NEW ZEALAND MEDICAL JOURNAL最新文献

Introduction: Gynaecological cancers are an increasing concern in Aotearoa New Zealand, with rapid growth in uterine cancer incidence in recent years. Understanding future incidence patterns is essential for planning and service delivery at a sub-national level.

Methods: Cancer registry data (2001-2022) were combined with population projections to estimate incidence of gynaecological cancers to 2045. Projections were generated using age-period-cohort Poisson regression models, with non-parametric bootstrapping to quantify uncertainty.

Results: Annual gynaecological cancer cases are projected to increase 82% by 2045, reaching 2,497 (95% uncertainty interval [UI] 2,263-2,774) compared with 1,375 in 2020-2022. The overall age-standardised rate is projected to rise 21% from 36.6 (95% confidence interval [CI] 35.5-37.8) to 44.2 per 100,000 (95% UI 38.9-50.3). Uterine cancer contributes the largest increase, more than doubling from 717 to 1,506 cases annually (110%). Among Māori, cases rise 132% from 214 to 497 per year (95% UI 449-553); for Pacific women, they rise 137% from 165 to 391 (95% UI 340-449). Uterine cancer age-standardised rates are projected to increase from 27.3 to 39.6 per 100,000 for Māori, and from 74.3 to 97.5 for Pacific women. Regional variation is expected: the Northern Region is projected to have the largest absolute increase (+506 cases, 527 to 1,033) and the largest percentage increase (96%).

Conclusion: Gynaecological cancer incidence in Aotearoa New Zealand is projected to rise substantially over the next 20 years, driven by demographic change and increasing incidence of uterine cancer likely associated with risk factors such as excess body weight and diabetes. Findings highlight the need to prioritise prevention, proactive service planning and equity-focussed early detection.

Achieving equity in health research requires sub-groups to have meaningful, if not equal, explanatory power, ideally through similiar sample sizes. Obtaining equal sample size, though, is often not possible. Small sub-group sizes increase the risk of false conclusions being drawn, which may reinforce inequities if results are misinterpreted (e.g., saying there is a difference between study arms when there is not and, conversely, saying there is no difference when there is). Here we provide examples of common pitfalls and potential considerations to guide researchers, reviewers and editors when analysing and interpreting sub-group data. We propose that researchers focus on presenting effect sizes and confidence intervals rather than statistical significance.

In the late nineteenth century, the popularity of cycling prompted a series of medicalised warnings, particularly for women. Among these was "bicycle face": a "nervous condition" attributed to a constant state of stress from attempting to balance a bicycle combined with prolonged facial grimacing, which was believed to result in nervous exhaustion and facial disfigurement. In New Zealand, media coverage peaked between 1895 and 1897, framing it as a threat to women's health, beauty and morals. Related conditions included "cyclemania", "bicycle stoop", "bicycle hump", "bicycle walk" and "bicycle heart". These designations reflected gender norms and anxieties over female independence, rather than medical evidence. The episode mirrors a broader historical pattern in which emerging technologies have triggered dubious health fears which parallel contemporary concerns over the safety of mobile phones, 5G towers and wind turbines. The authors explore the cultural and medical construction of "bicycle face" during the late nineteenth and early twentieth centuries, showing how a small number of rogue physicians used the media to amplify unfounded fears, implanting them into the public consciousness. The historical tendency for health practitioners to superimpose prevailing attitudes and beliefs onto health risks linked to new technologies highlights the need for evidence-based evaluations and vigilance against allowing cultural anxieties to masquerade as novel medical conditions.

Aim: Computed tomography coronary angiography (CTCA) is a sensitive tool for the diagnosis of atherosclerotic coronary artery disease (CAD). The study aim was to determine whether the finding of coronary atheroma on CTCA was associated with the subsequent use of statin therapy.

Methods: Patients with chest pain who underwent CTCA in 2020-2021 were identified from the Aotearoa New Zealand All Cardiology Services Quality Improvement (ANZACS-QI) cardiac computed tomography (CT) registry at Middlemore Hospital, Auckland, New Zealand. Patients were categorised into three groups: no atheroma, atheroma with non-obstructive CAD and atheroma with obstructive CAD.

Results: There were 548 patients with acute chest pain and 746 with stable chest pain. Of those with acute chest pain, no atheroma, non-obstructive and obstructive CAD was documented in 37.2%, 38% and 24.8%, respectively. In patients with obstructive CAD, statin dispensing was 52.9% pre-admission, 92.6% early post-CTCA and 87.5% at 1 year. In those with non-obstructive CAD, statin dispensing was 45.7% pre-admission, 67.8% early post-CTCA and 59.6% at 1 year. In those without atheroma, statins were dispensed in 23.5% at pre-admission and in 28.9% at 1 year. In the stable chest pain cohort, patterns of statin dispensing post-CTCA were similar to those in the acute chest pain cohort. On multivariate regression the presence of atheroma both with/without obstructive CAD was associated with higher levels of statin dispensing.

Conclusion: The finding of atheroma with obstructive CAD on CTCA is associated with appropriate increases in statin use. There are opportunities to optimise care by greater statin utilisation in non-obstructive CAD and down-titration in those without atheroma.

Aims: This study aimed to determine the association between demographic and clinical characteristics of mental health-related callouts to the ambulance services in Aotearoa New Zealand, focussing on differences among Māori, Pacific peoples and non-Māori non-Pacific peoples (NMNPP).

Methods: A retrospective cross-sectional study analysed routinely collected data from electronic patient report forms between 1 July 2022 and 30 June 2023. Mental health-related callouts were identified using clinician-coded impressions from the Aotearoa New Zealand Paramedic Care Collection.

Results: Of 26,847 callouts, a higher proportion involved individuals under the age of 24 among Māori (31.9%) and Pacific people (29.3%) compared to NMNPP (19.1%) (p<0.001). Callout proportion was higher in the most deprived areas, particularly among Māori (47.7%) and Pacific peoples (49.9%) versus NMNPP (24.5%) (p<0.001). Of total individual callouts, 15.8% presented more than once, with a higher proportion among Māori.

Conclusions: This study demonstrates an association between ethnicity, deprivation and mental health-related ambulance callouts, with Māori and Pacific populations in deprived areas experiencing proportionately higher callouts. Findings highlight the need for culturally responsive interventions and equitable access to care. Ambulance data can inform policy and monitor mental health trends.

Aim: We aimed to validate the interRAI Detection of Indicators and Vulnerabilities for Emergency Room Trips (DIVERT) scale in predicting unplanned hospital admissions following emergency department (ED) visits among community-dwelling older adults in an urban Aotearoa New Zealand population.

Methods: We conducted a retrospective cohort study of adults aged ≥55 years who underwent interRAI home care (HC) version 9.1 assessment between May 2021 and April 2022. The DIVERT score, derived from HC assessment data, categorised patients into risk levels. Hospital records were reviewed for unplanned hospital admissions via ED within 90 days of assessment. Statistical analyses, including survival and regression models, were used to evaluate predictive validity and explore risk factors.

Results: Between May 2021 and April 2022, 2,006 patients were assessed, with a mean age of 79.8 years (range 55-103). Admission rates within 90 days increased with higher DIVERT scores, from 18.2% (score 1) to 41.9% (score 6). Among high-risk groups (scores 5-6), a higher comorbidity burden was significantly associated with admission (p<0.001), while age, ethnicity and deprivation showed no statistically significant association. Primary causes of admission included infections, heart failure and falls. Mortality rates were notably higher in admitted patients at both 30 and 90 days.

Conclusions: This study confirms the predictive validity of the interRAI DIVERT scale for unplanned hospital admissions among community-dwelling older adults in urban Aotearoa New Zealand. The strong association between higher scores and increased admission rates supports its use in risk-stratification within this population.