Evidence map›Paper›PMID 34414082›Full record

ArticleInternational journal of ophthalmology2021

Comparison of the SITA Faster-a new visual field strategy with SITA Fast strategy.

Chao-Xu Qian, Qin Chen, Qing Cun, Yi-Jin Tao, Wen-Yan Yang, Yue Yang, Zhong-Yin Hu, Ying-Ting Zhu, Hua Zhong

Abstract read
In one paragraph

Article in International journal of ophthalmology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

9 authors.

Chao-Xu QianThe First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China.
Qin ChenThe First Affiliated Hospital of Nanjing Medical University, Nanjing 210000, Jiangsu Province, China.
Qing CunThe First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China.
Yi-Jin TaoThe First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China.
Wen-Yan YangThe First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China.
Yue YangThe First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China.
Zhong-Yin HuThe First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China.
Ying-Ting ZhuTissue Tech, Inc., 7300 Corporate Center Drive, Suite B, Miami, FL 33126, USA.
Hua ZhongThe First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo compare visual field defects using the Swedish Interactive Thresholding Algorithm (SITA) Fast strategy with SITA Faster strategy, a newly developed time-saving threshold visual field strategy.

methodsNinety-three participants (60 glaucoma patients and 33 normal controls) were enrolled. One eye from each participant was selected randomly for the study. SITA Fast and SITA Faster were performed using the 24-2 default mode for each test. The differences of visual field defects between the two strategies were compared using the test duration, false-positive response errors, mean deviation (MD), visual field index (VFI) and the numbers of depressed test points at the significant levels of

resultsMean test durations were 246.0±60.9s for SITA Fast, and 156.3±46.3s for SITA Faster (

conclusionSITA Faster, which saves considerable test time, has a great test quality comparing to SITA Fast, but may be not directly interchangeable.

Indexed as

glaucomaSITA Faster strategySITA Fast strategyvisual field

Identifiers

PMID34414082
PMCPMC8342287

What OpenQuestion holds

Textmetadata
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Registered trials

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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.