Sight Impairment registration in Trinidad: 35-year trend in causes and population coverage in comparison to the National Eye Survey of Trinidad and Tobago
Bibliographic record
Abstract
Abstract Background: Little was known causes and coverage of sight impairment (SI) registration in the Caribbean. We compared the Trinidad and Tobago Blind Welfare Association (TTBWA) register and findings from the 2014 National Eye Survey of Trinidad and Tobago (NESTT). Methods: This study included TTBWA register analysis; cross-sectional validation studies of registered clients, involving interviews, vision function and cause ascertainment in July 2013, and interview and visual function measurement only in July 2016; comparison of causes of SI between register and national survey, and estimation of registration coverage. Results: The TTBWA register included 863 people (all ages) registered between 1980 and 2015, 48.1%(n=415) male. The NESTT identified 1.1%(75/7158) people aged >5years eligible for SI or SSI registration, 49.3%(n=37) male. The causes of SI and SSI agreed closely between the register and population-representative survey, with glaucoma being the leading cause in both the register (26.1%,n=225) and population survey (26.1%, 18/69 adults), followed by cataract and diabetic retinopathy. In the validation studies combined, 62.6%(93/151) clients had SSI, 28.5%(43/151) had (partial) SI and 9.9%(15/151) did not meet SI eligibility criteria. Registration coverage was approximately 7% of the eligible population in Trinidad. SI and SSI were potentially avoidable in at least 58%(n=36/62) adults and 50%(n=7/14) children examined in the 2013 validation study. Conclusion: We report close agreement in causes of SI between a national register and contemporaneous national population-based eye survey, but highlight low register coverage, and that at least half of all SI resulted from preventable, treatable or curable eye diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".