Evidence map›Paper›PMID 32899534›Full record

ArticleInternational journal of environmental research and public health2020

Applying the WHO ICF Framework to the Outcome Measures Used in the Evaluation of Long-Term Clinical Outcomes in Coronavirus Outbreaks.

Kajal Patel, Sofia Straudi, Ng Yee Sien, Nora Fayed, John L Melvin, Manoj Sivan

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 5% 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

33 citing papers in PubMed, 1 synthesis or guideline pooled it, 57 citations in OpenAlex.

  1. Guideline
  2. Article
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  5. Article
  6. Review
  7. Observational
  8. Article
  9. Article
  10. Applying the WHO ICF framework to long COVID patients with persistent respiratory symptoms.Turkish journal of physical medicine and rehabilitation · 2023
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
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  19. Article
  20. Self-Assessed Aspects of Health 3 Months after COVID-19 Hospitalization-A Swedish Cross-Sectional Study.International journal of environmental research and public health · 2022
    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

6 authors at 6 institutions in 5 countries.

Kajal PatelSchool of Medicine, University of Manchester, Manchester M13 9PG, UK.ORCID 0000-0002-2756-0839
Sofia StraudiNeuroscience and Rehabilitation Department, Ferrara University Hospital, 44100 Ferrara, Italy.
Ng Yee SienDepartment of Rehabilitation Medicine, Singapore General Hospital, Outram Road, Singapore 169608, Singapore.
Nora FayedSchool of Rehabilitation Therapy, Queen's University, Louise D. Acton Building, 31 George Street, Kingston, ON K7L 3N6, Canada.
John L MelvinDepartment of Rehabilitation Medicine, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA 19144, USA.ORCID 0000-0002-8401-9248
Manoj SivanDivision of Neurosciences and Experimental Psychology, University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0002-0334-2968
Queen's University · CASingapore General Hospital · SGThomas Jefferson University · USUniversity of Ferrara · ITUniversity of Leeds · GBUniversity of Manchester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

(1) Objective: The World Health Organization's (WHO) International Classification of Functioning, Disability and Health (ICF) classification is a unified framework for the description of health and health-related states. This study aimed to use the ICF framework to classify outcome measures used in follow-up studies of coronavirus outbreaks and make recommendations for future studies. (2) Methods: EMBASE, MEDLINE, CINAHL and PsycINFO were systematically searched for original studies assessing clinical outcomes in adult survivors of severe acute respiratory distress syndrome (SARS), middle east respiratory syndrome (MERS) and coronavirus disease-19 (COVID-19) after hospital discharge. Individual items of the identified outcome measures were linked to ICF second-level and third-level categories using ICF linking rules and categorized according to an ICF component. (3) Results: In total, 33 outcome measures were identified from 36 studies. Commonly used (a) ICF body function measures were Pulmonary Function Tests (PFT), Impact of event scale (IES-R) and Hospital Anxiety and Depression Scale (HADS); (b) ICF activity was 6-Minute Walking Distance (6MWD); (c) ICF participation measures included Short Form-36 (SF-36) and St George's Respiratory Questionnaire (SGRQ). ICF environmental factors and personal factors were rarely measured. (4) Conclusions: We recommend future COVID-19 follow-up studies to use the ICF framework to select a combination of outcome measures that capture all the components for a better understanding of the impact on survivors and planning interventions to maximize functional return.

Indexed as

Patient Outcome AssessmentActivities of Daily LivingAdultBetacoronavirusCoronavirus InfectionsCOVID-19Disability EvaluationHumansInternational Classification of Functioning, Disability and HealthMiddle East Respiratory Syndrome CoronavirusPandemicsPneumonia, ViralSARS-CoV-2Severe Acute Respiratory SyndromeSevere acute respiratory syndrome-related coronavirusWorld Health OrganizationCOVID-19exercise tolerancefollow-up studieslung functionmental healthMERSoutcome measuresprevalencequality of lifeSARS

Identifiers

PMID32899534
PMCPMC7558385
OpenAlexW3083047554

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.