Evidence map›Paper›PMID 33158594›Full record

ArticleMedicina intensiva

[Comparison of the demographic characteristics and comorbidities of patients with COVID-19 who died in Spanish hospitals based on whether they were or were not admitted to an intensive care unit].

Ò Miró, A Alquézar-Arbé, P Llorens, F J Martín-Sánchez, S Jiménez, A Martín, G Burillo-Putze, J Jacob, E J García-Lamberechts, P Piñera and 2 more

Abstract readComparative Study
In one paragraph

Article in Medicina intensiva. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. COVID-19 Mortality Rate and Its Incidence in Latin America: Dependence on Demographic and Economic Variables.International journal of environmental research and public health · 2021
    Article
  6. 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

12 authors.

Ò MiróServicio de Urgencias, Hospital Clínic, IDIBAPS, Universitat de Barcelona, Barcelona, España. Electronic address: omiro@clinic.cat.
A Alquézar-ArbéServicio de Urgencias, Hospital de la Santa Creu i Sant Pau, Barcelona, España.
P LlorensServicio de Urgencias, Hospital General Universitario de Alicante, Universidad Miguel Hernández, Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), Alicante, España.
F J Martín-SánchezServicio de Urgencias, Hospital Clínico San Carlos, IDISSC, Universidad Complutense, Madrid, España.
S JiménezServicio de Urgencias, Hospital Clínic, IDIBAPS, Universitat de Barcelona, Barcelona, España.
A MartínServicio de Urgencias, Hospital Universitario de Móstoles, Madrid, España.
G Burillo-PutzeServicio de Urgencias, Hospital Universitario de Canarias, Tenerife, España.
J JacobServicio de Urgencias, Hospital Universitario de Bellvitge, L'Hospitalet de Llobregat, Barcelona, España.
E J García-LamberechtsServicio de Urgencias, Hospital Clínico San Carlos, IDISSC, Universidad Complutense, Madrid, España.
P PiñeraServicio de Urgencias, Hospital General Universitario Reina Sofía, Murcia, España.
J González Del CastilloServicio de Urgencias, Hospital Clínico San Carlos, IDISSC, Universidad Complutense, Madrid, España.
en representación de la red de investigación SIESTA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo describe and compare the demographic characteristics and comorbidities of patients with COVID-19 who died in Spanish hospitals during the 2020 pandemic based on whether they were or were not admitted to an intensive care unit (ICU) prior to death.

methodsWe performed a secondary analysis of COVID-19 patients who died during hospitalization included by 62 Spanish emergency departments in the SIESTA cohort. We collected the demographic characteristics and comorbidities, determined both individually and estimated globally by the Charlson index (ChI). Independent factors related to ICU admission were identified and different analyses of sensitivity were performed to contrast the consistency of the findings of the principal analysis.

resultsWe included the 338 patients from the SIESTA cohort that died during hospitalization. Of these, 77 (22.8%) were admitted to an ICU before dying. After multivariate adjustment, 3 out of the 20 basal characteristics analyzed in the present study were independently associated with ICU admission: dementia (no patients with dementia who died were admitted to the ICU: OR = 0, 95%CI = not calculable), active cancer (OR = 0.07; 95%CI = 0.02-0.21) and age (< 70 years: OR = 1, reference; 70-74 years: OR = 0.21; 95%CI = 0.08-0.54; 75-79 years: OR = 0.21; 95%CI = 0.08-0.54; ≥ 80 years: OR = 0.02; 95%CI = 0.01-0.05). The probability of ICU admission significantly increased in parallel to the ChI, even after adjustment for age (ChI 0 points: OR = 0, reference; ChI 1 point: OR = 0.36; 95%CI = 0.16-0.83; ChI 2 points: OR = 0.36; 95%CI = 0.16-0.83; ChI >2 points: OR = 0.09; 95%CI = 0.04-0.23). The sensitivity analyses showed no gross differences compared to the principal analysis.

conclusionsThe profile of COVID-19 patients who died without ICU admission is similar to that observed in the usual medical practice before the pandemic. The basal characteristics limiting their admission were age and global burden due to comorbidity, especially dementia and active cancer.

Indexed as

Hospital MortalitySARS-CoV-2AgedAged, 80 and overAge DistributionAnalysis of VarianceAsthmaCohort StudiesComorbidityConfidence IntervalsCoronary DiseaseCOVID-19DementiaDiabetes MellitusDyslipidemiasFemaleCaracterísticas clínicasClinical characteristicsComorbiditiesComorbilidadesCOVID-19Emergency departmentsSARS-CoV-2Servicios de urgencias

Identifiers

PMID33158594
PMCPMC7522623

What OpenQuestion holds

Textmetadata
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.