key: cord-0264661-3wj2wh08
authors: Moal, B.; Orieux, A.; Ferte, T.; Neuraz, A.; Brat, G. A.; Avillach, P.; Bonzel, C.-L.; Cai, T.; Cho, K.; Cossin, S.; Griffier, R.; Hanauer, D. A.; Haverkamp, C.; Ho, Y.-L.; Hong, C.; Hutch, M. R.; Klann, J. G.; Le, T. T.; Loh, N. H. W.; Luo, Y.; Makoudjou, A.; Morris, M.; Mowery, D. L.; Olsen, K. L.; Patel, L. P.; Samayamuthu, M. J.; Sanz Vidorreta, F. J.; Schriver, E. R.; Schubert, P.; Verdy, G.; Visweswaran, S.; Wang, X.; Weber, G. M.; Xia, Z.; Yuan, W.; Zhang, H. G.; Zöller, D.; Kohane, I. S.; The Consortium for Clinical Characterization of COVID-19 by EHR,; Boyer, A.; Jouhet, V.
title: Acute respiratory distress syndrome after SARS-CoV-2 infection on young adult population: international observational federated study based on electronic health records through the 4CE consortium ARDS after SARS-CoV-2 infection on young adult
date: 2022-04-03
journal: nan
DOI: 10.1101/2022.03.31.22273257
sha: a2843065b915f0e62db2fe0b617122370aa646d6
doc_id: 264661
cord_uid: 3wj2wh08

Purpose : In young adults (18 to 49 years old), investigation of the acute respiratory distress syndrome (ARDS) after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been limited. We evaluated the risk factors and outcomes of ARDS following infection with SARS-CoV-2 in a young adult population. Methods : A retrospective cohort study was conducted between January 1st, 2020 and February 28th, 2021 using patient-level electronic health records (EHR), across 241 United States hospitals and 43 European hospitals participating in the Consortium for Clinical Characterization of COVID-19 by EHR (4CE). To identify the risk factors associated with ARDS, we compared young patients with and without ARDS through a federated analysis. We further compared the outcomes between young and old patients with ARDS. Results : Among the 75,377 hospitalized patients with positive SARS-CoV-2 PCR, 1001 young adults presented with ARDS ( 7.8% of young hospitalized adults). Their mortality rate at 90 days was 16.2% and they presented with a similar complication rate for infection than older adults with ARDS. Peptic ulcer disease, paralysis, obesity, congestive heart failure, valvular disease, diabetes, chronic pulmonary disease and liver disease were associated with a higher risk of ARDS. We described a high prevalence of obesity (53%), hypertension (38%- although not significantly associated with ARDS), and diabetes (32%). Conclusion : Trough an innovative method, a large international cohort study of young adults developing ARDS after SARS-CoV-2 infection has been gather. It demonstrated the poor outcomes of this population and associated risk factor.

. CC-BY 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 3, 2022. 

. CC-BY 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 3, 2022. 128 Results : Among the 75,377 hospitalized patients with positive SARS-CoV-2 PCR, 1001 young 129 adults presented with ARDS ( 7.8% of young hospitalized adults). Their mortality rate at 90 days 130 was 16.2% and they presented with a similar complication rate for infection than older adults with 131 ARDS. Peptic ulcer disease, paralysis, obesity, congestive heart failure, valvular disease, diabetes, 132 chronic pulmonary disease and liver disease were associated with a higher risk of ARDS. We 133 described a high prevalence of obesity (53%), hypertension (38%-although not significantly 134 associated with ARDS), and diabetes (32%).

135 Conclusion : Trough an innovative method, a large international cohort study of young adults 136 developing ARDS after SARS-CoV-2 infection has been gather. It demonstrated the poor 137 outcomes of this population and associated risk factor.

. CC-BY 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. (which was not certified by peer review)

The copyright holder for this preprint this version posted April 3, 2022. 169 Through a federated analysis, the objectives were to evaluate the risk factors for developing ARDS 170 following infection with SARS-CoV-2 and hospitalization in young adults and to compare 171 characteristics, care, and outcomes between this population and an older population (greater than 172 49 years old) who similarly developed ARDS during their COVID-19 hospitalization.

. CC-BY 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. (which was not certified by peer review)

The copyright holder for this preprint this version posted April 3, 2022. [16] [17] [18] [19] [20] [21] has developed a framework to extract and standardize data directly 175 from the EHRs of participating healthcare systems (HS) and to streamline federated analyses 176 without sharing patient-level data. A common data model for structuring patient-level data was 177 adopted to enable identical analyses across all participating HS. Figure 1 presents the workflow 178 from 4CE data collection to ARDS analysis. 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 3, 2022. ; https://doi.org/10.1101/2022.03.31.22273257 doi: medRxiv preprint . CC-BY 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 3, 2022. ; https://doi.org/10.1101/2022.03.31.22273257 doi: medRxiv preprint 13 213 All patient-level data were standardized to a common format, then stored and analyzed locally at 214 each HS. Several quality controls were conducted iteratively at each HS to ensure the quality of 215 the data. . CC-BY 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 3, 2022. ; https://doi.org/10.1101/2022.03.31.22273257 doi: medRxiv preprint 14 234 Aggregate data were centrally collected, and several quality controls were executed before pooling 235 the aggregated data together. Descriptive analysis was presented e- Table 1 . CC-BY 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 3, 2022. 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 3, 2022. 

. CC-BY 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 3, 2022. . CC-BY 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 3, 2022. . CC-BY 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 3, 2022. 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 3, 2022. ; https://doi.org/10.1101/2022.03.31.22273257 doi: medRxiv preprint . CC-BY 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. 384 To identify comorbidities associated with ARDS following hospitalization with COVID, a . CC-BY 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. (which was not certified by peer review)

The copyright holder for this preprint this version posted April 3, 2022. ; https://doi.org/10.1101/2022.03.31.22273257 doi: medRxiv preprint

Acute respiratory distress syndrome (ARDS)[1], is a frequent complication after severe acute 143 respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. According to studies

ARDS has a severe impact on patient outcomes

ARDS has been 149 frequently associated with long-term disabilities[6-10] and represents a heavy care burden for 150 health systems[11] due to long ICU stays and extended rehabilitation

Age is an important risk factor for developing ARDS

18-49 years old) 152 represented a third of hospitalized patients[12] and a quarter of patients admitted to the ICU

Based on the Premier Healthcare Database

COVID-19 disease were admitted to the ICU and 10% required mechanical ventilation. Similarly, 156 in a separate cohort

have investigated the young adult population, mostly were single-center 159 analyses, all exclusively in the U.S. population and none focused on ARDS patients

Angeles determined that this study does not need IRB approval because research using limited

Across each participating HS, we included all hospitalized patients within 7 days before and up to 197 14 days after a positive PCR SARS-CoV-2 test. The first hospital admission date within this time 198 window was considered day 0 (the index date). Note that although all patients had a positive PCR 199 test near their admission date

Patient-level data were collected by HSs, which can represent one or several hospitals

Diagnoses 206 were collected from the first 3 digits of the billing code using international classification disease 207 (ICD) version 10. This 3-digit rollup was adopted to account for finer-grained differences in coding 208 practices across hospitals. Procedures related to endotracheal tube insertion or invasive mechanical 209 ventilation were collected and were denoted as severe procedures

Among those young ARDS patients only 4,3% 340 were aged between 18-and 25-years old. Patients developing ARDS in this young adult population 341 had a high prevalence of obesity (53%), hypertension (38%) and diabetes (32%)

In our analysis, comorbidities were considered 344 as those diagnoses from billing codes assigned up to one year before and up to 90 days after the 345 admission. This approach is more sensitive, but it can lead to considering complications as analysis on the sub population who had previous hospital visits and considering only 350 the ICD code related to those previous visits as comorbidities (one year and -14 days before the 351 admission)

Appendix 2); but a common co-occurrence is reduced lung capacity which could contribute to its 358 association with ARDS. The association with peptic ulcer as comorbidities remains unclear and 359 requires additional investigations

Compared to the other groups, 391 SEVERE_NO_ARDS population had the higher percentage of women (52.2%) and of patients 392 with previous contact with the healthcare system (72%). In addition, 15.1% of those patients had 393 a billing code associated with pregnancy and 36.1% with long-term drug therapy

ARDS development was associated with peptic ulcer disease, paralysis, 403 obesity, congestive heart failure, valvular disease, diabetes, chronic pulmonary disease, and liver 404 disease

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What's Next After ARDS: Long-Term 437

Acute 439 Management and Long-Term Survival Among Subjects With Severe Middle East 440 Respiratory Syndrome Coronavirus Pneumonia and ARDS

Long-term outcome after the acute respiratory 442 distress syndrome: different from general critical illness? Respir Syst

Economics of Mechanical Ventilation and Respiratory Failure

Characteristics of Adults aged 18-49 Years without Underlying Conditions Hospitalized 447 with Laboratory-Confirmed COVID-19 in the United States, COVID-NET

Risk factors for severity of COVID-453 19 in hospital patients age 18-29 years

Characteristics, comorbidities and survival analysis of young adults hospitalized with 456 COVID-19 in

The copyright holder for this preprint this version posted April 3, 2022. 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 3, 2022. . CC-BY 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 3, 2022. ; https://doi.org/10.1101/2022.03.31.22273257 doi: medRxiv preprint . CC-BY 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 3, 2022. 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 3, 2022. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)The copyright holder for this preprint this version posted April 3, 2022. ; https://doi.org/10.1101/2022.03.31.22273257 doi: medRxiv preprint