Metabolic Monitoring for Adults Living with a Serious Mental Illness on a Second-Generation Antipsychotic Agent: A Scoping Review

Premature mortality in people living with a severe mental illness (SMI) is often attributed to multiple factors including the use of medicines such as antipsychotics. Second-generation antipsychotics (SGAs) are known to cause metabolic syndrome which can increase the risk of cardiovascular disease. Practice guidelines have recommended regular physical health monitoring, particularly of metabolic parameters, however, metabolic monitoring for people living with SMI using antipsychotics remains suboptimal. Therefore, highlighting the need for ongoing research. This scoping review aimed to provide an overview of current metabolic monitoring practices. We anticipate that this information will assist clinicians and policymakers and inform future research. The following databases were searched: MEDLINE (Ovid), Embase (Ovid), CINAHL (EBSCO), the Cochrane Database of Systemic Reviews (Wiley), APA PsycInfo (Ovid) and Scopus (Elsevier Science Publishers). The target group was adults (aged ≥ 18) diagnosed with SMI (including bipolar disorder, major depressive disorder and psychotic disorders) and taking SGAs. In total, 44 studies from 14 countries were retrieved. Our findings highlighted that most studies conducted in hospitals did not report on metabolic monitoring practices. Additionally, the roles and responsibilities of healthcare professionals in metabolic monitoring for SMI were infrequently described and parameters such as waist circumference and BMI were often poorly monitored. The scoping review highlights that no streamlined approach towards metabolic monitoring currently exists. There is a need to stipulate and define the roles and responsibilities of all health professionals involved in metabolic monitoring in SMI to optimise care for these individuals. Moreover, there is a need for ongoing research, particularly in the community setting, to promote increased accessibility to metabolic monitoring for SMI.

Impact of institutional quality improvement initiatives on metabolic monitoring in mental disorder in patients treated with antipsychotics: A meta-analysis of intervention studies

Background

Compliance with guidelines regarding monitoring of metabolic adverse effects induced by antipsychotics has been consistently low. We characterised and evaluated the quality of institutional quality improvement (QI) interventions designed to address disparities between guidelines and real-world practices. Furthermore, we assessed the impact of these interventions on the screening and management of metabolic risks for inpatients receiving treatment with antipsychotic medications.

Methods

We conducted a meta-analysis of institutional QI intervention studies aimed at improving antipsychotic-associated metabolic risk monitoring in hospitalised mental disease patients. Relevant studies were identified through searches conducted in the Embase and PubMed databases, as well as by reviewing previous reviews and meta-analyses. Quantitative analyses were performed, calculating odds ratios (ORs) and 95% confidence intervals (CIs) to assess the impact of QI programmes on guideline adherence in clinical practice.

Results

We identified 12 intervention studies (n = 10 128 and n = 2667 patients in the pre-and post-intervention groups, respectively) and included them in our meta-analysis. QI interventions demonstrated effectiveness in bridging the guideline-practice gap in monitoring antipsychotic-induced metabolic adverse effects, as supported by the ORs and 95% CIs for post-intervention monitoring of plasma glucose, lipids, and blood pressure (BP) vs the pre-intervention period being OR = 6.90 (95% CI = 1.51-31.48), OR = 5.39 (95% CI = 4.01-7.24), and OR = 4.81 (95% CI = 1.23-18.79), respectively. Only 33.3% (4/12) of studies reported screening rates for all four metabolic parameters (plasma glucose, lipids, weight/body mass index (BMI), and BP). The median rates for metabolic screening of plasma glucose, lipids, and BP increased from 51.0-80.0%, 28.7-66.7%, and 91.7-95.8%, respectively. Up to 66.7% (8/12) of intervention studies lacked follow-up measures to treat or manage identified risks in hospitalised psychiatric patients, such as patient referrals, prescription of medications, and switching of antipsychotics. The odds of monitoring weight/BMI and glucose were greatest when QI programmes involved the participation of multidisciplinary health care professionals and patients, yielding OR = 3.35 (95% CI = 2.45-4.59) and OR = 57.51 (95% CI = 24.11-137.21), respectively.

Conclusions

Institutional QI interventions were effective in enhancing monitoring practices in alignment with established guidelines for metabolic risk screening among hospitalised patients with mental disorders maintained on antipsychotic medications. Future institutional QI programmes should incorporate multidisciplinary strategies involving patient engagement and extend their focus beyond screening to incorporate follow-up risk management strategies once risks have been identified.

Registration

PROSPERO CRD42023452138.

Physical health assessment and cardiometabolic monitoring practices across three adult mental health inpatient units - a retrospective cohort study

Australians with lived experience of mental illness die on average 10 or more years earlier than the general population. Cardiometabolic disorders, including cardiovascular disease and diabetes mellitus, are common causes of premature death in this cohort. Little is known about cardiometabolic monitoring practices in mental health inpatient units. The aim of this study was to examine the characteristics of cardiometabolic monitoring and physical health assessments of adult mental health consumers within the first 72 hours of admission to an inpatient unit. We implemented a retrospective descriptive exploratory design by medical record audit. Data were collected using a pre-validated audit tool, adapted with recent literature and policy, from a randomly selected sample of consumers admitted to three acute mental health adult inpatient units of a large Australian metropolitan health service in 2016. Of 228 consumers, the mean age was 37.5 (range 18-64) years and 51.3% were women. Cardiometabolic risks were common, yet most consumers received incomplete cardiometabolic monitoring. While few consumers (15%) were diagnosed with cardiometabolic comorbidities, 67.5% were prescribed psychotropic medications with high cardiometabolic risk. Compliance with recommended cardiometabolic monitoring varied considerably between risk factors: for example, blood pressure was measured in 56.1% of consumers, whereas waist circumference was never recorded. There were no statistically significant associations between cardiometabolic monitoring completion and sex or cardiometabolic risk. These findings demonstrate the need for increased education and awareness of cardiometabolic risk and identify a critical gap between physical health assessment practices and recommendations for this cohort.

Schizophrenia and "unmet needs": From diagnosis to care in Italy

Background.

Schizophrenia is a leading cause of disability. People living with schizophrenia (PLWS) present unemployment, social isolation, excess mortality and morbidity, and poor quality of life. Early recognition and appropriate treatment reduce the risk of chronicity and comorbidity. Personalization and integration of pharmacological and psychosocial interventions, as well as accurate identification and management of psychiatric and somatic comorbidities, can significantly improve mental and physical health of PLWS, promoting recovery.

Methods.

A three-step Delphi approach was used to explore consensus on the essential components of early recognition and intervention, personalization, and integration of care to improve schizophrenia outcome, and on barriers and challenges to close treatment gaps. The consensus involved 8 Italian experts of schizophrenia, 100 psychiatrists from academic and nonacademic settings, including representatives of Italian Society of Psychiatry, and 65 trainees in psychiatry.

Results.

A strong consensus (from mostly agree to totally agree) emerged on the importance of early diagnosis (97%), standardized assessments (91%), correct management of somatic and psychiatric comorbidities (99%), and personalization and integration of care (94%). Lack of time, human resources, and training were identified as the main barriers and challenges to the translation of knowledge into clinical practice.

Conclusions.

The results of this Delphi study demonstrated a strong consensus on main components of schizophrenia care, as well as on unmet needs to promote best practice and gaps between knowledge and clinical practice. The involvement of a large group of professionals and trainees in this in-depth consensus process might contribute to raise awareness and stimulate innovative strategies to improve the outcome of PLWS.

Twelve-month prospective randomized study of pharmacists utilizing point-of-care testing for metabolic syndrome and related conditions in subjects prescribed antipsychotics

OBJECTIVE

Determine the percentage of subjects taking antipsychotics who meet criteria for metabolic syndrome based on point-of-care testing analyses. Evaluate pharmacist comprehensive medication management services using point-of-care tests to reduce the mean difference in number of metabolic syndrome risk parameters at 6 and 12 months.

METHOD

This 12-month, prospective, multisite, randomized, controlled study included 120 subjects taking antipsychotics (mean [SD] age of 42.9 [11.3] years) recruited from 3 community mental health clinics in Minnesota. Subjects consented to receive either pharmacist (PCS; n = 60) or no pharmacist (NCS; n = 60) comprehensive medication management services. Data were collected from February 2010 to January 2012.

RESULTS

No statistical differences in metabolic syndrome based on point-of-care tests were observed between the 2 groups at baseline (PCS: 85.2%, n = 46 versus NCS: 71.2%, n = 42, P = .073) or at 12 months (PCS: 84.4%, n = 38 versus NCS: 70.2%, n = 33, P = .104). Subjects, overall, screened positive at baseline for dyslipidemia (85.8%, n = 106), hypertension (52.5%, n = 63), and diabetes (22.5%, n = 27) based on point-of-care testing for metabolic risk criteria. After 12 months, a nonsignificant (P = .099) higher adjusted mean number of metabolic syndrome parameters in PCS subjects compared to NCS subjects (mean difference [95% CI] = 0.41 [-0.08 to 0.90]) were found.

CONCLUSIONS

A relatively high proportion of subjects met criteria for metabolic syndrome, although no significant improvement was observed between the groups after 12 months. Point-of-care test analyses identified a high proportion of subjects meeting criteria for dyslipidemia, hypertension, and diabetes. Utilizing point-of-care tests in mental health settings and fostering interprofessional partnerships with comprehensive medication management pharmacists may improve identification and long-term management of metabolic risks among patients prescribed antipsychotics.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02029989.

Guideline concordant monitoring of metabolic risk in people treated with antipsychotic medication: systematic review and meta-analysis of screening practices

BACKGROUND

Despite increased cardiometabolic risk in individuals with mental illness taking antipsychotic medication, metabolic screening practices are often incomplete or inconsistent.

METHOD

We undertook a systematic search and a PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) meta-analysis of studies examining routine metabolic screening practices in those taking antipsychotics both for patients in psychiatric care before and following implementation of monitoring guidelines.

RESULTS

We identified 48 studies (n=290 534) conducted between 2000 and 2011 in five countries; 25 studies examined predominantly schizophrenia-spectrum disorder populations; 39 studies (n=218 940) examined routine monitoring prior to explicit guidelines; and nine studies (n=71 594) reported post-guideline monitoring. Across 39 studies, routine baseline screening was generally low and above 50% only for blood pressure [69.8%, 95% confidence interval (CI) 50.9-85.8] and triglycerides (59.9%, 95% CI 36.6-81.1). Cholesterol was measured in 41.5% (95% CI 18.0-67.3), glucose in 44.3% (95% CI 36.3-52.4) and weight in 47.9% (95% CI 32.4-63.7). Lipids and glycosylated haemoglobin (HbA1c) were monitored in less than 25%. Rates were similar for schizophrenia patients, in US and UK studies, for in-patients and out-patients. Monitoring was non-significantly higher in case-record versus database studies and in fasting samples. Following local/national guideline implementation, monitoring improved for weight (75.9%, CI 37.3-98.7), blood pressure (75.2%, 95% CI 45.6-95.5), glucose (56.1%, 95% CI 43.4-68.3) and lipids (28.9%, 95% CI 20.3-38.4). Direct head-to-head pre-post-guideline comparison showed a modest but significant (15.4%) increase in glucose testing (p=0.0045).

CONCLUSIONS

In routine clinical practice, metabolic monitoring is concerningly low in people prescribed antipsychotic medication. Although guidelines can increase monitoring, most patients still do not receive adequate testing.

Targeted intervention to improve monitoring of antipsychotic-induced weight gain and metabolic disturbance in first episode psychosis

OBJECTIVE

International guidelines recommend monitoring for weight gain and metabolic disturbance in patients prescribed second generation antipsychotics. We aimed to investigate whether a targeted intervention could improve levels of monitoring in a first episode psychosis clinic.

METHOD

A pre-intervention audit of both metabolic screening rates and specific monitoring of weight and metabolic indices following the initiation of antipsychotic medication was performed in our first episode psychosis clinic. This was repeated 18 months later, following an intervention that included a number of targeted improvement strategies based on an analysis of barriers and enablers to performing monitoring within the clinic. The intervention included provision of monitoring equipment, interactive educational events, reminders and prompts and embedding processes for monitoring within team structure.

RESULTS

There were significant improvements in both the screening of metabolic indices and the monitoring of indices following initiation of antipsychotic medications. There were also improvements in the number of active interventions offered to clients by clinicians. However, the level of guideline concordant monitoring remains low within our service.

CONCLUSIONS

A comprehensive programme of implementation strategies can improve both screening and monitoring of the metabolic side-effects of antipsychotic medications. Further focused strategies are necessary to continue to improve monitoring to guideline concordant levels.