Machine Learning Prediction of Quality of Life Improvement During Antidepressant Treatment of Patients With Major Depressive Disorder: A STAR*D and CAN-BIND-1 Report
Conclusions: Machine learning can predict normative QoL after antidepressant treatment with similar performance to that of prior work predicting depressive symptom response and remission. These results suggest that QoL outcomes in MDD patients can be predicted with simple patient-rated measures and provide a foundation to further improve performance and demonstrate clinical utility.Trial Registration: ClinicalTrials.gov identifiers NCT00021528 and NCT01655706.PMID:37967350 | DOI:10.4088/JCP.23m14864 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Tejas Phaterpekar John-Jose Nunez Emma Morton Yang S Liu Bo Cao Benicio N Frey Roumen V Milev Daniel J M üller Susan Rotzinger Claudio N Soares Valerie H Taylor Rudolf Uher Sidney H Kennedy Raymond W Lam Source Type: research

Predictors and Risk Factors of Treatment-Resistant Depression: A Systematic Review
Conclusions: TRD is a complex disorder with many contributing factors that need to be identified and addressed earlier in the disease course to prevent its development or facilitate better treatment outcomes. Future work should focus on replicating the key predictors/risk factors identified in this review.PMID:37967334 | DOI:10.4088/JCP.23r14885 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Shane J O'Connor Nilay Hewitt Joanna Kuc Lucinda S Orsini Source Type: research

Machine Learning Prediction of Quality of Life Improvement During Antidepressant Treatment of Patients With Major Depressive Disorder: A STAR*D and CAN-BIND-1 Report
Conclusions: Machine learning can predict normative QoL after antidepressant treatment with similar performance to that of prior work predicting depressive symptom response and remission. These results suggest that QoL outcomes in MDD patients can be predicted with simple patient-rated measures and provide a foundation to further improve performance and demonstrate clinical utility.Trial Registration: ClinicalTrials.gov identifiers NCT00021528 and NCT01655706.PMID:37967350 | DOI:10.4088/JCP.23m14864 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Tejas Phaterpekar John-Jose Nunez Emma Morton Yang S Liu Bo Cao Benicio N Frey Roumen V Milev Daniel J M üller Susan Rotzinger Claudio N Soares Valerie H Taylor Rudolf Uher Sidney H Kennedy Raymond W Lam Source Type: research

Predictors and Risk Factors of Treatment-Resistant Depression: A Systematic Review
Conclusions: TRD is a complex disorder with many contributing factors that need to be identified and addressed earlier in the disease course to prevent its development or facilitate better treatment outcomes. Future work should focus on replicating the key predictors/risk factors identified in this review.PMID:37967334 | DOI:10.4088/JCP.23r14885 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Shane J O'Connor Nilay Hewitt Joanna Kuc Lucinda S Orsini Source Type: research

Machine Learning Prediction of Quality of Life Improvement During Antidepressant Treatment of Patients With Major Depressive Disorder: A STAR*D and CAN-BIND-1 Report
Conclusions: Machine learning can predict normative QoL after antidepressant treatment with similar performance to that of prior work predicting depressive symptom response and remission. These results suggest that QoL outcomes in MDD patients can be predicted with simple patient-rated measures and provide a foundation to further improve performance and demonstrate clinical utility.Trial Registration: ClinicalTrials.gov identifiers NCT00021528 and NCT01655706.PMID:37967350 | DOI:10.4088/JCP.23m14864 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Tejas Phaterpekar John-Jose Nunez Emma Morton Yang S Liu Bo Cao Benicio N Frey Roumen V Milev Daniel J M üller Susan Rotzinger Claudio N Soares Valerie H Taylor Rudolf Uher Sidney H Kennedy Raymond W Lam Source Type: research

Predictors and Risk Factors of Treatment-Resistant Depression: A Systematic Review
Conclusions: TRD is a complex disorder with many contributing factors that need to be identified and addressed earlier in the disease course to prevent its development or facilitate better treatment outcomes. Future work should focus on replicating the key predictors/risk factors identified in this review.PMID:37967334 | DOI:10.4088/JCP.23r14885 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Shane J O'Connor Nilay Hewitt Joanna Kuc Lucinda S Orsini Source Type: research

Machine Learning Prediction of Quality of Life Improvement During Antidepressant Treatment of Patients With Major Depressive Disorder: A STAR*D and CAN-BIND-1 Report
Conclusions: Machine learning can predict normative QoL after antidepressant treatment with similar performance to that of prior work predicting depressive symptom response and remission. These results suggest that QoL outcomes in MDD patients can be predicted with simple patient-rated measures and provide a foundation to further improve performance and demonstrate clinical utility.Trial Registration: ClinicalTrials.gov identifiers NCT00021528 and NCT01655706.PMID:37967350 | DOI:10.4088/JCP.23m14864 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Tejas Phaterpekar John-Jose Nunez Emma Morton Yang S Liu Bo Cao Benicio N Frey Roumen V Milev Daniel J M üller Susan Rotzinger Claudio N Soares Valerie H Taylor Rudolf Uher Sidney H Kennedy Raymond W Lam Source Type: research

Predictors and Risk Factors of Treatment-Resistant Depression: A Systematic Review
Conclusions: TRD is a complex disorder with many contributing factors that need to be identified and addressed earlier in the disease course to prevent its development or facilitate better treatment outcomes. Future work should focus on replicating the key predictors/risk factors identified in this review.PMID:37967334 | DOI:10.4088/JCP.23r14885 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Shane J O'Connor Nilay Hewitt Joanna Kuc Lucinda S Orsini Source Type: research

Machine Learning Prediction of Quality of Life Improvement During Antidepressant Treatment of Patients With Major Depressive Disorder: A STAR*D and CAN-BIND-1 Report
Conclusions: Machine learning can predict normative QoL after antidepressant treatment with similar performance to that of prior work predicting depressive symptom response and remission. These results suggest that QoL outcomes in MDD patients can be predicted with simple patient-rated measures and provide a foundation to further improve performance and demonstrate clinical utility.Trial Registration: ClinicalTrials.gov identifiers NCT00021528 and NCT01655706.PMID:37967350 | DOI:10.4088/JCP.23m14864 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Tejas Phaterpekar John-Jose Nunez Emma Morton Yang S Liu Bo Cao Benicio N Frey Roumen V Milev Daniel J M üller Susan Rotzinger Claudio N Soares Valerie H Taylor Rudolf Uher Sidney H Kennedy Raymond W Lam Source Type: research

Predictors and Risk Factors of Treatment-Resistant Depression: A Systematic Review
Conclusions: TRD is a complex disorder with many contributing factors that need to be identified and addressed earlier in the disease course to prevent its development or facilitate better treatment outcomes. Future work should focus on replicating the key predictors/risk factors identified in this review.PMID:37967334 | DOI:10.4088/JCP.23r14885 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Shane J O'Connor Nilay Hewitt Joanna Kuc Lucinda S Orsini Source Type: research

Machine Learning Prediction of Quality of Life Improvement During Antidepressant Treatment of Patients With Major Depressive Disorder: A STAR*D and CAN-BIND-1 Report
Conclusions: Machine learning can predict normative QoL after antidepressant treatment with similar performance to that of prior work predicting depressive symptom response and remission. These results suggest that QoL outcomes in MDD patients can be predicted with simple patient-rated measures and provide a foundation to further improve performance and demonstrate clinical utility.Trial Registration: ClinicalTrials.gov identifiers NCT00021528 and NCT01655706.PMID:37967350 | DOI:10.4088/JCP.23m14864 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Tejas Phaterpekar John-Jose Nunez Emma Morton Yang S Liu Bo Cao Benicio N Frey Roumen V Milev Daniel J M üller Susan Rotzinger Claudio N Soares Valerie H Taylor Rudolf Uher Sidney H Kennedy Raymond W Lam Source Type: research

Predictors and Risk Factors of Treatment-Resistant Depression: A Systematic Review
Conclusions: TRD is a complex disorder with many contributing factors that need to be identified and addressed earlier in the disease course to prevent its development or facilitate better treatment outcomes. Future work should focus on replicating the key predictors/risk factors identified in this review.PMID:37967334 | DOI:10.4088/JCP.23r14885 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Shane J O'Connor Nilay Hewitt Joanna Kuc Lucinda S Orsini Source Type: research

Machine Learning Prediction of Quality of Life Improvement During Antidepressant Treatment of Patients With Major Depressive Disorder: A STAR*D and CAN-BIND-1 Report
Conclusions: Machine learning can predict normative QoL after antidepressant treatment with similar performance to that of prior work predicting depressive symptom response and remission. These results suggest that QoL outcomes in MDD patients can be predicted with simple patient-rated measures and provide a foundation to further improve performance and demonstrate clinical utility.Trial Registration: ClinicalTrials.gov identifiers NCT00021528 and NCT01655706.PMID:37967350 | DOI:10.4088/JCP.23m14864 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 15, 2023 Category: Psychiatry Authors: Tejas Phaterpekar John-Jose Nunez Emma Morton Yang S Liu Bo Cao Benicio N Frey Roumen V Milev Daniel J M üller Susan Rotzinger Claudio N Soares Valerie H Taylor Rudolf Uher Sidney H Kennedy Raymond W Lam Source Type: research

Pimavanserin 34 mg at Bedtime for the Treatment of Insomnia in 6 Veterans With Posttraumatic Stress Disorder
J Clin Psychiatry. 2023 Nov 6;84(6):23br14992. doi: 10.4088/JCP.23br14992.NO ABSTRACTPMID:37943987 | DOI:10.4088/JCP.23br14992 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 9, 2023 Category: Psychiatry Authors: Melissa B Jones Ritwick Agrawal Amir Sharafkhaneh Gursimrat Bhatti Ruosha Li Laura Marsh Ricardo E Jorge Source Type: research

Longitudinal Description and Prediction of Smoking Among Borderline Patients: An 18-Year Follow-Up Study
Conclusions: Taken together, the results of this study suggest that recovery status was an important element in the prevalence of smoking among borderline patients over time. They also suggest that smoking was predicted by 3 factors: prior psychopathology, demographics, and psychological maturity.PMID:37943989 | DOI:10.4088/JCP.22m14756 (Source: Journal of Clinical Psychiatry)
Source: Journal of Clinical Psychiatry - November 9, 2023 Category: Psychiatry Authors: Marcelo J A A Bra ñas Frances R Frankenburg Christina M Temes Garrett M Fitzmaurice Mary C Zanarini Source Type: research