Axial length elongation profiles from 3 to 6 years in an Asian paediatric population: the Growing Up in Singapore Towards Healthy Outcomes birth cohort study (GUSTO)

AIMS

To determine axial length (AL) elongation profiles in children aged 3-6 years in an Asian population.

METHODS

Eligible subjects were recruited from the Growing Up in Singapore Towards Healthy Outcomes birth cohort. AL measurement was performed using IOLMaster (Carl Zeiss Meditec, Jena, Germany) at 3 and 6 years. Anthropometric measurements at birth, cycloplegic refraction at 3 and 6 years, questionnaires on the children's behavioural habits at 2 years and parental spherical equivalent refraction were performed. Multivariable linear regression model with generalised estimating equation was performed to determine factors associated with AL elongation.

RESULTS

273 eyes of 194 children were included. The mean AL increased from 21.72±0.59 mm at 3 years to 22.52±0.66 mm at 6 years (p<0.001). Myopic eyes at 6 years had greater AL elongation (1.02±0.34 mm) compared with emmetropic eyes (0.85±0.25 mm, p=0.008) and hyperopic eyes (0.74±0.16 mm, p<0.001). The 95th percentile limit of AL elongation was 1.59 mm in myopes, 1.34 mm in emmetropes and 1.00 mm in hyperopes. Greater birth weight (per 100 g, β=0.010, p=0.02) was significantly associated with greater AL elongation from 3 to 6 years, while parental and other behavioural factors assessed at 2 years were not (all p≥0.08).

CONCLUSION

In this preschool cohort, AL elongates at an average length of 0.80 mm from 3 to 6 years, with myopes demonstrating the greatest elongation. The differences in 95th percentile limits for AL elongation between myopes, emmetropes and hyperopes can be valuable information in identifying myopia development in preschool children.

Benchmarking large language models' performances for myopia care: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and Google Bard

BACKGROUND

Large language models (LLMs) are garnering wide interest due to their human-like and contextually relevant responses. However, LLMs' accuracy across specific medical domains has yet been thoroughly evaluated. Myopia is a frequent topic which patients and parents commonly seek information online. Our study evaluated the performance of three LLMs namely ChatGPT-3.5, ChatGPT-4.0, and Google Bard, in delivering accurate responses to common myopia-related queries.

METHODS

We curated thirty-one commonly asked myopia care-related questions, which were categorised into six domains-pathogenesis, risk factors, clinical presentation, diagnosis, treatment and prevention, and prognosis. Each question was posed to the LLMs, and their responses were independently graded by three consultant-level paediatric ophthalmologists on a three-point accuracy scale (poor, borderline, good). A majority consensus approach was used to determine the final rating for each response. 'Good' rated responses were further evaluated for comprehensiveness on a five-point scale. Conversely, 'poor' rated responses were further prompted for self-correction and then re-evaluated for accuracy.

FINDINGS

ChatGPT-4.0 demonstrated superior accuracy, with 80.6% of responses rated as 'good', compared to 61.3% in ChatGPT-3.5 and 54.8% in Google Bard (Pearson's chi-squared test, all p ≤ 0.009). All three LLM-Chatbots showed high mean comprehensiveness scores (Google Bard: 4.35; ChatGPT-4.0: 4.23; ChatGPT-3.5: 4.11, out of a maximum score of 5). All LLM-Chatbots also demonstrated substantial self-correction capabilities: 66.7% (2 in 3) of ChatGPT-4.0's, 40% (2 in 5) of ChatGPT-3.5's, and 60% (3 in 5) of Google Bard's responses improved after self-correction. The LLM-Chatbots performed consistently across domains, except for 'treatment and prevention'. However, ChatGPT-4.0 still performed superiorly in this domain, receiving 70% 'good' ratings, compared to 40% in ChatGPT-3.5 and 45% in Google Bard (Pearson's chi-squared test, all p ≤ 0.001).

INTERPRETATION

Our findings underscore the potential of LLMs, particularly ChatGPT-4.0, for delivering accurate and comprehensive responses to myopia-related queries. Continuous strategies and evaluations to improve LLMs' accuracy remain crucial.

FUNDING

Dr Yih-Chung Tham was supported by the National Medical Research Council of Singapore (NMRC/MOH/HCSAINV21nov-0001).

Preventing transition "regret": An institutional ethnography of gender-affirming medical care assessment practices in Canada

When a person openly "regrets" their gender transition or "detransitions" this bolsters within the medical community an impression that transgender and non-binary (trans) people require close scrutiny when seeking hormonal and surgical interventions. Despite the low prevalence of "regretful" patient experiences, and scant empirical research on "detransition", these rare transition outcomes profoundly organize the gender-affirming medical care enterprise. Informed by the tenets of institutional ethnography, we examined routine gender-affirming care clinical assessment practices in Canada. Between 2017 and 2018, we interviewed 11 clinicians, 2 administrators, and 9 trans patients (total n = 22), and reviewed 14 healthcare documents pertinent to gender-affirming care in Canada. Through our analysis, we uncovered pervasive regret prevention techniques, including requirements that trans patients undergo extensive psychosocial evaluations prior to transitioning. Clinicians leveraged psychiatric diagnoses as a proxy to predict transition regret, and in some cases delayed or denied medical treatments. We identified cases of patient dissatisfaction with surgical results, and a person who detransitioned. These accounts decouple transition regret and detransition, and no participants endorsed stricter clinical assessments. We traced the clinical work of preventing regret to cisnormativity and transnormativity in medicine which together construct regret as "life-ending", and in turn drives clinicians to apply strategies to mitigate the perceived risk of malpractice legal action when treating trans people, specifically. Yet, attempts to prevent these outcomes contrast with the material healthcare needs of trans people. We conclude that regret and detransitioning are unpredictable and unavoidable clinical phenomena, rarely appearing in "life-ending" forms. Critical research into the experiences of people who detransition is necessary to bolster comprehensive gender-affirming care that recognizes dynamic transition trajectories, and which can address clinicians' fears of legal action-cisgender anxieties projected onto trans patients who are seeking medical care.