纬度和海拔与COVID-19患者不良后果的关系:病毒登记

Aysun Tekin, Shahraz Qamar, Romil Singh, Vikas Bansal, Mayank Sharma, Allison M LeMahieu, Andrew C Hanson, Phillip J Schulte, Marija Bogojevic, Neha Deo, Simon Zec, Diana J Valencia Morales, Katherine A Belden, Smith F Heavner, Margit Kaufman, Sreekanth Cheruku, Valerie C Danesh, Valerie M Banner-Goodspeed, Catherine A St Hill, Amy B Christie, Syed A Khan, Lynn Retford, Karen Boman, Vishakha K Kumar, John C O'Horo, Juan Pablo Domecq, Allan J Walkey, Ognjen Gajic, Rahul Kashyap, Salim Surani
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引用次数: 0

摘要

背景2019冠状病毒病(新冠肺炎)病程可能受到环境因素的影响。生态研究先前表明气候因素与新冠肺炎死亡率之间存在联系。然而,这些因素在个体层面的影响还没有得到彻底的评估。目的研究与患者位置相关的气候因素与患者不良预后的关系。方法在这项对重症监护医学会发现病毒感染和呼吸系统疾病通用研究新冠肺炎登记队列的观察性分析中,医院的纬度和海拔被检查为入院28天内死亡率和住院时间的协变量。调整基线参数和入院日期后,采用多变量回归模型。采用广义估计方程对模型进行拟合。结果对来自20多个国家的28名患者进行了评估。中位年龄为62岁(四分位间距:49-74),54%的纳入患者为男性。中位年龄随着纬度和合并症频率的增加而增加。相反,在高海拔地区,合并症的百分比较低。入院后28天内的死亡率为25%。所有纳入患者的平均无住院天数为20天。尽管死亡率和无住院天数之间存在显著的线性关系(调整后的比值比(aOR)=1.39(1.04,1.86),但入院28天内的死亡率P=0.025;aOR=-1.47(-2.60,-0.33),无住院天数P=0.011),表明患者的不良后果在远离赤道的地区更为常见;当校正基线差异时,结果不再显著(aOR=1.32(1.00,1.74),28天死亡率P=0.051;aOR=1.07(-2.13,-0.01),无住院天数P=0.050)。当我们观察海拔高度的影响时,我们发现,与148 m.a.s.l的参考海拔相比,75 MASL、125 MASL、400 MASL和600 MASL的海拔点与入院28天内的死亡率呈非线性关系(aOR=0.96(0.62,1.47)、1.04(0.92,1.19)、0.49(0.22,0.90)和0.51(0.27,0.98)。P=0.001)。在这项全球研究中,我们发现纬度与28天死亡率以及无住院天数之间存在关联。然而,当考虑到基线特征时,这并没有保持显著性。结论我们的研究结果表明,在以前的流行病学研究中观察到的差异可能是由于生态谬误,而不是暗示患者层面的因果关系。
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Association of latitude and altitude with adverse outcomes in patients with COVID-19: The VIRUS registry.

Background: The coronavirus disease 2019 (COVID-19) course may be affected by environmental factors. Ecological studies previously suggested a link between climatological factors and COVID-19 fatality rates. However, individual-level impact of these factors has not been thoroughly evaluated yet.

Aim: To study the association of climatological factors related to patient location with unfavorable outcomes in patients.

Methods: In this observational analysis of the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study: COVID-19 Registry cohort, the latitudes and altitudes of hospitals were examined as a covariate for mortality within 28 d of admission and the length of hospital stay. Adjusting for baseline parameters and admission date, multivariable regression modeling was utilized. Generalized estimating equations were used to fit the models.

Results: Twenty-two thousand one hundred eight patients from over 20 countries were evaluated. The median age was 62 (interquartile range: 49-74) years, and 54% of the included patients were males. The median age increased with increasing latitude as well as the frequency of comorbidities. Contrarily, the percentage of comorbidities was lower in elevated altitudes. Mortality within 28 d of hospital admission was found to be 25%. The median hospital-free days among all included patients was 20 d. Despite the significant linear relationship between mortality and hospital-free days (adjusted odds ratio (aOR) = 1.39 (1.04, 1.86), P = 0.025 for mortality within 28 d of admission; aOR = -1.47 (-2.60, -0.33), P = 0.011 for hospital-free days), suggesting that adverse patient outcomes were more common in locations further away from the Equator; the results were no longer significant when adjusted for baseline differences (aOR = 1.32 (1.00, 1.74), P = 0.051 for 28-day mortality; aOR = -1.07 (-2.13, -0.01), P = 0.050 for hospital-free days). When we looked at the altitude's effect, we discovered that it demonstrated a non-linear association with mortality within 28 d of hospital admission (aOR = 0.96 (0.62, 1.47), 1.04 (0.92, 1.19), 0.49 (0.22, 0.90), and 0.51 (0.27, 0.98), for the altitude points of 75 MASL, 125 MASL, 400 MASL, and 600 MASL, in comparison to the reference altitude of 148 m.a.s.l, respectively. P = 0.001). We detected an association between latitude and 28-day mortality as well as hospital-free days in this worldwide study. When the baseline features were taken into account, however, this did not stay significant.

Conclusion: Our findings suggest that differences observed in previous epidemiological studies may be due to ecological fallacy rather than implying a causal relationship at the patient level.

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