Antipsychotic Prescribing Research Articles

The impact of patient-facility language discordance on potentially inappropriate prescribing of antipsychotics in long-term care home in Ontario, Canada: a retrospective population health cohort study

BackgroundAppropriate use of medication is a key indicator of the quality of care provided in long-term care (LTC). The objective of this study was to determine whether resident-facility language concordance/discordance is associated with the odds of potentially inappropriate prescribing of antipsychotics (PIP-AP) in LTC.MethodsWe conducted a population-based, retrospective cohort study of LTC residents in Ontario, Canada from 2010 to 2019. We obtained resident language from standardized resident assessments, and derived facility language by determining the proportion of residents belonging to each linguistic group within individual LTC homes. Using linked administrative databases, we identified all instances of PIP-AP during a 1-year follow-up period. PIP-AP was defined using the STOPP-START criteria, which have previously been shown to predict adverse clinical events such as emergency department (ED) visits and hospitalizations. The association between linguistic factors and PIP-AP was assessed using adjusted multivariable logistic regression analysis.ResultsWe identified 198,729 LTC residents consisting of 162,814 Anglophones (81.9%), 6,230 Francophones (3.1%), and 29,685 Allophones (14.9%). The odds of PIP-AP of were higher for both Francophones (aOR 1.15, 95% CI 1.08–1.23) and Allophones (aOR 1.11, 95% CI 1.08–1.15) when compared to Anglophones. When compared to English LTC homes, French LTC homes had greater odds of PIP-AP (aOR 1.12, 95% CI 1.05–1.20), while Allophone homes had lower odds of PIP-AP (aOR 0.82, 95% CI 0.77–0.86). Residents living in language-discordant LTC homes had higher odds of PIP-AP when compared to LTC residents living in language-concordant LTC homes (aOR 1.07, 95% CI 1.04–1.10).ConclusionThis study identified linguistic factors related to the odds of PIP-AP in LTC, suggesting that the linguistic environment may have an impact on the quality of care provided to residents.

Antipsychotic prescribing practices and their association with rehospitalization in a forensic psychiatric sample

While there is extensive literature examining the effectiveness of antipsychotic prescribing to patients with schizophrenia spectrum or other psychotic disorders in general psychiatric services, there is a dearth of studies examining antipsychotic prescribing practices and their effectiveness in forensic psychiatric services. Forensic psychiatric patients have unique challenges often due to their high-profile offences, public scrutiny, and legal requirements. This longitudinal, retrospective study aimed to examine antipsychotic prescribing and rehospitalization rates in a forensic psychiatric sample, along with relevant socio-demographic, clinical, and forensic characteristics. All patients had a psychotic illness and were prescribed antipsychotic medication. The sample included 153 patients, of which the majority were male (85.6%), Caucasian (71.2%), middle aged (30s to 50s), had schizophrenia or schizoaffective disorder (76.5%), had a substance use disorder (62.1%), and had a most serious index offence against the person (80.4%). Atypical antipsychotics accounted for the majority of antipsychotic prescriptions (75.9%) and the sample had an antipsychotic polypharmacy rate of 39.9%. The sample was divided into four primary antipsychotic formulation types, which were oral (34.0%), injection (39.2%), clozapine (19.0%), and subtherapeutic (7.8%). Regarding rehospitalization, 52.9% of the sample was rehospitalized, with the average number of rehospitalizations being 1.2 (SD = 1.7) and proportion of the follow up period rehospitalized being 16.4% (SD = 27.7%). Patients prescribed clozapine had numerically lower rates of rehospitalization than those prescribed oral and injection formulation types, but it was not statistically significant. With a 19.0% prescription rate, clozapine may be underutilized in this sample. Further research is needed to demonstrate the potential benefits of clozapine regarding rehospitalization in forensic psychiatric patients, as has already been done in general psychiatry. Advancing treatment of the high-profile forensic population can reduce stigma toward people with mental illness and criminal justice involvement.

Exploring Connections Between Living Situations and Antipsychotic Prescribing Practices for People With Intellectual Disabilities

ObjectiveAntipsychotic prescribing practices in people with intellectual disabilities (ID) have sparked growing concerns about appropriateness and potential risks. The connection between living situations and antipsychotic prescribing practices in this population is a crucial but underexplored area. This study aims to investigate the association between living situation and antipsychotic prescriptions among people with ID.MethodsThis retrospective chart review included 112 adults with ID who received care from 2019 to 2021. The investigation examined participants' living situations and assessed antipsychotic prescription rates, antipsychotic class, the presence of a corresponding mental health diagnoses, and polypharmacy. Statistical analyses included univariate and multivariate tests to assess the relationship between living situations and antipsychotic prescriptions, controlling for relevant covariates.ResultsUnivariate analysis revealed a significant association between living situation and antipsychotic prescriptions (p < 0.05), with patients in non‐familial support homes and group homes more likely to receive antipsychotics. However, multivariate analysis did not confirm this association after adjusting for other variables. Male gender (OR = 4.207, 95% confidence interval (CI) 1.721–10.286) and total medication count (OR = 1.101, 95% CI 1.038–1.169) emerged as significant predictors of antipsychotic prescriptions.ConclusionsThese findings highlight the complexity of antipsychotic prescribing practices among people with ID. While living situation initially appeared to influence prescription patterns, multivariate analysis suggests the importance of considering other factors. Gender and medication count emerge as significant predictors, underscoring the need for tailored interventions and closer monitoring in this population.

Association Between Antipsychotic Medication Use and Dementia Risk in Patients With Schizophrenia or Schizoaffective Disorder.

To determine the association between antipsychotic prescriptions and incident dementia in patients with schizophrenia or schizoaffective disorder. In this retrospective cohort study, Cox Proportional hazard models estimated the association between antipsychotic prescriptions and incident dementia in participants ≥50 years of age with a schizophrenia/schizoaffective disorder diagnosis over 12years. Confounding was controlled by E-balance. Cumulative dementia incidence was significantly greater among those with an antipsychotic prescription compared to those without (7.9% vs 5.5%, P < 0.0001). After controlling for confounding, antipsychotic prescriptions were associated with a 92% increased risk for dementia (HR = 1.92; 95% CI:1.13-3.27). This association was not significant among those aged ≥65 years. Antipsychotic prescription type (eg, first generation, yes or no) did not affect dementia risk but prescription number did. Antipsychotic prescriptions were associated with almost twice the incidence of dementia compared to patients without in those with schizophrenia/schizoaffective disorder.

Neurodevelopmental or behavioural disorders in children conceived after assisted reproductive technologies: A nationwide cohort study

To study differences in risk for drug-treated neurodevelopmental or behavioural disorders in children conceived through assisted reproductive technologies in comparison with children conceived without assisted reproductive technologies and to examine if different treatments alter these risks. Nationwide registry-based cohort study. Liveborn children born in Denmark between 1994 and 2012 after assisted reproductive technologies in comparison to children conceived without assisted reproductive technologies aged 0-7. Conception following assisted reproductive technologies treatment, including in vitro fertilisation, intra-cytoplasmic sperm injection, intrauterine insemination and 'others' comprising frozen embryo transfer, and frozen embryo transfer in both in vitro fertilisation and intra-cytoplasmic sperm injection and testicular sperm aspiration. Prescription of neurodevelopmental or behavioural disorders medication in offspring: Antipsychotics, anxiolytics, antidepressants, antiepileptics, attention deficit hyperactivity disorder medication and hypnotics/sedatives obtained from nationwide registers. Unadjusted and adjusted odds ratios with 95% confidence intervals were calculated. The association was examined in different sensitivity analyses, including sibling and mediator analyses. In total, 57,964 (4.7%) children conceived after assisted reproductive technologies and 1,183,070 (95.3%) children not conceived using assisted reproductive technologies were included. The adjusted analysis showed higher odds of prescribing neurodevelopmental or behavioural medication to assisted reproductive technology-conceived children (OR 1.15; 95% Cl 1.09-1.20) compared to other children. Prescription of antipsychotics in assisted reproductive technology-conceived children was the most common association in intrauterine insemination treatments, hypnotics/sedatives with both including in vitro fertilisation and intra-cytoplasmic sperm injection and antiepileptics with 'other' treatments. Birth weight partially mediated the association between assisted reproductive technologies and diminished the odds of neurodevelopmental or behavioural medication use in children conceived using assisted reproductive technologies. Sibling analysis showed no increased risk for the first-born child conceived without assisted reproductive technology vs. the second-born child conceived with assisted reproductive technology and vice-versa. Based on the minor observed effects, a potentially higher increased attentiveness of assisted reproductive technology parents, the demonstrated mediation effect of birth weight and preterm birth on the observed association, and the no effect of the within-mother analysis, we find little evidence for increased risk of neurodevelopmental or behavioural disorders in children conceived using assisted reproductive technologies.

Age and sex differences in outpatient antipsychotic prescriptions for schizophrenia: a claims data study.

Most studies on antipsychotic efficacy and safety, including sex differences, focus on young schizophrenia patients. However, with an aging population, the number of older schizophrenia patients is increasing. This group faces challenges due to varying treatment responses and higher risks of adverse reactions, and guidelines often lack specific recommendations due to insufficient trials. Therefore, we investigated how age and sex influence antipsychotic prescribing practices in schizophrenia using the German Pharmacoepidemiological Research Database (GePaRD). We included patients diagnosed with schizophrenia (ICD-10 code F20.X) who had been prescribed at least one antipsychotic on an outpatient basis in at least two consecutive quarters in 2020, analyzing prescription data for 49,681 patients. Key findings include a notable preference for second-generation antipsychotics (SGAs) across all age groups, especially in younger patients, possibly due to their perceived better tolerability and efficacy. Treatment intensity with SGAs (expressed as the defined daily doses of SGAs per patient in 2020) initially increased with age, peaked among 35- to 44-year-olds, and then decreased, with the lowest treatment intensity in patients aged 65years and older. The prescription patterns of specific SGAs and first-generation antipsychotics varied across age groups, highlighting the complexity of treatment decisions in schizophrenia management. Sex differences in prescription frequency and treatment intensity were also observed. The basic recommendation of the guideline to consider sex and age when prescribing antipsychotics therefore appears to be followed. Whether this prescribing practice is really optimal for older male and female schizophrenia patients, however, still needs to be proven in clinical trials.

Appropriate Prescribing of Antipsychotic Medication Amongst Long-Term Care Facility Residents Admitted to Hospital

Abstract Background In Ireland, it is estimated that up to 45% of long-term care facility residents (LTCR) living with dementia are prescribed antipsychotic medication1. Although antipsychotics have moderate benefit in treating neuropsychiatric symptoms, their use must be carefully weighed against an adverse side effect profile. This study aims to describe the prevalence of antipsychotic usage in LTCR admitted to hospital, and to determine the appropriateness of the prescription as outlined by the National Clinical Guideline 21. This study describes the efficacy of a new Nursing Home Liaison (NHL) service (consisting of two advanced practice nurses) in reducing inappropriate prescribing. Methods Hospital admissions were screened daily to identify LTCR. Medical chart and drug kardex review was performed to collect demographic data, dementia diagnosis, and antipsychotic prescription. Anticholinergic burden was calculated using the ACB score. If the indication for antipsychotic was not clear post review, the NHL service obtained collateral history to determine reason for prescription, making recommendations to wean and stop the medication where appropriate. Results Data was prospectively collected on 50 consecutive LTCR, 28 (57%) were male and the average age was 81years. 26 (51%) of patients had a diagnosis of dementia. A total of 11 (22%) patients were prescribed antipsychotics; of these, seven (64%) had dementia and the rest had psychiatric diagnoses. The mean anticholinergic burden was 2.4 (range 0-7). Five (45%) of the antipsychotic prescriptions were not justified as per Guideline 21 or were no longer needed. These were amended as per the advice of the NHL service. Conclusion This study highlights rates of inappropriate prescribing of antipsychotics among LTCR, resulting in high anticholinergic burden and the associated risks. Medication review and advice from a specialist NHL service, was effective in reducing inappropriate prescriptions. Further education and dissemination of Guideline 21 is prudent to ensure proper prescribing and de-prescribing practices.

Optimising Delirium Pathways in Geriatric Care: The Impact of Consultant Led Old Age Psychiatry Liaison Service

Abstract Background Delirium is a common and severe condition affecting up to 50% of older adults in hospitals. Delirium is compounded by the noisy and frightening environment of medical wards, often leading to prescription of antipsychotics. There is often no clear plan to monitor effects of these medications. Delirium is also associated with increased rates of institutionalised care on discharge, readmission rates and mortality. Methods This QIP examines the effectiveness of interventions for patients with delirium in COE wards, focusing on involvement of consultant led old-age psychiatry liaison service. This 2-cycle process included 106 patients in the 1st cycle (Feb 2020-Sep 202, nurse-led), and 64 patients in the 2nd cycle (Nov 2022-Aug 2023, consultant-led). Outcome measures the number of patients assessed, new antipsychotic prescription, new nursing home placement, follow-up plans, readmission rate, and 1year mortality. Results The QIP revealed an increase in the number of inpatients reviewed by the POA team (330%) and planned out-patient POA follow-up (320%). There was an increase in the number of antipsychotics prescribed on discharge (61.5%) and discharge to a new appropriate placement (27.6%). The overall readmissions rates had slightly decreased (2.5%), and readmissions with delirium had further reduced (4%) (not significant, p=0.66). The overall mortality rate increased by 4% since the introduction of these measures (not significant, p=0.63), however, this is small and at a level expected with this population group. Conclusion These results suggest that the new consultant led liaison team resulted in an increased use of their expert opinion on challenging patients with delirium. Significantly, more patients received psychiatric follow-up crucial for antipsychotic monitoring. There is a slight reduction in the readmission rates. Although, the increase in the mortality rate is insignificant, this warrants a closer look as antipsychotics are associated with cardiovascular diseases. A larger study over a longer period of time would provide more useful data.

Antipsychotic Prescribing and Falls Risk in Nursing Home Residents with Dementia

Abstract Background Falls are a common syndrome in older adults leading to adverse outcomes including functional decline, activity restriction, injury and death. They can still occur in residential care. We examined prescribing of medications included in STOPPFall (Screening Tool of Older Persons Prescriptions in older adults with high fall risk) (1) in nursing home residents with dementia. Methods A point prevalence audit was conducted in a dementia-specific nursing home. Data were collected from the electronic healthcare record on demographics, dementia severity, and number of falls in the preceding 12 months. The number and class of regular medications were recorded. Non-cognitive symptoms of dementia were quantified using the Cohen Mansfield Agitation Inventory (CMAI). Results Seventy-four residents were included with mean age 82 years, 59(70%) female. The average Mini Mental State Examination (MMSE) was 5/30 and 80% had severe dementia. The average CMAI score was 50. The mean number of falls was 3 (range 0-14). Regular prescribing of specific STOPPFall medications was as follows: antipsychotics 42/74 (57%), benzodiazepines 8/74 (11%), opioids 13/74 (18%), antidepressants 44/74 (59%), antiepileptics 11.74 (15%), diuretics 12/74 (16%). Prescription of a regular antipsychotic was associated with one or more falls (OR 3.19, p = 0.029). There was no significant difference in falls with the other medications studied. The number of falls increased with higher agitation scores. Conclusion Antipsychotics increased the risk of falls in a nursing home setting. Fallers had higher rates of agitation, perhaps explaining the increased usage of antipsychotics. Medications should be reviewed on a regular basis and deprescribing considered where appropriate. Reference 1. Seppala LJ, Petrovic M, Ryg J, Bahat G, Topinkova E, Szczerbińska K, et al. STOPPFall (Screening Tool of Older Persons Prescriptions in older adults with high fall risk): a Delphi study by the EuGMS Task and Finish Group on Fall-Risk-Increasing Drgs. Age and Ageing. 2020;50(4):1189-99.

Improving Delirium Care: A Retrospective Audit of Early Detection and Management Practices

Abstract Background Delirium, an acute change in cognition, consciousness, attention, and perception, is prevalent among older adults in hospitals. Patients with delirium experience longer hospital stays, higher fall risks, increased mortality, and greater care needs upon discharge. However, delirium is under-recognized, with up to 50% of cases missed. With an aging population, the need for improved delirium recognition and management is critical. Methods We conducted a retrospective audit on the charts of 47 patients over the age of 65 on two General Medical Wards at an Irish Model 3 hospital. We assessed medical admission proformas and notes to evaluate delirium recognition and management within the first 24 hours. The audit measured compliance with the 4AT cognitive screening tool, documentation of delirium and risk factors, non-pharmacological management, and antipsychotic use against HSE National Guidelines. Data was analysed in Excel. Results 47 patients with a median age of 80 years, 51% (n=24) male and 49% (n=23) female, were captured. Cognitive screening within 24 hours was performed in 34% (n=16) of patients, with 75% (n=12) showing abnormal results. Delirium was documented in 8.5% (n=4) of patients, and 50% (n=2) of these had a 4AT score recorded. 15% (n=7) were prescribed new antipsychotics within 24 hours, with 57% (n=4) lacking a formal delirium diagnosis. Conclusion This audit reveals deficiencies in initial cognitive screening and delirium recognition among high-risk patients. Only 8.5% of the cohort was identified with delirium compared to national statistics that suggest up to 31% of older patients are affected upon admission. Compliance with cognitive screening and diagnostic tool use was poor. Antipsychotic prescribing without a documented delirium diagnosis was prevalent, highlighting the need for improved diagnostic accuracy and non-pharmacological management. We plan to introduce a “Delirium Tool” for 4AT assessments and “PINCH-ME” risk-factors, alongside regular education sessions. A re-audit will measure improvements in care and outcomes.

Clozapine, relapse, and adverse events: a 10-year electronic cohort study in Canada.

Clozapine is the most effective medication for treatment-resistant psychoses, but the balance of benefits and risks is understudied in real-world settings. To examine the relative re-hospitalisation rates for mental health relapse and adverse events associated with clozapine and other antipsychotics in adult and child/youth cohorts. Data were obtained from the Canadian Institute of Health Information for adults (n = 45 616) and children/youth (n = 1476) initially hospitalised for mental health conditions in British Columbia, Manitoba and Saskatchewan from 2008 to 2018. Patient demographics and hospitalisations were linked with antipsychotic prescriptions dispensed following the initial visit. Recurrent events survival analysis for relapse and adverse events were created and compared between clozapine and other antipsychotics. In adults, clozapine was associated with a 14% lower relapse rate versus other drugs (adjusted hazard ratio: 0.86, 95% CI: 0.83-0.90) over the 10-year follow-up. In the first 21 months, the relapse rate was higher for clozapine but then reversed. Over 1000 person-months, clozapine-treated adults could be expected to have 38 relapse hospitalisations compared with 45 for other drugs. In children/youth, clozapine had a 38% lower relapse rate compared with other antipsychotic medications (adjusted hazard ratio: 0.62, 95% CI: 0.49-0.78) over the follow-up period. This equates to 29 hospitalisations for clozapine and 48 for other drugs over 1000 person-months. In adults, clozapine had a higher risk for adverse events (hazard ratio: 1.34, 95% CI: 1.18-1.54) over the entire follow-up compared with other antipsychotics. This equates to 1.77 and 1.30 hospitalisations over 1000 person-months for clozapine and other drugs, respectively. Clozapine was associated with lower relapse overall, but this was accompanied by higher adverse events for adults. For children/youth, clozapine was associated with lower relapse all throughout and had no difference in adverse events compared with other antipsychotics.

Development and Validation of Machine Learning Models to Predict Postoperative Delirium Using Clinical Features and Polysomnography Variables.

Background: Delirium affects up to 50% of patients following high-risk surgeries and is associated with poor long-term prognosis. This study employed machine learning to predict delirium using polysomnography (PSG) and sleep-disorder questionnaire data, and aimed to identify key sleep-related factors for improved interventions and patient outcomes. Methods: We studied 912 adults who underwent surgery under general anesthesia at a tertiary hospital (2013-2024) and had PSG within 5 years of surgery. Delirium was assessed via clinical diagnoses, antipsychotic prescriptions, and psychiatric consultations within 14 days postoperatively. Sleep-related data were collected using PSG and questionnaires. Machine learning predictions were performed to identify postoperative delirium, focusing on model accuracy and feature importance. Results: This study divided the 912 patients into an internal training set (700) and an external test set (212). Univariate analysis identified significant delirium risk factors: midazolam use, prolonged surgery duration, and hypoalbuminemia. Sleep-related variables such as fewer rapid eye movement (REM) episodes and higher daytime sleepiness were also linked to delirium. An extreme gradient-boosting-based classification task achieved an AUC of 0.81 with clinical variables, 0.60 with PSG data alone, and 0.84 with both, demonstrating the added value of PSG data. Analysis of Shapley additive explanations values highlighted important predictors: surgery duration, age, midazolam use, PSG-derived oxygen saturation nadir, periodic limb movement index, and REM episodes, demonstrating the relationship between sleep patterns and the risk of delirium. Conclusions: The artificial intelligence model integrates clinical and sleep variables and reliably identifies postoperative delirium, demonstrating that sleep-related factors contribute to its identification. Predicting patients at high risk of developing postoperative delirium and closely monitoring them could reduce the costs and complications associated with delirium.

Characterising the nature of psychiatric disorders and patterns of antipsychotic medications prescribed in a psychiatric ward in a public hospital in Tasmania.

We present an evaluation of antipsychotic prescribing in an inpatient psychiatry ward in Hobart, Tasmania, to establish pattern of use, alignment with other psychiatric wards orcentres and the recommendations in the Royal Australian and New Zealand College of Psychiatry Clinical Practice Guidelines, and to determine predictors of polypharmacy. A descriptive cross-sectional survey design was used. Data from 118 patients discharged from the Royal Hobart Hospital (RHH) Mental Health Inpatient Unit between 01/02/2021 to 01/08/2021 were evaluated. Antipsychotic polypharmacy (APP) was observed in 40% of patients. When low doses of adjunctive ('PRN') use of olanzapine and quetiapine were excluded, the APP proportion was 35%. APP was predicted by age and by a schizophrenia diagnosis. Long-acting injections (LAIs) were used in 46% of the patients. The most common LAI was risperidone (52%). Average daily dose of antipsychotic at the time of discharge was 529mg chlorpromazine (CPZ) equivalents. High dose antipsychotics (more than 1000mg CPZ equivalents per day) was observed in 13% of the patients. The observed prescribing practice is consistent with other clinical settings. Antipsychotic prescribing practice should, however, continue to be monitored to ensure adherence to best practice guidelines.

Antipsychotic prescription patterns among schizophrenia patients in Guangdong Province, China’s 686 program: A retrospective study

Schizophrenia is a severe mental disorder. However, there is limited data on the prescribing patterns of patients under China’s Central Government Support for the Local Management and Treatment of Severe Mental Illnesses Program, known as the “686 program.” This study aimed to investigate the use of antipsychotic medications and associated factors among discharged schizophrenia patients in Guangdong Province, within the 686 Program. This study encompassed schizophrenia patients who were discharged from the Affiliated Brain Hospital, Guangzhou Medical University and enrolled in the 686 Program between January 2019 and December 2019. A total of 1645 hospitalized schizophrenia patients were included in the analysis. Clinical and sociodemographic data were acquired from medical records upon discharge. A total of 15 unique antipsychotic medications were utilized, comprising 4 first-generation (FGAs) and 11 second-generation (SGAs) options. FGAs were prescribed at a rate of 8.3%, while SGAs dominated at 98.8%. Risperidone (40.8%), olanzapine (30.2%), clozapine (24.6%), and amisulpride (15.4%) emerged as the top 4 prescribed medications. Additionally, mood stabilizers were used by 20.4%, antidepressants by 14.8%, sedative-hypnotics by 33.6%, anticholinergics by 26.9%, and other internal medicine drugs by 46.4%. Notably, 60.5% received antipsychotic monotherapy (AMT), while 39.5% underwent antipsychotic polypharmacy (APP). Predictors of polypharmacy included multiple hospital admissions, longer hospital stays, and undergoing modified Electroconvulsive Therapy (mECT) during hospitalization. In Guangdong Province, China’s 686 Program, hospitalized patients commonly receive multiple antipsychotic medications simultaneously. Due to the varying outcomes in current studies on the benefits and risks of polypharmacy, it’s vital to educate psychiatrists about the importance of AMT to reduce APP. Additionally, randomized, controlled trials are essential to identify the safest and most effective antipsychotic combinations, as well as to understand which patient profiles may benefit from these combinations.

Initiation and Persistence of Antipsychotic Medications at Hospital Discharge Among Community-Dwelling Veterans With Dementia

ObjectivesAdults with dementia are frequently prescribed antipsychotic medications despite concerns that risks outweigh benefits. Understanding conditions where antipsychotics are initially prescribed, such as hospitalization, may offer insights into reducing inappropriate use. Design, Setting, ParticipantsRetrospective cohort study of community-dwelling veterans with dementia aged ≥68 with VA hospitalizations in 2014, using Veterans Health Administration (VA) and Medicare data. MeasurementsThe primary outcome was new outpatient antipsychotic prescription at hospital discharge. We used generalized estimating equations to study associations between antipsychotic initiation and patient, hospitalization, and facility characteristics. Among veterans with antipsychotic initiation, we used a cumulative incidence function to evaluate discontinuation in the year following hospitalization, accounting for competing risks. Results4,719 community-dwelling veterans with dementia had VA hospitalizations in 2014; 264 (5.6%) filled new antipsychotic prescriptions at discharge. Antipsychotic initiation was associated with discharge unit (surgical vs medical, OR 0.41, 95% CI 0.19–0.87; psychiatric vs medical, OR 6.58, 95% CI 4.48–9.67), length of stay (OR 1.03/day, 95% CI 1.02–1.05), and delirium diagnosis (OR 2.61, 95% CI 1.78–3.83), but not demographic or facility characteristics. Among veterans with antipsychotic initiation, the 1-year cumulative incidence of discontinuation was 18.2% (n = 47); 15.9% (n = 42) of those who were alive and not censored remained on antipsychotics at 1 year. ConclusionsAntipsychotic initiation at hospital discharge was uncommon among community-dwelling veterans with dementia; however, once initiated, antipsychotic persistence at 1 year was common among those who remained community-dwelling. Hospitalization is a contributor to potentially-inappropriate medications in the community, suggesting an opportunity for medication review after hospitalization.

Prediction of Clinical Outcomes in Psychotic Disorders Using Artificial Intelligence Methods: A Scoping Review.

Psychotic disorders are major psychiatric disorders that can impact multiple domains including physical, social, and psychological functioning within individuals with these conditions. Being able to better predict the outcomes of psychotic disorders will allow clinicians to identify illness subgroups and optimize treatment strategies in a timely manner. In this scoping review, we aimed to examine the accuracy of the use of artificial intelligence (AI) methods in predicting the clinical outcomes of patients with psychotic disorders as well as determine the relevant predictors of these outcomes. This review was guided by the PRISMA Guidelines for Scoping Reviews. Seven electronic databases were searched for relevant published articles in English until 1 February 2024. Thirty articles were included in this review. These studies were mainly conducted in the West (63%) and Asia (37%) and published within the last 5 years (83.3%). The clinical outcomes included symptomatic improvements, illness course, and social functioning. The machine learning models utilized data from various sources including clinical, cognitive, and biological variables such as genetic, neuroimaging measures. In terms of main machine learning models used, the most common approaches were support vector machine, random forest, logistic regression, and linear regression models. No specific machine learning approach outperformed the other approaches consistently across the studies, and an overall range of predictive accuracy was observed with an AUC from 0.58 to 0.95. Specific predictors of clinical outcomes included demographic characteristics (gender, socioeconomic status, accommodation, education, and employment); social factors (activity level and interpersonal relationships); illness features (number of relapses, duration of relapses, hospitalization rates, cognitive impairments, and negative and disorganization symptoms); treatment (prescription of first-generation antipsychotics, high antipsychotic doses, clozapine, use of electroconvulsive therapy, and presence of metabolic syndrome); and structural and functional neuroimaging abnormalities, especially involving the temporal and frontal brain regions. The current review highlights the potential and need to further refine AI and machine learning models in parsing out the complex interplay of specific variables that contribute to the clinical outcome prediction of psychotic disorders.

Pharmacotherapy and electroconvulsive therapy prescription for women with depressive and anxiety disorders in a psychiatric mother-baby unit.

The purpose of this study was to understand the pharmacotherapy and electroconvulsive therapy (ECT) prescription of women with depression and anxiety admitted to an Australian inpatient psychiatric mother-baby unit (MBU) and compare prescription to national clinical practice guidelines. A retrospective audit was conducted on women diagnosed with depression or anxiety admitted to a public psychiatric inpatient MBU from March 2017 to July 2019. Data was captured at three time points to assess demographic, clinical and pharmacotherapy treatment characteristics. Descriptive statistics were completed. Of the 74 women, 57 women had depression, with 73% prescribed Selective Serotonin Reuptake Inhibitors (SSRIs) and 14% provided ECT during admission. For women with anxiety (n = 17), 23% were prescribed a benzodiazepine with concurrent antidepressant prescription. SSRI prescription increased, with other antidepressant prescription up trending through admission. Atypical antipsychotic prescription was increased initially and trended downwards at discharge. This study explored the therapeutic armamentarium employed for the treatment of mothers admitted to an inpatient psychiatric MBU with depression and anxiety. The results point to the intricate prescribing practices in a naturalistic setting and highlight that prescribing practices were in line with national guidelines.

Antipsychotic Treatment in People at Clinical High Risk for Psychosis: A Narrative Review of Suggestions for Clinical Practice.

The "early intervention" paradigm in psychiatry holds significant promise for preventing psychosis. Recent evidence showed that individuals at clinical high risk for psychosis (CHR-P) with antipsychotic (AP) prescription at baseline have higher psychosis transition rates compared with those without AP, although the underlying cause remains unclear. In this article, we reviewed international guidelines on early intervention in CHR-P people, paying specific attention to clinical recommendations on AP treatment. Then, we comment on these suggestions in the light of recent empirical evidence examining AP prescription in CHR-P populations within "real-world" clinical settings. This search was conducted on PubMed/MEDLINE, PsycINFO, EMBASE, and Google, looking for both "Guidelines AND CHR-P OR UHR OR Early Psychosis." International guidelines generally recommend not using AP as first-line treatment, but only when psychosocial interventions have failed. CHR-P people with AP drug showed high prevalence rates and had more severe clinical picture at entry. Is this a "warning signal" for potentially higher psychosis transition risk? Is it a direct AP iatrogenic effect? Is it possible to detect specific CHR-P subgroup that may benefit from AP? These are the questions that this article seeks to explore. The current framework for identifying CHR-P subjects has defined psychometric criteria mainly based on positive symptoms. In our opinion, this is reductive, especially for evaluating therapeutic outcomes and prognosis. A more comprehensive assessment considering quality of life, psychiatric comorbidity, persistent negative symptoms, subjective experience of CHR-P psychopathology, and social/personal recovery is thus needed.

Profiles of healthcare use of persons living with dementia: A population-based cohort study.

Persons living with dementia are a heterogeneous population with complex needs whose healthcare use varies widely. This study aimed to identify the healthcare use profiles in a cohort of persons with incident dementia, and to describe their characteristics. This is a retrospective cohort study of health administrative data in Quebec (Canada). The study population included persons who: (i) had an incident dementia diagnosis between 1 April 2015 and 31 March 2016; (ii) were aged ≥65 years and living in the community at the time of diagnosis. We carried out a latent class analysis to identify subgroups of healthcare users. The final number of groups was chosen based on clinical interpretation and statistical indicators. The study cohort consisted of 15 584 individuals with incident dementia. Four profiles of healthcare users were identified: (i) Low Users (36.4%), composed of individuals with minimal healthcare use and fewer comorbidities; (ii) Ambulatory Care-Centric Users (27.5%), mainly composed of men with the highest probability of visiting cognition specialists; (iii) High Acute Hospital Users (23.6%), comprised of individuals mainly diagnosed during hospitalization, with higher comorbidities and mortality rate; and (iv) Long-Term Care Destined Users (12.5%), who showed the highest proportion of antipsychotics prescriptions and delayed hospitalization discharge. We identified four distinct subgroups of healthcare users within a population of persons living with dementia, providing a valuable context for the development of interventions tailored to specific needs within this diverse population. Geriatr Gerontol Int 2024; 24: 789-796.

A real-world data analysis of electronic health records to investigate the associations of predominant negative symptoms with healthcare resource utilisation, costs and treatment patterns among patients with schizophrenia

ObjectivesNegative symptoms in schizophrenia are associated with significant illness burden. We sought to investigate clinical outcomes for patients with schizophrenia who present with predominant negative symptoms (PNS) vs without PNS.DesignRetrospective...