Evidence map›Paper›PMID 33988767›Full record

ArticleAnnals of intensive care2021

Characteristics, management, and prognosis of elderly patients with COVID-19 admitted in the ICU during the first wave: insights from the COVID-ICU study : Prognosis of COVID-19 elderly critically ill patients in the ICU.

Martin Dres, David Hajage, Said Lebbah, Antoine Kimmoun, Tai Pham, Gaëtan Béduneau, Alain Combes, Alain Mercat, Bertrand Guidet, Alexandre Demoule and 2 more

Abstract read
In one paragraph

Article in Annals of intensive care, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 2 pooled it
–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

34 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Observational
  5. Article
  6. Article
  7. Article
  8. Article
  9. Outcomes of critically ill older adults with COVID-19: a multicentre retrospective cohort study.Canadian journal of anaesthesia = Journal canadien d'anesthesie · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. The impact of age on intensive care.Ageing research reviews · 2023
    Review
  16. Article
  17. Review
  18. Article
  19. Article
  20. Caring for older adults during the COVID-19 pandemic.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2022
    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

12 authors.

Martin DresMédecine Intensive Réanimation (Département R3S), Service de Médecine intensive Réanimation, Groupe Hospitalier Universitaire APHP-Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Site Pitié-Salpêtrière, 47-73, bd de l'Hôpital, 75651, Paris Cedex 13, France. martin.dres@aphp.fr.ORCID http://orcid.org/0000-0001-9191-6089
David HajageSorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris, France.
Said LebbahUnité de Recherche Clinique, AP-HP, Paris, France.
Antoine KimmounService de Médecine Intensive et Réanimation Brabois, Université de Lorraine, CHRU de Nancy, Paris, France.
Tai PhamService de Médecine Intensive-Réanimation, Hôpital Bicêtre, Hôpitaux Universitaires Paris-Saclay, Le Kremlin-Bicêtre, France.
Gaëtan BéduneauNormandie Univ, UNIROUEN, EA 3830, Rouen, France.
Alain CombesSorbonne Université, INSERM, UMRS_1166-iCAN, Institute of Cardiometabolism and Nutrition, 75651, Paris Cedex 13, France.
Alain MercatDépartement de Médecine Intensive-Réanimation et Médecine Hyperbare, Faculté de Santé, CHU d'Angers, Université d'Angers, Angers, France.
Bertrand GuidetSorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris, France.
Alexandre DemouleMédecine Intensive Réanimation (Département R3S), Service de Médecine intensive Réanimation, Groupe Hospitalier Universitaire APHP-Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Site Pitié-Salpêtrière, 47-73, bd de l'Hôpital, 75651, Paris Cedex 13, France.
Matthieu SchmidtSorbonne Université, INSERM, UMRS_1166-iCAN, Institute of Cardiometabolism and Nutrition, 75651, Paris Cedex 13, France.
COVID-ICU investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic is a heavy burden in terms of health care resources. Future decision-making policies require consistent data on the management and prognosis of the older patients (> 70 years old) with COVID-19 admitted in the intensive care unit (ICU).

methodsCharacteristics, management, and prognosis of critically ill old patients (> 70 years) were extracted from the international prospective COVID-ICU database. A propensity score weighted-comparison evaluated the impact of intubation upon admission on Day-90 mortality.

resultsThe analysis included 1199 (28% of the COVID-ICU cohort) patients (median [interquartile] age 74 [72-78] years). Fifty-three percent, 31%, and 16% were 70-74, 75-79, and over 80 years old, respectively. The most frequent comorbidities were chronic hypertension (62%), diabetes (30%), and chronic respiratory disease (25%). Median Clinical Frailty Scale was 3 (2-3). Upon admission, the PaO

conclusionPatients over 70 years old represented more than a quarter of the COVID-19 population admitted in the participating ICUs during the first wave. Day-90 mortality was 46%, with dismal outcomes reported for patients older than 80 years or those intubated upon ICU admission.

Indexed as

Acute respiratory distress syndromeCOVID-19FrailtyIntensive care unitIntubationMortalityOld patients

Identifiers

PMID33988767
PMCPMC8120254

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.