Translational artificial intelligence-led optimization and realization of estimated discharge with a supportive weekend interprofessional flow team (TAILORED-SWIFT).

Weekend discharges occur less frequently than discharges on weekdays, contributing to hospital congestion. Artificial intelligence algorithms have previously been derived to predict which patients are nearing discharge based upon ward round notes. In this implementation study, such an artificial intelligence algorithm was coupled with a multidisciplinary discharge facilitation team on weekend shifts. This approach was implemented in a tertiary hospital, and then compared to a historical cohort from the same time the previous year. There were 3990 patients included in the study. There was a significant increase in the proportion of inpatients who received weekend discharges in the intervention group compared to the control group (median 18%, IQR 18-20%, vs median 14%, IQR 12% to 17%, P = 0.031). There was a corresponding higher absolute number of weekend discharges during the intervention period compared to the control period (P = 0.025). The studied intervention was associated with an increase in weekend discharges and economic analyses support this approach as being cost-effective. Further studies are required to examine the generalizability of this approach to other centers.

Near-death experiences after cardiac arrest: a scoping review.

BACKGROUND: This scoping review aimed to characterise near-death experiences in the setting of cardiac arrest, a phenomenon that is poorly understood and may have clinical consequences. METHOD: PubMed/MEDLINE was searched to 23 July 2023 for prospective studies describing near-death experiences in cardiac arrest. PRISMA-ScR guidelines were adhered to. Qualitative and quantitative data were synthesised. Meta-analysis was precluded due to data heterogeneity. RESULTS: 60 records were identified, of which 11 studies involving interviews were included from various countries. Sample size ranged from 28-344, and proportion of female patients (when reported) was 0-50%, with mean age (when reported) ranging 54-64 years. Comorbidities and reasons for cardiac arrest were heterogeneously reported. Incidence of near-death experiences in the included studies varied from 6.3% to 39.3%; with variation between in-hospital (6.3-39.3%) versus out-of-hospital (18.9-21.2%) cardiac arrest. Individual variables regarding patient characteristics demonstrated statistically significant association with propensity for near-death experiences. Reported content of near-death experiences tended to reflect the language of the questionnaires used, rather than the true language used by individual study participants. Three studies conducted follow-up, and all suggested a positive life attitude change, however one found significantly higher 30-day all-cause mortality in patients with near-death experiences versus those without, in non-controlled analysis. CONCLUSIONS: From prospective studies that have investigated the phenomenon, near-death experiences may occur in as frequent as over one-third of patients with cardiac arrest. Lasting effects may follow these events, however these could also be confounded by clinical characteristics.

Subcutaneous sodium valproate in palliative care: A systematic review.

BACKGROUND: Seizures are an important palliative symptom, the management of which can be complicated by patients' capacity to swallow oral medications. In this setting, and the wish to avoid intravenous access, subcutaneous infusions may be employed. Options for antiseizure medications that can be provided subcutaneously may be limited. Subcutaneous sodium valproate may be an additional management strategy. AIM: To evaluate the published experience of subcutaneous valproate use in palliative care, namely with respect to effectiveness and tolerability. DESIGN: A systematic review was registered (PROSPERO CRD42023453427), conducted and reported according to PRISMA reporting guidelines. DATA SOURCES: The databases PubMed, EMBASE and Scopus were searched for publications until August 11, 2023. RESULTS: The searches returned 429 results, of which six fulfilled inclusion criteria. Case series were the most common study design, and most studies included <10 individuals who received subcutaneous sodium valproate. There were three studies that presented results on the utility of subcutaneous sodium valproate for seizure control, which described it to be an effective strategy. One study also described it as an effective treatment for neuropathic pain. The doses were often based on presumed 1:1 oral to subcutaneous conversion ratios. Only one study described a local site adverse reaction, which resolved with a change of administration site. CONCLUSIONS: There are limited data on the use of subcutaneous sodium valproate in palliative care. However, palliative symptoms for which subcutaneous sodium valproate have been used successfully are seizures and neuropathic pain. The available data have described few adverse effects, supporting its use with an appropriate degree of caution.

Renal disease is not associated with delays in hyperacute stroke management in South Australia.

OBJECTIVE: The aims of the present study were to determine how renal disease is associated with the time to receive hyperacute stroke care. METHODS: The present study involved a 5-year cohort of all patients admitted to stroke units in South Australia. RESULTS: In those with pre-existing renal disease there were no significant differences in the time taken to receive a scan, thrombolysis or endovascular thrombectomy. CONCLUSIONS: The present study shows that in protocolised settings there were no significant delays in hyperacute stroke management for patients with renal disease.

Identifying epilepsy surgery referral candidates with natural language processing in an Australian context.

OBJECTIVE: Epilepsy surgery is known to be underutilized. Machine learning-natural language processing (ML-NLP) may be able to assist with identifying patients suitable for referral for epilepsy surgery evaluation. METHODS: Data were collected from two tertiary hospitals for patients seen in neurology outpatients for whom the diagnosis of "epilepsy" was mentioned. Individual case note review was undertaken to characterize the nature of the diagnoses discussed in these notes, and whether those with epilepsy fulfilled prespecified criteria for epilepsy surgery workup (namely focal drug refractory epilepsy without contraindications). ML-NLP algorithms were then developed using fivefold cross-validation on the first free-text clinic note for each patient to identify these criteria. RESULTS: There were 457 notes included in the study, of which 250 patients had epilepsy. There were 37 (14.8%) individuals who fulfilled the prespecified criteria for epilepsy surgery referral without described contraindications, 32 (12.8%) of whom were not referred for epilepsy surgical evaluation in the given clinic visit. In the prediction of suitability for epilepsy surgery workup using the prespecified criteria, the tested models performed similarly. For example, the random forest model returned an area under the receiver operator characteristic curve of 0.97 (95% confidence interval 0.93-1.0) for this task, sensitivity of 1.0, and specificity of 0.93. SIGNIFICANCE: This study has shown that there are patients in tertiary hospitals in South Australia who fulfill prespecified criteria for epilepsy surgery evaluation who may not have been referred for such evaluation. ML-NLP may assist with the identification of patients suitable for such referral. PLAIN LANGUAGE SUMMARY: Epilepsy surgery is a beneficial treatment for selected individuals with drug-resistant epilepsy. However, it is vastly underutilized. One reason for this underutilization is a lack of prompt referral of possible epilepsy surgery candidates to comprehensive epilepsy centers. Natural language processing, coupled with machine learning, may be able to identify possible epilepsy surgery candidates through the analysis of unstructured clinic notes. This study, conducted in two tertiary hospitals in South Australia, demonstrated that there are individuals who fulfill criteria for epilepsy surgery evaluation referral but have not yet been referred. Machine learning-natural language processing demonstrates promising results in assisting with the identification of such suitable candidates in Australia.

Beware of little expenses: Low-value endocrinological blood tests in geriatric medical inpatients.

OBJECTIVES: Blood tests for endocrinological derangements are frequently requested in general medical inpatients, in particular those in the older age group. Interrogation of these tests may present opportunities for healthcare savings. METHODS: This multicentre retrospective study over a 2.5-year period examined the frequency with which three common endocrinological investigations [thyroid stimulating hormone (TSH), HbA1c, 25-hydroxy Vitamin D3] were performed in this population, including the frequency of duplicate tests within a given admission, and the frequency of abnormal test results. The Medicare Benefits Schedule was used to calculate the cost associated with these tests. RESULTS: There were 28,564 individual admissions included in the study. Individuals ≥65 years old were the majority of inpatients in whom the selected tests were performed (80% of tests). TSH was performed in 6730 admissions, HbA1c was performed in 2259 admissions, and vitamin D levels were performed in 5632 admissions. There were 6114 vitamin D tests performed during the study period, of which 2911 (48%) returned outside the normal range. The cost associated with vitamin D level testing was $183,726. Over the study period, 8% of tests for TSH, HbA1c, and Vitamin D were duplicates (where a second test was performed within a single admission), which was associated with a cost of $32,134. CONCLUSIONS: Tests for common endocrinological abnormalities are associated with significant healthcare costs. Avenues by which future savings may be pursued include the investigation of strategies to reduce duplicate ordering and examining the rationale and guidelines associated with ordering tests such as vitamin D levels.

Pre-stroke anticoagulation for atrial fibrillation in primary English speakers and non-primary English speakers: a multicentre retrospective cohort study.

BACKGROUND: Anticoagulation can prevent most strokes in individuals with atrial fibrillation (AF); however, many people presenting with stroke and known AF are not anticoagulated. Language barriers and poor health literacy have previously been associated with decreased patient medication adherence. The association between language barriers and initiation of anticoagulation therapy for AF is uncertain. AIMS: The aims of this study were to determine whether demographic factors, including non-English primary language, were (1) associated with not being initiated on anticoagulation for known AF prior to admission with stroke, and (2) associated with non-adherence to anticoagulation in the setting of known AF prior to admission with stroke. METHODS: A multicentre retrospective cohort study was conducted for consecutive individuals admitted to the three South Australian tertiary hospitals with stroke units over a 5-year period. RESULTS: There were 6829 individuals admitted with stroke. These cases included 5835 ischaemic stroke patients, 1333 of whom had pre-existing AF. Only 40.0% presenting with ischaemic stroke in the setting of known pre-existing AF were anticoagulated. When controlling for demographics, socioeconomic status and past medical history (including the components of the CHADS2VASC score and anticoagulation contraindications), having a primary language other than English was associated with a lower likelihood of having been commenced on anticoagulant for known pre-stroke AF (odds ratio: 0.52, 95% confidence interval: 0.36-0.77, P = 0.001), but was not associated with a differing likelihood of anticoagulation adherence. CONCLUSIONS: A significant proportion of patients with stroke have pre-existing unanticoagulated AF; these rates are substantially higher if the primary language is other than English. Targeted research and interventions to minimise evidence-treatment gaps in this cohort may significantly reduce stroke burden.

Artificial intelligence-enabled penicillin allergy delabelling: an implementation study.

Inaccurate penicillin allergy labels may be delabelled following evaluation. The intervention in this study was an email-based notification system regarding the appropriateness for penicillin allergy evaluation, with a view to delabelling, as identified by a deep learning artificial intelligence algorithm. Of the intervention group (n = 59), three (5.1%) individuals had their penicillin allergies delabelled, which was significantly more than the control group (0%, P = 0.002). Further research to optimise such approaches is required.

A systematic review of the symptomatic management of Lhermitte's phenomenon.

INTRODUCTION: Lhermitte's phenomenon (LP) is a transient shock-like sensation that radiates down the spine into the extremities, usually with neck flexion. The potential efficacy and tolerability of various symptomatic therapies in the management of LP have not been systematically reviewed previously. METHOD: A systematic review was conducted using PubMed, EMBASE, and the Cochrane Library from inception to August 2022 for peer-reviewed articles describing the treatment of patients with Lhermitte's phenomenon. The review adheres to the PRISMA guidelines and was registered on PROSPERO. RESULTS: This systematic review included sixty-six articles, which included 450 patients with LP. Treatment of the underlying cause varied by aetiology. Whilst LP is most commonly considered in the context of structural pathology of the cervical cord, medication-induced LP was a common theme in the literature. The most common cause of medication-induced LP was platinum-based chemotherapy agents such as cisplatin and oxaliplatin. In medication-induced LP, symptoms typically resolved with cessation of the causative agent. Non-pharmacological treatment options were associated with mild-moderate symptomatic improvement. The most commonly used agents to treat patients with LP were carbamazepine and gabapentin, which resulted in variable degrees of symptomatic benefit. CONCLUSIONS: No randomised studies currently exist to support the use of symptomatic therapies to treat LP. Observational data suggest that some therapies may yield a symptomatic benefit in the management of LP. However, this systematic review identified a significant paucity of evidence in the literature, which suggests that further controlled studies are needed to investigate the optimal management of this common neurologic phenomenon.

Improving health care efficiency one click at a time.

Computers are an integral component of modern hospitals. Mouse clicks are currently inherent to this use of computers. However, mouse clicks are not instantaneous. These clicks may be associated with significant costs. Estimated costs associated with 10 additional clicks per day for 20 000 staff exceed AU$500 000 annually. Workflow modifications that increase clicks should weigh the potential benefits of such changes against these costs. Future investigation of strategies to reduce low-value clicks may provide an avenue for health care savings.

Artificial intelligence for predicting acute appendicitis: a systematic review.

BACKGROUND: Paediatric appendicitis may be challenging to diagnose, and outcomes difficult to predict. While diagnostic and prognostic scores exist, artificial intelligence (AI) may be able to assist with these tasks. METHOD: A systematic review was conducted aiming to evaluate the currently available evidence regarding the use of AI in the diagnosis and prognostication of paediatric appendicitis. In accordance with the PRISMA guidelines, the databases PubMed, EMBASE, and Cochrane Library were searched. This review was prospectively registered on PROSPERO. RESULTS: Ten studies met inclusion criteria. All studies described the derivation and validation of AI models, and none described evaluation of the implementation of these models. Commonly used input parameters included varying combinations of demographic, clinical, laboratory, and imaging characteristics. While multiple studies used histopathological examination as the ground truth for a diagnosis of appendicitis, less robust techniques, such as the use of ICD10 codes, were also employed. Commonly used algorithms have included random forest models and artificial neural networks. High levels of model performance have been described for diagnosis of appendicitis and, to a lesser extent, subtypes of appendicitis (such as complicated versus uncomplicated appendicitis). Most studies did not provide all measures of model performance required to assess clinical usability. CONCLUSIONS: The available evidence suggests the creation of prediction models for diagnosis and classification of appendicitis using AI techniques, is being increasingly explored. However, further implementation studies are required to demonstrate benefit in system or patient-centred outcomes with model deployment and to progress these models to the stage of clinical usability.

Delays in the diagnosis of ischaemic stroke presenting with persistent reduced level of consciousness: A systematic review.

INTRODUCTION: Stroke presenting with a reduced level of consciousness (RLOC) may result in diagnostic error and/or delay. Missed or delayed diagnosis of acute ischaemic stroke may preclude otherwise applicable hyperacute stroke interventions. The frequency, reasons for, and consequences of diagnostic error and delay due to RLOC are uncertain. METHOD: The databases PubMed, EMBASE, and Cochrane library were searched in adherence with the PRISMA guidelines. The systematic review was prospectively registered on PROSPERO. RESULTS: Initial searches returned 1162 results, of which 6 fulfilled inclusion criteria. The majority of identified studies show that ischaemic stroke presenting with RLOC is at increased risk of missed or delayed diagnosis. Hyperacute stroke interventions may also be delayed. There is limited evidence regarding the reason for these delays; however, the delays may result from neuroimaging delay associated with diagnostic uncertainty. There is also limited evidence regarding the outcomes of patients with stroke and RLOC who experience diagnostic delay; however, the available literature suggests that outcomes may be poor, including motor and cognitive impairment, as well as long-term impaired consciousness. The included studies did not evaluate, but have suggested urgent MRI access, educational interventions, and protocolisation of the evaluation of RLOC as means to reduce poor outcomes. CONCLUSIONS: Ischaemic stroke patients with RLOC are at risk of diagnostic delay and error. These patients may have poor outcomes. Additional research is required to identify the contributing factors more clearly and to provide amelioration strategies.