A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

A Risk-Scoring Model to Predict One-year Major Adverse Cardiac Events after Percutaneous Coronary Intervention. | LitMetric

AI Article Synopsis

  • * Researchers analyzed data from 8,206 patients to develop the score, identifying key predictors such as diabetes, kidney function, and heart performance, which were then validated using a separate group of 2,875 patients.
  • * The resulting risk-scoring system successfully categorized patients into low, moderate, and high-risk groups for MACE, helping physicians enhance decision-making and manage patient care post-procedure.

Article Abstract

Background: The aim of the present study was to develop a scoring system for predicting 1-year major adverse cardiac events (MACE), including mortality, target vessel or target lesion revascularization, coronary artery bypass graft surgery, and non-fatal myocardial infarction after percutaneous coronary intervention (PCI).

Methods: The data were extracted from a single center PCI registry. The score was created based on the clinical, procedural, and laboratory characteristics of 8206 patients who underwent PCI between April 2004 and October 2009. Consecutive patients undergoing PCI between November 2009 and February 2011 (n= 2875) were included as a validation data set.

Results: Diabetes mellitus, increase in the creatinine level, decrease in the left ventricular ejection fraction, presentation with the acute coronary syndrome, number of diseased vessels, primary PCI, PCI on the left anterior descending artery and saphenous vein graft, and stent type and diameter were identified as the predictors of the outcome and used to develop the score (R² = 0.795). The models had adequate goodness of fit (Hosmer-Lemeshow statistic; p value = 0.601) and acceptable ability of discrimination (c-statistics = 0.63). The score categorized the individual patients as low-, moderate-, and high-risk for the occurrence of MACE. The validation of the model indicated a good agreement between the observed and expected risks.

Conclusion: An individual risk-scoring system based on both clinical and procedural variables can be used conveniently to predict 1-year MACE after PCI. Risk classification based on this score can assist physicians in decision-making and postprocedural health care.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4791644PMC

Publication Analysis

Top Keywords

major adverse
8
adverse cardiac
8
cardiac events
8
percutaneous coronary
8
coronary intervention
8
based clinical
8
clinical procedural
8
pci
6
risk-scoring model
4
model predict
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!