Evidence map›Paper›PMID 32995818›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Privacy-Protecting, Reliable Response Data Discovery Using COVID-19 Patient Observations.

Jihoon Kim, Larissa Neumann, Paulina Paul, Michael Aratow, Douglas S Bell, Jason N Doctor, Ludwig C Hinske, Xiaoqian Jiang, Katherine K Kim, Michael E Matheny and 7 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Jihoon KimUC San Diego Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093, USA.
Larissa NeumannUC San Diego Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093, USA.
Paulina PaulUC San Diego Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093, USA.
Michael AratowSan Mateo Medical Center, San Mateo, CA 94403, USA.
Douglas S BellBiomedical Informatics Program, UCLA Clinical and Translational Science Institute (CTSI) Los Angeles, CA 90024, USA.
Jason N DoctorUSC Schaeffer Center for Health Policy and Economics, Price School of Policy, University of Southern California, Los Angeles, CA 90031, USA.
Ludwig C HinskeInstitute for Medical Information Processing, Biometry, and Epidemiology (IBE), Ludwig Maximilian University of Munich, Munich, Bavaria 81377, Germany.
Xiaoqian JiangSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Katherine K KimBetty Irene Moore School of Nursing, University of California, Davis, Sacramento, CA 95817, USA.
Michael E MathenyGRECC Tennessee Valley Healthcare System, Nashville, TN 37212, USA.
Daniella MeekerUSC Schaeffer Center for Health Policy and Economics, Price School of Policy, University of Southern California, Los Angeles, CA 90031, USA.
Mark J PletcherDepartment of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA 94143, USA.
Lisa M SchillingData Science and Patient Value Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
Spencer SooHooDivision of Informatics, Department of Biomedical Sciences, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA.
Hua XuSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Kai ZhengDepartment of Informatics, Donald Bren School of Information and Computer Sciences, University of California, Irvine, Irvine, CA 92697, USA.
Lucila Ohno-MachadoUC San Diego Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA 92093, USA.

Funding

University of California Health Participation in the National COVID Cohort Collaborative (N3C)UL1TR001414 · NCATS · UNIVERSITY OF CALIFORNIA-IRVINE · PI COOPER, DAN M, VILAIN, ERIC J. · 2015 to 2023
$35.1M
San Diego Biomedical Informatics Education & Research (SABER)T15LM011271 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SHAMIM NEMATI · 2012 to 2026
$9.7M
Decentralized differentially-private methods for dynamic data release and analysisR01GM118609 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JIANG, XIAOQIAN, OHNO-MACHADO, LUCILA · 2017 to 2020
$2.3M
NCATS NIH HHS UL1 TR001414NIGMS NIH HHS R01 GM118609NLM NIH HHS T15 LM011271
6 · The paper itself

Abstract

There is an urgent need to answer questions related to COVID-19's clinical course and associations with underlying conditions and health outcomes. Multi-center data are necessary to generate reliable answers, but centralizing data in a single repository is not always possible. Using a privacy-protecting strategy, we launched a public Questions & Answers web portal (https://covid19questions.org) with analyses of comorbidities, medications and laboratory tests using data from 202 hospitals (59,074 COVID-19 patients) in the USA and Germany. We find, for example, that 8.6% of hospitalizations in which the patient was not admitted to the ICU resulted in the patient returning to the hospital within seven days from discharge and that, when adjusted for age, mortality for hospitalized patients was not significantly different by gender or ethnicity.

Identifiers

PMID32995818
PMCPMC7523159

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.