Evidence map›Paper›PMID 35087709›Full record

ArticleAnnals of global health2022

Impending Backlog of Cleft Palate Patients Due to COVID-19.

Jacob J Wood, Garrick Gu, Robert D Guber, Douglas M Rothkopf

Open access · goldAbstract read
In one paragraph

Article in Annals of global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

4 authors at 1 institution in 1 country.

Jacob J WoodDivision of Plastic Surgery, University of Massachusetts Chan Medical School, Worcester, Massachusetts, US.ORCID 0000-0001-6792-3772
Garrick GuDivision of Plastic Surgery, University of Massachusetts Chan Medical School, Worcester, Massachusetts, US.
Robert D GuberDivision of General Surgery, University of Massachusetts Chan Medical School, Worcester, Massachusetts, US.
Douglas M RothkopfDivision of Plastic Surgery, University of Massachusetts Chan Medical School, Worcester, Massachusetts, US.
University of Massachusetts Chan Medical School · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19) has placed an unprecedented strain on healthcare systems worldwide, but while high-income countries (HICs) have been able to adapt, low- and middle-income countries (LMICs) have been much slower to do so due to a lack of funding, skilled healthcare providers, equipment, and facilities. The redistribution of resources to combat the pandemic in LMICs has resulted in decreased surgical volumes at local surgical centers as well as a dramatic reduction in the number of humanitarian aid missions. Despite recent global investment in improving the surgical capacities of LMICs, even in the pre-COVID-19 era there was a vast unmet surgical need. This deficit in surgical capacity has grown during the pandemic and it will be a significant struggle to overcome the resulting backlog of patients. A topic of particular concern to the authors is the effect that the pandemic will have on the delivery of time-sensitive surgical care to patients with cleft palate deformities as delay in providing care can have enormous physical and psychosocial consequences. This paper draws increased attention to the lasting impact that the COVID-19 pandemic may have on cleft palate patients in LMICs.

Indexed as

Cleft PalateCOVID-19Developing CountriesHumansPandemicsSARS-CoV-2

Identifiers

PMID35087709
PMCPMC8782091
OpenAlexW4205447570

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.