Evidence map›Paper›PMID 38737481›Full record

ArticleChina CDC weekly2024

Epidemiological Insights into Foodborne Pathogens Through qPCR Exploration of Prevalence - Beijing Municipality, China, January 2022-April 2023.

Penghang Zhang, Xiaochen Ma, Yuzhu Liu, Tongyu Wang, Shuning Huo, Xiaoai Zhang

Abstract read
In one paragraph

Article in China CDC weekly, 2024. 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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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

6 authors.

Penghang ZhangBeijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning; Institute for Nutrition and Food Hygiene, Beijing Center for Disease Prevention and Control, Beijing, China.
Xiaochen MaBeijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning; Institute for Nutrition and Food Hygiene, Beijing Center for Disease Prevention and Control, Beijing, China.
Yuzhu LiuBeijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning; Institute for Nutrition and Food Hygiene, Beijing Center for Disease Prevention and Control, Beijing, China.
Tongyu WangBeijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning; Institute for Nutrition and Food Hygiene, Beijing Center for Disease Prevention and Control, Beijing, China.
Shuning HuoYanjing Medical College of Capital Medical University, Beijing, China.
Xiaoai ZhangBeijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning; Institute for Nutrition and Food Hygiene, Beijing Center for Disease Prevention and Control, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

What is already known on this topic?: Foodborne diseases present a substantial global health risk. Traditional diagnostic methods have constraints, but advancements in molecular techniques, like quantitative polymerase chain reaction (qPCR), provide a hopeful solution. What is added by this report?: We examined 1,011 stool samples from individuals suspected of foodborne illnesses. Our analysis indicated a significant presence of What are the implications for public health practice?: The data emphasize a notable prevalence of co-infections, highlighting the complexity of foodborne illnesses. This study underscores the significance of utilizing contemporary diagnostic methods in densely populated urban areas such as Beijing Municipality.

Indexed as

Foodborne PathogensPrevalencesQuantitative PCR Epidemiology

Identifiers

PMID38737481
PMCPMC11082648

What OpenQuestion holds

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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.