bims-covirf 2021-08-01 papers

Issue of 2021–08–01
three papers selected by
Catherine Rycroft, BresMed

PLoS One. 2021 ;16(7): e0255154

Can we predict the severe course of COVID-19 - a systematic review and meta-analysis of indicators of clinical outcome?

Stephan Katzenschlager, Alexandra J Zimmer, Claudius Gottschalk, Jürgen Grafeneder, Stephani Schmitz, Sara Kraker, Marlene Ganslmeier, Amelie Muth, Alexander Seitel, Lena Maier-Hein, Andrea Benedetti, Jan Larmann, Markus A Weigand, Sean McGrath, Claudia M Denkinger.

BACKGROUND: COVID-19 has been reported in over 40million people globally with variable clinical outcomes. In this systematic review and meta-analysis, we assessed demographic, laboratory and clinical indicators as predictors for severe courses of COVID-19.
METHODS: This systematic review was registered at PROSPERO under CRD42020177154. We systematically searched multiple databases (PubMed, Web of Science Core Collection, MedRvix and bioRvix) for publications from December 2019 to May 31st 2020. Random-effects meta-analyses were used to calculate pooled odds ratios and differences of medians between (1) patients admitted to ICU versus non-ICU patients and (2) patients who died versus those who survived. We adapted an existing Cochrane risk-of-bias assessment tool for outcome studies.
RESULTS: Of 6,702 unique citations, we included 88 articles with 69,762 patients. There was concern for bias across all articles included. Age was strongly associated with mortality with a difference of medians (DoM) of 13.15 years (95% confidence interval (CI) 11.37 to 14.94) between those who died and those who survived. We found a clinically relevant difference between non-survivors and survivors for C-reactive protein (CRP; DoM 69.10 mg/L, CI 50.43 to 87.77), lactate dehydrogenase (LDH; DoM 189.49 U/L, CI 155.00 to 223.98), cardiac troponin I (cTnI; DoM 21.88 pg/mL, CI 9.78 to 33.99) and D-Dimer (DoM 1.29mg/L, CI 0.9 to 1.69). Furthermore, cerebrovascular disease was the co-morbidity most strongly associated with mortality (Odds Ratio 3.45, CI 2.42 to 4.91) and ICU admission (Odds Ratio 5.88, CI 2.35 to 14.73).
DISCUSSION: This comprehensive meta-analysis found age, cerebrovascular disease, CRP, LDH and cTnI to be the most important risk-factors that predict severe COVID-19 outcomes and will inform clinical scores to support early decision-making.

DOI: https://doi.org/10.1371/journal.pone.0255154

PLoS One. 2021 ;16(7): e0255544

Risk factors for severity of COVID-19 in hospital patients age 18-29 years.

Micaela Sandoval, Duc T Nguyen, Farhaan S Vahidy, Edward A Graviss.

BACKGROUND: Since February 2020, over 2.5 million Texans have been diagnosed with COVID-19, and 20% are young adults at risk for SARS-CoV-2 exposure at work, academic, and social settings. This study investigated demographic and clinical risk factors for severe disease and readmission among young adults 18-29 years old, who were diagnosed at a hospital encounter in Houston, Texas, USA.
METHODS AND FINDINGS: A retrospective registry-based chart review was conducted investigating demographic and clinical risk factors for severe COVID-19 among patients aged 18-29 with positive SARS-CoV-2 tests within a large metropolitan healthcare system in Houston, Texas, USA. In the cohort of 1,853 young adult patients diagnosed with COVID-19 infection at a hospital encounter, including 226 pregnant women, 1,438 (78%) scored 0 on the Charlson Comorbidity Index, and 833 (45%) were obese (≥30 kg/m2). Within 30 days of their diagnostic encounter, 316 (17%) patients were diagnosed with pneumonia, 148 (8%) received other severe disease diagnoses, and 268 (14%) returned to the hospital after being discharged home. In multivariable logistic regression analyses, increasing age (adjusted odds ratio [aOR] 1.1, 95% confidence interval [CI] 1.1-1.2, p<0.001), male gender (aOR 1.8, 95% CI 1.2-2.7, p = 0.002), Hispanic ethnicity (aOR 1.9, 95% CI 1.2-3.1, p = 0.01), obesity (3.1, 95% CI 1.9-5.1, p<0.001), asthma history (aOR 2.3, 95% CI 1.3-4.0, p = 0.003), congestive heart failure (aOR 6.0, 95% CI 1.5-25.1, p = 0.01), cerebrovascular disease (aOR 4.9, 95% CI 1.7-14.7, p = 0.004), and diabetes (aOR 3.4, 95% CI 1.9-6.2, p<0.001) were predictive of severe disease diagnoses within 30 days. Non-Hispanic Black race (aOR 1.6, 95% CI 1.0-2.4, p = 0.04), obesity (aOR 1.7, 95% CI 1.0-2.9, p = 0.046), asthma history (aOR 1.7, 95% CI 1.0-2.7, p = 0.03), myocardial infarction history (aOR 6.2, 95% CI 1.7-23.3, p = 0.01), and household exposure (aOR 1.5, 95% CI 1.1-2.2, p = 0.02) were predictive of 30-day readmission.
CONCLUSIONS: This investigation demonstrated the significant risk of severe disease and readmission among young adult populations, especially marginalized communities and people with comorbidities, including obesity, asthma, cardiovascular disease, and diabetes. Health authorities must emphasize COVID-19 awareness and prevention in young adults and continue investigating risk factors for severe disease, readmission and long-term sequalae.

DOI: https://doi.org/10.1371/journal.pone.0255544

JAMA Psychiatry. 2021 Jul 28.

Association Between Mood Disorders and Risk of COVID-19 Infection, Hospitalization, and Death: A Systematic Review and Meta-analysis.

Felicia Ceban, Danica Nogo, Isidro P Carvalho, Yena Lee, Flora Nasri, Jiaqi Xiong, Leanna M W Lui, Mehala Subramaniapillai, Hartej Gill, Rene N Liu, Prianca Joseph, Kayla M Teopiz, Bing Cao, Rodrigo B Mansur, Kangguang Lin, Joshua D Rosenblat, Roger C Ho, Roger S McIntyre.

Importance: Preexisting noncommunicable diseases (eg, diabetes) increase the risk of COVID-19 infection, hospitalization, and death. Mood disorders are associated with impaired immune function and social determinants that increase the risk of COVID-19. Determining whether preexisting mood disorders represent a risk of COVID-19 would inform public health priorities.
Objective: To assess whether preexisting mood disorders are associated with a higher risk of COVID-19 susceptibility, hospitalization, severe complications, and death.
Data Sources: Systematic searches were conducted for studies reporting data on COVID-19 outcomes in populations with and without mood disorders on PubMed/MEDLINE, The Cochrane Library, PsycInfo, Embase, Web of Science, Google/Google Scholar, LitCovid, and select reference lists. The search timeline was from database inception to February 1, 2021.
Study Selection: Primary research articles that reported quantitative COVID-19 outcome data in persons with mood disorders vs persons without mood disorders of any age, sex, and nationality were selected. Of 1950 articles identified through this search strategy, 21 studies were included in the analysis.
Data Extraction and Synthesis: The modified Newcastle-Ottawa Scale was used to assess methodological quality and risk of bias of component studies. Reported adjusted odds ratios (ORs) were pooled with unadjusted ORs calculated from summary data to generate 4 random-effects summary ORs, each corresponding to a primary outcome.
Main Outcomes and Measures: The 4 a priori primary outcomes were COVID-19 susceptibility, COVID-19 hospitalization, COVID-19 severe events, and COVID-19 death. The hypothesis was formulated before study search. Outcome measures between individuals with and without mood disorders were compared.
Results: This review included 21 studies that involved more than 91 million individuals. Significantly higher odds of COVID-19 hospitalization (OR, 1.31; 95% CI, 1.12-1.53; P = .001; n = 26 554 397) and death (OR, 1.51; 95% CI, 1.34-1.69; P < .001; n = 25 808 660) were found in persons with preexisting mood disorders compared with those without mood disorders. There was no association between mood disorders and COVID-19 susceptibility (OR, 1.27; 95% CI, 0.73-2.19; n = 65 514 469) or severe events (OR, 0.94; 95% CI, 0.87-1.03; n = 83 240). Visual inspection of the composite funnel plot for asymmetry indicated the presence of publication bias; however, the Egger regression intercept test result was not statistically significant.
Conclusions and Relevance: The results of this systematic review and meta-analysis examining the association between preexisting mood disorders and COVID-19 outcomes suggest that individuals with preexisting mood disorders are at higher risk of COVID-19 hospitalization and death and should be categorized as an at-risk group on the basis of a preexisting condition.

DOI: https://doi.org/10.1001/jamapsychiatry.2021.1818