Focussing both eyes on health outcomes: revisiting cataract surgery
Bibliographic record
Abstract
BACKGROUND: The appropriateness of cataract surgery procedures has been questioned, the suggestion being that the surgery is sometimes undertaken too early in the disease progression. Our three study questions were: What is the level of visual impairment in patients scheduled for cataract surgery? What is the improvement following surgery? Given the thresholds for a minimal detectable change (MDC) and a minimal clinically important difference (MCID), do gains in visual function reach the MDC and MCID thresholds? METHODS: The sample included a prospective cohort of cataract surgery patients from four Fraser Health Authority ophthalmologists. Visual function (VF-14) was assessed pre-operatively and at seven weeks post-operatively. Two groups from this cohort were included in this analysis: 'all first eyes' (cataract extraction on first eye) and 'both eyes' (cataract removed from both eyes). Descriptive statistics, change scores for VF-14 for each eye group and proportion of patients who reach the MDC and MCID are reported. RESULTS: One hundred and forty-two patients are included in the 'all first eyes' analyses and 55 in the 'both eyes' analyses. The mean pre-operative VF-14 score for the 'all first eyes' group was 86.7 (on a 0-100 scale where 100 is full visual function). The mean change in VF-14 for the 'both eyes' group was 7.5. Twenty-three percent of patients achieved improvements in visual function beyond the MCID threshold and 35% saw improvement beyond the MDC. CONCLUSIONS: Neither threshold level for MDC or MCID for the VF-14 scale was achieved for a majority of patients. A plausible explanation for this is the very high levels of pre-operative visual functioning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".