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首页> 外文期刊>JMIR Medical Informatics >Effect of Seasonal Variation on Clinical Outcome in Patients with Chronic Conditions: Analysis of the Commonwealth Scientific and Industrial Research Organization (CSIRO) National Telehealth Trial
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Effect of Seasonal Variation on Clinical Outcome in Patients with Chronic Conditions: Analysis of the Commonwealth Scientific and Industrial Research Organization (CSIRO) National Telehealth Trial

机译:季节性变化对慢性病患者临床疗效的影响:联邦科学与工业研究组织(CSIRO)国家远程医疗试验的分析

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Background Seasonal variation has an impact on the hospitalization rate of patients with a range of cardiovascular diseases, including myocardial infarction and angina. This paper presents findings on the influence of seasonal variation on the results of a recently completed national trial of home telemonitoring of patients with chronic conditions, carried out at five locations along the east coast of Australia. Objective The aim is to evaluate the effect of the seasonal timing of hospital admission and length of stay on clinical outcome of a home telemonitoring trial involving patients (age: mean 72.2, SD 9.4 years) with chronic conditions (chronic obstructive pulmonary disease coronary artery disease, hypertensive diseases, congestive heart failure, diabetes, or asthma) and to explore methods of minimizing the influence of seasonal variations in the analysis of the effect of at-home telemonitoring on the number of hospital admissions and length of stay (LOS). Methods Patients were selected from a hospital list of eligible patients living with a range of chronic conditions. Each test patient was case matched with at least one control patient. A total of 114 test patients and 173 control patients were available in this trial. However, of the 287 patients, we only considered patients who had one or more admissions in the years from 2010 to 2012. Three different groups were analyzed separately because of substantially different climates: (1) Queensland, (2) Australian Capital Territory and Victoria, and (3) Tasmania. Time series data were analyzed using linear regression for a period of 3 years before the intervention to obtain an average seasonal variation pattern. A novel method that can reduce the impact of seasonal variation on the rate of hospitalization and LOS was used in the analysis of the outcome variables of the at-home telemonitoring trial. Results Test patients were monitored for a mean 481 (SD 77) days with 87% (53/61) of patients monitored for more than 12 months. Trends in seasonal variations were obtained from 3 years’ of hospitalization data before intervention for the Queensland, Tasmania, and Australian Capital Territory and Victoria subgroups, respectively. The maximum deviation from baseline trends for LOS was 101.7% (SD 42.2%), 60.6% (SD 36.4%), and 158.3% (SD 68.1%). However, by synchronizing outcomes to the start date of intervention, the impact of seasonal variations was minimized to a maximum of 9.5% (SD 7.7%), thus improving the accuracy of the clinical outcomes reported. Conclusions Seasonal variations have a significant effect on the rate of hospital admission and LOS in patients with chronic conditions. However, the impact of seasonal variation on clinical outcomes (rate of admissions, number of hospital admissions, and LOS) of at-home telemonitoring can be attenuated by synchronizing the analysis of outcomes to the commencement dates for the telemonitoring of vital signs. Trial Registration Australian New Zealand Clinical Trial Registry ACTRN12613000635763; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364030&isReview=true (Archived by WebCite at http://www.webcitation.org/ 6xLPv9QDb).
机译:背景季节性变化对包括心血管梗塞和心绞痛在内的一系列心血管疾病患者的住院率产生影响。本文介绍了在澳大利亚东海岸的五个地点进行的季节性变化对近期完成的慢性病患者家庭远程监护国家试验结果的影响发现。目的目的是评估入院季节性时机和住院时间对一项涉及长期病患(慢性阻塞性肺疾病,冠心病)的患者(年龄:平均72.2岁,标准差9.4岁)的家庭远程监护试验的临床结果的影响,高血压疾病,充血性心力衰竭,糖尿病或哮喘),并在分析家庭远程监护对住院人数和住院时间(LOS)的影响时探索将季节性变化的影响最小化的方法。方法从选自一系列慢性病的合格患者的医院名单中选择患者。每个测试患者均与至少一名对照患者进行病例匹配。在该试验中,总共有114名测试患者和173名对照患者。但是,在这287名患者中,我们仅考虑了2010年至2012年之间入院的患者。由于气候差异很大,分别对三个不同的组进行了分析:(1)昆士兰州,(2)澳大利亚首都特区和维多利亚州,以及(3)塔斯马尼亚州。在进行干预之前,使用线性回归分析了3年期间的时间序列数据,以获得平均季节性变化模式。在家里远程监视试验的结果变量的分析中使用了一种可以减少季节性变化对住院率和LOS的影响的新方法。结果监测了平均481天(SD 77)的受试患者,其中87%(53/61)的患者接受了12个月以上的监测。分别从昆士兰州,塔斯马尼亚州,澳大利亚首都地区和维多利亚州亚组干预之前的3年住院数据中得出季节性变化趋势。 LOS与基线趋势的最大偏差为101.7%(SD 42.2%),60.6%(SD 36.4%)和158.3%(SD 68.1%)。但是,通过将结果与干预开始日期同步,可以将季节性变化的影响最小化到最大9.5%(标准差7.7%),从而提高了所报告临床结果的准确性。结论季节性变化对慢性病患者的住院率和LOS有显着影响。但是,通过将结果分析与生命体征远程监测的开始日期同步,可以减轻季节性变化对在家远程监护的临床结局(入院率,住院次数和LOS)的影响。试验注册澳大利亚新西兰临床试验注册中心ACTRN12613000635763; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364030&isReview=true(由WebCite存档,网址为http://www.webcitation.org/ 6xLPv9QDb)。

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