Integrative Salt Selection and Formulation Optimization: Perspectives of Disproportionation and Microenvironmental pH Modulation.

We report a novel utilization of a pH modifier as a disproportionation retardant in a tablet formulation. The drug molecule of interest has significant bioavailability challenges that require solubility enhancement. In addition to limited salt/cocrystal options, disproportionation of the potential salt(s) was identified as a substantial risk. Using a combination of Raman spectroscopy with chemometrics and quantitative X-ray diffraction in specially designed stress testing, we investigated the disproportionation phenomena. The learnings and insight drawn from crystallography drove the selection of the maleate form as the target API. Inspired by the fumarate form's unique stability and solubility characteristics, we used fumaric acid as the microenvironmental pH modulator. Proof-of-concept experiments with high-risk (HCl) and moderate-risk (maleate) scenarios confirmed the synergistic advantage of fumaric acid, which interacts with the freebase released by disproportionation to form a more soluble species. The resultant hemifumarate helps maintain the solubility at an elevated level. This work demonstrates an innovative technique to mediate the solubility drop during the "parachute" phase of drug absorption using compendial excipients, and this approach can potentially serve as an effective risk-mitigating strategy for salt disproportionation.

Predictive performance of the common red flags in emergency department headache patients: a HEAD and HEAD-Colombia study.

OBJECTIVES: Only a small proportion of patients presenting to an ED with headache have a serious cause. The SNNOOP10 criteria, which incorporates red and orange flags for serious causes, has been proposed but not well studied. This project aims to compare the proportion of patients with 10 commonly accepted red flag criteria (singly and in combination) between patients with and without a diagnosis of serious secondary headache in a large, multinational cohort of ED patients presenting with headache. METHODS: Secondary analysis of data obtained in the HEAD and HEAD-Colombia studies. The outcome of interest was serious secondary headache. The predictive performance of 10 red flag criteria from the SNNOOP10 criteria list was estimated individually and in combination. RESULTS: 5293 patients were included, of whom 6.1% (95% CI 5.5% to 6.8%) had a defined serious cause identified. New neurological deficit, history of neoplasm, older age (>50 years) and recent head trauma (2-7 days prior) were independent predictors of a serious secondary headache diagnosis. After adjusting for other predictors, sudden onset, onset during exertion, pregnancy and immune suppression were not associated with a serious headache diagnosis. The combined sensitivity of the red flag criteria overall was 96.5% (95% CI 93.2% to 98.3%) but specificity was low, 5.1% (95% CI 4.3% to 6.0%). Positive predictive value was 9.3% (95% CI 8.2% to 10.5%) with negative predictive value of 93.5% (95% CI 87.6% to 96.8%). CONCLUSION: The sensitivity and specificity of the red flag criteria in this study were lower than previously reported. Regarding clinical practice, this suggests that red flag criteria may be useful to identify patients at higher risk of a serious secondary headache cause, but their low specificity could result in increased rates of CT scanning. TRIAL REGISTRATION NUMBER: ANZCTR376695.

Enhancing pain care with the American Pain Society Patient Outcome Questionnaire for use in the emergency department (APS-POQ-RED): validating a patient-reported outcome measure.

BACKGROUND: In general, the quality of pain care in emergency departments (ED) is poor, despite up to 80% of all ED patients presenting with pain. This may be due to the lack of well-validated patient-reported outcome measures (PROMs) of pain care in the ED setting. The American Pain Society-Patient Outcome Questionnaire-Revised Edition (APS-POQ-R), with slight modification for ED patients, is a potentially useful PROM for the adult ED, however it is yet to be completely validated. METHODS: Adult patients, who had presented with moderate to severe acute pain, were recruited at two large inner-city EDs in Australia. A modified version of the APS-POQ-R was administered at the completion of their ED care. Responses were randomly split into three groups and underwent multiple rounds of exploratory and confirmatory factor analysis with testing for construct, convergent, divergent validity and internal consistency. RESULTS: A total of 646 ED patients (55.6% female), with a median age of 48.3 years, and moderate to severe pain on arrival, completed the ED-modified APS-POQ-R. Psychometric evaluation resulted in a reduced nine-question tool, which measures three constructs (pain relief and satisfaction (α=0.891), affective distress (α=0.823) and pain interference (α=0.908)) and demonstrated construct, convergent, divergent validity, and internal consistency. CONCLUSIONS: This new tool, which we refer to as the American Pain Society-Patient Outcome Questionnaire-Revised for the ED (APS-POQ-RED), should form the basis for reporting patient-reported outcomes of ED pain care in future quality improvement and research.

Developing Robust Clinical Text Deep Learning Models - A "Painless" Approach.

The success of deep learning in natural language processing relies on ample labelled training data. However, models in the health domain often face data inadequacy due to the high cost and difficulty of acquiring training data. Developing such models thus requires robustness and performance on new data. A generalised incremental multiphase framework is proposed for developing robust and performant clinical text deep learning classifiers. It incorporates incremental multiphases for training data size assessments, cross-validation setup to avoid test data bias, and robustness testing through inter/intra-model significance analysis. The framework's effectiveness and generalisation were confirmed by the task of identifying patients presenting in 'pain' to the emergency department.

Analyzing pain patterns in the emergency department: Leveraging clinical text deep learning models for real-world insights.

OBJECTIVE: To determine the incidence of patients presenting in pain to a large Australian inner-city emergency department (ED) using a clinical text deep learning algorithm. MATERIALS AND METHODS: A fine-tuned, domain-specific, transformer-based clinical text deep learning model was used to interpret free-text nursing assessments in the electronic medical records of 235,789 adult presentations to the ED over a three-year period. The model classified presentations according to whether the patient had pain on arrival at the ED. Interrupted time series analysis was used to determine the incidence of pain in patients on arrival over time. We described the changes in the population characteristics and incidence of patients with pain on arrival occurring with the start of the Covid-19 pandemic. RESULTS: 55.16% (95%CI 54.95%-55.36%) of all patients presenting to this ED had pain on arrival. There were differences in demographics and arrival and departure patterns between patients with and without pain. The Covid-19 pandemic initially precipitated a decrease followed by a sharp, sustained rise in pain on arrival, with concurrent changes to the population arriving in pain and their treatment. DISCUSSION: Applying a clinical text deep learning model has successfully identified the incidence of pain on arrival. It represents an automated, reproducible mechanism to identify pain from routinely collected medical records. The description of this population and their treatment forms the basis of intervention to improve care for patients with pain. The combination of the clinical text deep learning models and interrupted time series analysis has reported on the effects of the Covid-19 pandemic on pain care in the ED, outlining a methodology to assess the impact of significant events or interventions on pain care in the ED. CONCLUSION: Applying a novel deep learning approach to identifying pain guides methodological approaches to evaluating pain care interventions in the ED, giving previously unavailable population-level insights.

Patterns of chemotherapy use in muscle-invasive bladder cancer in a tertiary centre.

Objectives: Although neoadjuvant chemotherapy (NAC) has been demonstrated to have significant benefits to survival in patients with muscle-invasive bladder cancer (MIBC), the current utilization of NAC in Australia is unknown. The aim of this study was to evaluate the patterns of neoadjuvant and adjuvant chemotherapy (AC) use in patients undergoing cystectomy for MIBC at a large tertiary institution in Australia. Methods: A retrospective study was conducted using data of patients who underwent a radical cystectomy (RC) at a high-volume centre for MIBC between 2011 and 2021. Results: Of 69 patients who had a cystectomy for ≥ pT2 bladder cancer, 73.9% were eligible for NAC. However, of those eligible, only five patients received NAC (9.8%). Of the total patients who were eligible for AC, only 44.4% received postoperative chemotherapy. Common reasons for the lack of uptake were due to patients being unfit or declining treatment. There was no difference in progression-free survival or overall survival in those who received NAC and AC. Conclusions: The majority of patients undergoing RC for MIBC received AC compared to NAC, reflecting the real-world challenge of NAC uptake. This highlights the need for ongoing improvements in selection and usage of NAC and less reliance of AC utilization post RC.