Evidence map›Paper›PMID 36414624›Full record

ArticleTranslational psychiatry2022

Trends in psychiatric diagnoses by COVID-19 infection and hospitalization among patients with and without recent clinical psychiatric diagnoses in New York city from March 2020 to August 2021.

Yunyu Xiao, Mohit M Sharma, Rohith K Thiruvalluru, Catherine Gimbrone, Myrna M Weissman, Mark Olfson, Katherine M Keyes, Jyotishman Pathak

Open access · goldAbstract read
In one paragraph

Article in Translational psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 11% of its field
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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Yunyu XiaoDepartment of Population Health Sciences, Weill Cornell Medicine, NewYork-Presbyterian, New York, NY, USA. yux4008@med.cornell.edu.ORCID 0000-0002-0479-1781
Mohit M SharmaDepartment of Population Health Sciences, Weill Cornell Medicine, NewYork-Presbyterian, New York, NY, USA.
Rohith K ThiruvalluruDepartment of Population Health Sciences, Weill Cornell Medicine, NewYork-Presbyterian, New York, NY, USA.ORCID 0000-0002-9229-8574
Catherine GimbroneDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
Myrna M WeissmanDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.ORCID 0000-0003-3490-3075
Mark OlfsonDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
Katherine M KeyesDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
Jyotishman PathakDepartment of Population Health Sciences, Weill Cornell Medicine, NewYork-Presbyterian, New York, NY, USA.ORCID 0000-0002-4856-410X
Cornell University · USColumbia University · USColumbia University Irving Medical Center · USNew York Psychoanalytic Society and Institute · US

Funding

Linking VA and non-VA data to study the risk of suicide in chronic pain patients.R01MH121907 · NIMH · WEILL MEDICAL COLL OF CORNELL UNIV · PI OSLIN, DAVID W., PATHAK, JYOTISHMAN · 2020 to 2024
$3.6M
Using claims data to study the association between Alzheimer's disease and suicidal behaviorsR01MH119177 · NIMH · WEILL MEDICAL COLL OF CORNELL UNIV · PI PATHAK, JYOTISHMAN · 2019 to 2022
$3.3M
4/4: Leveraging EHR-linked biobanks for deep phenotyping, polygenic risk score modeling, and outcomes analysis in psychiatric disordersR01MH121922 · NIMH · WEILL MEDICAL COLL OF CORNELL UNIV · PI PATHAK, JYOTISHMAN · 2019 to 2023
$2.0M
City Tech-WCM Big Data Training Program in Biomedical InformaticsR25MD011713 · NIMHD · NEW YORK CITY COLLEGE OF TECHNOLOGY · PI GIANNOPOULOU, EVGENIA, PATHAK, JYOTISHMAN · 2017 to 2020
$1.1M
NIMHD NIH HHS R25 MD011713NIMH NIH HHS R01 MH119177NIMH NIH HHS R01 MH121907NIMH NIH HHS R01 MH121922
6 · The paper itself

Abstract

Determining emerging trends of clinical psychiatric diagnoses among patients infected with the SARS-CoV-2 virus is important to understand post-acute sequelae of SARS-CoV-2 infection or long COVID. However, published reports accounting for pre-COVID psychiatric diagnoses have usually relied on self-report rather than clinical diagnoses. Using electronic health records (EHRs) among 2,358,318 patients from the New York City (NYC) metropolitan region, this time series study examined changes in clinical psychiatric diagnoses between March 2020 and August 2021 with month as the unit of analysis. We compared trends in patients with and without recent pre-COVID clinical psychiatric diagnoses noted in the EHRs up to 3 years before the first COVID-19 test. Patients with recent clinical psychiatric diagnoses, as compared to those without, had more subsequent anxiety disorders, mood disorders, and psychosis throughout the study period. Substance use disorders were greater between March and August 2020 among patients without any recent clinical psychiatric diagnoses than those with. COVID-19 positive patients (both hospitalized and non-hospitalized) had greater post-COVID psychiatric diagnoses than COVID-19 negative patients. Among patients with recent clinical psychiatric diagnoses, psychiatric diagnoses have decreased since January 2021, regardless of COVID-19 infection/hospitalization. However, among patients without recent clinical psychiatric diagnoses, new anxiety disorders, mood disorders, and psychosis diagnoses increased between February and August 2021 among all patients (COVID-19 positive and negative). The greatest increases were anxiety disorders (378.7%) and mood disorders (269.0%) among COVID-19 positive non-hospitalized patients. New clinical psychosis diagnoses increased by 242.5% among COVID-19 negative patients. This study is the first to delineate the impact of COVID-19 on different clinical psychiatric diagnoses by pre-COVID psychiatric diagnoses and COVID-19 infections and hospitalizations across NYC, one of the hardest-hit US cities in the early pandemic. Our findings suggest the need for tailoring treatment and policies to meet the needs of individuals with pre-COVID psychiatric diagnoses.

Indexed as

COVID-19HospitalizationHumansNew York CityPost-Acute COVID-19 SyndromeSARS-CoV-2

Identifiers

PMID36414624
PMCPMC9681844
OpenAlexW4309650718

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.