Type of study and findings.

<p>Type of study and findings.</p

Models to predict relapse in psychosis: A systematic review

<div><p>Background</p><p>There is little evidence on the accuracy of psychosis relapse prediction models. Our objective was to undertake a systematic review of relapse prediction models in psychosis.</p><p>Method</p><p>We conducted a literature search including studies that developed and/or validated psychosis relapse prediction models, with or without external model validation. Models had to target people with psychosis and predict relapse. The key databases searched were; Embase, Medline, Medline In-Process Citations & Daily Update, PsychINFO, BIOSIS Citation Index, CINAHL, and Science Citation Index, from inception to September 2016. Prediction modelling studies were assessed for risk of bias and applicability using the PROBAST tool.</p><p>Results</p><p>There were two eligible studies, which included 33,088 participants. One developed a model using prodromal symptoms and illness-related variables, which explained 14% of relapse variance but was at high risk of bias. The second developed a model using administrative data which was moderately discriminative (C = 0.631) and associated with relapse (OR 1.11 95% CI 1.10, 1.12) and achieved moderately discriminative capacity when validated (C = 0.630). The risk of bias was low.</p><p>Conclusions</p><p>Due to a lack of high quality evidence it is not possible to make any specific recommendations about the predictors that should be included in a prognostic model for relapse. For instance, it is unclear whether prodromal symptoms are useful for predicting relapse. The use of routine data to develop prediction models may be a more promising approach, although we could not empirically compare the two included studies.</p></div

PRISMA Flowchart of search and review strategy.

<p>PRISMA Flowchart of search and review strategy.</p

Quality assessment of studies included in the systematic review–areas of concern using PROBAST guidelines.

<p>Quality assessment of studies included in the systematic review–areas of concern using PROBAST guidelines.</p

Study flow diagram.

BMI, body mass index; B&A, Black and Asian ethnic groups; HES, Hospital Episode Statistics.</p

Percentage of adults with overweight or obesity in England as recorded in CPRD GOLD.

a, by (a) sex, (b) age categoryb, and (c) regionc. aIncludes data from January 2007 until June 2020. bAge at end of study period (earliest of: death, transfer out from practice, end of practice data collection). cEast Midlands and North East drop out of the dataset after 2015 and 2017, respectively. (DOCX)</p

Characteristics of adults with severe and complex obesity in CPRD GOLD undergoing bariatric surgery in England, by BMI group (all years 2007–2020).

Characteristics of adults with severe and complex obesity in CPRD GOLD undergoing bariatric surgery in England, by BMI group (all years 2007–2020).</p

Approved ISAC protocol including statistical analysis plan.

ISAC, Independent Scientific Advisory Committee. (PDF)</p

Adjusted RRs for WM referral within adults eligible for WM referral in England with at least 2 years of follow-up data in CPRD GOLD (2007–2020)—People with unknown ethnicity dropped (<i>n =</i> 284,156).

Adjusted RRs for WM referral within adults eligible for WM referral in England with at least 2 years of follow-up data in CPRD GOLD (2007–2020)—People with unknown ethnicity dropped (n = 284,156).</p

Exposure definitions^a.

BackgroundAdults living with overweight/obesity are eligible for publicly funded weight management (WM) programmes according to national guidance. People with the most severe and complex obesity are eligible for bariatric surgery. Primary care plays a key role in identifying overweight/obesity and referring to WM interventions. This study aimed to (1) describe the primary care population in England who (a) are referred for WM interventions and (b) undergo bariatric surgery and (2) determine the patient and GP practice characteristics associated with both.Methods and findingsAn observational cohort study was undertaken using routinely collected primary care data in England from the Clinical Practice Research Datalink linked with Hospital Episode Statistics. During the study period (January 2007 to June 2020), 1,811,587 adults met the inclusion criteria of a recording of overweight/obesity in primary care, of which 54.62% were female and 20.10% aged 45 to 54. Only 56,783 (3.13%) were referred to WM, and 3,701 (1.09% of those with severe and complex obesity) underwent bariatric surgery. Multivariable Poisson regression examined the associations of demographic, clinical, and regional characteristics on the likelihood of WM referral and bariatric surgery. Higher body mass index (BMI) and practice region had the strongest associations with both outcomes. People with BMI ≥40 kg/m2 were more than 6 times as likely to be referred for WM (10.05% of individuals) than BMI 25.0 to 29.9 kg/m2 (1.34%) (rate ratio (RR) 6.19, 95% confidence interval (CI) [5.99,6.40], p 2 with a comorbidity (0.53%) (RR 5.52, 95% CI [5.07,6.02], p p p p p p ConclusionsBetween 2007 and 2020, a very small percentage of the primary care population eligible for WM referral or bariatric surgery according to national guidance received either. Higher BMI and GP practice region had the strongest associations with both. Regional inequalities may reflect differences in commissioning and provision of WM services across the country. Multi-stakeholder qualitative research is ongoing to understand the barriers to accessing WM services and potential solutions. Together with population-wide prevention strategies, improved access to WM interventions is needed to reduce obesity levels.</div