From the Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
From the Department of Biostatistics, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
Ann Saudi Med. 2023 Jul-Aug;43(4):254-261. doi: 10.5144/0256-4947.2023.254. Epub 2023 Aug 3.
Coronavirus disease 2019 (COVID-19), caused by a novel coronavirus, manifests as a respiratory illness primarily and symptoms range from asymptomatic to severe respiratory syndrome and even death. During the pandemic, due to overcrowding of medical facilities, clinical assessment to triage patients for home care or in-hospital treatment was an essential element of management.
Study the demographic features, comorbidities and bio-markers that predict severe illness and mortality from COVID-19 infection.
Retrospective observational SETTING: Single tertiary care center PATIENTS AND METHODS: The study included all patients admitted with a positive PCR test for COVID-19 during the period from March 2020 to September 2020 (7 months). Data on demographics, clinical data and laboratory parameters was collected from medical records every 3 days during hospital stay or up until transfer to ICU.
Demographic, comorbidities and biochemical features that might predict severe COVID-19 disease.
372 RESULTS: Of the 372 patients, 72 (19.4%) had severe disease requiring admission to intensive care unit (ICU); 6 (1.6%) died. Individuals over 62 years were more likely to be admitted to the ICU (=.0001, while a BMI of 40 and higher increased the odds of severe disease (=.032). Male gender (=.042), hypertension (=.006) and diabetes (=.001) conferred a statistically significant increased risk of admission to ICU, while coexisting COPD, and ischemic heart disease did not. Laboratory features related to severe COVID-19 infection were: leukocytosis (=.015), thrombocytopenia (=.001), high levels of C-reactive protein (=.0001), lactic dehydrogenase (=.0001), D-dimer (=.0001) and ferritin (=.001). With the multivariate analysis, diabetes, high lac-tate dehydrogenase, C-reactive protein and thrombocytopenia were associated with severity of illness.
Particular demographic and clinical parameters may predict severe illness and need for ICU care.
Single referral center, several cases of severe COVID-19 could not be included due to lack of consent and or data.
None.
由新型冠状病毒引起的 2019 年冠状病毒病（COVID-19）主要表现为呼吸道疾病，症状从无症状到严重呼吸综合征甚至死亡不等。在大流行期间，由于医疗设施拥挤，对患者进行临床评估以分流到家庭护理或住院治疗是管理的重要组成部分。
研究预测 COVID-19 感染严重疾病和死亡的人口统计学特征、合并症和生物标志物。
回顾性观察性研究
单一体三叶式关怀中心
该研究纳入了 2020 年 3 月至 2020 年 9 月（7 个月）期间因 COVID-19 阳性 PCR 检测而住院的所有患者。从病历中收集住院期间每 3 天的人口统计学、临床数据和实验室参数，或直至转移至 ICU。
可能预测严重 COVID-19 疾病的人口统计学、合并症和生化特征。
372
在 372 名患者中，有 72 名（19.4%）患有需要入住重症监护病房（ICU）的严重疾病；有 6 名（1.6%）死亡。62 岁以上的患者更有可能被收入 ICU（<.0001），而 BMI 为 40 及以上则增加严重疾病的几率（=.032）。男性（=.042）、高血压（=.006）和糖尿病（=.001）使 ICU 入院的风险具有统计学意义的增加，而同时患有 COPD 和缺血性心脏病则没有。与严重 COVID-19 感染相关的实验室特征包括：白细胞增多（=.015）、血小板减少症（=.001）、C 反应蛋白水平升高（=.0001）、乳酸脱氢酶升高（=.0001）、D-二聚体升高（=.0001）和铁蛋白升高（=.001）。在多变量分析中，糖尿病、高乳酸脱氢酶、C 反应蛋白和血小板减少症与疾病严重程度相关。
特定的人口统计学和临床参数可能预测严重疾病和对 ICU 护理的需求。
单一转诊中心，由于缺乏同意和/或数据，无法纳入几例严重 COVID-19 病例。
无。
