Naslov
Posttraumatic Stress Disorder: Diagnostic Data Analysis by Data Mining Methodology

Autori
Marinić, Igor ; Supek, Fran ; Kovačić, Zrnka ; Rukavina, Lea ; Jendričko, Tihana ; Kozarić - Kovačić, Dragica

Izvornik
Croatian medical journal (0353-9504) 48 (2007), 2; 185-197

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
posttraumatic stress disorder ; data mining analysis ; diagnostic

Sažetak
Aim To use data mining methods in assessing diagnostic symptoms in posttraumatic stress disorder (PTSD). Methods The study included 102 inpatients: 51 with a diagnosis of PTSD and 51 with psychiatric diagnoses other than PTSD. Several models for predicting diagnosis were built using the random forest classifier, one of the intelligent data analysis methods. The first prediction model was based on a structured psychiatric interview, the second on psychiatric scales (Clinician-administered PTSD Scale - CAPS, Positive and Negative Syndrome Scale -PANSS, Hamilton Anxiety Scale - HAMA, and Hamilton Depression Scale - HAMD), and the third on combined data from both sources. Additional models placing more weight on one of the classes (PTSD or non-PTSD) were trained, and prototypes representing subgroups in the classes constructed. Results The first model was the most relevant for distinguishing PTSD diagnosis from comorbid diagnoses such as neurotic, stress-related, and somatoform disorders. The second model pointed out the scores obtained on the CAPS scale and additional PANSS scales, together with comorbid diagnoses of neurotic, stress-related, and somatoform disorders as most relevant. In the third model, psychiatric scales and the same group of comorbid diagnoses were found to be most relevant. Specialized models placing more weight on either the PTSD or non-PTSD class were able to better predict their targeted diagnoses at some expense of overall accuracy. Class subgroup prototypes mainly differed in values achieved on psychiatric scales and frequency of comorbid diagnoses. Conclusion Our work demonstrated the applicability of data mining methods for the analysis of structured psychiatric data for PTSD. In all models, the group of comorbid diagnoses, including neurotic, stress-related, and somatoform disorders, surfaced as important. The important attributes of the data, based on the structured psychiatric interview, were the current symptoms and conditions such as presence and degree of disability, hospitalizations, and duration of military service during the war, while CAPS total scores, symptoms of increased arousal, and PANSS additional criteria scores were indicated as relevant from the psychiatric symptom scales.

Izvorni jezik
Engleski

Znanstvena područja
Kliničke medicinske znanosti

POVEZANOST RADA