Evidence map›Paper›PMID 38302061›Full record

SynthesisThe Journal of infection2024

Disparities in COVID-19 mortality amongst the immunosuppressed: A systematic review and meta-analysis for enhanced disease surveillance.

Meredith Leston, Willam Elson, Jose M Ordóñez-Mena, Debasish Kar, Heather Whitaker, Mark Joy, Nia Roberts, F D Richard Hobbs, Simon de Lusignan

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in The Journal of infection, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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  20. Persistent COVID-19 Pneumonia in a Patient on Rituximab.Journal of investigative medicine high impact case reports
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Meredith LestonNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, United Kingdom. Electronic address: meredith.leston@phc.ox.ac.uk.
Willam ElsonNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, United Kingdom.
Jose M Ordóñez-MenaNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, United Kingdom.
Debasish KarNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, United Kingdom.
Heather WhitakerImmunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, 61 Colindale Avenue, London NW9 5EQ, United Kingdom.
Mark JoyNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, United Kingdom.
Nia RobertsBodleian Health Care Libraries, University of Oxford, Old Campus Road, Old Campus Research Building, Headington, Oxford OX3 7DQ, United Kingdom.
F D Richard HobbsNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, United Kingdom.
Simon de LusignanNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, United Kingdom.

Funding

Medical Research Council
6 · The paper itself

Abstract

backgroundEffective disease surveillance, including that for COVID-19, is compromised without a standardised method for categorising the immunosuppressed as a clinical risk group.

methodsWe conducted a systematic review and meta-analysis to evaluate whether excess COVID-associated mortality compared to the immunocompetent could meaningfully subdivide the immunosuppressed. Our study adhered to UK Immunisation against infectious disease (Green Book) criteria for defining and categorising immunosuppression. Using OVID (EMBASE, MEDLINE, Transplant Library, and Global Health), PubMed, and Google Scholar, we examined relevant literature between the entirety of 2020 and 2022. We selected for cohort studies that provided mortality data for immunosuppressed subgroups and immunocompetent comparators. Meta-analyses, grey literature and any original works that failed to provide comparator data or reported all-cause or paediatric outcomes were excluded. Odds Ratios (OR) and 95% confidence intervals (CI) of COVID-19 mortality were meta-analysed by immunosuppressed category and subcategory. Subgroup analyses differentiated estimates by effect measure, country income, study setting, level of adjustment, use of matching and publication year. Study screening, extraction and bias assessment were performed blinded and independently by two researchers; conflicts were resolved with the oversight of a third researcher. PROSPERO registration number is CRD42022360755.

findingsWe identified 99 unique studies, incorporating data from 1,542,097 and 56,248,181 unique immunosuppressed and immunocompetent patients with COVID-19 infection, respectively. Compared to immunocompetent people (pooled OR, 95%CI), solid organ transplants (2.12, 1.50-2.99) and malignancy (2.02, 1.69-2.42) patients had a very high risk of COVID-19 mortality. Patients with rheumatological conditions (1.28, 1.13-1.45) and HIV (1.20, 1.05-1.36) had just slightly higher risks than the immunocompetent baseline. Case type, setting income and mortality data matching and adjustment were significant modifiers of excess immunosuppressed mortality for some immunosuppressed subgroups.

interpretationExcess COVID-associated mortality among the immunosuppressed compared to the immunocompetent was seen to vary significantly across subgroups. This novel means of subdivision has prospective benefit for targeting patient triage, shielding and vaccination policies during periods of high disease transmission.

Indexed as

COVID-19Immunocompromised HostSARS-CoV-2HumansCovidCOVID-19Digital healthDisease surveillanceImmunocompromisedImmunosuppressedPandemic preparednessPersonalised medicineVaccinationVaccines

Identifiers

PMID38302061
PMCPMC10943183

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.