Evidence map›Paper›PMID 35404963›Full record

Observational studyPloS one2022

Mortality rates among COVID-19 patients hospitalised during the first three waves of the epidemic in Milan, Italy: A prospective observational study.

Andrea Giacomelli, Anna Lisa Ridolfo, Laura Pezzati, Letizia Oreni, Giorgia Carrozzo, Martina Beltrami, Andrea Poloni, Beatrice Caloni, Samuel Lazzarin, Martina Colombo and 11 more

Abstract readObservational Study
In one paragraph

Observational study in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
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

22 citing papers in PubMed.

  1. Article
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  3. Management of patients hospitalized for SARS-CoV-2 infection: A real-world economic evaluation from the hospital perspective.American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists · 2026
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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

21 authors.

Andrea GiacomelliInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.ORCID 0000-0003-3685-4289
Anna Lisa RidolfoInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Laura PezzatiInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Letizia OreniInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Giorgia CarrozzoInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Martina BeltramiInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Andrea PoloniInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Beatrice CaloniInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Samuel LazzarinInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Martina ColomboInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Giacomo PozzaInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Simone PaganoInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Stefania CaronniInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Chiara FusettiInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Martina GerbiInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Francesco PetriInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Fabio BorgonovoInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Fabiana D'AloiaDepartment of Biomedical and Clinical Sciences, University of Milan, Milan, Italy.
Cristina NegriInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Giuliano RizzardiniInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.
Spinello AntinoriInfectious Diseases Department, ASST Fatebenefratelli Sacco, Ospedale Luigi Sacco, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThis paper describes how mortality among hospitalised COVID-19 patients changed during the first three waves of the epidemic in Italy.

methodsThis prospective cohort study used the Kaplan-Meier method to analyse the time-dependent probability of death of all of the patients admitted to a COVID-19 referral centre in Milan, Italy, during the three consecutive periods of: 21 February-31 July 2020 (first wave, W1), 1 August 2020-31 January 2021 (second wave, W2), and 1 February-30 April 2021 (third wave, W3). Cox models were used to examine the association between death and the period of admission after adjusting for age, biological sex, the time from symptom onset to admission, disease severity upon admission, obesity, and the comorbidity burden.

resultsOf the 2,023 COVID-19 patients admitted to our hospital during the study period, 553 (27.3%) were admitted during W1, 838 (41.5%) during W2, and 632 (31.2%) during W3. The crude mortality rate during W1, W2 and W3 was respectively 21.3%, 23.7% and 15.8%. After adjusting for potential confounders, hospitalisation during W2 or W3 was independently associated with a significantly lower risk of death than hospitalisation during W1 (adjusted hazard ratios [AHRs]: 0.75, 95% confidence interval [CI] 0.59-0.95, and 0.58, 95% CI 0.44-0.77). Among the patients aged >75 years, there was no significant difference in the probability of death during the three waves (AHRs during W2 and W3 vs W1: 0.93, 95% CI 0.65-1.33, and 0.88, 95% CI 0.59-1.32), whereas those presenting with critical disease during W2 and W3 were at significantly lower risk of dying than those admitted during W1 (AHRs 0.61, 95% CI 0.43-0.88, and 0.44, 95% CI 0.28-0.70).

conclusionsHospitalisation during W2 and W3 was associated with a reduced risk of COVID-19 death in comparison with W1, but there was no difference in survival probability in patients aged >75 years.

Indexed as

COVID-19EpidemicsComorbidityHospitalizationHumansProspective Studies

Identifiers

PMID35404963
PMCPMC9000097

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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.