Refractive error magnitude and variability: Relation to age
Bibliographic record
Abstract
To investigate mean ocular refraction (MOR) and astigmatism, over the human age range and compare severity of refractive error to earlier studies from clinical populations having large age ranges. For this descriptive study patient age, refractive error and history of surgery affecting refraction were abstracted from the Waterloo Eye Study database (WatES). Average MOR, standard deviation of MOR and astigmatism were assessed in relation to age. Refractive distributions for developmental age groups were determined. MOR standard deviation relative to average MOR was evaluated. Data from earlier clinically based studies with similar age ranges were compared to WatES. Right eye refractive errors were available for 5933 patients with no history of surgery affecting refraction. Average MOR varied with age. Children <1 yr of age were the most hyperopic (+1.79 D) and the highest magnitude of myopia was found at 27yrs (−2.86 D). MOR distributions were leptokurtic, and negatively skewed. The mode varied with age group. MOR variability increased with increasing myopia. Average astigmatism increased gradually to age 60 after which it increased at a faster rate. By 85+ years it was 1.25 D. J0 power vector became increasingly negative with age. J45 power vector values remained close to zero but variability increased at approximately 70 years. In relation to comparable earlier studies, WatES data were most myopic. Mean ocular refraction and refractive error distribution vary with age. The highest magnitude of myopia is found in young adults. Similar to prevalence, the severity of myopia also appears to have increased since 1931. Estudiar la refracción ocular media (MOR) y el astigmatismo a lo largo del rango de la vida humana, y comparar la magnitud del error refractivo con estudios previos sobre poblaciones clínicas con rangos de edad amplios. Para este estudio descriptivo, se extrajeron de la base de datos Waterloo Eye Study (WatES) la edad del paciente, el error refractivo y el historial de cirugía con repercusión en la refracción. Se evaluaron la MOR media, la desviación estándar de MOR y el astigmatismo con relación a la edad. Se calcularon las distribuciones refractivas para los grupos de edad evolutiva. Se evaluó la desviación estándar de MOR con respecto a MOR media. Se compararon los datos de los estudios clínicos previos con los rangos de edad similares de WatES. Se dispuso de los errores refractivos del ojo derecho de 5.933 pacientes sin historial de cirugía con repercusión en la refracción. La MOR media sufrió variaciones con la edad. Los niños con edad <1 año reflejaron mayor hipermetropía (+1,79D), encontrándose el mayor valor de miopía a los 27 años (−2,86D). Las distribuciones de MOR fueron leptocúrticas, y negativamente sesgadas. La moda varió con el grupo de edad. La variabilidad de MOR se incrementó al aumentar la miopía. El astigmatismo medio aumentó gradualmente hasta los 60 años, pasados los cuales se incrementó a mayor velocidad. A los 85 años, o más, su valor fue de 1,25D. El vector de potencia J0 se modificó hacia valores más negativos con la edad. Los valores del vector de potencia J45 fueron cercanos a 0, aunque su variabilidad se incrementó a los 70 años, aproximadamente. Con relación a los estudios previos comparables, los datos WatES fueron más miópicos. La refracción ocular media y la distribución del error refractivo varían con la edad. La mayor magnitud de la miopía se encontró en los adultos jóvenes. Al igual que la prevalencia, la gravedad de la miopía parece haberse incrementado desde 1931.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".