Evidence map›Paper›PMID 37377787›Full record

SynthesisPeerJ2023

Paediatric hospitalizations over three waves of COVID-19 (February 2020 to May 2021) in Italy: determinants and rates.

Manuela Martella, Alberto Peano, Gianfranco Politano, Roberta Onorati, Maria Michela Gianino

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 21% 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

5 citing papers in PubMed, 4 citations in OpenAlex.

  1. Disease severity among hospitalized children during the COVID-19 pandemic in Israel.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
    Article
  2. Observational
  3. Economic Burden of COVID-19 Hospitalization in Almaty, Kazakhstan.ClinicoEconomics and outcomes research : CEOR · 2026
    Article
  4. Article
  5. 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

5 authors at 1 institution in 1 country.

Manuela MartellaDepartment of Public Health Sciences and Pediatrics, University of Turin, Turin, Piedmont, Italy.ORCID 0000-0002-4269-6902
Alberto PeanoDepartment of Public Health Sciences and Pediatrics, University of Turin, Turin, Piedmont, Italy.ORCID 0000-0002-7673-7522
Gianfranco PolitanoDepartment of Control and Computer Engineering, University of Turin, Turin, Piedmont, Italy.ORCID 0000-0001-5268-9899
Roberta OnoratiEpidemiology Unit, Local Health Authority TO3, Grugliasco (Turin), Piedmont, Italy.
Maria Michela GianinoDepartment of Public Health Sciences and Pediatrics, University of Turin, Turin, Piedmont, Italy.
University of Turin · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: After a pneumonia outbreak in late 2019 in China, a new virus related to the Coronaviridae strain, called Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2), was identified as the pathogen of an emerging disease known as COronaVIrus Disease 19 (COVID-19). Preliminary evidence outlines a higher prevalence in adults and lower susceptibility in children. However, recent epidemiologic research highlighted that transmissibility and susceptibility among children and adolescents become higher due to new virus variants. Infections among youth arises with mainly respiratory and gastrointestinal symptoms and malaise. Nevertheless, critical illness affects new-borns and fragile children, requiring hospitalization and possibly intensive care support. Aim of this study was to examine the impact of COVID-19 pandemic on hospital admissions among children and adolescents aged 0 to 17 years over three waves of COVID-19 (from February 2020 to May 2021) in Piedmont, a large Italian region, and to investigate the possible determinants of hospitalizations. Methods: A meta-analysis for risk assessment was performed over three waves of COVID-19 (from February 2020 to May 2021). Data were extracted from the official Italian National Information System and ISTAT. Results: Overall, 442 paediatric patients were enrolled and admissions concerned mostly the age group 0-4 years (60.2%). Trends of hospitalization showed a slight increase of paediatric admissions already in March 2020 and a rise during second and third waves (November 2020, March 2021). Paediatric age-grouped hospitalizations (0-4; 12-17; 5-11) reproduced an analogous trend. The children and adolescent hospitalization rate appeared lower than overall population with a moderate slope of increase in comparison with population slope. Monthly hospitalization rate (per 100,000) of children and adolescents aged 0-17 years reproduced the increasing trend of hospitalization numbers. This trend was influenced, in particular, by the trend of hospitalization rates for children aged 0-4 years. The meta-analysis for risk assessment showed a decreased likelihood of rescue of hospitalizations in female, 5-11 and 12-17 age groups. Conversely, the meta-analysis showed a positive association between foreign nationality and hospitalizations. Conclusions: Our results show a comparable trend of paediatric hospital admissions for COVID-19 and of the entire population hospitalizations over three waves. COVID-19 hospital admissions increase with a bimodal age distribution and the most admissions are among patients aged ≤4 or 5-11 years. Significant predictive factors of hospitalization are identified.

Indexed as

COVID-19AdolescentAdultChildFemaleHospitalizationHumansItalyPandemicsSARS-CoV-2AdolescentChildrenCOVID-19DeterminantsHospitalization

Identifiers

PMID37377787
PMCPMC10292193
OpenAlexW4381741032

What OpenQuestion holds

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LicenceCC BY
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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.