Posttraumatic stress disorder: diagnostic data analysis by data mining methodology.

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.

Evolution of stapedectomy prostheses over time.

The history of stapedectomy prostheses started in 1956, when John J. Shea first described the microsurgical technique of the stapedectomy procedure in which an otosclerotic stapes was replaced with a prosthesis made of Teflon. Over the years, the evolution of the prostheses was influenced by the changes in the microsurgical technique, materials used and technical properties. The materials evolved from Teflon, metal, to plastic, and most recently to gold and titanium. While initially the diameter of the pistons used was 0.8 and 0.6 mm, from the 1970s onwards, it has been becoming even smaller in order to ease the procedure and reduce the risk of inner ear damage. Improvement was made in the way the prosthesis is fixed to the long incus process, resulting in different solutions like Teflon memory effect, platinum and gold band, titanium-gold clip prostheses or nickel-titanium alloy. Eventually, the most decisive factor for successful surgery is surgical experience with a specific type of prostheses and the expertise in the microsurgery technique.