key: cord-1007286-cv5c3df0 authors: Singh, S.; Chowdhry, M.; Chatterjee, A.; Khan, A. title: Gender-Based Disparities in COVID-19: Clinical Characteristics and Propensity-matched Analysis of Outcomes date: 2020-04-29 journal: nan DOI: 10.1101/2020.04.24.20079046 sha: 84a25a27acc6693176eebc9a3b245d1eabf7b771 doc_id: 1007286 cord_uid: cv5c3df0 Importance COVID-19 epidemiological data show higher mortality rates among males compared to females. However, it remains unclear if the disparity in mortality is due to gender differences in high-risk characteristics. Objective To study the clinical characteristics of a large and diverse cohort of COVID-19 patients stratified by gender and determine the outcomes after matching for age and other high-risk characteristics. Design Retrospective cohort between January 20, 2020, and April 15, 2020 Setting TriNetX COVID-19 Research Network consisting of multiple healthcare organizations (HCOs) predominantly in the United States Participants and Exposure A cohort of male and female patients > 10 years of age diagnosed with COVID-19 identified with real-time analyses of electronic medical records of patients from participating HCOs. A 1:1 propensity score matching of cohorts was performed for age, race, nicotine use, and all possible confounding comorbidities. Main Outcome Risk of mortality, hospitalization and mechanical ventilation within 30 days after the diagnosis of COVID-19 Results A total of 5980 males and 7730 females diagnosed with COVID-19 were identified. Males were significantly older than females (54.9 (18.3) vs. 50.9 (18.4), p-value <0.0001). There were significant differences in patient characteristics, but after propensity matching, both groups (N=5350 each group) were balanced. Males had a significantly higher risk for mortality both before (Risk Ratio (RR) 2.1, 95% CI 1.8-2.4) and after matching (RR 1.4, 95% CI 1.2-1.7). Similarly, the risk of hospitalization (RR 1.3, 95%CI 1.2-1.4) and mechanical ventilation (RR 1.71, 95% CI 1.3-2.3) was significantly higher in males even after matching. On subanalysis, males age > 50 had higher mortality than matched females of similar age (RR 1.6, 95% CI 1.4-1.8), whereas the risk of mortality in matched groups < 40 years was similar (RR 1.00, 95% CI 0.4-2.4). Conclusion In conclusion, males are more severely affected and have higher mortality from COVID-19. This gender-specific risk is especially more pronounced in advanced age. Gender disparity in poor outcomes can only be partially explained by differences in high-risk behavior and comorbidities. Further research is needed to understand the causes of this disparity. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. . It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. . A l l s t a t i s t i c a l a n a l y s e s w e r e p e r f o r m e d i n r e a l -t i m e u s i n g T r i N e t X . T r i N e t X o b f u s c a t e s p a t i e n t c o u n t s t o s a f e g u a r d p r o t e c t e d h e a l t h is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. e r v e d h i g h e r l e v e l s o f s e r u m c r e a t i n i n e , l i v e r f u n c t i o n t e s t s , a n d i n f l a m m a t o r y m a r k e r s l i k e f e r r i t i n , C R P , a n d I L -6 i n m a l . It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. . G e n d e r d i f f e r e n c e s i n a s y m p t o m a t i c o r m i l d c a s e s o f C O V I D -1 9 t h a t r e m a i n u n d i a g n o s e d o r d i d n o t s e e k m e d i c a l c a r e w e r e n o t a c c o u n t e d f o is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. h t t p s : is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. F i g u r e 1 : K a p l a n -M e i e r s u r v i v a l c u r v e s e s t i m a t i n g t h e s u r v i v a l p r o b a b i l i t y f o r o u t c o m e s u p t o 3 0 d a y s a f t e r d i a g n o s i s o f C O V I D -1 is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. . T a b l e 2 : O u t c o m e s a m o n g C O V I D -1 9 m a l e a n d f e m a l e p a t i e n t s . O u t c o m e s a r e c o m p a r e d b e f o r e a n d a f t e r p r o p e n s i t y s c o r e m a t c h i n g o f c o h o r t s . is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. TriNetX cloud-based features allow real-time access to the de-identified longitudinal clinical data along with the analytics to analyze complex research questions. The de-identified clinical data such as diagnoses, procedures, medications, laboratory values, and genomic information are aggregated directly from the electronic medical records (EMR) systems of the participating HCOs continuously. Both the patients and HCO's as data sources stay anonymous. Participating HCO's include a mix of inpatient, outpatient, and specialty care services and provide care to a diverse patient population from different age groups, ethnicity, income levels, and geographical region. As a federated network, TriNetX received a waiver from Western IRB since only aggregated counts, statistical summaries of de-identified information, but no protected health information is received, and no study-specific activities are performed in retrospective analyses. The search was conducted following the criteria provided by the TriNETX to identify potential COVID-19 patients as per the CDC COVID-19 coding guidelines. We used the search query provided by the TriNetX network to identify COVID-19 patients for our study to build patient cohorts. These codes included International Classification of Diseases, Ninth Revision and tenth Revision, Clinical Modification (ICD-10-CM) codes U07.1 (COVID-19, virus identified), B34.2 (Coronavirus infection, unspecified), B97.29 (Other coronavirus as the cause of diseases classified elsewhere) and J12.81 (Pneumonia due to SARS-associated coronavirus). Patients identified with diagnosis code 079.89 (Other specified viral infection) were excluded. Only patients diagnosed with the codes, as mentioned earlier between January 20, 2020 (first confirmed case in the USA) to April 15, 2020, were included. The B97.29 code was specifically included based on the recommendation from the general guidance of the ICD-10-CM Official Coding Guidelines released by the CDC on February 20, 2020. Similarly, U07.1 is the new specific code for a confirmed diagnosis of the COVID-19 with a positive COVID-19 test result starting April 1, 2020, as per the new CDC guidelines. The codes B34.2 and J12.81 were used more often before the CDC guidelines. Patients with ICD-9 code 079.89 (mapped to ICD-10 code B34.2 and B97.2) were excluded to reduce any false positive COVID-19 patients because this ICD-9 code can still be used occasionally as "catch-all' code for more than 50 viral infections. Patient age, race, comorbid conditions, signs and symptoms, laboratory data, medications, and hospitalization related data were recorded for both male and female cohort of COVID-19 patients. The diagnosis of COVID-19 was defined as the index event. Patient comorbidities were estimated based on diagnosis . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. reported at the index event or any time before the index event. The patient presenting signs and symptoms were estimated at the time of the index event or up to 14 days before the index event. The time window to estimate all outcomes was up to 30 days from the day of COVID-19 diagnosis. The primary outcome was the risk of mortality, mechanical ventilation, and hospitalization. Other outcomes also included laboratory data and medications specific to COVID-19 treatment. All statistical analyses were performed in real-time using TriNetX. The means, standard deviations, and proportions of clinical facts were used to describe and compare patient characteristics. The 1:1 propensity score matching was performed using a greedy nearest-neighbor matching algorithm with a caliper of 0.1 pooled standard deviations to account for confounding variables. For each outcome, the risk difference and risk ratio were calculated to compare the association of the gender with the outcome. Kaplan-Meier survival analyses to estimate the survival probability of each outcome at the end 30 days after diagnosis of COVID-19. Patients were censored when the time window ended or on the day after the last fact in their record. Hypothesis testing for Kaplan-Meier survival curves was conducted using the log-rank test for each outcome with an a-priori defined two-sided alpha of less than <0.05 for statistical significance. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. . It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 29, 2020. Anxiety, stress-related 63% (3.10%, 6.16%)