Evidence map›Paper›PMID 34037838›Full record

Observational studyEuropean journal of pediatrics2021

Using ICD-10 diagnostic codes to identify 'missing' paediatric patients during nationwide COVID-19 lockdown in Oxfordshire, UK.

James E G Charlesworth, Rhian Bold, Rani Pal

Open access · bronzeAbstract readObservational Study
In one paragraph

Observational study in European journal of pediatrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Effects of Relaxed Lockdown on Pediatric ER Visits during SARS-CoV-2 Pandemic in Italy.International journal of environmental research and public health · 2021
    Article
  7. Article
  8. Review
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

3 authors at 1 institution in 1 country.

James E G CharlesworthOxford University Hospitals NHS Foundation Trust (John Radcliffe and Horton Hospitals), Oxfordshire, UK. James.charlesworth@doctors.org.uk.ORCID http://orcid.org/0000-0001-9859-7383
Rhian BoldOxford University Hospitals NHS Foundation Trust (John Radcliffe and Horton Hospitals), Oxfordshire, UK.
Rani PalOxford University Hospitals NHS Foundation Trust (John Radcliffe and Horton Hospitals), Oxfordshire, UK.
Horton General Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study aims to identify 'missing' diagnoses amongst paediatric admissions during the UK's first national lockdown, compared with the previous 5 years. A retrospective observational cohort study of all children (0-15 years) attending for urgent care across Oxfordshire, during the first UK lockdown in 2020, compared to matched dates in 2015-2019, across two paediatric hospitals providing secondary care, including one with tertiary services. Our outcome measures were changes in numbers of patients attending and inpatient diagnoses (using ICD-10 classification) during the first 2020 lockdown, compared with the previous 5 years, were used. We found that total Emergency Department (ED) attendances (n = 4030) and hospital admissions (n = 1416) during the first UK lockdown were reduced by 56.8% and 59.4%, respectively, compared to 2015-2019 (5-year means n = 7446.8 and n = 2491.6, respectively). Proportions of patients admitted from ED and length of stay were similar across 2015-2020. ICD-10 diagnoses in lockdown of 2020 (n = 2843) versus matched 2015-2019 dates (n = 19,946) demonstrated significantly greater neoplasm diagnoses (p = 0.0123). Of diagnoses 'missing' in lockdown, 80% were categorised as infectious diseases or their sequelae and 20% were non-specific pains/aches/malaise and accidental injury/poisonings.Conclusions: Pandemic public health measures significantly altered paediatric presentations. Oxfordshire hospitals had a 58% reduction in ED attendances/inpatient admissions, with 'missing' diagnoses predominantly infection-related illnesses. These are likely driven by a combination of the following: (1) public health infection control measures successfully reducing disease transmission, (2) parents/carers keeping mild/self-limiting disease at home, and (3) pandemic-related healthcare anxieties. Prospective studies are needed to ensure referral pathways identify vulnerable children, those with social concerns, and avoid delayed presentation. What is Known: • Significant reductions of paediatric ED attendances and inpatient admissions are reported globally, throughout national and regional lockdowns for COVID-19. • Previous studies (supplemental table 5) examined only ED diagnoses or specific inpatient diagnoses during lockdown periods, demonstrating reductions of infectious diseases, accidents/injuries, and safeguarding referrals. What is New: • Using ICD-10 coding, robustly controlling for five historical years and adopting a hypothesis-independent analysis, demonstrating 80% of 'missing' inpatient diagnoses during national COVID-19 lockdown were infectious diseases or its sequelae, the remainder being non-specific aches/pains/malaise and accidental injuries/poisonings. • Greater numbers of neoplasms and other specific diagnoses were detected during lockdown, including greater documentation of co-morbidities and incidental findings.

Indexed as

COVID-19ChildEmergency Service, HospitalHumansInfection ControlInternational Classification of DiseasesRetrospective StudiesSARS-CoV-2United KingdomCOVID-19ICD-10LockdownMissing patientsPaediatric admissions

Identifiers

PMID34037838
PMCPMC8150620
OpenAlexW3136121810

What OpenQuestion holds

Textmetadata
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.