Rhabdomyolysis in a Patient With a Possible Mitochondrial Pathogenic Variant in the Peri-operative Period: A Case Report.

Mitochondrial disorders are often underrecognized as potential causes of rhabdomyolysis, a condition characterized by acute muscle breakdown that can lead to local and potentially systemic complications, with the possibility of being life-threatening. Accounts of rhabdomyolysis as a peri-operative complication associated with mitochondrial disorders are rare; therefore, this study is noteworthy. We describe a case of rhabdomyolysis that occurred during the peri-operative period in a middle-aged male with Charcot-Marie-Tooth (CMT) disease-like peripheral neuropathy.

Views and experiences of women, peer supporters and healthcare professionals on breastfeeding peer support: A systematic review of qualitative studies.

Objective: To examine and synthesise qualitative evidence of women's, peer supporters' and healthcare professionals' views and experiences of breastfeeding peer support.

Design: The Joanna Briggs Institute (JBI) approach to systematic reviews of qualitative studies was followed. Seven databases: CINAHL, MEDLINE, EMBASE, PsycINFO, Scopus, Maternal & Infant Care, and Web of Science were searched.

Medical students in the pre-hospital environment - An untapped resource for undergraduate acute care and interprofessional education.

Background: The King's College London Pre-hospital Care Programme (KCL PCP) is a student-run programme that provides undergraduate medical students with the opportunity to attend observer shifts with the local ambulance service. This study evaluates the contribution of pre-hospital exposure to medical students' clinical and professional development.

Methods: Students were asked to complete a Likert-scale based survey on self-reported exposure and confidence in various aspects of acute patient assessment, communication and interprofessional education, both before and after the programme; additional qualitative questions querying their experience were asked post-programme.

Developing a Natural Language Processing tool to identify perinatal self-harm in electronic healthcare records.

Background: Self-harm occurring within pregnancy and the postnatal year ("perinatal self-harm") is a clinically important yet under-researched topic. Current research likely under-estimates prevalence due to methodological limitations. Electronic healthcare records (EHRs) provide a source of clinically rich data on perinatal self-harm.

Generation and evaluation of artificial mental health records for Natural Language Processing.

A serious obstacle to the development of Natural Language Processing (NLP) methods in the clinical domain is the accessibility of textual data. The mental health domain is particularly challenging, partly because clinical documentation relies heavily on free text that is difficult to de-identify completely. This problem could be tackled by using artificial medical data.

Temporal information extraction from mental health records to identify duration of untreated psychosis.

Background: Duration of untreated psychosis (DUP) is an important clinical construct in the field of mental health, as longer DUP can be associated with worse intervention outcomes. DUP estimation requires knowledge about when psychosis symptoms first started (symptom onset), and when psychosis treatment was initiated. Electronic health records (EHRs) represent a useful resource for retrospective clinical studies on DUP, but the core information underlying this construct is most likely to lie in free text, meaning it is not readily available for clinical research.

Annotating Temporal Relations to Determine the Onset of Psychosis Symptoms.

For patients with a diagnosis of schizophrenia, determining symptom onset is crucial for timely and successful intervention. In mental health records, information about early symptoms is often documented only in free text, and thus needs to be extracted to support clinical research. To achieve this, natural language processing (NLP) methods can be used.