PMID- 38062589
OWN - NLM
STAT- MEDLINE
DCOM- 20231216
LR  - 20231216
IS  - 1681-7168 (Electronic)
IS  - 1022-386X (Linking)
VI  - 33
IP  - 12
DP  - 2023 Dec
TI  - Developing and Validating a New Model to Predict In-Hospital Mortality in 
      Patients with Acute Myocardial Infarction.
PG  - 1361-1366
LID - 10.29271/jcpsp.2023.12.1361 [doi]
AB  - OBJECTIVE: To derive and validate a regression model that can successfully and 
      robustly predict in-hospital mortality of patients who underwent percutaneous 
      coronary intervention (PCI) after admission to the Department of Emergency 
      Medicine (ED) with acute myocardial infarction (AMI). STUDY DESIGN: Cohort study. 
      PLACE AND DURATION OF THE STUDY: ED of University of Health Sciences, Sancaktepe 
      Training and Research Hospital, that worked as a PCI centre between January and 
      March 2022. METHODOLOGY: Patients older than 18 years of age, diagnosed with 
      acute ST elevation myocardial infarction (STEMI) or non-STEMI (NSTEMI) in the ED, 
      and consequently underwent PCI were included. Patients with missing information 
      of the outcome were excluded. For the regression model, backward stepwise 
      logistic regression was utilised. The non-random split-sample development and 
      validation method was used for the internal and external validation of the model. 
      Ejection fraction, diastolic blood pressure, haemoglobin A1c, and haemoglobin 
      were selected as the predictors. RESULTS: A total of 279 patients were included 
      in the analysis. The area under the curve (AUC) of the final model in the 
      derivation cohort was 0.982 (95% CI = 0.956-1.0). The sensitivity was 92.3% (95% 
      CI = 64-99.8) and the specificity was 96.2% (95% CI = 92.3-98.4). The AUC of the 
      final model in the validation cohort was 0.956 (95% CI = 0.904-1.0). The 
      sensitivity was 80% (95% CI = 28.3-99.5) and the specificity was 92.3% (95% CI = 
      84-97.1). CONCLUSION: The suggested model generated results that can be utilised 
      as a screening tool for predicting in-hospital mortality in patients diagnosed 
      with STEMI or NSTEMI who are admitted to PCI in emergency medicine settings. 
      Nonetheless, it is essential to validate the model in different populations. KEY 
      WORDS: Percutaneous coronary intervention, Mortality, In-hospital mortality, 
      Prediction model, Logistic regression.
FAU - Islam, Selma Atay
AU  - Islam SA
AD  - Department of Emergency Medicine, University of Health Sciences, Sancaktepe 
      Training and Research Hospital, Sancaktepe, Turkey.
FAU - Islam, Mehmet Muzaffer
AU  - Islam MM
AD  - Department of Emergency Medicine, University of Health Sciences, Umraniye 
      Training and Research Hospital, Umraniye, Turkey.
FAU - Kahraman, Hande Akbal
AU  - Kahraman HA
AD  - Department of Emergency Medicine, University of Health Sciences, Sancaktepe 
      Training and Research Hospital, Sancaktepe, Turkey.
FAU - Ciril, Muhammed Fatih
AU  - Ciril MF
AD  - Department of Emergency Medicine, University of Health Sciences, Sancaktepe 
      Training and Research Hospital, Sancaktepe, Turkey.
FAU - Mizrak, Aysegul
AU  - Mizrak A
AD  - Department of Emergency Medicine, University of Health Sciences, Sancaktepe 
      Training and Research Hospital, Sancaktepe, Turkey.
FAU - Tayfur, Ismail
AU  - Tayfur I
AD  - Department of Emergency Medicine, University of Health Sciences, Sancaktepe 
      Training and Research Hospital, Sancaktepe, Turkey.
LA  - eng
PT  - Journal Article
PL  - Pakistan
TA  - J Coll Physicians Surg Pak
JT  - Journal of the College of Physicians and Surgeons--Pakistan : JCPSP
JID - 9606447
RN  - 0 (Hemoglobins)
SB  - IM
MH  - Humans
MH  - *ST Elevation Myocardial Infarction/surgery
MH  - *Non-ST Elevated Myocardial Infarction
MH  - Hospital Mortality
MH  - Cohort Studies
MH  - *Percutaneous Coronary Intervention
MH  - *Myocardial Infarction/diagnosis/surgery
MH  - Hemoglobins
MH  - Risk Factors
MH  - Treatment Outcome
MH  - Retrospective Studies
EDAT- 2023/12/08 06:41
MHDA- 2023/12/17 13:19
CRDT- 2023/12/08 00:06
PHST- 2023/07/17 00:00 [received]
PHST- 2023/11/25 00:00 [accepted]
PHST- 2023/12/17 13:19 [medline]
PHST- 2023/12/08 06:41 [pubmed]
PHST- 2023/12/08 00:06 [entrez]
AID - 040579197 [pii]
AID - 10.29271/jcpsp.2023.12.1361 [doi]
PST - ppublish
SO  - J Coll Physicians Surg Pak. 2023 Dec;33(12):1361-1366. doi: 
      10.29271/jcpsp.2023.12.1361.