Department of Medicine (Critical Care), University of Ottawa, Ottawa, ON, K1Y 4E9, Canada.
Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada.
BMC Med Res Methodol. 2018 Sep 15;18(1):94. doi: 10.1186/s12874-018-0553-3.
Conducting prospective epidemiological studies of hospitalized patients with rare diseases like primary subarachnoid hemorrhage (pSAH) are difficult due to time and budgetary constraints. Routinely collected administrative data could remove these barriers. We derived and validated 3 algorithms to identify hospitalized patients with a high probability of pSAH using administrative data. We aim to externally validate their performance in four hospitals across Canada.
Eligible patients include those ≥18 years of age admitted to these centres from January 1, 2012 to December 31, 2013. We will include patients whose discharge abstracts contain predictive variables identified in the models (ICD-10-CA diagnostic codes I60** (subarachnoid hemorrhage), I61** (intracranial hemorrhage), 162** (other nontrauma intracranial hemorrhage), I67** (other cerebrovascular disease), S06** (intracranial injury), G97 (other postprocedural nervous system disorder) and CCI procedural codes 1JW51 (occlusion of intracranial vessels), 1JE51 (carotid artery inclusion), 3JW10 (intracranial vessel imaging), 3FY20 (CT scan (soft tissue of neck)), and 3OT20 (CT scan (abdominal cavity)). The algorithms will be applied to each patient and the diagnosis confirmed via chart review. We will assess each model's sensitivity, specificity, negative and positive predictive value across the sites.
Validating the Ottawa SAH Prediction Algorithms will provide a way to accurately identify large SAH cohorts, thereby furthering research and altering care.
由于时间和预算的限制,对原发性蛛网膜下腔出血(pSAH)等罕见病的住院患者进行前瞻性流行病学研究较为困难。常规收集的行政数据可以消除这些障碍。我们开发并验证了 3 种算法,以使用行政数据识别患有高概率 pSAH 的住院患者。我们旨在在加拿大的 4 家医院外部验证这些算法的性能。
符合条件的患者包括 2012 年 1 月 1 日至 2013 年 12 月 31 日期间入住这些中心的年龄≥18 岁的患者。我们将纳入那些出院摘要中包含模型中确定的预测变量的患者(ICD-10-CA 诊断代码 I60**(蛛网膜下腔出血)、I61**(颅内出血)、I62**(其他非创伤性颅内出血)、I67**(其他脑血管疾病)、S06**(颅内损伤)、G97(其他术后神经系统疾病)和 CCI 手术代码 1JW51(颅内血管闭塞)、1JE51(颈动脉包含)、3JW10(颅内血管成像)、3FY20(颈部软组织 CT 扫描)和 3OT20(腹腔 CT 扫描))。将算法应用于每个患者,并通过病历回顾确认诊断。我们将评估每个模型在各个地点的敏感性、特异性、阴性和阳性预测值。
验证渥太华 SAH 预测算法将为准确识别大的 SAH 队列提供一种方法,从而推进研究并改变护理方式。