Bhosale Shilpushp J, Kulkarni Atul P
Department of Anesthesia, Critical Care and Pain, Division of Critical Care Medicine, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra, India.
Indian J Crit Care Med. 2020 Dec;24(12):1161-1162. doi: 10.5005/jp-journals-10071-23694.
Efforts are continuing worldwide to understand the epidemiology, pathogenesis, and treatments for coronavirus disease-2019 (COVID-19). However, at the moment treatment remains supportive with oxygen therapy, steroids, repurposed antivirals, and prevention of multiple organ dysfunction by using immunomodulators. COVID-19 remains challenging since the disease spectrum varies from asymptomatic infection to severe acute respiratory distress syndrome (ARDS) with high fatality rates. It is thus necessary to predict clinical outcomes and risk-stratify patients for ensuring early intensive care unit (ICU) admissions. An important aspect is building surge capacity, managing and optimizing therapeutic and operational resources. So far, data have been scarce, particularly from India, to identify predictors of poor outcomes and mortality early in the course of the disease. Risk models need to be developed in larger patient cohorts and the models need to be simple and easy to employ at the onset of the disease process to predict the risk of severe disease, need for mechanical ventilation, ICU length of stay (LOS), and mortality. Bhosale SJ, Kulkarni AP. Crystal Gazing: Myth or Reality for Critical Care for COVID-19 Patients? Indian J Crit Care Med 2020;24(12):1161-1162.
全球各国都在持续努力了解2019冠状病毒病（COVID-19）的流行病学、发病机制及治疗方法。然而，目前的治疗仍以支持治疗为主，包括氧疗、使用类固醇、重新利用抗病毒药物以及通过使用免疫调节剂预防多器官功能障碍。由于COVID-19的疾病谱从无症状感染到具有高死亡率的严重急性呼吸窘迫综合征（ARDS）不等，因此仍然具有挑战性。因此，有必要预测临床结果并对患者进行风险分层，以确保早期入住重症监护病房（ICU）。一个重要方面是建立应急能力，管理和优化治疗及运营资源。到目前为止，数据稀缺，尤其是来自印度的数据，难以在疾病早期识别不良结局和死亡的预测因素。需要在更大的患者队列中开发风险模型，并且这些模型需要简单易用，以便在疾病过程开始时预测严重疾病的风险、机械通气需求、ICU住院时间（LOS）和死亡率。 博萨尔·SJ，库尔卡尼·AP。《展望未来：COVID-19患者重症监护是神话还是现实？》《印度重症监护医学杂志》2020年；24(12):1161 - 1162。
