Evidence map›Paper›PMID 35639022›Full record

ArticleAnnals of the Royal College of Surgeons of England2023

The reorganisation of emergency general surgery services during the COVID-19 pandemic in the UK: outcomes of delayed presentation, socio-economic deprivation and Black, Asian and Minority Ethnic patients.

A Chan, P Stathakis, P Goldsmith, S Smith, C Macutkiewicz

Abstract read
In one paragraph

Article in Annals of the Royal College of Surgeons of England, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

5 authors.

A ChanManchester University NHS Foundation Trust, UK.
P StathakisManchester University NHS Foundation Trust, UK.
P GoldsmithManchester University NHS Foundation Trust, UK.
S SmithManchester University NHS Foundation Trust, UK.
C MacutkiewiczManchester University NHS Foundation Trust, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe COVID-19 pandemic is a global public health emergency. Lockdown restrictions and the reconfiguration of healthcare systems to accommodate an increase in critical care capacity have had an impact on 'non-COVID' specialties. This study characterises the utilisation of emergency general surgery (EGS) services during the UK lockdown period at a university teaching hospital with a catchment population that represents one of the most deprived and ethnically diverse areas in the UK.

methodsEGS admissions during the UK lockdown period (March to May 2020) were compared with the same period in 2019. Patient demographics were recorded together with clinical presentation, hospital stay and treatment outcomes, and readmission data.

resultsThe study included 645 patients, comprising 223 in the COVID-19 period and 422 in the non-COVID-19 period. There was no difference in age, sex, comorbidity or socio-economic status. A lower proportion of patients of Black, Asian and Minority Ethnicity (BAME) were admitted during the pandemic (20.6% vs 35.4%,

conclusionsThe reorganisation of EGS to a senior-led model has been successful in terms of outcomes and access to treatment despite a more unwell population. There was a significantly lower proportion of BAME admissions suggesting additional barriers to healthcare access under pandemic lockdown conditions.

Indexed as

COVID-19Communicable Disease ControlHumansPandemicsSocioeconomic FactorsUnited KingdomBAMECOVID-19EmergenciesGeneral surgery

Identifiers

PMID35639022
PMCPMC10390243

What OpenQuestion holds

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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.