Factors associated with electroconvulsive therapy treatment for adults with serious psychiatric conditions in Australia.

OBJECTIVE: To identify factors associated with receiving electroconvulsive therapy (ECT) for serious psychiatric conditions. METHODS: Retrospective observational study using hospital administrative data linked with death registrations and outpatient mental health data in New South Wales (NSW), Australia. The cohort included patients admitted with a primary psychiatric diagnosis between 2013 and 2022. The outcome measure was receipt of ECT. RESULTS: Of 94,950 patients, 3465 (3.6%) received ECT. The likelihood of receiving ECT was higher in older (hazard ratio [HR] = 1.03), female (HR = 1.24) patients. Compared to depression, patients with schizophrenia/schizoaffective disorder (HR = 0.79), schizophrenia-related disorders (HR = 0.37), mania (HR = 0.64) and other mood disorders (HR = 0.45) had lower odds of receiving ECT. Patients with depression and one other serious psychiatric condition had higher odds of receiving ECT than depression alone. Bipolar disorder likelihood of ECT did not differ from depression. A higher number of mental health outpatient visits in the prior year and an involuntary index admission with depression were also associated with receiving ECT. Likelihood of receiving ECT increased with year of admission (HR = 1.32), private patient status (HR = 2.06), higher socioeconomic status (HR = 1.09) and being married (HR = 1.25). CONCLUSIONS: ECT use for depression and bipolar disorder in NSW aligns with clinical national guidelines. Patients with schizophrenia/schizoaffective, schizophrenia-related disorders, mania and other mood disorders had lower likelihood of ECT than depression, despite ECT being recommended by clinical guidelines for these diagnoses. Variations in ECT were strongly associated with healthcare access, with private patients twice as likely to receive ECT than their public counterparts, suggesting a need to explore ECT accessibility.

Estimating the impact of bias in causal epidemiological studies: the case of health outcomes following assisted reproduction.

Researchers interested in causal questions must deal with two sources of error: random error (random deviation from the true mean value of a distribution), and bias (systematic deviance from the true mean value due to extraneous factors). For some causal questions, randomization is not feasible, and observational studies are necessary. Bias poses a substantial threat to the validity of observational research and can have important consequences for health policy developed from the findings. The current piece describes bias and its sources, outlines proposed methods to estimate its impacts in an observational study, and demonstrates how these methods may be used to inform debate on the causal relationship between medically assisted reproduction (MAR) and health outcomes, using cancer as an example. In doing so, we aim to enlighten researchers who work with observational data, especially regarding the health effects of MAR and infertility, on the pitfalls of bias, and how to address them. We hope that, in combination with the provided example, we can convince readers that estimating the impact of bias in causal epidemiologic research is not only important but necessary to inform the development of robust health policy and clinical practice recommendations.

Predicting Adverse Outcomes Following Catheter Ablation Treatment for Atrial Flutter/Fibrillation.

BACKGROUND & AIM: To develop prognostic survival models for predicting adverse outcomes after catheter ablation treatment for non-valvular atrial fibrillation (AF) and/or atrial flutter (AFL). METHODS: We used a linked dataset including hospital administrative data, prescription medicine claims, emergency department presentations, and death registrations of patients in New South Wales, Australia. The cohort included patients who received catheter ablation for AF and/or AFL. Traditional and deep survival models were trained to predict major bleeding events and a composite of heart failure, stroke, cardiac arrest, and death. RESULTS: Out of a total of 3,285 patients in the cohort, 177 (5.3%) experienced the composite outcome-heart failure, stroke, cardiac arrest, death-and 167 (5.1%) experienced major bleeding events after catheter ablation treatment. Models predicting the composite outcome had high-risk discrimination accuracy, with the best model having a concordance index >0.79 at the evaluated time horizons. Models for predicting major bleeding events had poor risk discrimination performance, with all models having a concordance index <0.66. The most impactful features for the models predicting higher risk were comorbidities indicative of poor health, older age, and therapies commonly used in sicker patients to treat heart failure and AF and AFL. DISCUSSION: Diagnosis and medication history did not contain sufficient information for precise risk prediction of experiencing major bleeding events. Predicting the composite outcome yielded promising results, but future research is needed to validate the usefulness of these models in clinical practice. CONCLUSIONS: Machine learning models for predicting the composite outcome have the potential to enable clinicians to identify and manage high-risk patients following catheter ablation for AF and AFL proactively.

Six-minute walk test distance at time of hospital discharge is strongly and independently associated with all-cause mortality following cardiac surgery.

We investigated the impact of distance covered in the six-minute walk test (6mWT) before being discharged from the hospital after cardiac surgery on the risk of all-cause mortality. Our study included 1127 patients who underwent cardiac surgery and then took part in a standardised physiotherapist-supervised inpatient rehabilitation programme during 2007-2017. The percentage of the predicted 6mWT distance, and the lower limit of normal distance was calculated based on individual patients' age, sex, and body mass index. We used Cox regression with adjustment for confounders to determine multivariable-adjusted hazard ratios (HRs) for mortality. Over a median follow-up period of 6.4 (IQR: 3.5-9.2) years, 15% (n = 169) patients died. We observed a strong and independent inverse association between 6mWT distance and mortality, with every 10 m increase in distance associated to a 4% reduction in mortality (HR: 0.96, 95% CI 0.94-0.98, P < 0.001). Those in the top tertile for predicted 6mWT performance had a 49% reduced risk of mortality (HR: 0.51, 95% CI 0.33-0.79) compared to those in the bottom tertile. Patients who met or exceeded the minimum normal 6mWT distance had 36% lower mortality risk (HR: 0.64, 95% CI 0.45-0.92) compared to those who did not meet this benchmark. Subgroup analysis showed that combined CABG and valve surgery patients walked less in the 6mWT compared to those undergoing isolated CABG or valve surgeries, with a significant association between 6mWT and mortality observed in the isolated procedure groups only. In conclusion, the longer the distance covered in the 6mWT before leaving the hospital, the lower the risk of mortality.