Evidence map›Paper›PMID 39272633›Full record

ArticleDiagnostics (Basel, Switzerland)2024

Inflammatory Protein Panel: Exploring Diagnostic Insights for Peripheral Artery Disease Diagnosis in a Cross-Sectional Study.

Ben Li, Rakan Nassereldine, Farah Shaikh, Houssam Younes, Batool AbuHalimeh, Abdelrahman Zamzam, Rawand Abdin, Mohammad Qadura

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  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

8 authors.

Ben LiDivision of Vascular Surgery, St. Michael's Hospital, Unity Health Toronto, University of Toronto, Toronto, ON M5B 1W8, Canada.ORCID 0000-0002-7191-1034
Rakan NassereldineDivision of Vascular Surgery, American University of Beirut Medical Center, Beirut 1107 2020, Lebanon.
Farah ShaikhDivision of Vascular Surgery, St. Michael's Hospital, Unity Health Toronto, University of Toronto, Toronto, ON M5B 1W8, Canada.
Houssam YounesHeart, Vascular, & Thoracic Institute, Cleveland Clinic Abu Dhabi, Abu Dhabi 112412, United Arab Emirates.
Batool AbuHalimehHeart, Vascular, & Thoracic Institute, Cleveland Clinic Abu Dhabi, Abu Dhabi 112412, United Arab Emirates.
Abdelrahman ZamzamDivision of Vascular Surgery, St. Michael's Hospital, Unity Health Toronto, University of Toronto, Toronto, ON M5B 1W8, Canada.
Rawand AbdinDepartment of Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada.
Mohammad QaduraDivision of Vascular Surgery, St. Michael's Hospital, Unity Health Toronto, University of Toronto, Toronto, ON M5B 1W8, Canada.

Funding

Blair Foundation N/A
6 · The paper itself

Abstract

Cytokine-induced neutrophil chemoattractant 1 (CINC-1), a cluster of differentiation 95 (CD95), fractalkine, and T-cell immunoglobulin and mucin domain 1 (TIM-1) are circulating proteins known to be involved in inflammation. While their roles have been studied in neurological conditions and cardiovascular diseases, their potential as peripheral artery disease (PAD) biomarkers remain unexplored. We conducted a cross-sectional diagnostic study using data from 476 recruited patients (164 without PAD and 312 with PAD). Plasma levels of CINC-1, CD95, fractalkine, and TIM-1 were measured at baseline. A PAD diagnosis was established at recruitment based on clinical exams and investigations, defined as an ankle-brachial index < 0.9 or toe-brachial index < 0.67 with absent/diminished pedal pulses. Using 10-fold cross-validation, we trained a random forest algorithm, incorporating clinical characteristics and biomarkers that showed differential expression in PAD versus non-PAD patients to predict a PAD diagnosis. Among the proteins tested, CINC-1, CD95, and fractalkine were elevated in PAD vs. non-PAD patients, forming a 3-biomarker panel. Our predictive model achieved an AUROC of 0.85 for a PAD diagnosis using clinical features and this 3-biomarker panel. By combining the clinical characteristics with these biomarkers, we developed an accurate predictive model for a PAD diagnosis. This algorithm can assist in PAD screening, risk stratification, and guiding clinical decisions regarding further vascular assessment, referrals, and medical/surgical management to potentially improve patient outcomes.

Indexed as

biomarkersdiagnosisperipheral artery disease

Identifiers

PMID39272633
PMCPMC11394143

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Registered trials

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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.