The development of the Cough Hypersensitivity Questionnaire for chronic cough.

Introduction: Chronic cough is considered a disorder of neuronal hypersensitivity in which patients frequently report abnormal laryngeal and chest sensations, and excessive triggers. To facilitate clinical assessment, we developed the Cough Hypersensitivity Questionnaire (CHQ).

Methods: Candidate questionnaire items were developed following interviews with patients with refractory chronic cough (n=10, United Kingdom), and review by a multidisciplinary team.

Patient-reported assessments of chronic cough in clinical trials: accessory or primary endpoints?

Chronic cough is a complex disorder that affects up to 5-10% of the general population. It can be challenging to manage as there are few effective treatments, although several novel antitussives are in clinical development. The endpoints used to assess their efficacy in clinical trials should be optimal; most large clinical trials currently use objective measures as the primary outcome, especially cough frequency.

Environmental impact of large language models in medicine.

The environmental impact of large language models (LLMs) in medicine spans carbon emission, water consumption and rare mineral usage. Prior-generation LLMs, such as GPT-3, already have concerning environmental impacts. Next-generation LLMs, such as GPT-4, are more energy intensive and used frequently, posing potentially significant environmental harms.

Large-Scale Pharmacogenomics Analysis of Patients With Cancer Within the 100,000 Genomes Project Combining Whole-Genome Sequencing and Medical Records to Inform Clinical Practice.

Purpose: As part of the 100,000 Genomes Project, we set out to assess the potential viability and clinical impact of reporting genetic variants associated with drug-induced toxicity for patients with cancer recruited for whole-genome sequencing (WGS) as part of a genomic medicine service.

Methods: Germline WGS from 76,805 participants was analyzed for pharmacogenetic (PGx) variants in four genes (, , , ) associated with toxicity induced by five drugs used in cancer treatment (capecitabine, fluorouracil, mercaptopurine, thioguanine, irinotecan). Linking genomic data with prescribing and hospital incidence records, a phenome-wide association study (PheWAS) was performed to identify whether phenotypes indicative of adverse drug reactions (ADRs) were enriched in drug-exposed individuals with the relevant PGx variants.

Artificial intelligence in the detection of choledocholithiasis: a systematic review.

Importance: Choledocholithiasis is a potentially life-threatening manifestation of acute biliary dysfunction (ABD) often requiring magnetic resonance cholangiopancreatography (MRCP) for diagnosis when standard investigation findings are inconclusive. Machine learning models (MLMs) may offer alternatives to diagnose choledocholithiasis.

Objective: This systematic review seeks to evaluate the performance of MLMs in predicting choledocholithiasis and to compare this performance with the American Society of Gastrointestinal Endoscopy (ASGE) guidelines.

MEDI1814 selectively reduces free Aβ42 in cerebrospinal fluid of non-clinical species and Alzheimer's disease patients.

Introduction: Small molecules and antibodies are being developed to lower amyloid beta (Aβ) peptides.

Methods: We describe MEDI1814, a fully human high-affinity monoclonal antibody selective for Aβ, the pathogenic self-aggregating species of Aβ.

Results: MEDI1814 reduces free Aβ without impacting Aβ in the cerebrospinal fluid of rats and cynomolgus monkeys after systemic administration.

The future is bright: artificial intelligence for trainee medical officers in Australia and New Zealand.

Given their frontline role in Australia and Aotearoa New Zealand (ANZ) healthcare, trainee medical officers (TMOs) will play a crucial role in the development and use of artificial intelligence (AI) for clinical care, ongoing medical education and research. As 'digital natives', particularly those with technical expertise in AI, TMOs should also be leaders in informing the safe uptake and governance of AI within ANZ healthcare as they have a practical understanding of its associated risks and benefits. However, this is only possible if a culture of broad collaboration is instilled while the use of AI in ANZ is still in its initial phase.

The epidemiology of acute pancreatitis in Tasmania over a 12-year period: Is this a disease of disadvantage?

Background: The global incidence of acute pancreatitis (AP) is increasing, but little information exists about trends in Australia. This study aimed to describe incidence trends, along with clinical and socio-demographic associations, in the state of Tasmania over a recent 12-year period.

Methods: The study cohort was obtained by linking clinical and administrative datasets encompassing the whole Tasmanian population between 2007 and 2018, inclusive.

Using artificial intelligence to predict choledocholithiasis: can machine learning models abate the use of MRCP in patients with biliary dysfunction?

Background: Prompt diagnosis of choledocholithiasis is crucial for reducing disease severity, preventing complications and minimizing length of stay. Magnetic resonance cholangiopancreatography (MRCP) is commonly used to evaluate patients with suspected choledocholithiasis but is expensive and may delay definitive intervention. To optimize patient care and resource utilization, we have developed five machine learning models that predict a patients' risk of choledocholithiasis based on clinical presentation and pre-MRCP investigation results.

Chronic cough: is the end nigh?

Chronic cough (lasting more than 8 weeks) is a common condition with substantial psychosocial impact. Despite huge efforts following robust guidelines, chronic cough in many patients remains refractory or unexplained (RU-CC). Recent insights support a significant role for cough hypersensitivity in RU-CC, including neuropathophysiological evidence from inhalational cough challenge testing, functional magnetic resonance imaging, and airway nerve biopsy.

Adapting the ADVANCE group program for digitally-supported delivery to reduce intimate partner violence by men in substance use treatment: a feasibility study.

Introduction: COVID-19 restrictions created barriers to "business as usual" in healthcare but also opened the door to innovation driven by necessity. This manuscript (1) describes how ADVANCE, an in-person group perpetrator program to reduce intimate partner violence (IPV) against female (ex)partners by men in substance use treatment, was adapted for digitally-supported delivery (ADVANCE-D), and (2) explores the feasibility and acceptability of delivering ADVANCE-D to men receiving substance use treatment.

Methods: Firstly, the person-based approach and mHealth development framework were used to iteratively adapt ADVANCE for digitally-supported delivery including conceptualization, formative research, and pre-testing.

Chronic Cough as a Genetic Neurological Disorder? Insights from Cerebellar Ataxia with Neuropathy and Vestibular Areflexia Syndrome (CANVAS).

Chronic cough is common, and in many cases unexplained or refractory to otherwise effective treatment of associated medical conditions. Cough hypersensitivity has developed as a paradigm that helps to explain clinical and research observations that frequently point towards chronic cough as a neuropathic disorder. Cerebellar ataxia with neuropathy and vestibular areflexia syndrome (CANVAS) is a recently described neurological condition whose clinical features include gait ataxia, unsteadiness, peripheral neuropathy, and autonomic dysfunction.

Cough in chronic lung disease: a state of the art review.

Chronic cough (CC; ≥8 weeks in duration) is a common and burdensome feature of respiratory diseases. The understanding of cough has progressed significantly in recent years, albeit largely in refractory (unexplained) chronic cough (RCC) in the absence of other respiratory conditions. The prevalence of CC in respiratory diseases is poorly described, but estimates have been reported: asthma (8-58%), chronic obstructive pulmonary disease (COPD; 10-74%), bronchiectasis (82-98%), interstitial lung disease (ILD; 50-89%) and sarcoidosis (3-64%).

Enhanced harvest performance predictability through advanced multivariate data analysis of mammalian cell culture particle size distribution.

The industry's pursuit for higher antibody production has led to increased cell density cultures that impact the performance of subsequent product recovery steps. This increase in cell concentration has highlighted the critical role of solids concentration in centrifugation yield, while recent product degradation cases have shed light on the impact of cell lysis on product quality. Current methods for measuring solids concentration and cell lysis are not suited for early-stage high-throughput experimentation, which means that these cell culture outputs are not well characterized in early process development.

Patient Global Impression of Severity Scale in Chronic Cough: Validation and Formulation of Symptom Severity Categories.

Background: The Patient Global Impression of Severity (PGI-S) scale is a self-reported, single-item categorical scale that is increasingly used when assessing chronic cough (CC).

Objective: This study aimed to establish validity, repeatability, and responsiveness of the PGI-S scale in CC and use the scale to define discrete categories of severity when measured with other commonly used patient-reported outcome (PRO) tools.

Methods: Consecutive patients with CC completed the PGI-S scale, cough severity and urge to cough visual analog scales (VAS), and cough-specific health status Leicester Cough Questionnaire (LCQ) at a clinic visit.

Next-generation cell line selection methodology leveraging data lakes, natural language generation and advanced data analytics.

Cell line development is an essential stage in biopharmaceutical development that often lies on the critical path. Failure to fully characterise the lead clone during initial screening can lead to lengthy project delays during scale-up, which can potentially compromise commercial manufacturing success. In this study, we propose a novel cell line development methodology, referenced as , which involves four steps enabling autonomous data-driven selection of the lead clone.