Literature DB >> 28592928

Comparison of six outcome prediction models in an adult burn population in a developing country.

S H Salehi1,2, K As'adi2,3, A Abbaszadeh-Kasbi2, M S Isfeedvajani4, N Khodaei2.   

Abstract

There are two types of prognostic model - burn-specific and general - to predict mortality risk in burn patients. Most prediction models were devised in developed countries. The aim of this study was to compare the performance of six outcome models in a developing country. In a retrospective cohort study, data of all thermal burned adult patients (age ≥ 18 years) admitted to the Burn Intensive Care Unit (BICU) were collected and then the following six prediction models were used to assess each patient: Acute Physiology and Chronic Health Evaluation (APACHE II), Abbreviated Burn Severity Index (ABSI), Belgian Outcome in Burn Injury (BOBI), the Ryan model, revised Baux and FLAMES model. Discriminative ability and goodness-of-fit of the prediction models were determined by receiver operating characteristic curve analysis and Hosmer-Lemeshow tests. We included 238 patients (mean age: 38.3 ± 18.39 years, average TBSA: 58.27% ± 24.55) in our study; 172 (72.3%) of them were diagnosed with inhalation injury and 178 (72.4%) were intubated. Mortality rate was 69.7%. Deceased patients had significantly higher mean age, %TBSA and number of inhalation injury. The area under the curve of the models was between 64.5 (APACHE II) and 85.9 (ABSI). The best estimation of predicted mortality was obtained with the ABSI model (67.2%).

Entities:  

Keywords:  ABSI score; APACHE II; adult burn population; developing country; outcome prediction models

Year:  2017        PMID: 28592928      PMCID: PMC5446902     

Source DB:  PubMed          Journal:  Ann Burns Fire Disasters        ISSN: 1592-9558


  31 in total

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Authors:  Joachim E Fischer; Lucas M Bachmann; Roman Jaeschke
Journal:  Intensive Care Med       Date:  2003-05-07       Impact factor: 17.440

Review 2.  Predicting outcome in critical care: the current status of the APACHE prognostic scoring system.

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3.  Development and validation of a model for prediction of mortality in patients with acute burn injury.

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Journal:  Br J Surg       Date:  2009-01       Impact factor: 6.939

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Authors:  Turner Osler; Laurent G Glance; David W Hosmer
Journal:  J Trauma       Date:  2010-03

5.  Characteristics and outcomes of multiple organ dysfunction syndrome among severe-burn patients.

Authors:  Lam Nhu Nguyen; Tien Gia Nguyen
Journal:  Burns       Date:  2009-06-23       Impact factor: 2.744

6.  Revised Baux Score and updated Charlson comorbidity index are independently associated with mortality in burns intensive care patients.

Authors:  Jacob S Heng; Olivia Clancy; Joanne Atkins; Jorge Leon-Villapalos; Andrew J Williams; Richard Keays; Michelle Hayes; Masao Takata; Isabel Jones; Marcela P Vizcaychipi
Journal:  Burns       Date:  2015-07-14       Impact factor: 2.744

7.  Outcome and changes over time in survival following severe burns from 1985 to 2004.

Authors:  Nele Brusselaers; Eric A J Hoste; Stan Monstrey; Kirsten E Colpaert; Jan J De Waele; Koenraad H Vandewoude; Stijn I Blot
Journal:  Intensive Care Med       Date:  2005-10-12       Impact factor: 17.440

8.  A nomogram for calculation of the Revised Baux Score.

Authors:  D J Williams; J D Walker
Journal:  Burns       Date:  2014-06-14       Impact factor: 2.744

Review 9.  Inflammatory mediators in smoke inhalation injury.

Authors:  James B Sterner; Thomas B Zanders; Michael J Morris; Leopoldo C Cancio
Journal:  Inflamm Allergy Drug Targets       Date:  2009-03

10.  APACHE-acute physiology and chronic health evaluation: a physiologically based classification system.

Authors:  W A Knaus; J E Zimmerman; D P Wagner; E A Draper; D E Lawrence
Journal:  Crit Care Med       Date:  1981-08       Impact factor: 7.598

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  8 in total

1.  Measurements Of Injury-Related Outcomes: Statistical And Analytical Data From Albania.

Authors:  M K Belba; L N Deda; G P Belba
Journal:  Ann Burns Fire Disasters       Date:  2021-12-31

2.  The Predictive Capacity of American Society of Anesthesiologists Physical Status (ASA PS) Score in Burn Patients.

Authors:  Katherine J Choi; Christopher H Pham; Zachary J Collier; Melissa Mert; Ryan K Ota; Ruibei Li; Haig A Yenikomshian; Mandeep Singh; T Justin Gillenwater; Catherine M Kuza
Journal:  J Burn Care Res       Date:  2020-07-03       Impact factor: 1.845

3.  Prognosis value of revised Baux score among burn patients in developing country.

Authors:  Nguyen N Lam; Ngo T Hung; Ngo M Duc
Journal:  Int J Burns Trauma       Date:  2021-06-15

4.  Development of a risk prediction model (Hangang) and comparison with clinical severity scores in burn patients.

Authors:  Youngmin Kim; Dohern Kym; Jun Hur; Jinwoo Jeon; Jaechul Yoon; Haejun Yim; Yong Suk Cho; Wook Chun
Journal:  PLoS One       Date:  2019-02-06       Impact factor: 3.240

5.  Predictors of mortality and validation of burn mortality prognostic scores in a Malaysian burns intensive care unit.

Authors:  Henry Tan Chor Lip; Mohamad Azim Md Idris; Farrah-Hani Imran; Tuan Nur' Azmah; Tan Jih Huei; Mathew Thomas
Journal:  BMC Emerg Med       Date:  2019-11-07

6.  Using a machine learning approach to predict mortality in critically ill influenza patients: a cross-sectional retrospective multicentre study in Taiwan.

Authors:  Chien-An Hu; Chia-Ming Chen; Yen-Chun Fang; Shinn-Jye Liang; Hao-Chien Wang; Wen-Feng Fang; Chau-Chyun Sheu; Wann-Cherng Perng; Kuang-Yao Yang; Kuo-Chin Kao; Chieh-Liang Wu; Chwei-Shyong Tsai; Ming-Yen Lin; Wen-Cheng Chao
Journal:  BMJ Open       Date:  2020-02-25       Impact factor: 2.692

7.  Predicting Burn Mortality Using a Simple Novel Prediction Model.

Authors:  Sneha Sharma; Raman Tandon
Journal:  Indian J Plast Surg       Date:  2021-03-04

8.  Clinical outcome and comparison of burn injury scoring systems in burn patient in Indonesia.

Authors:  Risa Herlianita; Edi Purwanto; Indri Wahyuningsih; Indah Dwi Pratiwi
Journal:  Afr J Emerg Med       Date:  2021-06-05
  8 in total

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