Evidence mapPaperPMID 37712883Full record

ReviewBiomolecules & biomedicine2024

The laboratory parameters in predicting the severity and death of COVID-19 patients: Future pandemic readiness strategies.

Ahmad R Alsayed, Syed Imran Ahmed, Anas Osama Al Shweiki, Mustafa Al-Shajlawi, Nancy Hakooz

Open access · diamondAbstract readReview
In one paragraph

Review in Biomolecules & biomedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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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

5 authors at 3 institutions in 2 countries.

Ahmad R AlsayedDepartment of Clinical Pharmacy and Therapeutics, Faculty of Pharmacy, Applied Science Private University, Amman, Jordan.
Syed Imran AhmedCollege of Health and Science, School of Pharmacy, University of Lincoln, Lincoln, United Kingdom.
Anas Osama Al ShweikiDepartment of Clinical Pharmacy and Therapeutics, Faculty of Pharmacy, Applied Science Private University, Amman, Jordan.
Mustafa Al-ShajlawiDepartment of Clinical Pharmacy and Therapeutics, Faculty of Pharmacy, Applied Science Private University, Amman, Jordan.
Nancy HakoozSchool of Pharmacy, The University of Jordan, Amman, Jordan.
Applied Science Private University · JOUniversity of Jordan · JOUniversity of Lincoln · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The range of clinical manifestations associated with the infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encompasses a broad spectrum, ranging from flu-like symptoms to the occurrence of multiple organ failure and death. The severity of the coronavirus disease 2019 (COVID-19) is categorized based on clinical presentation and is divided into three distinct levels of severity identified as non-severe, severe, and critical. Although individuals of all age groups are susceptible to SARS-CoV-2 infection, middle-aged and older adults are more frequently impacted, with the latter being more likely to develop severe illness. Various laboratory characteristics observed in hospitalized COVID-19 patients have been correlated with adverse outcomes. These include elevated levels of D-dimer, liver enzymes, lactate dehydrogenase, C-reactive protein, ferritin, prothrombin time, and troponin, as well as decreased lymphocyte and platelets counts. This review investigated the relationship between baseline clinical characteristics, initial laboratory parameters upon hospital admission, and the severity of illness and mortality rates among COVID-19 patients. Although the COVID-19 pandemic has concluded, understanding the laboratory predictors of virus severity and mortality remains crucial, and examining these predictors can have long-term effects. Such insights can help healthcare systems manage resources more effectively and deliver timely and appropriate care by identifying and targeting high-risk individuals. This knowledge can also help us better prepare for future pandemics. By examining these predictors, we can take steps to protect public health and mitigate the impact of future pandemics.

Indexed as

COVID-19AgedC-Reactive ProteinHumansLaboratoriesMiddle AgedPandemicsSARS-CoV-2C-Reactive Protein

Identifiers

PMID37712883
PMCPMC10950347
OpenAlexW4386738348

What Socratic 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 Socratic graph.