Evidence map›Paper›PMID 42775244›Full record

ArticleJournal of ophthalmology2026

Association Between Lens Thickness and SRK/T Refractive Prediction Error After Cataract Surgery: A Single-Center Retrospective Cohort Study.

Tao Liu, Haifeng Jiang, Yanxia Tong, Zhanpeng Zhu, Lihan Luo, Yong Wang

Abstract read
In one paragraph

Article in Journal of ophthalmology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Tao LiuZhoukou Aier Eye Hospital, Zhoukou, Henan, China.ORCID https://orcid.org/0009-0006-2917-6327
Haifeng JiangZhoukou Aier Eye Hospital, Zhoukou, Henan, China.ORCID https://orcid.org/0009-0007-8813-0000
Yanxia TongAier Eye Hospital of Wuhan University (Wuhan Aier Eye Hospital), Wuhan, Hubei, China.ORCID https://orcid.org/0009-0005-7516-8777
Zhanpeng ZhuAier Eye Hospital of Wuhan University (Wuhan Aier Eye Hospital), Wuhan, Hubei, China.ORCID https://orcid.org/0009-0004-9600-1645
Lihan LuoAier Eye Hospital of Wuhan University (Wuhan Aier Eye Hospital), Wuhan, Hubei, China.ORCID https://orcid.org/0009-0009-5087-5503
Yong WangAier Eye Hospital of Wuhan University (Wuhan Aier Eye Hospital), Wuhan, Hubei, China.ORCID https://orcid.org/0000-0002-7645-9972

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To evaluate the association between lens thickness (LT) and SRK/T refractive prediction error following cataract surgery and to analyze its underlying mechanism. Methods: This retrospective cohort study collected data from patients who underwent surgical treatment for age-related cataracts between January 2025 and June 2025. Patients were stratified into three groups based on LT: Group 1 (< 4.0 mm), Group 2 (4.0 ≤ LT < 5.0 mm), and Group 3 (≥ 5.0 mm). Intraocular lens (IOL) power was calculated using the SRK/T formula. Manifest refraction results were collected at ≥ 4 weeks postoperatively. Accuracy of IOL power calculation was analyzed using prediction error (PE), mean absolute error (MAE), median absolute error (MedAE), and the proportions of PE within ±0.25 D, ±0.50 D, and ±1.00 D. Correlations between LT and effective lens position (ELP) as well as postoperative refractive error were assessed. Results: A total of 431 patients (431 eyes) were included, with a mean LT of 4.50 ± 0.58 mm. The overall mean PE was -0.08 ± 0.44 D, and the mean ELP Conclusion: Increased deviation of LT from the mean results in larger ELP prediction errors and greater postoperative refractive error. Thin-lens eyes tended to be myopic, while thick-lens eyes tended to be hyperopic.

Indexed as

cataracteffective lens positionlens thicknessrefractive error

Identifiers

PMID42775244
PMCPMC13595810

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.