Prevalence and correlates of subjective cognitive impairment in Chinese psychiatric patients during the fifth wave of COVID-19 in Hong Kong

IntroductionThe extent of cognitive impairment and its association with psychological distress among people with pre-existing mental illness during COVID-19 is understudied. This study aimed to investigate prevalence and correlates of subjective cognitive impairment (SCI) in Chinese psychiatric patients during fifth-wave of COVID-19 in Hong Kong (HK).MethodsFour-hundred-eight psychiatric outpatients aged 18–64 years were assessed with questionnaires between 28 March and 8 April 2022, encompassing illness profile, psychopathological symptoms, coping-styles, resilience, and COVID-19 related factors. Participants were categorized into moderate-to-severe and intact/mild cognitive impairment (CI+ vs. CI-) groups based on severity of self-reported cognitive complaints. Univariate and multivariate regression analyses were conducted to determine variables associated with CI+ status.ResultsOne-hundred-ninety-nine participants (48.8%) experienced CI+. A multivariate model on psychopathological symptoms found that depressive and post-traumatic-stress-disorder (PTSD)-like symptoms were related to CI+, while a multivariate model on coping, resilience and COVID-19 related factors revealed that avoidant coping, low resilience and more stressors were associated with CI+. Final combined model demonstrated the best model performance and showed that more severe depressive and PTSD-like symptoms, and adoption of avoidant coping were significantly associated with CI+.ConclusionAlmost half of the sample of psychiatric patients reported cognitive complaints during fifth-wave of COVID-19 in HK. Greater depressive and PTSD-like symptom severity, and maladaptive (avoidant) coping were found as correlates of SCI. COVID-19 related factors were not independently associated with SCI in psychiatric patients. Early detection with targeted psychological interventions may therefore reduce psychological distress, and hence self-perceived cognitive difficulties in this vulnerable population

Development of an individualized risk calculator of treatment resistance in patients with first-episode psychosis (TRipCal) using automated machine learning: a 12-year follow-up study with clozapine prescription as a proxy indicator

Abstract About 15–40% of patients with schizophrenia are treatment resistance (TR) and require clozapine. Identifying individuals who have higher risk of development of TR early in the course of illness is important to provide personalized intervention. A total of 1400 patients with FEP enrolled in the early intervention for psychosis service or receiving the standard psychiatric service between July 1, 1998, and June 30, 2003, for the first time were included. Clozapine prescriptions until June 2015, as a proxy of TR, were obtained. Premorbid information, baseline characteristics, and monthly clinical information were retrieved systematically from the electronic clinical management system (CMS). Training and testing samples were established with random subsampling. An automated machine learning (autoML) approach was used to optimize the ML algorithm and hyperparameters selection to establish four probabilistic classification models (baseline, 12-month, 24-month, and 36-month information) of TR development. This study found 191 FEP patients (13.7%) who had ever been prescribed clozapine over the follow-up periods. The ML pipelines identified with autoML had an area under the receiver operating characteristic curve ranging from 0.676 (baseline information) to 0.774 (36-month information) in predicting future TR. Features of baseline information, including schizophrenia diagnosis and age of onset, and longitudinal clinical information including symptoms variability, relapse, and use of antipsychotics and anticholinergic medications were important predictors and were included in the risk calculator. The risk calculator for future TR development in FEP patients (TRipCal) developed in this study could support the continuous development of data-driven clinical tools to assist personalized interventions to prevent or postpone TR development in the early course of illness and reduce delay in clozapine initiation

Table_1_Prevalence and correlates of subjective cognitive impairment in Chinese psychiatric patients during the fifth wave of COVID-19 in Hong Kong.DOCX

IntroductionThe extent of cognitive impairment and its association with psychological distress among people with pre-existing mental illness during COVID-19 is understudied. This study aimed to investigate prevalence and correlates of subjective cognitive impairment (SCI) in Chinese psychiatric patients during fifth-wave of COVID-19 in Hong Kong (HK).MethodsFour-hundred-eight psychiatric outpatients aged 18–64 years were assessed with questionnaires between 28 March and 8 April 2022, encompassing illness profile, psychopathological symptoms, coping-styles, resilience, and COVID-19 related factors. Participants were categorized into moderate-to-severe and intact/mild cognitive impairment (CI+ vs. CI-) groups based on severity of self-reported cognitive complaints. Univariate and multivariate regression analyses were conducted to determine variables associated with CI+ status.ResultsOne-hundred-ninety-nine participants (48.8%) experienced CI+. A multivariate model on psychopathological symptoms found that depressive and post-traumatic-stress-disorder (PTSD)-like symptoms were related to CI+, while a multivariate model on coping, resilience and COVID-19 related factors revealed that avoidant coping, low resilience and more stressors were associated with CI+. Final combined model demonstrated the best model performance and showed that more severe depressive and PTSD-like symptoms, and adoption of avoidant coping were significantly associated with CI+.ConclusionAlmost half of the sample of psychiatric patients reported cognitive complaints during fifth-wave of COVID-19 in HK. Greater depressive and PTSD-like symptom severity, and maladaptive (avoidant) coping were found as correlates of SCI. COVID-19 related factors were not independently associated with SCI in psychiatric patients. Early detection with targeted psychological interventions may therefore reduce psychological distress, and hence self-perceived cognitive difficulties in this vulnerable population.</p