Evidence map›Paper›PMID 37361287›Full record

ArticleZeitschrift fur Gesundheitswissenschaften = Journal of public health2023

Hospital admission and mortality rates for non-Covid diseases among residents of the long-term care facilities before and during the pandemic: a cohort study in two Italian regions.

Sara Mazzilli, Giuditta Scardina, Francesca Collini, Silvia Forni, Giulio Gianolio, Lucia Bisceglia, Pier Luigi Lopalco, Antonio Chieti, Graziano Onder, Nicola Vanacore and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Zeitschrift fur Gesundheitswissenschaften = Journal of public health, 2023. 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
2.2field-weighted citation impact, top 13% 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

13 authors at 6 institutions in 1 country.

Sara MazzilliScuola Normale Superiore, Pisa, Italy.
Giuditta ScardinaDepartment of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy.ORCID 0000-0001-5196-3120
Francesca ColliniQuality and Equity Unit, Regional Health Agency of Tuscany, Florence, Italy.
Silvia ForniQuality and Equity Unit, Regional Health Agency of Tuscany, Florence, Italy.
Giulio GianolioDepartment of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy.
Lucia BiscegliaStrategic Regional Health and Social Agency of Puglia (AReSS Puglia), Bari, Italy.
Pier Luigi LopalcoDepartment of Biological and Environmental Sciences and Technology, University of Salento, Lecce, Italy.
Antonio ChietiStrategic Regional Health and Social Agency of Puglia (AReSS Puglia), Bari, Italy.
Graziano OnderDepartment of Cardiovascular, Endocrine-Metabolic Diseases and Aging, National Institute of Health, Rome, Italy.
Nicola VanacoreNational Centre for Disease Prevention and Health Promotion, National Institute of Health, Rome, Italy.
Guglielmo BonaccorsiDepartment of Health Science, University of Florence, Florence, Italy.
Fabrizio GemmiQuality and Equity Unit, Regional Health Agency of Tuscany, Florence, Italy.
Lara TavoschiDepartment of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy.
University of Pisa · ITAgenzia Regionale di Sanità della Toscana · ITAgenzia Regionale Sanitaria della Puglia · ITIstituto Superiore di Sanità · ITUniversity of Florence · ITUniversity of Salento · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: Long-term-care facility residents are a vulnerable population who experienced reduced healthcare access during the pandemic. This study aimed to assess the indirect impact of the COVID-19 pandemic, in terms of hospitalisation and mortality rates, among this population in two Italian Regions, Tuscany and Apulia, during 2020 in comparison with the pre-pandemic period. Subject and methods: We conducted a retrospective cohort study on people residing in long-term-care facilities from 1 January 2018 to 31 December 2020 (baseline period: 1 January 2018-8 March 2020; pandemic period: and 9 March-31 December 2020). Hospitalisation rates were stratified by sex and major disease groups. Standardised weekly rates were estimated with a Poisson regression model. Only for Tuscany, mortality risk at 30 days after hospitalisation was calculated with the Kaplan-Meier estimator. Mortality risk ratios were calculated using Cox proportional regression models. Results: Nineteen thousand two hundred and fifty individuals spent at least 7 days in a long-term-care facility during the study period. The overall mean non-Covid hospital admission rate per 100 000 residents/week was 144.1 and 116.2 during the baseline and pandemic periods, with a decrease to 99.7 and 77.3 during the first (March-May) and second lockdown (November-December). Hospitalisation rates decreased for all major disease groups. Thirty-day mortality risk ratios for non-Covid conditions increased during the pandemic period (1.2, 1.1 to 1.4) compared with baseline. Conclusion: The pandemic resulted in worse non-COVID-related health outcomes for long-term-care facilities' residents. There is a need to prioritise these facilities in national pandemic preparedness plans and to ensure their full integration in national surveillance systems. Supplementary information: The online version contains supplementary material available at 10.1007/s10389-023-01925-1.

Indexed as

Covid-19 pandemicHospital admissionLong-term care facilitiesMortality risk

Identifiers

PMID37361287
PMCPMC10185456
OpenAlexW4376646461

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.