A prior meta-analysis showed that antidepressant use in major depressive disorder was associated with reduced plasma levels of several pro-inflammatory mediators, which have been associated with severe COVID-19. Recent studies also suggest that several antidepressants may inhibit acid sphingomyelinase activity, which may prevent the infection of epithelial cells with SARS-CoV-2, and that the SSRI fluoxetine may exert in-vitro antiviral effects on SARS-CoV-2. We examined the potential usefulness of antidepressant use in patients hospitalized for COVID-19 in an observational multicenter retrospective cohort study conducted at AP-HP Greater Paris University hospitals. Of 7230 adults hospitalized for COVID-19, 345 patients (4.8%) received an antidepressant within 48 h of hospital admission. The primary endpoint was a composite of intubation or death. We compared this endpoint between patients who received antidepressants and those who did not in time-to-event analyses adjusted for patient characteristics, clinical and biological markers of disease severity, and other psychotropic medications. The primary analysis was a multivariable Cox model with inverse probability weighting. This analysis showed a significant association between antidepressant use and reduced risk of intubation or death (HR, 0.56; 95% CI, 0.43-0.73, p < 0.001). This association remained significant in multiple sensitivity analyses. Exploratory analyses suggest that this association was also significant for SSRI and non-SSRI antidepressants, and for fluoxetine, paroxetine, escitalopram, venlafaxine, and mirtazapine (all p < 0.05). These results suggest that antidepressant use could be associated with lower risk of death or intubation in patients hospitalized for COVID-19. Double-blind controlled randomized clinical trials of antidepressant medications for COVID-19 are needed.

This study proposes evidence-based thresholds for patient-to-caregiver ratios, above which patient safety may be endangered in the ICU. Real-time monitoring of staffing levels and workload is feasible for adjusting caregivers' resources to patients' needs.

Several medications commonly used for a number of medical conditions share a property of functional inhibition of acid sphingomyelinase (ASM), or FIASMA. Preclinical and clinical evidence suggest that the (ASM)/ceramide system may be central to SARS‐CoV‐2 infection. We examined the potential usefulness of FIASMA use among patients hospitalized for severe COVID‐19 in an observational multicenter study conducted at Greater Paris University hospitals. Of 2,846 adult patients hospitalized for severe COVID‐19, 277 (9.7%) were taking a FIASMA medication at the time of their hospital admission. The primary endpoint was a composite of intubation and/or death. We compared this endpoint between patients taking vs. not taking a FIASMA medication in time‐to‐event analyses adjusted for sociodemographic characteristics and medical comorbidities. The primary analysis was a Cox regression model with inverse probability weighting (IPW). Over a mean follow‐up of 9.2 days (SD=12.5), the primary endpoint occurred in 104 patients (37.5%) receiving a FIASMA medication, and 1,060 patients (41.4%) who did not. Despite being significantly and substantially associated with older age and greater medical severity, FIASMA medication use was significantly associated with reduced likelihood of intubation or death in both crude (HR=0.71; 95%CI=0.58‐0.87; p<0.001) and primary IPW (HR=0.58; 95%CI=0.46‐0.72; p<0.001) analyses. This association remained significant in multiple sensitivity analyses and was not specific to one particular FIASMA class or medication. These results show the potential importance of the ASM/ceramide system in COVID‐19 and support the continuation of FIASMA medications in these patients. Double‐blind controlled randomized clinical trials of these medications for COVID‐19 are needed.

A survey conducted after 6 months of use at the Necker Children's Hospital shows a high rate of satisfaction among the users (96.6%). During this period, 122 users performed 2837 queries, accessed 4,267 patients' records and included 36,632 patients in 131 cohorts. The source code is available at this github link https://github.com/imagine-bdd/DRWH. A demonstration based on PubMed abstracts is available at https://imagine-plateforme-bdd.fr/dwh_pubmed/.

Objective: Preliminary data from different cohorts of small sample size or with short follow-up indicate poorer prognosis in people with obesity compared with other patients. This study aims to precisely describe the strength of association between obesity in patients hospitalized with coronavirus disease 2019 (COVID-19) and mortality and to clarify the risk according to usual cardiometabolic risk factors in a large cohort. Methods: This is a prospective cohort study including 5,795 patients aged 18 to 79 years hospitalized from February 1 to April 30, 2020, in the Paris area, with confirmed infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Adjusted regression models were used to estimate the odds ratios (ORs) and 95% CIs for the mortality rate at 30 days across BMI classes, without and with imputation for missing BMI values. Results: Eight hundred ninety-one deaths had occurred at 30 days. Mortality was significantly raised in people with obesity, with the following ORs for BMI of 30 to 35 kg/m 2 , 35 to 40 kg/m 2 , and >40 kg/m 2 : 1.89 (95% CI: 1.45-2.47), 2.79 (95% CI: 1.95-3.97), and 2.55 (95% CI: 1.62-3.95), respectively (18.5-25 kg/m 2 was used as the reference class). This increase holds for all age classes. Conclusions: Obesity doubles mortality in patients hospitalized with COVID-19.

Coincident with the tsunami of COVID-19–related publications, there has been a surge of studies using real-world data, including those obtained from the electronic health record (EHR). Unfortunately, several of these high-profile publications were retracted because of concerns regarding the soundness and quality of the studies and the EHR data they purported to analyze. These retractions highlight that although a small community of EHR informatics experts can readily identify strengths and flaws in EHR-derived studies, many medical editorial teams and otherwise sophisticated medical readers lack the framework to fully critically appraise these studies. In addition, conventional statistical analyses cannot overcome the need for an understanding of the opportunities and limitations of EHR-derived studies. We distill here from the broader informatics literature six key considerations that are crucial for appraising studies utilizing EHR data: data completeness, data collection and handling (eg, transformation), data type (ie, codified, textual), robustness of methods against EHR variability (within and across institutions, countries, and time), transparency of data and analytic code, and the multidisciplinary approach. These considerations will inform researchers, clinicians, and other stakeholders as to the recommended best practices in reviewing manuscripts, grants, and other outputs from EHR-data derived studies, and thereby promote and foster rigor, quality, and reliability of this rapidly growing field.

The acid sphingomyelinase (ASM)/ceramide system may provide a useful framework for better understanding SARS-CoV-2 infection and the repurposing of psychotropic medications functionally inhibiting the acid sphingomyelinase/ceramide system (named FIASMA psychotropic medications) against COVID-19. We examined the potential usefulness of FIASMA psychotropic medications in patients with psychiatric disorders hospitalized for severe COVID-19, in an observational multicenter study conducted at Greater Paris University hospitals. Of 545 adult inpatients, 164 (30.1%) received a FIASMA psychotropic medication upon hospital admission for COVID-19. We compared the composite endpoint of intubation or death between patients who received a psychotropic FIASMA medication at baseline and those who did not in time-to-event analyses adjusted for sociodemographic characteristics, psychiatric and other medical comorbidity, and other medications. FIASMA psychotropic medication use at baseline was significantly associated with reduced risk of intubation or death in both crude (HR = 0.42; 95%CI = 0.31–0.57; p < 0.01) and primary inverse probability weighting (IPW) (HR = 0.50; 95%CI = 0.37–0.67; p < 0.01) analyses. This association was not specific to one FIASMA psychotropic class or medication. Patients taking a FIASMA antidepressant at baseline had a significantly reduced risk of intubation or death compared with those taking a non-FIASMA antidepressant at baseline in both crude (HR = 0.57; 95%CI = 0.38–0.86; p < 0.01) and primary IPW (HR = 0.57; 95%CI = 0.37–0.87; p < 0.01) analyses. These associations remained significant in multiple sensitivity analyses. Our results show the potential importance of the ASM/ceramide system framework in COVID-19 and support the continuation of FIASMA psychotropic medications in these patients and the need of large- scale clinical trials evaluating FIASMA medications, and particularly FIASMA antidepressants, against COVID-19.

Phenome-Wide Association Studies (PheWAS) investigate whether genetic polymorphisms associated with a phenotype are also associated with other diagnoses. In this study, we have developed new methods to perform a PheWAS based on ICD-10 codes and biological test results, and to use a quantitative trait as the selection criterion. We tested our approach on thiopurine S-methyltransferase (TPMT) activity in patients treated by thiopurine drugs. We developed 2 aggregation methods for the ICD-10 codes: an ICD-10 hierarchy and a mapping to existing ICD-9-CM based PheWAS codes. Eleven biological test results were also analyzed using discretization algorithms. We applied these methods in patients having a TPMT activity assessment from the clinical data warehouse of a French academic hospital between January 2000 and July 2013. Data after initiation of thiopurine treatment were analyzed and patient groups were compared according to their TPMT activity level. A total of 442 patient records were analyzed representing 10,252 ICD-10 codes and 72,711 biological test results. The results from the ICD-9-CM based PheWAS codes and ICD-10 hierarchy codes were concordant. Cross-validation with the biological test results allowed us to validate the ICD phenotypes. Iron-deficiency anemia and diabetes mellitus were associated with a very high TPMT activity (p = 0.0004 and p = 0.0015, respectively). We describe here an original method to perform PheWAS on a quantitative trait using both ICD-10 diagnosis codes and biological test results to identify associated phenotypes. In the field of pharmacogenomics, PheWAS allow for the identification of new subgroups of patients who require personalized clinical and therapeutic management.