基于微信小程序的代谢综合征智能健康管理平台的设计与开发

目的：设计与开发满足代谢综合征风险预测及健康管理需求的微信小程序。方法：依托智能手机与互联网技术，根据健康体检人群、代谢综合征患者以及医护人员的需求分析结果，以健康数据采集、健康风险预测、健康管理知识库融合及决策建模、数据隐私及安全为技术关键点，设计与开发基于微信小程序的智能健康管理平台。结果：平台包括体检者及患者端、医护人员端和系统管理者后台三个端口，具有代谢综合征风险预测、健康管理策略智能推荐、健康行为记录与督促提醒、专家咨询、健康知识推送等主要功能。结论：开发了可用于代谢综合征高危人群风险预测和患者健康管理的微信小程序，有助于提升该人群的健康管理意识和健康行为依从性，从而更精准、高效地实现健康促进的目标。     

Narratives that address affective forecasting errors reduce perceived barriers to colorectal cancer screening

Narratives from similar others may be an effective way to increase important health behaviors. In this study, we used a narrative intervention to promote colorectal cancer screening. Researchers have suggested that people may overestimate barriers to colorectal cancer screening. We recruited participants from the US, ages 49–60 who had never previously been screened for colorectal cancer, to read an educational message about screening for the disease. One-half of participants were randomly assigned to also receive a narrative within the message (control participants did not receive a narrative). The narrative intervention was developed according to predictions of affective forecasting theory. Compared to participants who received only the educational message, participants who received the message along with a narrative reported that the barriers to screening would have less of an impact on a future screening experience. The narrative also increased risk perception for colorectal cancer and interest in screening in the next year.     

民用发动机状态混沌预测算法研究

摘 要：本文首先应用Haar和Db16小波对航空发动机排气温度的原始数据序列进行去噪处理,并且证明了处理后的数据序列具有混沌特征。其次应用混沌理论建立发动机状态预测算法,实现对排气温度的预测。通过检验排气温度预测值是否超过所规定的红线,以及该曲线是否平稳,从而进行发动机的健康状态排查。作为验证实例,文中使用一组某机型发动机实际飞行数据对预测算法进行了验证,并与加权一阶局域法和自回归滑动平均模型预测法进行了对比。结果表明,该组合模型算法精度优于加权一阶局域法和自回归滑动平均模型预测法,该方法可以为这种机型发动机故障预测提供决策依据。     

晚期非小细胞肺癌治疗的新趋势

当今肺癌研究的热点是以与肿瘤发生、发展相关的驱动基因为靶点,研发新的药物,进行有针对性的个体化分子靶向治疗,从而改善患者预后。靶向药物、新型化疗药物、抗血管新生药物以及治疗性疫苗等各种治疗手段在晚期非小细胞肺癌(NSCLC)患者的治疗中均取得了显著的进展。其中表皮生长因子受体酪氨酸激酶抑制剂(EGFR-TKI)对于EGFR突变阳性NSCLC患者无论在一线、维持还是二线治疗中疗效均得到肯定;替吉奥胶囊有望成为晚期NSCLC一线、二线治疗新的选择;克唑替尼是棘皮动物微管结合蛋白4与间变淋巴瘤激酶融合基因(EML4-ALK)阳性患者治疗的新标准;抗血管新生药物在NSCLC的治疗疗效得到了进一步证实;EGF疫苗在晚期NSCLC治疗中的结果值得期待。这些成果将会改变目前晚期NSCLC的治疗策略,而基于患者临床特点及分子分型的个体化治疗将成为晚期非小细胞肺癌治疗的新趋势。     

Forecasting COVID-19 Hospital Census: A Multivariate Time-Series Model Based on Local Infection Incidence

BackgroundCOVID-19 has been one of the most serious global health crises in world history. During the pandemic, health care systems require accurate forecasts for key resources to guide preparation for patient surges. Forecasting the COVID-19 hospital census is among the most important planning decisions to ensure adequate staffing, number of beds, intensive care units, and vital equipment.ObjectiveThe goal of this study was to explore the potential utility of local COVID-19 infection incidence data in developing a forecasting model for the COVID-19 hospital census.MethodsThe study data comprised aggregated daily COVID-19 hospital census data across 11 Atrium Health hospitals plus a virtual hospital in the greater Charlotte metropolitan area of North Carolina, as well as the total daily infection incidence across the same region during the May 15 to December 5, 2020, period. Cross-correlations between hospital census and local infection incidence lagging up to 21 days were computed. A multivariate time-series framework, called the vector error correction model (VECM), was used to simultaneously incorporate both time series and account for their possible long-run relationship. Hypothesis tests and model diagnostics were performed to test for the long-run relationship and examine model goodness of fit. The 7-days-ahead forecast performance was measured by mean absolute percentage error (MAPE), with time-series cross-validation. The forecast performance was also compared with an autoregressive integrated moving average (ARIMA) model in the same cross-validation time frame. Based on different scenarios of the pandemic, the fitted model was leveraged to produce 60-days-ahead forecasts.ResultsThe cross-correlations were uniformly high, falling between 0.7 and 0.8. There was sufficient evidence that the two time series have a stable long-run relationship at the .01 significance level. The model had very good fit to the data. The out-of-sample MAPE had a median of 5.9% and a 95th percentile of 13.4%. In comparison, the MAPE of the ARIMA had a median of 6.6% and a 95th percentile of 14.3%. Scenario-based 60-days-ahead forecasts exhibited concave trajectories with peaks lagging 2 to 3 weeks later than the peak infection incidence. In the worst-case scenario, the COVID-19 hospital census can reach a peak over 3 times greater than the peak observed during the second wave.ConclusionsWhen used in the VECM framework, the local COVID-19 infection incidence can be an effective leading indicator to predict the COVID-19 hospital census. The VECM model had a very good 7-days-ahead forecast performance and outperformed the traditional ARIMA model. Leveraging the relationship between the two time series, the model can produce realistic 60-days-ahead scenario-based projections, which can inform health care systems about the peak timing and volume of the hospital census for long-term planning purposes.     

脑卒中常用量表对急性脑梗死患者死亡预测的价值

目的评价急性生理学和慢性健康状况评分(APACHEⅡ、APACHEⅢ)、改良的爱丁堡-斯堪的纳维亚评分(CSS)、美国国立卫生研究院卒中量表(NIHSS)评分、欧洲卒中评分(ESS)、既往史和伴发疾病评分对急性脑梗死患者预后评估的价值。方法选择441例急性脑梗死患者,在入院24 h内分别进行APACHEⅡ、APACHEⅢ、CSS、NIHSS、ESS、既往史和伴发疾病评分,并据患者发病后1个月时的预后分为生存组279例和死亡组162例,对2组患者的资料进行统计分析。通过ROC曲线评定分析6个量表对预后的预测价值。结果死亡组APACHEⅡ、APACHEⅢ、CSS、NIHSS和伴发疾病评分高于生存组(P<0.01),ESS评分低于生存组(P<0.01)。2组既往史评分比较差异无统计学意义(P>0.05)。APACHEⅡ、APACHEⅢ、CSS、NIHSS、ESS和伴发疾病评分6个量表预测急性脑梗死预后的ROC曲线下面积分别为0.867、0.858、0.896、0.876、0.886和0.841,差异有统计学意义(P<0.01),其预测界值分别为12、31、15、26、33和10分。结论 APACHEⅡ、APACHEⅢ、CSS、NIHSS、ESS和伴发疾病评分对急性脑梗死患者的预后均有较好的预测价值,预测准确度在75%左右。     

妊娠糖尿病患者血清C肽对妊娠不良事件和胎儿生长发育的预测价值

目的 探讨妊娠糖尿病（GDM）患者血清C肽对妊娠不良事件和胎儿生长发育的预测价值。方法 回顾性分析2021年6月—2022年12月在宣城市人民医院分娩的98例GDM患者的临床资料,统计GDM患者临床妊娠结局和胎儿生长发育情况。根据GDM患者妊娠结局分为结局不良组和结局良好组;根据胎儿生长发育情况分为发育异常组和发育正常组。比较结局不良组、结局良好组,发育异常组、发育正常组的临床资料及血清C肽水平。采用多因素Logistic逐步回归模型分析影响GDM患者妊娠结局和胎儿生长发育的相关因素。绘制受试者工作特征（ROC）曲线分析血清C肽对GDM患者妊娠不良事件和胎儿生长发育的预测效能。结果 98例GDM患者临床妊娠结局不良共37例、妊娠结局良好61例,胎儿发育异常22例、发育正常76例。结局不良组的年龄、孕次、空腹血糖（FPG）、糖化血红蛋白（HbA1c）及C肽水平高于结局良好组（P<0.05）。发育异常组FPG、HbA1c及C肽水平高于发育正常组（P<0.05）。多因素Logistic逐步回归分析结果显示：年龄[■=2.927(95%CI:1.056,8.111）]、HbA1c[...