Evidence map›Paper›PMID 35626375›Full record

ArticleDiagnostics (Basel, Switzerland)2022

The Coronavirus Disease 2019 Spatial Care Path: Home, Community, and Emergency Diagnostic Portals.

Gerald J Kost

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. 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

1 author.

Gerald J KostFulbright Scholar 2020-2022, ASEAN Program, Point-of-Care Testing Center for Teaching and Research (POCT•CTR), Pathology and Laboratory Medicine, School of Medicine, University of California, Davis, CA 95616, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research uses mathematically derived visual logistics to interpret COVID-19 molecular and rapid antigen test (RAgT) performance, determine prevalence boundaries where risk exceeds expectations, and evaluate benefits of recursive testing along home, community, and emergency spatial care paths. Mathematica and open access software helped graph relationships, compare performance patterns, and perform recursive computations. Tiered sensitivity/specificity comprise: (T1) 90%/95%; (T2) 95%/97.5%; and (T3) 100%/≥99%, respectively. In emergency medicine, median RAgT performance peaks at 13.2% prevalence, then falls below T1, generating risky prevalence boundaries. RAgTs in pediatric ERs/EDs parallel this pattern with asymptomatic worse than symptomatic performance. In communities, RAgTs display large uncertainty with median prevalence boundary of 14.8% for 1/20 missed diagnoses, and at prevalence > 33.3−36.9% risk 10% false omissions for symptomatic subjects. Recursive testing improves home RAgT performance. Home molecular tests elevate performance above T1 but lack adequate validation. Widespread RAgT availability encourages self-testing. Asymptomatic RAgT and PCR-based saliva testing present the highest chance of missed diagnoses. Home testing twice, once just before mingling, and molecular-based self-testing, help avoid false omissions. Community and ER/ED RAgTs can identify contagiousness in low prevalence. Real-world trials of performance, cost-effectiveness, and public health impact could identify home molecular diagnostics as an optimal diagnostic portal.

Indexed as

Emergency Use Authorization (EUA)endemicfalse omission rate (RFO)home testingpoint-of-care testing (POCT)positive predictive value geometric mean-squared (PV GM2)prevalence boundaryrecursive protocoltiervisual logistics

Identifiers

PMID35626375
PMCPMC9140623

What OpenQuestion holds

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LicenceCC BY
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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.