Mortality rates of coronavirus disease‐2019 (COVID‐19) continue to rise across the world. Information regarding the predictors of mortality in patients with COVID‐19 remains scarce. Herein, we performed a systematic review of published articles, from 1 January to 24 April 2020, to evaluate the risk factors associated with mortality in COVID‐19. Two investigators independently searched the articles and collected the data, in accordance with PRISMA guidelines. We looked for associations between mortality and patient characteristics, comorbidities, and laboratory abnormalities. A total of 14 studies documenting the outcomes of 4659 patients were included. The presence of comorbidities such as hypertension (odds ratio [OR], 2.5; 95% confidence interval [CI], 2.1‐3.1; P < .00001), coronary heart disease (OR, 3.8; 95% CI, 2.1‐6.9; P < .00001), and diabetes (OR, 2.0; 95% CI, 1.7‐2.3; P < .00001) were associated with significantly higher risk of death amongst patients with COVID‐19. Those who died, compared with those who survived, differed on multiple biomarkers on admission including elevated levels of cardiac troponin (+44.2 ng/L, 95% CI, 19.0‐69.4; P = .0006); C‐reactive protein (+66.3 µg/mL, 95% CI, 46.7‐85.9; P < .00001); interleukin‐6 (+4.6 ng/mL, 95% CI, 3.6‐5.6; P < .00001); D‐dimer (+4.6 µg/mL, 95% CI, 2.8‐6.4; P < .00001); creatinine (+15.3 µmol/L, 95% CI, 6.2‐24.3; P = .001); and alanine transaminase (+5.7 U/L, 95% CI, 2.6‐8.8; P = .0003); as well as decreased levels of albumin (−3.7 g/L, 95% CI, −5.3 to −2.1; P < .00001). Individuals with underlying cardiometabolic disease and that present with evidence for acute inflammation and end‐organ damage are at higher risk of mortality due to COVID‐19 infection and should be managed with greater intensity.
Loss of function mutations in the autoimmune regulator (Aire) gene in autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy patients and mutant mice lead to autoimmune manifestations that segregate as a monogenic trait, but with wide variation in the spectrum of organs targeted. To investigate the cause of this variability, the Aire knockout mutation was backcrossed to mice of diverse genetic backgrounds. The background loci strongly influenced the pattern of organs that were targeted (stomach, eye, pancreas, liver, ovary, thyroid, and salivary gland) and the severity of the targeting (particularly strong on the nonobese diabetic background, but very mild on the C57BL/6 background). Autoantibodies mimicked the disease pattern, with oligoclonal reactivity to a few antigens that varied between Aire-deficient strains. Congenic analysis and a whole genome scan showed that autoimmunity to each organ had a distinctive pattern of genetic control and identified several regions that controlled the pattern of targeting, including the major histocompatibility complex and regions of Chr1 and Chr3 previously identified in controlling type 1 diabetes.
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