Emergency Department, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.
Quality Management Center, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.
J Med Syst. 2022 Jun 8;46(7):49. doi: 10.1007/s10916-022-01833-z.
Hemorrhagic stroke is a serious clinical condition that requires timely diagnosis. An artificial intelligence algorithm system called DeepCT can identify hemorrhagic lesions rapidly from non-contrast head computed tomography (NCCT) images and has received regulatory clearance. A non-controlled retrospective pilot clinical trial was conducted. Patients who received NCCT at the emergency department (ED) of Kaohsiung Veteran General Hospital were collected. From 2020 January-1 to April-30, the physicians read NCCT images without DeepCT. From 2020May-1 to August-31, the physicians were assisted by DeepCT. The length of ED stays (LOS) for the patients was collected. 2,999 patients were included (188 and 2811 with and without ICH). For patients with a final diagnosis of ICH, implementing DeepCT significantly shortened their LOS (560.67 ± 604.93 min with DeepCT vs. 780.83 ± 710.27 min without DeepCT; p = 0.0232). For patients with a non-ICH diagnosis, the LOS did not significantly differ (705.90 ± 760.86 min with DeepCT vs. 679.45 ± 681.97 min without DeepCT; p = 0.3362). For patients with ICH, those assisted with DeepCT had a significantly shorter LOS than those without DeepCT. For patients with a non-ICH diagnosis, implementing DeepCT did not affect the LOS, because emergency physicians need same efforts to identify the underlying problem(s) with or without DeepCT. In summary, implementing DeepCT system in the ED will save costs, decrease LOS, and accelerate patient flow; most importantly, it will improve the quality of care and increase the confidence and shorten the response time of the physicians and radiologists.
脑出血是一种严重的临床病症，需要及时诊断。一种名为 DeepCT 的人工智能算法系统可以从非对比头部计算机断层扫描 (NCCT) 图像中快速识别出血性病变，并已获得监管部门批准。进行了一项非对照回顾性试点临床试验。收集了在高雄荣民总医院急诊科接受 NCCT 的患者。2020 年 1 月 1 日至 4 月 30 日，医生阅读没有 DeepCT 的 NCCT 图像。2020 年 5 月 1 日至 8 月 31 日，医生使用 DeepCT 辅助诊断。收集了患者的急诊停留时间 (LOS)。共纳入 2999 例患者 (ICH 患者 188 例，无 ICH 患者 2811 例)。对于最终诊断为 ICH 的患者，实施 DeepCT 可显著缩短其 LOS (有 DeepCT 组为 560.67 ± 604.93 分钟，无 DeepCT 组为 780.83 ± 710.27 分钟；p=0.0232)。对于非 ICH 诊断的患者，LOS 无显著差异 (有 DeepCT 组为 705.90 ± 760.86 分钟，无 DeepCT 组为 679.45 ± 681.97 分钟；p=0.3362)。对于 ICH 患者，辅助 DeepCT 组的 LOS 明显短于无 DeepCT 组。对于非 ICH 诊断的患者，实施 DeepCT 不会影响 LOS，因为急诊医生需要同样的努力来识别有或没有 DeepCT 的潜在问题。总之，在急诊科实施 DeepCT 系统将节省成本、缩短 LOS、加快患者流量；最重要的是，它将提高护理质量，并增加医生和放射科医生的信心并缩短其反应时间。
