Evidence map›Paper›PMID 36966161›Full record

ArticleScientific reports2023

A prospective cohort study assessing the relationship between long-COVID symptom incidence in COVID-19 patients and COVID-19 vaccination.

Bayan Abu Hamdh, Zaher Nazzal

Open access · goldFull text read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 3 pooled it
7.0field-weighted citation impact, top 2% 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

23 citing papers in PubMed, 3 syntheses or guidelines pooled it, 34 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Bayan Abu HamdhDepartment of Public Health, Faculty of Graduate Studies, An-Najah National University, Nablus, Palestine.
Zaher NazzalDepartment of Medicine, Faculty of Medicine and Health Sciences, An-Najah National University, Box 7707, Nablus, Palestine. znazzal@najah.edu.ORCID 0000-0002-2655-6109
An-Najah National University · PS

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current studies about the long-term effects of COVID-19 show a wide range of symptoms. This prospective cohort study aimed to find the incidence of long-COVID symptoms and the associated risk factors. We followed 669 confirmed COVID-19 patients. Sociodemographic and clinical data were extracted from medical records and collected via semi-structured telephone interviews on days 10, 30, 60, and 90. The incidence of long-COVID symptoms was 41.6% (95% CI 37.8-45.4%). Females [aOR = 1.5 (95% CI 1.1-2.3)], the elderly [aOR = 4.9 (95% CI 2.0-11.3)], and those who required hospitalization [aOR = 5.0 (95% CI 1.3-3.7)] were at a higher risk of developing long-COVID. Patients with dyspnea at day 10 [aOR: 2.4 (95% CI 1.6-3.7] and fatigue at day 60 [aOR: 3.1 (95% CI 1.5-6.3] were also at risk. While non-vaccinated patients were almost seven times more likely to report long-COVID symptoms than vaccinated patients [aOR: 6.9 (95% CI 4.2-11.3)]. In conclusion, long-COVID was common among COVID-19 patients, with higher rates among females, older age groups, hospitalized patients, and those with dyspnea and fatigue, while vaccination provided protection. Interventions should educate health professionals, raise general public awareness about the risks and consequences of Long COVID, and the value of vaccination.

Indexed as

COVID-19Post-Acute COVID-19 SyndromeAgedCOVID-19 VaccinesDyspneaFatigueFemaleHumansIncidenceProspective StudiesVaccinationCOVID-19 Vaccines

Identifiers

PMID36966161
PMCPMC10039348
OpenAlexW4360945124

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read185
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.