Evidence map›Paper›PMID 42876616›Full record

Observational studyFrontiers in public health2026

Hospital SARS-CoV-2 surveillance across inpatient testing, fever clinic, and general outpatient settings: positivity, Ct gradients, and short-lag warning signals.

Guanglin Cui, Ning Song, Wanhai Wang

Abstract readObservational Study
In one paragraph

Observational study in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

Guanglin Cui *Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Ning Song *Center for Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Wanhai WangClinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hospital-based SARS-CoV-2 surveillance needs to distinguish front-end detection settings from inpatient testing burden and evaluate whether outpatient virological signals can provide early warning for downstream hospital pressure. Methods: We conducted a single-center retrospective observational study using all SARS-CoV-2 nucleic acid test records from Zhengdong Campus, The First Affiliated Hospital of Zhengzhou University, between 20 December 2022 and 31 December 2025. The unit of analysis was individual test specimens, classified into fever clinic, general outpatient, and inpatient testing groups. Statistical analyses included chi-square tests, non-parametric tests, logistic regression, and time-lagged correlation analyses. Results: Among 24,751 tests, 5,000 were positive (overall positivity 20.2%). Positivity was highest in the fever clinic (26.9%), followed by general outpatient (23.5%) and inpatient settings (16.3%). Among 4,134 positive tests with available cycle threshold (Ct) values, median Ct was highest in inpatients (30.0) and lower in fever clinic (28.0) and general outpatient (27.0) settings. The proportion of general outpatient positives with Ct < 25 showed the strongest overall association with subsequent inpatient positivity at a lag of 2 biweekly intervals. Outpatient settings concentrated stronger virological signals, while inpatient testing carried the largest absolute burden of positive results. Conclusion: The general outpatient clinic functions as a meaningful front-end surveillance interface rather than a low-risk background category. Monitoring low-Ct enrichment in outpatient settings can provide a pragmatic early warning for short-term inpatient pressure, supporting broader outpatient-focused hospital infection prevention strategies.

Indexed as

COVID-19FeverInpatientsOutpatientsChinaCOVID-19 Nucleic Acid TestingFemaleHumansMaleMiddle AgedRetrospective StudiesSARS-CoV-2cycle thresholdearly warning signalhospital surveillanceinpatient testingoutpatient screeningSARS-CoV-2

Identifiers

PMID42876616
PMCPMC13661547

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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.