Article in Journal of endourology, 2021. 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.
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.
David B BayneDepartment of Urology, University of California San Francisco, San Francisco, California, USA.
Manuel Armas-PhanDepartment of Urology, University of California San Francisco, San Francisco, California, USA.
Sudarshan SrirangapatanamDepartment of Urology, University of California San Francisco, San Francisco, California, USA.
Justin AhnDepartment of Urology, University of California San Francisco, San Francisco, California, USA.
Timothy T BrownBerkeley Center for Health Technology, School of Public Health, University of California, Berkeley, Berkeley, California, USA.
Marshall StollerDepartment of Urology, University of California San Francisco, San Francisco, California, USA.
Thomas L ChiDepartment of Urology, University of California San Francisco, San Francisco, California, USA.
Funding
UCSF-Kaiser Urological Epidemiology Research Career Development ProgramK12DK111028 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HUANG, ALISON · 2016 to 2025
$5.3M
Optimizing Kidney Stone Management Using Metallomics and MetabolomicsP20DK100863 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI STOLLER, MARSHALL · 2013 to 2016
$1.6M
Validating an automated nephrolithiasis registry as a community research toolP20DK116193 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHAN, JUNE ML · 2017 to 2018
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.
Low Urologist Density Predicts High-Cost Surgical Treatment of Stone Disease. · full record | OpenQuestion