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Record W4224243247 · doi:10.7759/cureus.24344

Co-relation of Monocyte Count in High vs. Low Thrombus Burden ST-Segment Elevated Myocardial Infarction (STEMI) Patients Undergoing Primary Percutaneous Coronary Intervention

2022· article· en· W4224243247 on OpenAlexaff
Muhammad Zeeshan, Sara Yousaf, Adeel Ahmed, Hina Bahadar, Usman Ali, Sidra Jabeen, Hassan ul Hussain, Hassan Mumtaz, Mohammad Hasan

Bibliographic record

VenueCureus · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineMyocardial infarctionPercutaneous coronary interventionInternal medicineCardiologyConfidence intervalClopidogrelOdds ratioThrombusThrombosisAspirinCoronary thrombosisPopulationThrombolysisTIMI

Abstract

fetched live from OpenAlex

Introduction Primary percutaneous coronary intervention (PPCI) in ST-elevation myocardial infarction (STEMI) patients can lead to poor outcomes. Intra-coronary thrombus development due to atherosclerotic plaque rupture and coronary blood flow blockage causes STEMI. Intracranial thrombosis in STEMI patients is fatal. It was our goal to establish how often patients with STEMI underwent PPCI with a high thrombus burden versus a low thrombus burden and to compare the mean monocyte count between the two groups. Material and methods This cross-sectional study was conducted at KRL Hospital Islamabad from October 2021 to March 2022. At a 95% level of confidence, a 5% margin of error, and keeping a population size of 330, a sample size of 178 was obtained using the Raosoft sample size calculator (Raosoft, Inc., Seattle, WA). The non-probability consecutive sampling method was used. All patients with STEMI undergoing PPCI, aged between 18 and 80 years, and presenting within 24 hours of symptoms were included in our study. Pre-PPCI pharmacological treatment given within three hours of the onset of a heart attack to stabilize patients with myocardial infarction included aspirin, clopidogrel, and an intravenous bolus of 70 U/kg of body weight of un-fractionated heparin. The collected data were analyzed using SPSS version 26.0 (IBM Corp., Armonk, NY). Fisher's exact test was employed, and a p-value of less than 0.05 was deemed statistically significant. The odds ratio and confidence interval were also calculated. Results A total of 178 participants were included in the research, out of which males were predominant with more than half of the study population. The mean age in patients having a low thrombus burden was 37.75 ± 6.39 years and that of patients with a high thrombus burden was mean 56.04 ± 7.98 years. In high thrombus burden patients, diabetes mellitus was found in 98.3%, hypertension in 120 patients (100%), obesity in (60%), and tobacco consumption in 120 patients (100%). The mean monocyte count in high burden patients was 70.27 ± 3.24, whereas it was 61.89 ± 5.71 in low burden patients. Only five patients had a Thrombolysis In Myocardial Infarction (TIMI) score of 5 while 34.8% of patients arrived in three to six hours and 12.9% arrived in less than three hours. Patients with a high monocyte count have 1.3 times more chances of developing the disease when the monocyte count was high (OR = 1.318, 95% CI = 1.140-1.524). Conclusion Patients with STEMI undergoing PPCI had a higher monocyte count upon admission, which was an independent clinical predictor of a high thrombus burden. Our findings suggest that admission monocyte count may be available for early risk stratification of high-thrombus burden in acute STEMI patients and might allow the optimization of anti-thrombotic therapy to improve the outcomes of PPCI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.278
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

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