Cognitive and clinical predictors of a long-term course in obsessive compulsive disorder: A machine learning approach in a prospective cohort study

BACKGROUND

Obsessive compulsive disorder (OCD) is a disabling illness with a chronic course, yet data on long-term outcomes are scarce. This study aimed to examine the long-term course of OCD in patients treated with different approaches (drugs, psychotherapy, and psychosurgery) and to identify predictors of clinical outcome by machine learning.

METHOD

We included outpatients with OCD treated at our referral unit. Demographic and neuropsychological data were collected at baseline using standardized instruments. Clinical data were collected at baseline, 12 weeks after starting pharmacological treatment prescribed at study inclusion, and after follow-up.

RESULTS

Of the 60 outpatients included, with follow-up data available for 5-17 years (mean = 10.6 years), 40 (67.7 %) were considered non-responders to adequate treatment at the end of the study. The best machine learning model achieved a correlation of 0.63 for predicting the long-term Yale-Brown Obsessive Compulsive Scale (Y-BOCS) score by adding clinical response (to the first pharmacological treatment) to the baseline clinical and neuropsychological characteristics.

LIMITATIONS

Our main limitations were the sample size, modest in the context of traditional ML studies, and the sample composition, more representative of rather severe OCD cases than of patients from the general community.

CONCLUSIONS

Many patients with OCD showed persistent and disabling symptoms at the end of follow-up despite comprehensive treatment that could include medication, psychotherapy, and psychosurgery. Machine learning algorithms can predict the long-term course of OCD using clinical and cognitive information to optimize treatment options.

Late-onset postoperative angioedema triggered by angiotensin-converting enzyme inhibitor: An emergent airway forethought

Angioedema is a potentially life-threatening condition due to the risk of airway compromise leading to deterioration of respiratory function, hypoxia, and ultimately, cardiopulmonary arrest. It can be either unprovoked or triggered by pharmaceutical agents, emotional or physiologic factors, upper airway trauma, or surgical stress. A 46-year-old man previously prescribed perindopril developed angioedema of the tongue 4 h after being discharged from the Post Anesthesia Care Unit (PACU). A multidisciplinary team was called and they outlined an airway management strategy to use in the event of worsening. The strategy consisted of either fiberoptic intubation by an anesthesiologist or surgical tracheostomy performed by the surgical team, both performed with the patient awake and in spontaneous ventilation. The aim of this case report is to raise awareness that angioedema is a potentially life-threatening condition. For optimal management, it is important to prepare in advance a detailed airway management strategy to be implemented by a multidisciplinary team.