Publications by authors named "Joshua Inglis"

The management of paracetamol poisoning in our local health network and consistency with national guidelines is unclear. We conducted a 4-month retrospective study of all paracetamol poisonings identified in two South Australian hospitals. Most presentations were deliberate self-poisoning (90.

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Article Synopsis
  • Sodium-glucose co-transporter 2 inhibitors (SGLT2i) are commonly used in treating heart failure (HF), but their association with ketosis risk during hospitalization is uncertain.
  • A study measured ketone levels in hospitalized patients with worsening HF and stable HF to determine if SGLT2i use influenced ketone concentrations.
  • Results showed that ketone levels were low across all patients, regardless of SGLT2i use or the severity of heart failure, indicating minimal risk of ketosis in these individuals.
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Objectives: To describe the type of evidence and the clinical benefit of cancer medicines assessed for funding in Australia by the Pharmaceutical Benefits Advisory Committee (PBAC) and to assess it with the European Society of Medical Oncology Magnitude of Clinical Benefit Scale version 1.1 (ESMO-MCBS).

Methods: All data on applications submitted to PBAC between 2010 and 2020 were extracted from PBAC Public Summary Documents available online.

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Background: Inappropriate prescribing (IP) is common in hospitalised older adults with frailty. However, it is not known whether the presence of frailty confers an increased risk of mortality and readmissions from IP nor whether rectifying IP reduces this risk. This review was conducted to determine whether IP increases the risk of adverse outcomes in hospitalised middle-aged and older adults with frailty.

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Introduction: Hospital-acquired adverse drug reactions (HA-ADRs) are common in older adults. However, there is limited knowledge regarding the association between HA-ADRs and adverse clinical outcomes.

Objective: To investigate the incidence and characteristics of HA-ADRs in older adults, and any association with mortality, length of stay, and readmissions.

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Background And Objective: Multimorbidity is common in hospitalised adults who are at increased risk of inappropriate prescribing including drug-disease interactions. These interactions occur when a medicine being used to treat one condition exacerbates a concurrent medical condition and may lead to adverse health outcomes. The aim of this review was to examine the association between drug-disease interactions and the risk of mortality and readmission in hospitalised middle-aged and older adults.

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Background: Machine learning may assist with the identification of potentially inappropriate penicillin allergy labels. Strategies to improve the performance of existing models for this task include the use of additional training data, synthetic data and transfer learning.

Aims: The aims of this study were to investigate the use of additional training data and novel machine learning strategies, namely synthetic data and transfer learning, to improve the performance of penicillin adverse drug reaction (ADR) machine learning classification.

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Antiviral drugs were rapidly implemented into clinical practice for the treatment of high-risk patients with COVID-19, prompting the development of statewide guidelines. This South-Australian study reviewed guideline adherence, assessed prescribing patterns and highlighted the inappropriate management of relative drug-drug interactions and dosing for renal function. Additionally, it evaluated the impact of inappropriate antiviral drug use and suggested methods to improve quality use of medicines.

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Trimethoprim-sulfamethoxazole (TMP-SMX) is a broad spectrum antibiotic in use for more than 50 years. It has an important indication as first line agent in the prophylaxis of opportunistic infections, particularly pneumonia (PJP), in immunosuppressed patients. For those who have a history of allergy or severe intolerance to TMP-SMX, pentamidine, dapsone or atovaquone may be substituted; however there is evidence that TMP-SMX offers superior coverage for PJP, toxoplasmosis, and nocardiosis.

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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.

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Clinical leadership is necessary to improve the performance of large public hospitals. Trainee medical officers (TMOs) are important stakeholders in organisation-wide initiatives that affect the medical workforce and support clinician engagement. This case study describes the development of a representative body known as the 'TMO Forum' within the Central Adelaide Local Health Network as a mechanism to promote engagement between medical trainees and the hospital executive to facilitate escalation and discussion of system-based issues.

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Introduction: Trimethoprim-sulfamethoxazole (TMP-SMX) is an important antibiotic, with the most compelling indications for Pneumocystis jirovecii pneumonia prophylaxis and methicillin-resistant Staphylococcus aureus treatment. Previous adverse reactions (AR) to TMP-SMX may limit the usability of TMP-SMX. Electronic medical record (EMR) of AR for other antibiotics has previously been shown to be inaccurate; however, the extent to which this occurs for TMP-SMX is unknown.

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Blocking a protein known as EPAC1 may prevent the development of heart-related side effects caused by a chemotherapy drug.

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There is a growing interest in the appropriate evaluation of penicillin adverse drug reaction (ADR) labels. We have developed machine learning models for classifying penicillin ADR labels using free-text reaction descriptions, and here report external and practical validation. The models performed comparably with expert criteria for the categorisation of allergy or intolerance and identification of high-risk allergies.

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Purpose Of The Article: Patients with penicillin allergy labels are more likely to have postoperative wound infections. When penicillin allergy labels are interrogated, a significant number of individuals do not have penicillin allergies and may be delabeled. This study was conducted to gain preliminary evidence into the potential role of artificial intelligence in assisting with perioperative penicillin adverse reaction (AR) evaluation.

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Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are a class of oral glucose-lowering agents commonly used for the treatment of type 2 diabetes. With increased use, there has been an increase in the incidence of the rare but life-threatening complication of euglycemic diabetic ketoacidosis. A common but underappreciated precipitant is colonoscopy.

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Introduction: Penicillin allergy labels are common. However, many penicillin allergy labels have been applied incorrectly and in fact represent penicillin intolerance. Patients with penicillin intolerance can receive penicillin antibiotics.

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Purpose Of Review: Breathlessness is a common symptom in patients with respiratory failure in the terminal phase of their illness. Noninvasive methods of oxygen delivery are frequently used in the palliative setting. We review the evidence supporting noninvasive respiratory supports for the relief of terminal breathlessness in those with life-limiting illnesses.

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Background: The penicillin adverse drug reaction (ADR) label is common in electronic health records (EHRs). However, there is significant misclassification between allergy and intolerance within the EHR and most patients can be delabelled after an immunologic assessment. Machine learning natural language processing may be able to assist with the categorisation and risk stratification of penicillin ADRs.

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Background: Allergy to opioids is the second most common drug allergy label in electronic health records (EHR). Adverse drug reactions (ADR) to opioids cause significant morbidity and contribute to healthcare costs, while incorrect opioid allergy labels may unnecessarily complicate patient management.

Aims: To examine the documentation of opioid ADR in a large-scale hospital-based EHR.

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A 55-year-old man presented with severe right upper quadrant abdominal pain and hypertension up to 231/171 mm Hg on a background of a known adrenal mass, intravenous drug use and recurrent anxiety attacks. CT showed heterogenous lesion of the right adrenal gland but the sudden severe pain remained unexplained. After correction of the blood pressure with analgesia and antihypertensives, the patient developed a type 2 non-ST-elevation myocardial infarction that was treated with aspirin and therapeutic enoxaparin.

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