Evidence map›Paper›PMID 42382287›Full record

ArticleDigital journal of ophthalmology : DJO2025

From normalcy to pandemic: analyzing cataract surgery patterns through case volumes and Google Trends (2014-2020).

Vinit Majmudar, Monali S Ardeshna, Raghav Vadhul

Abstract read
In one paragraph

Article in Digital journal of ophthalmology : DJO, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

3 authors.

Vinit Majmudar *Albany Medical College, Albany, New York.
Monali S Ardeshna *Albany Medical College, Albany, New York.
Raghav VadhulOhio State University Medical Center, Columbus, Ohio.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To examine cataract surgery rates among Medicare beneficiaries alongside Google Trends data to unveil insights into patient engagement and healthcare dynamics before and during the COVID-19 pandemic (2014 to 2020). Methods: Data of Google Trends (GT) relative search volumes (RSV) was collected for 9 total Google search terms related to cataracts or cataract procedures. Univariate linear regression was used to determine the correlation between average annual Google RSV for each search term and the total annual case volumes among US Medicare beneficiaries. Seasonal and pandemic trends were also studied. Results: There were statistically significant positive correlations between search data and the annual case volumes for cataract surgeries among Medicare beneficiaries for 5 of the 9 search terms selected. There was greater search traffic in summer and fall. Annual case volumes remained consistent and increasing from 2019 to 2020 during the pandemic, but search traffic decreased sharply. Conclusions: The stable rate in cataract surgeries among Medicare beneficiaries despite decreased patient engagement during the pandemic represents successful maintenance of health-care continuity. Google Trends is useful in understanding public interest and determining resource allocation and healthcare needs.

Indexed as

CataractCataract ExtractionCOVID-19InternetPandemicsSearch EngineHumansMedicareSARS-CoV-2United States

Identifiers

PMID42382287
PMCPMC13317496

What OpenQuestion holds

Textmetadata
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.