Evidence map›Paper›PMID 37153106›Full record

ArticleFrontiers in medicine2023

Total severity score and age predict long-term hospitalization in COVID-19 pneumonia.

Athina Nasoufidou, Marianthi Kavelidou, Theodora Griva, Eleni Melikidou, Charalampos Maskalidis, Konstantina Machaira, Barbara Nikolaidou

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 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
0.6field-weighted citation impact, top 36% 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, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

7 authors at 1 institution in 1 country.

Athina Nasoufidou *Internal Medicine Department, General Hospital Agios Pavlos, Thessaloniki, Greece.
Marianthi Kavelidou *Surgery Department, General Hospital Agios Pavlos, Thessaloniki, Greece.
Theodora GrivaInternal Medicine Department, General Hospital Agios Pavlos, Thessaloniki, Greece.
Eleni MelikidouRadiology Department, General Hospital Agios Pavlos, Thessaloniki, Greece.
Charalampos MaskalidisRadiology Department, General Hospital Agios Pavlos, Thessaloniki, Greece.
Konstantina MachairaInternal Medicine Department, General Hospital Agios Pavlos, Thessaloniki, Greece.
Barbara NikolaidouInternal Medicine Department, General Hospital Agios Pavlos, Thessaloniki, Greece.
Agios Pavlos General Hospital · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Severe COVID-19 pneumonia implies increased oxygen demands and length of hospitalization (LOS). We aimed to assess a possible correlation between LOS and COVID-19 patients' clinical laboratory data of admission, including the total severity score (TSS) from chest computed tomography (CT). Methods: Data were assessed retrospectively at the General Hospital "Agios Pavlos" in Greece. Clinical laboratory data, TSS, and LOS were recorded. Results: A total of 317 patients, 136 women and 181 men, with a mean age of 66.58 ± 16.02 years were studied. Significant comorbidities were hypertension (56.5%), dyslipidemia (33.8%), type 2 diabetes mellitus (22.7%), coronary heart disease (12.9%), underlying pulmonary disease (10.1%), and malignancy (4.4%). Inpatient time was related to age ( Conclusion: Early identification of disease severity using the TSS and patients' age could be useful for inpatient resource allocation and for maintaining vigilance for those requiring long-term hospitalizations.

Indexed as

chest computed tomographyCOVID-19hospitalization lengthpneumoniatotal severity score

Identifiers

PMID37153106
PMCPMC10157639
OpenAlexW4365142346

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.