British Journal of Psychiatry最新文献

Background: Attempts to use artificial intelligence (AI) in psychiatric disorders show moderate success, highlighting the potential of incorporating information from clinical assessments to improve the models. This study focuses on using large language models (LLMs) to detect suicide risk from medical text in psychiatric care.

Aims: To extract information about suicidality status from the admission notes in electronic health records (EHRs) using privacy-sensitive, locally hosted LLMs, specifically evaluating the efficacy of Llama-2 models.

Method: We compared the performance of several variants of the open source LLM Llama-2 in extracting suicidality status from 100 psychiatric reports against a ground truth defined by human experts, assessing accuracy, sensitivity, specificity and F1 score across different prompting strategies.

Results: A German fine-tuned Llama-2 model showed the highest accuracy (87.5%), sensitivity (83.0%) and specificity (91.8%) in identifying suicidality, with significant improvements in sensitivity and specificity across various prompt designs.

Conclusions: The study demonstrates the capability of LLMs, particularly Llama-2, in accurately extracting information on suicidality from psychiatric records while preserving data privacy. This suggests their application in surveillance systems for psychiatric emergencies and improving the clinical management of suicidality by improving systematic quality control and research.

Background: Breast cancer is a major global health issue, especially among women. Previous research has indicated a possible association between psychiatric conditions, particularly schizophrenia, and an increased risk of breast cancer. However, the specific risk of breast cancer in women with schizophrenia, compared with those with other psychiatric disorders and the general population, remains controversial and needs further clarification.

Aims: To estimate the risk of breast cancer among people with schizophrenia compared with people with other psychiatric disorders and people in the general population.

Method: We utilised medical claims data of women aged 18 to 80 years in the Korean National Health Information Database from 2007 to 2018. Individuals with schizophrenia were defined as women with ICD-10 codes F20 or F25 (n = 224 612). The control groups were defined as women with other psychiatric disorders (n = 224 612) and women in the general Korean population (n = 449 224). Cases and controls were matched by index date and age, in a 1:1:2 ratio. We estimated the hazard of breast cancer using the Cox proportional hazards model, adjusting for insurance premiums and medical comorbidities. Among the people with schizophrenia, we used the landmark method to estimate the association between duration of antipsychotic medication use and the incidence of breast cancer.

Results: In multivariable Cox regression models, the hazard rate of breast cancer was 1.26 times higher in the people with schizophrenia than in the general population (95% CI: 1.20-1.32). In comparison with the psychiatric patient group, the hazard ratio was 1.17 (95% CI: 1.11-1.28). Among women with schizophrenia, the hazard of breast cancer was greater among those who took antipsychotic medications for 1 year or more compared with those who took antipsychotics for less than 6 months.

Conclusions: Women with schizophrenia have an elevated risk of breast cancer, and long-term use of antipsychotics is associated with an increased risk of breast cancer.

Background: Social prescribing is growing rapidly globally as a way to tackle social determinants of health. However, whom it is reaching and how effectively it is being implemented remains unclear.

Aims: To gain a comprehensive picture of social prescribing in the UK, from referral routes, reasons, to contacts with link workers and prescribed interventions.

Method: This study undertook the first analyses of a large database of administrative data from over 160 000 individuals referred to social prescribing across the UK. Data were analysed using descriptive analyses and regression modelling, including logistic regression for binary outcomes and negative binomial regression for count variables.

Results: Mental health was the most common referral reason and mental health interventions were the most common interventions prescribed. Between 72% and 85% of social prescribing referrals were from medical routes (primary or secondary healthcare). Although these referrals demonstrated equality in reaching across sociodemographic groups, individuals from more deprived areas, younger adults, men, and ethnic minority groups were reached more equitably via non-medical routes (e.g. self-referral, school, charity). Despite 90% of referrals leading to contact with a link worker, only 38% resulted in any intervention being received. A shortage of provision of community activities - especially ones relevant to mental health, practical support and social relationships - was evident. There was also substantial heterogeneity in how social prescribing is implemented across UK nations.

Conclusions: Mental health is the leading reason for social prescribing referrals, demonstrating its relevance to psychiatrists. But there are inequalities in referrals. Non-medical referral routes could play an important role in addressing inequality in accessing social prescribing and therefore should be prioritised. Additionally, more financial and infrastructural resource and strategic planning are needed to address low intervention rates. Further investment into large-scale data platforms and staff training are needed to continue monitoring the development and distribution of social prescribing.

Background: Systemic changes in multiple diseases may influence the onset of dementia. However, the specific temporality between exposure diseases and dementia remains uncertain.

Aims: By characterising the full spectrum of temporal disease trajectories before dementia, this study aims to yield a global picture of precursor diseases to dementia and to provide detailed instructions for risk management and primary prevention of dementia.

Method: Using the multicentre, community-based prospective UK Biobank, we constructed disease trajectories before dementia utilising the phenome-wide association analysis, paired directional test and association quantification. Stratified disease trajectories were constructed by dementia subtypes, gender, age of diagnosis and Apolipoprotein E (ApoE) status, respectively.

Results: Our study population comprised 434 266 participants without baseline dementia and 4638 individuals with all-cause dementia. In total, 1253 diseases were extracted as potential components of the disease trajectory before dementia. We identified three clusters of disease trajectories preceding all-cause dementia, initiated by circulatory, metabolic and respiratory diseases occurring approximately 5-15 years before dementia. Cerebral infarction or chronic renal failure following chronic ischaemic heart disease was the specific trajectory before vascular dementia. Apolipoprotein E (ApoE) ε4 non-carriers exhibited more complex trajectories compared with carriers. Lipid metabolism disorders remained in the trajectories regardless of dementia subtypes, gender, age of diagnosis and ApoE status.

Conclusions: This study provides a comprehensive view of the longitudinal disease trajectories before dementia and highlights the potential targets of midlife cardiometabolic dysfunction for dementia screening and prevention.

Background: Observational studies have shown a controversial relationship between dietary fat intake and Alzheimer's disease, and the causal effects are unclear.

Aims: To assess the causal effects of total fat, saturated fat and polyunsaturated fat (PUF) intakes on the risk of Alzheimer's disease.

Method: A two-sample Mendelian randomisation analysis was performed using genome-wide association study summary statistics on different types of fat intake from UK Biobank (n = 51 413) and on late-onset Alzheimer's disease (LOAD; 4282 cases, n = 307 112) and all forms of Alzheimer's disease (6281 cases, n = 309 154) from the FinnGen consortium. In addition, a multivariable Mendelian randomisation (MVMR) analysis was conducted to estimate the effects independent of carbohydrate and protein intakes.

Results: Genetically predicted per standard deviation increase in the total fat and saturated fat intakes were associated with 44 and 38% higher risks of LOAD (total fat: odds ratio = 1.44, 95% CI 1.03-2.02; saturated fat: odds ratio = 1.38, 95% CI 1.002-1.90; P = 0.049). The associations remained significant in the MVMR analysis (total fat: odds ratio = 3.31, 95% CI 1.74-6.29; saturated fat: odds ratio = 2.04, 95% CI 1.16-3.59). Total fat and saturated fat intakes were associated with a higher risk of all forms of Alzheimer's disease in the MVMR analysis (total fat: odds ratio = 2.09, 95% CI 1.22-3.57; saturated fat: odds ratio = 1.60, 95% CI 1.01-2.52). The PUF intake was not associated with LOAD or all forms of Alzheimer's disease.

Conclusions: This study indicated that total dietary fat intake, especially saturated fat, contributed to the risk of Alzheimer's disease, and the effects were independent of other nutrients. These findings informed prevention strategies and management for Alzheimer's disease directly towards reducing dietary saturated fat intake.

Oloyede and colleagues advocate for updating haematological monitoring requirements for clozapine, arguing that current protocols overestimate the risk of clozapine-induced agranulocytosis. Their research suggests that stringent monitoring may unnecessarily limit access to clozapine, a crucial treatment for resistant schizophrenia. The editorial supports calls for international consensus to carefully weigh the pros and cons of relaxing monitoring guidelines while ensuring comprehensive care for patients.

Background: Anxiety disorders are a major public health burden with limited treatment options.

Aims: We investigated the long-term safety and efficacy of lysergic acid diethylamide (LSD)-assisted therapy in patients with anxiety with or without life-threatening illness.

Method: This study was an a priori-planned long-term follow-up of an investigator-initiated, two-centre trial that used a double-blind, placebo-controlled, two-period, random-order, crossover design with two sessions with either oral LSD (200 μg) or placebo per period. Participants (n = 39) were followed up 1 year after the end-of-study visit to assess symptoms of anxiety, depression and long-term effects of psychedelics using Spielberger's State-Trait Anxiety Inventory-Global (STAI-G), the Beck Depression Inventory (BDI), the Persisting Effects Questionnaire and measures of personality traits using the NEO-Five-Factor Inventory.

Results: Participants reported a sustained reduction of STAI-G scores compared with baseline (least square means (95% CI) = -21.6 (-32.7, -10.4), d = 1.04, P < 0.001, for those who received LSD in the first period (94 weeks after the last LSD treatment) and -16.5 (-26.2, -6.8), d = 1.02, P < 0.05, for those who received LSD in the second period (68 weeks after the last LSD treatment)). Similar effects were observed for comorbid depression with change from baseline BDI scores of -8.1 (-13.2, -3.1), d = 0.71, P < 0.01, and -8.9 (-12.9, -4.9), d = 1.21, P < 0.01, for the LSD-first and placebo-first groups, respectively. Personality trait neuroticism decreased (P < 0.0001) and trait extraversion increased (P < 0.01) compared with study inclusion. Individuals attributed positive long-term effects to the psychedelic experience.

Conclusions: Patients reported sustained long-term effects of LSD-assisted therapy for anxiety.