Evidence map›Paper›PMID 29538278›Full record

ArticleSexually transmitted diseases2018

Going Off Grid: Modeling an Automated Record Search to Process Electronically Reported Reactive Nontreponemal Syphilis Tests.

James Matthias, Gayle Keller, Susan Cha, Craig Wilson, Thomas A Peterman

Abstract read
In one paragraph

Article in Sexually transmitted diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

5 authors.

James Matthias
Gayle KellerFlorida Department of Health, Tallahassee, FL.
Susan Cha
Craig WilsonFlorida Department of Health, Tallahassee, FL.
Thomas A Peterman

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

backgroundBefore searching prior records, sexually transmitted disease programs use syphilis reactor grids to exclude some reactive nontreponemal test results (RNTs) based on patient age, gender, and test titer. We propose a new algorithm that starts with comparing RNTs to previous syphilis nontreponemal tests and current treponemal test results.

methodsDeduplicated RNTs from Florida's surveillance system (2006-2015) were extracted and stratified on morbidity. An algorithm was developed to triage RNTs. Sensitivity and specificity of the algorithm and the current reactor grid were estimated using reported syphilis cases. A random sample of cases missed by the proposed algorithm, stratified by stage of disease, was reviewed to verify case classification.

resultsReported RNTs increased 58% from 2006 (n = 34,808) to 2015 (n = 55,001) (total = 372,902). The current reactor grid removed 91,518 (24.5%) RNTs and missed 1149 potential cases. Strictly following the reactor grid would result in a sensitivity of 97.4% and a specificity of 27.5%. The proposed algorithm would remove 242,078 (64.9%) RNTs and miss 2768 potential cases. This results in a slightly lower sensitivity of 93.8%, but nearly triples the specificity, 72.9%. A review of a random sample of the 2768 cases estimated that 72.7% would not have met the syphilis surveillance case definition, resulting in an adjusted sensitivity of 98.4%.

conclusionsIn Florida, an algorithm that starts by searching previous syphilis test results vastly improved specificity and slightly improved sensitivity compared with the current reactor grid. Implementing an automated algorithm could increase case ascertainment efficiency and further prioritize likely cases for investigation.

Indexed as

AlgorithmsAutomationAdultAgedCenters for Disease Control and Prevention, U.S.Epidemiological MonitoringFemaleFloridaHumansMaleMass ScreeningMiddle AgedModels, TheoreticalSensitivity and SpecificitySyphilisSyphilis Serodiagnosis

Identifiers

PMID29538278
PMCPMC6190675

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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.