Evidence map›Paper›PMID 38259841›Full record

ArticleFrontiers in medicine2023

Total keratometry for toric intraocular lens calculation: comparison from two swept-source optical coherence tomography biometers.

Feiyan Chai, Jack X Ma, Xiaogang Wang, Jiewei Liu, Lin Jiang, Wanmin Wu, Junhong Li

Abstract read
In one paragraph

Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Feiyan ChaiShanxi Eye Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China.
Jack X MaRuiz Department of Ophthalmology and Visual Science, McGovern Medical School at The University of Texas Health Science Center at Houston, Houston, TX, United States.
Xiaogang WangShanxi Eye Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China.
Jiewei LiuShanxi Eye Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China.
Lin JiangShanxi Eye Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China.
Wanmin WuShanxi Eye Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China.
Junhong LiShanxi Eye Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To compare the astigmatism prediction accuracy of total keratometry (TK) from the IOLMaster 700 and total corneal power (TCP) from Anterion based on swept-source optical coherence tomography (SS-OCT) technology in toric intraocular lens (toric IOL) calculation. Design: A retrospective observational study. Methods: Total corneal astigmatism (TCA) were obtained using IOLMaster 700 and Anterion. Z CALC 2.0 was used to calculate the expected postoperative refractive astigmatism in conjunction with TCA. Prediction errors (PE) in refractive outcomes was analyzed 1 month postoperatively using the vector analysis by the Holladay method, including the mean vector PE magnitude, percentage of cases with vector PE in certain intervals, and the centroid PE. Results: A total of 56 eyes from 56 patients were enrolled in the study with an insertion of an AT TORBI 709 toric IOL. The difference in mean vector PE of postoperative refractive astigmatism between TK and TCP was not statistically significant (0.48D versus 0.46D, Conclusion: IOLMaster 700 and Anterion provided comparable astigmatic predictability in toric IOL implantation using total keratometry and Z CALC 2.0.

Indexed as

AnterionIOLMaster 700prediction errortotal corneal powertotal keratometry

Identifiers

PMID38259841
PMCPMC10800841

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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.