IntroductionPrimary care dentistry is the first point of contact that someone has with the dental system and is predominantly focused on the treatment and prevention of dental caries and periodontal disease. The aim of this paper was to review the Australian primary dental care system. MethodsThis paper reviews the primary dental care system in Australia, drawing on data reporting on the dental workforce, funding sources for dental care, oral health outcome measures and dental visiting patterns. ResultsPrimary dental health care in Australia is predominantly provided by dentists working in private practice, with the number of dentists per 100,000 people in Australia increasing from 46.9 in 2000 to 65.1 in 2022. However, there has been a gradual shift over the past twenty years towards greater service provision by other members of the dental team who now represent one quarter of the dental workforce, and some expansion of publicly funded dental care. Despite this dentistry remains isolated from the rest of primary health care, and the lack of government funding means that many people continue to miss out of necessary dental care, particularly those living in regional and rural Australia and from low-income groups. ConclusionsAustralians should be able to access primary dental care services when and where they need it with adequate financial protection, from services that are well integrated into the broader primary health care system to ensure they are able to achieve optimal oral and general health. For many Australians, this is not currently the case. Clinical significanceAustralia is at a crossroads with respect to access to dental care, and there is a need for stronger advocacy from stakeholders to improve oral health outcomes and reduce inequalities.

IntroductionCurrent guidelines suggest preoperative direct oral anticoagulant levels of < 30–50 ng/ml. However, there is limited evidence to guide this expert consensus. Reviewing assay titres and clinical outcomes may be able to inform perioperative care of the anticoagulated patient. This review aimed to determine whether DOAC assay plasma concentrations are associated with bleeding or systemic embolic events to better appreciate a possible therapeutic or hazardous reference range. MethodsSystematic search, performed by an information specialist using a peer-reviewed search. Main search concepts were direct oral anticoagulant therapy for atrial fibrillation or venous thromboembolism. Data synthesised in narrative and tabular format whilst data that could be pooled was subjected to meta-analysis, using a random effects model. Meta regression was conducted for DOAC peak levels and clinical events. PRISMA guidelines were adhered to. ResultsOf 6717 retrieved publications, a total of 17 studies were included in the systematic review and 14 in the meta-analysis/regression. Studies report clinical outcome follow up ranging from 28 to 128 weeks. For every 10 ng/ml increase in DOAC assay trough and peak levels, the mean number of bleeding cases increases by 0.03(95 %CI: –0.32 –0.38, P = 0.84) and 0.09(95 %CI: –3.4 –5.3, P = 0.55) respectively, the mean number of major bleed cases increases by 0.01(95 %CI: –0.05 –0.07, P = 0.62) and 0.011(95 %CI: –0.32 –0.34, P = 0.74) respectively and the mean number of systemic embolic event cases decreases by 0.00039(95 %CI: –0.06 –0.0054, P = 0.88) and 0.04(95 %CI: –0.56 –0.48, P = 0.77) respectively. ConclusionThere exists no significant, independent relationship, as determined by a univariate meta regression, between DOAC assay concentrations and a patient's risk of bleeding or systemic embolic embolism. This review also highlights the possibility of an absolute, patient specific DOAC assay concentration that may indicate adequate anticoagulation, above which further increases do not confer an increased risk of bleeding. However, further research to characterise this and its utility in the perioperative setting is required.

With the advent of novel and emerging technologies, long duration spaceflight will become more common; along with it, an increase in its inherent health risks. However, health-related ethical issues arising during long-duration spaceflight remain poorly characterized, uncertain and unpredictable. Medical ethics is defined as a set of moral principles, beliefs and values that guides choices about medical care. This set of principles, founded in our sense of right and wrong, helps us make fair and just decisions. The paper conceptually and analytically investigates the ethical issues likely to arise from medical complications during spaceflight, mapping unfilled gaps of the current status quo. Furthermore, this paper explores broad ethical themes of autonomy, nonmaleficence, beneficence and justice, while also delving deeper into specific scenarios within each theme. The manuscript represents an up-to-date review of the available literature in the field of space medical ethics and recommends guiding ethical principles and a framework for their application to negotiate the resolution of complex ethical scenarios during long-duration spaceflight.

Severe asthma is a subset of difficult-to-treat asthma which requires a systematic and multidimensional approach including the need to manage multiple comorbidities that mimic asthma. Multidisciplinary care is becoming the standard for the assessment of such patients. Multidisciplinary team (MDT) clinics are virtually nonexistent in the private space. We developed an MDT clinic to handle needs in the private space and found it was an invaluable tool for assessment, reflective practice and professional development.

Australia is the only country with a national surgical mortality audit. Every Australian surgical mortality is independently and externally reviewed by another surgeon. Extensive educational feedback to surgeons and hospitals is provided through individual patient reviews, state and national symposia and reports, and the distribution of deidentified informative cases. This study reports a longitudinal analysis of the Australian surgical morality audit. The standardised mortality ratio (SMR) was calculated for each state and territory, nine surgical specialties and nationally. The index year used was 2016, or every 5years for those states with earlier data. Overall data were analysed in three groups-all deaths, postoperative deaths and non-operative deaths. Overall specialty data were analysed nationally. There was a consistent progressive fall, usually in excess of 20%, in the SMR in each state and territory and by specialty when compared to the index year. This was statistically significant nationally (p = 0.044). The same change was observed in earlier years in states with longer-term data. The period of this observational study has been associated with a nationwide fall in surgical mortality. As other improvements in care will have occurred during this period, the contribution that Australia's national mortality audit made towards the lower surgical mortality cannot be stated with certainty.

The frequency of oxycodone adverse reactions, subsequent opioid prescription, effect on pain and patient care in general surgery patients are not well known. This study aimed to determine prevalence of documented oxycodone allergy and intolerances (independent variables) in a general surgical cohort, and association with prescribing other analgesics (particularly opioids), subjective pain scores, and length of hospital stay (dependent variables). This retrospective cohort study included general surgery patients from two South Australian hospitals between April 2020 and March 2022. Multivariable logistic regression evaluated associations between previous oxycodone allergies and intolerances, prescription records, subjective pain scores, and length of hospital stay. Of 12 846 patients, 216 (1.7%) had oxycodone allergies, and 84 (0.7%) oxycodone intolerances. The 216 oxycodone allergy patients had lower odds of receiving oxycodone (OR 0.17, P < 0.001), higher odds of tramadol (OR 3.01, P < 0.001) and tapentadol (OR 2.87, P = 0.001), but 91 (42.3%) still received oxycodone and 19 (8.8%) morphine. The 84 with oxycodone intolerance patients had lower odds of receiving oxycodone (OR 0.23, P < 0.001), higher odds of fentanyl (OR 3.6, P < 0.001) and tramadol (OR 3.35, P < 0.001), but 42 (50%) still received oxycodone. Patients with oxycodone allergies and intolerances had higher odds of elevated subjective pain (OR 1.60, P = 0.013; OR 2.36, P = 0.002, respectively) and longer length of stay (OR 1.36, P = 0.038; OR 2.24, P = 0.002, respectively) than patients without these. General surgery patients with oxycodone allergies and intolerances are at greater risk of worse postoperative pain and longer length of stay, compared to patients without. Many still receive oxycodone, and other opioids that could cause cross-reactivity.

BackgroundThis study aimed to examine the accuracy with which multiple natural language processing artificial intelligence models could predict discharge and readmissions after general surgery. MethodsNatural language processing models were derived and validated to predict discharge within the next 48 hours and 7 days and readmission within 30 days (based on daily ward round notes and discharge summaries, respectively) for general surgery inpatients at 2 South Australian hospitals. Natural language processing models included logistic regression, artificial neural networks, and Bidirectional Encoder Representations from Transformers. ResultsFor discharge prediction analyses, 14,690 admissions were included. For readmission prediction analyses, 12,457 patients were included. For prediction of discharge within 48 hours, derivation and validation data set area under the receiver operator characteristic curves were, respectively: 0.86 and 0.86 for Bidirectional Encoder Representations from Transformers, 0.82 and 0.81 for logistic regression, and 0.82 and 0.81 for artificial neural networks. For prediction of discharge within 7 days, derivation and validation data set area under the receiver operator characteristic curves were, respectively: 0.82 and 0.81 for Bidirectional Encoder Representations from Transformers, 0.75 and 0.72 for logistic regression, and 0.68 and 0.67 for artificial neural networks. For readmission prediction within 30 days, derivation and validation data set area under the receiver operator characteristic curves were, respectively: 0.55 and 0.59 for Bidirectional Encoder Representations from Transformers and 0.77 and 0.62 for logistic regression. ConclusionModern natural language processing models, particularly Bidirectional Encoder Representations from Transformers, can effectively and accurately identify general surgery patients who will be discharged in the next 48 hours. However, these approaches are less capable of identifying general surgery patients who will be discharged within the next 7 days or who will experience readmission within 30 days of discharge.