResultsOf total participants, the prevalence of MetS was 21.0% (n = 815). During 58.6 days of mean follow-up, 3.1 % (n = 120) of the participants died. Compared to individuals without MetS, COVID-19 patients with MetS had a significantly increased mortality risk after adjusting for confounders in total participants (hazard ratio [HR]: 1.68, 95 % confidence interval [CI]: 1.14–2.47) and women (HR: 2.41, 95 % CI: 1.17–4.96). A low high-density lipoprotein cholesterol level in total participants (HR: 1.63, 95 % CI: 1.12–2.37) and hyperglycemia in women (HR: 1.97, 95 % CI: 1.01–3.84) was associated with higher mortality risk. The mortality risk increased as the number of MetS components increased among total participants and women (P for trend = 0.009 and 0.016, respectively). In addition, MetS groups had higher mortality risk in aged ≥ 60 years (HR: 1.60, 95 % CI: 1.07–2.39), and never-smokers (2.08, 1.21–3.59).ConclusionsThe presence of MetS and greater number of its components were associated with increased mortality risks particularly in female patients with COVID-19. Managing MetS may contribute to better outcomes of COVID-19.