Evidence map›Paper›PMID 40951464›Full record

ArticleNarra J2025

Biomarkers for predicting COVID-19 mortality: A study at Sulianti Saroso Infectious Disease Hospital, Indonesia.

Siti Maemun, Aninda D Widiantari, Farida Murtiani, Herlina Herlina, Dian W Tanjungsari, Kunti Wijiarti, Tiara Z Pratiwi, Faisal Matondang, Adria Rusli, Rivaldiansyah Rivaldiansyah and 4 more

Abstract read
In one paragraph

Article in Narra J, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Siti MaemunDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Aninda D WidiantariDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Farida MurtianiDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Herlina HerlinaDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Dian W TanjungsariDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Kunti WijiartiDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Tiara Z PratiwiDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Faisal MatondangDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Adria RusliDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Rivaldiansyah RivaldiansyahDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Maria L TampubolonDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Nina MarianaDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Vivi SetiawatyDepartment of Research, Sulianti Saroso Infectious Disease Hospital, Jakarta, Indonesia.
Tri B PurnamaIndonesian Epidemiology Collegium, Jakarta, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The high transmissibility and mortality rates of the COVID-19 pandemic pose significant challenges. Patients can deteriorate rapidly, making it crucial to identify laboratory biomarkers for high-risk individuals. The aim of this study was to evaluate the predictive value of various laboratory parameters, including C-reactive protein (CRP), D-dimer, ferritin, neutrophil-to-lymphocyte ratio (NLR), prothrombin time (PT), and procalcitonin (PCT), in predicting COVID-19 mortality. A retrospective cohort study was conducted at Sulianti Saroso Infectious Disease Hospital, where COVID-19 patients were categorized into survivors and non-survivors. The Mann-Whitney test was used to assess group differences, while receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performance of each biomarker, with Youden's index (J) determining optimal cut-off values. Kaplan-Meier analysis was used to compare median survival times, and Cox regression assessed hazard rates and the relationship between biomarkers and mortality. A total of 1,598 patients were analyzed, the majority of whom were admitted with oxygen saturation levels >95% and classified as having mild to moderate disease severity. Among them, 216 patients died, resulting in a mortality rate of 13.52%. Significant variations in mortality rates were observed along the survival functions for NLR, ferritin, D-dimer, CRP, and PCT (

Indexed as

BiomarkersCOVID-19SARS-CoV-2Severity of Illness IndexAdultC-Reactive ProteinFemaleFerritinsFibrin Fibrinogen Degradation ProductsHumansIndonesiaKaplan-Meier EstimateLeukocyte CountMaleMiddle AgedPredictive Value of TestsBiomarkersC-Reactive ProteinFerritinsFibrin Fibrinogen Degradation Productsfibrin fragment DProcalcitoninbiomarkerCOVID-19mortalitySulianti Saroso Hospitalsurvival

Identifiers

PMID40951464
PMCPMC12425506

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.