Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/15091
ชื่อเรื่อง: Prediction of UGIB event in NSAID users: A model development
ผู้แต่ง: Tangkiatkumjai M.
Vadcharavivad S.
Mahachai V.
Keywords: antiulcer agent
corticosteroid
diclofenac
histamine H2 receptor antagonist
nonsteroid antiinflammatory agent
proton pump inhibitor
warfarin
adult
aged
blood clotting disorder
case control study
chronic kidney failure
conference paper
digestive system cancer
female
gastroscopy
human
logistic regression analysis
major clinical study
male
Mallory Weiss syndrome
medical record
model
risk factor
risk reduction
treatment planning
upper gastrointestinal bleeding
Aged
Anti-Inflammatory Agents, Non-Steroidal
Case-Control Studies
Female
Gastrointestinal Hemorrhage
Humans
Male
Middle Aged
Models, Statistical
Risk Assessment
Upper Gastrointestinal Tract
วันที่เผยแพร่: 2005
บทคัดย่อ: The purpose of this study was to create a predicting tool for UGIB event in NSAID users. The patients of this case-control study were NSAID users who had received NSAIDs for at least 3 days and were gastroscoped. The patients with a history of gastrointestinal varices, gastrointestinal cancer, chronic renal failure, coagulopathy, or Mallory-Weiss tear were excluded. The data was collected between July 2001 and January 2002 by patient interviewing and medical record reviewing. One hundred and fifty four NSAID users were identified (89 in the UGIB group, 65 in the non-bleeding group). Most patients were elderly (mean age ± SD: 60.9 ± 12.6 years). Age and the number of current NSAlD users were significantly higher in UGIB patients than in non-bleeding patients (p < 0.05 and p < 0.01, respectively). The number of antiulceration drug users in non-bleeding patients was higher than in UGIB patients (p < 0.01). An equation for prediction of UGIB probability in NSAID users was generated by using enter logistic regression. The best model of predicting the risk of UGIB event in NSAID users was logit (UGIB) = 0.33 + 2.09 Multiple NSAID use + 1.43 H. pylori infection + 0.34 Current NSAID use + 0.12 (Age × Sex) - 8.53 Sex - 2.41 Antiulceration drugs - 0.000048 Age. The model had 80.2% of the overall rate of correct classification. The positive and negative predictive values were 80.8% and 78.9% respectively. The probability of UGIB = e logit(UGIB)/ 1 + e logit(UGIB). If the value of the probability of UGIB is more than 0.5, the patient has a high risk of UGIB. Multiple NSAID use is the strongest factor that affects the probability of UGIB in NSAID users. H. pylori infection is another strong risk factor of NSAID-related UGIB. Antiulceration drug usage reduced the risk of UGIB in this group of patients. The developed model can be used as a guide for pharmacotherapeutic planning in clinical practices.
URI: https://ir.swu.ac.th/jspui/handle/123456789/15091
https://www.scopus.com/inward/record.uri?eid=2-s2.0-23044450563&partnerID=40&md5=cdc75097f99395c4d421f721870b2324
ISSN: 1252208
Appears in Collections:Scopus 1983-2021

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