Evidence map›Paper›PMID 37810906›Full record

ReviewMedicine international

Temporal evolution of laboratory characteristics in patients critically ill with COVID‑19 admitted to the intensive care unit (Review).

Stelios Kokkoris, Angeliki Kanavou, Panagiotis Kremmydas, Dimitrios Katsaros, Stavros Karageorgiou, Aikaterini Gkoufa, Vasiliki Epameinondas Georgakopoulou, Demetrios A Spandidos, Charalampos Giannopoulos, Marina Kardamitsi and 1 more

Open access · hybridAbstract readReview
In one paragraph

Review in Medicine international. 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
0.8field-weighted citation impact, top 29% 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, 4 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

11 authors at 2 institutions in 1 country.

Stelios KokkorisFirst Department of Intensive Care, Evangelismos Hospital, Medical School, National and Kapodistrian University of Athens, 10676 Athens, Greece.
Angeliki KanavouFirst Department of Intensive Care, Evangelismos Hospital, Medical School, National and Kapodistrian University of Athens, 10676 Athens, Greece.
Panagiotis KremmydasFirst Department of Intensive Care, Evangelismos Hospital, Medical School, National and Kapodistrian University of Athens, 10676 Athens, Greece.
Dimitrios KatsarosFirst Department of Intensive Care, Evangelismos Hospital, Medical School, National and Kapodistrian University of Athens, 10676 Athens, Greece.
Stavros KarageorgiouFirst Department of Intensive Care, Evangelismos Hospital, Medical School, National and Kapodistrian University of Athens, 10676 Athens, Greece.
Aikaterini GkoufaFirst Department of Intensive Care, Evangelismos Hospital, Medical School, National and Kapodistrian University of Athens, 10676 Athens, Greece.
Vasiliki Epameinondas GeorgakopoulouDepartment of Infectious Diseases, Laiko General Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.
Demetrios A SpandidosLaboratory of Clinical Virology, School of Medicine, University of Crete, 71003 Heraklion, Greece.
Charalampos GiannopoulosFirst Department of Intensive Care, Evangelismos Hospital, Medical School, National and Kapodistrian University of Athens, 10676 Athens, Greece.
Marina KardamitsiFirst Department of Intensive Care, Evangelismos Hospital, Medical School, National and Kapodistrian University of Athens, 10676 Athens, Greece.
Christina RoutsiFirst Department of Intensive Care, Evangelismos Hospital, Medical School, National and Kapodistrian University of Athens, 10676 Athens, Greece.
National and Kapodistrian University of Athens · GRUniversity of Crete · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the context of coronavirus disease 2019 (COVID-19), laboratory medicine has played a crucial role in both diagnosis and severity assessment. Although the importance of baseline laboratory findings has been extensively reported, data regarding their evolution over the clinical course are limited. The aim of the present narrative review was to provide the dynamic changes of the routine laboratory variables reported in patients with severe COVID-19 over the course of their critical illness. A search was made of the literature for articles providing data on the time-course of routine laboratory tests in patients with severe COVID-19 during their stay in the intensive care unit (ICU). White blood cell, neutrophil and lymphocyte counts, neutrophil to lymphocyte ratio, platelet counts, as well as D-dimer, fibrinogen, C-reactive protein, lactate dehydrogenase and serum albumin levels were selected as disease characteristics and routine laboratory parameters. A total of 25 research articles reporting dynamic trends in the aforementioned laboratory parameters over the clinical course of severe COVID-19 were identified. During the follow-up period provided by each study, the majority of the laboratory values remained persistently abnormal in both survivors and non-survivors. Furthermore, in the majority of studies, the temporal trends of laboratory values distinctly differentiated patients between survivors and non-survivors. In conclusion, there are distinct temporal trends in selected routine laboratory parameters between survivors and non-survivors with severe COVID-19 admitted to the ICU, indicating their importance in the prognosis of clinical outcome.

Indexed as

clinical chemistrycoronavirusCOVID-19evolutionintensive care unitlaboratory valuesmortalitytemporal changestrajectory

Identifiers

PMID37810906
PMCPMC10557099
OpenAlexW4386747754

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.