A hierarchical machine learning model for predicting self-harm and suicidal behaviour in hospitalised patients with schizophrenia using clinical history and nursing observations

ObjectiveThis study aimed to develop and evaluate a two-layered machine learning framework that combines admission clinical information with longitudinal nursing observations to identify schizophrenia inpatients at high risk of self-harm or suicidal acts.MethodsWe retrospectively reviewed the records of 477 patients with schizophrenia hospitalised in Liaoning Province between July 2021 and July 2024. According to whether at least one self-injurious or suicidal episode was documented during the index admission, 159 individuals were assigned to a high-risk group and 318 to a non-high-risk group. At admission, 18 baseline variables (including age, sex, history of self-harm, hopelessness/depression, and educational attainment) were extracted from electronic medical records, and 39 nurse-rated behavioural items were scored weekly using the Psychiatric Patient Nursing Observation Scale. Static and dynamic feature sets were used to train six classifiers [regularized logistic regression (LR), support vector machine (SVM), extreme gradient boosting, random forest, multi-layer perceptron, and K-nearest neighbours]. The best static model (regularized LR) and the best dynamic model (SVM) were combined through probability-level weighted fusion to generate a hierarchical risk score.ResultsMultivariable analysis of admission features showed that previous self-harm [odds ratio (OR) = 4.323], hopelessness/depression (OR = 3.090), younger age (OR = 0.938), and higher educational level (OR = 1.357) were independent predictors of self-harm/suicidal behaviour. Among dynamic indicators, negative self-evaluation (OR = 2.303), self-reported depression (OR = 1.812), insomnia (OR = 1.768), talking to oneself (OR = 1.733), crying (OR = 1.700), and reduced conversation with others (OR = 1.422) remained significant. The optimised static LR model achieved an area under the curve (AUC) of 0.7564, and the dynamic SVM model reached an AUC of 0.8531. Their fusion further improved performance (AUC = 0.9048; sensitivity 0.8542; specificity 0.7789; accuracy 0.8042). This hierarchical model outperformed the best flat combined-feature model (SVM; AUC = 0.9022) in sensitivity (0.8542 vs. 0.6667), indicating a more clinically appropriate detection of high-risk patients.ConclusionA hierarchical machine learning approach that integrates baseline clinical history with repeated nursing assessments can effectively flag schizophrenia inpatients at high risk for self-harm and suicidal behaviour, supporting timely and individualised preventive strategies in psychiatric wards.

Context-dependent interaction between oxytocin gene polymorphisms and alcohol dependence in modulating negative emotions during acute alcohol withdrawal in adult males

ObjectiveThe importance of multiple gene-environment interaction (G × E) has been highlighted in understanding the etiology of negative emotions. This study examines the impact of oxytocin (OXT) polymorphisms (rs2740210, rs6133010, and rs2740209) in combination with alcohol dependence on anxiety and depression symptoms during acute alcohol withdrawal under different social and environmental contexts.MethodA total of 414 Chinese Han male adults undergoing acute alcohol withdrawal were recruited. Participants provided blood samples for genotyping, self-reported measures of depression and anxiety, assessments of alcohol dependence severity, and demographic information regarding social and environmental contexts.ResultsResults revealed a positive correlation between severity of alcohol dependence and symptoms of depression and anxiety, while oxytocin polymorphism did not have a direct effect on depressive and anxiety symptoms. A significant interaction between OXT polymorphism (rs2740210 and rs2740209) and alcohol dependence in relation to anxiety symptoms solely among adults living with family and/or those who were married was observed. Further analyses indicate that the GG and CC genotypes are risk genotypes, while the T allele (rs2740210) and G allele (rs2740209) are non-risk alleles in the interaction between OXT genotypes (rs2740210, rs2740209) and alcohol dependence on anxiety among the aforementioned participants.ConclusionsThese findings provide evidence for distinct G × E interaction effects on anxiety and depression symptoms during acute alcohol withdrawal, supporting the weak diathesis-stress model. Furthermore, the study highlights the importance of considering environmental factors when investigating the role of oxytocin as a biological substrate underlying social bonding and the regulation of negative emotions.

Validation of a criterion-based screening and triage pathway for adult ADHD: a prospective observational study of safety and operational efficiency

BackgroundThe increasing demand for adult attention-deficit hyperactivity disorder (ADHD) assessments has required the development of efficient triage pathways. This study provides a formal assessment of a criterion-based screening model designed to prioritise patient safety and operational efficiency within a National Health Service (NHS) specialist secondary care setting.MethodsA prospective observational validation design was employed, involving 49 consecutive adults referred for ADHD assessment none of whom had a previous ADHD diagnosis. The Comprehensive ADHD Screening Questionnaire (CASQ), a clinician-administered instrument based on DSM-5 criteria, was utilised by four trained Physician Assistants. To ensure an assessment of triage safety, a universal assessment model was adopted: all participants received a blinded, gold-standard diagnostic assessment (NICE-compliant) regardless of the initial triage recommendation thereby eliminating verification bias. The primary outcome measure was the Number Needed to Harm (NNH), defined as the number of people screened before a single false-negative result occurs.ResultsOf the 48 participants who completed the diagnostic process, six (12.5%) received an ADHD diagnosis. The triage pathway correctly identified all six cases, resulting in a sensitivity of 100.0% (95% CI: 61.0%–100.0%) and an infinite NNH. Specificity was 45.2% (95% CI: 31.2%–59.9%), with a positive predictive value of 20.7%. The pathway permitted 39.6% (n = 19) of referrals to be triaged to alternative pathways rather than full ADHD assessment, potentially saving significant specialist clinician time. Exploratory analyses indicated that score magnitude did not reliably distinguish between true and false positives within the group triaged as appropriate for further assessment.ConclusionsThese preliminary findings suggest that criterion-based screening conducted by appropriately trained non-specialist clinicians can achieve high levels of safety whilst improving service efficiency. The findings support the feasibility of task-shifting models in adult ADHD services, provided that triage thresholds are calibrated to prioritise sensitivity. These results require replication in adequately powered multi-site studies before firm conclusions regarding pathway safety can be drawn. Further research is required to establish inter-rater reliability and cost-effectiveness across diverse clinical settings.

Protracted encephalopathy and subacute combined degeneration associated with chronic nitrous oxide use: a case report

Nitrous oxide is a dissociative hallucinogen that is increasingly used recreationally, in part due to its widespread availability. Its use is known to cause subacute combined degeneration via inactivation of vitamin B12; it may also result in acute delirium and chronic progressive encephalopathy. Though current practice guidelines call for treatment of neurological sequelae of nitrous oxide use with vitamin B12 supplementation, a paucity of long-term outcome data limits our ability to guide extended courses of treatment. In this report, we discuss a case of protracted encephalopathy associated with nitrous oxide use. We track the response to vitamin B12 supplementation in the hospital setting using the Mini-Mental Status Exam to assess the severity and improvement of cognitive impairment. We also review the patient’s comorbid medical and psychiatric conditions, which complicate diagnosis and treatment planning in this patient population.

Shifting the Overton Window: enhancing therapeutic outcomes for Māori experiencing Ngā Māuiui kai (eating disorders) through the integration of traditional Māori and Western healing systems in Aotearoa New Zealand

Ngā māuiui kai (eating disorders) are understood within a Māori worldview as a manifestation of imbalance across hinengaro (mind), tinana (body), wairua (spirit) and whānau (family or support system). Prevailing Western treatment, which prioritise biopsychosocial interventions, do not address the cultural and spiritual determinants of health for Māori, creating a gap in culturally responsive care for Māori. This gap is rooted in and sustained by the enduring impacts of colonisation, which marginalised mātauranga Māori (Māori knowledge) and disrupted traditional healing systems. This paper proposes that Specialist Supportive Clinical Management, a flexible, patient-centred psychotherapy, provides a unique point of alignment for the integration of Rongoā Māori, the traditional Māori healing system. Rongoā Māori encompasses modalities such as rongoā rākau (herbal remedies), mirimiri/romiromi (physical therapies), puku kōrero (talk therapy), and karakia (incantations/prayer) and offers a framework embedded within Māori knowledge systems. We argue that rongoā-informed Specialist Supportive Clinical Management, where puku kōrero aligns with Specialist Supportive Clinical Management patient-led dialogue, can synergistically support biopsychosocial goals while ensuring a holistic, culturally grounded approach. This conceptual analysis proposes a culturally adapted intervention to enhance therapeutic engagement, improve health outcomes, and honour the treatment aspirations of Māori by addressing the whole person within their cultural context.