Evidence map›Paper›PMID 26605353›Full record

ReviewEye and vision (London, England)2014

Practical issues concerning tear protein assays in dry eye.

Sharon D'Souza, Louis Tong

Open access · hybridAbstract readReview
In one paragraph

Review in Eye and vision (London, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.9field-weighted citation impact, top 13% of its field
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

14 citing papers in PubMed, 45 citations in OpenAlex.

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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

2 authors at 2 institutions in 2 countries.

Sharon D'SouzaNarayana Nethralaya Superspeciality Eye Hospital and Post Graduate Institute, Bangalore, Karnataka India.
Louis TongSingapore Eye Research Institute, 11, Third Hospital Avenue, Singapore, 168751 Singapore ; Singapore National Eye Center, Singapore, Singapore ; Duke-NUS Graduate Medical School, Singapore, Singapore ; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Narayana Nethralaya · INSingapore Eye Research Institute · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dry eye is a common clinical condition diagnosed by cumulative evidence of symptoms and signs. Many new treatments in dry eye are either expensive, invasive, have potential for side effects, or are not easily accessible. In severe dry eye, the ideal modality of treatment to begin with is often not clear as specific molecular disturbances are not evident from just examination of clinical manifestations. Assessing the effects of ongoing treatment is not straight forward since there is lack of agreement between clinical signs and symptoms. There is a need to have more objective methods of selecting treatment for dry eye and monitoring the effect of treatment. Recently, there are many new technologies applied to the discovery of tear biomarkers, for e.g., mass spectrometry based proteomics techniques and multiplex assays such as the bead-based sandwich indirect immunofluorescent assays. Tear proteins assays have even been made available as point-of-care devices. This review focuses on the evidence for the involvements of tear proteins in dry eye, possible changes in tear concentrations with therapy and the strength of evidence regarding dry eye pathology. Much remains to be done in terms of developing office-based assays and ascertaining their reliability, but current evidence suggests that tear proteins have a role in the clinical practice of dry eye.

Indexed as

BiomarkerDry eyeHumanProteomicsReviewTear

Identifiers

PMID26605353
PMCPMC4604107
OpenAlexW2113818659

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.