Evidence map›Paper›PMID 37853349›Full record

ArticleBMC gastroenterology2023

Lifestyle-based nomogram for identifying the Chaoshan inhabitants of China at high risk of Helicobacter pylori infection.

Yi-Ting Lin, Pei-Ru Wang, Wen-Wen Xue, Si-Si Zhou, Ze-Yu Huang, Yu-Ting Li, Zhuo-Na Zheng, Wen-Jing Hou, Qi-Xian Chen, Jing Yu

Abstract read
In one paragraph

Article in BMC gastroenterology, 2023. 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
  2. Article
  3. Current concepts of Helicobacter pylori infection.European journal of medical research · 2025
    Review
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

10 authors.

Yi-Ting LinDepartment of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Pei-Ru WangDepartment of Nursing, Shantou Central Hospital, Shantou, China.
Wen-Wen XueDepartment of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Si-Si ZhouDepartment of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Ze-Yu HuangDepartment of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Yu-Ting LiDepartment of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Zhuo-Na ZhengDepartment of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Wen-Jing HouDepartment of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Qi-Xian ChenDepartment of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Jing YuDepartment of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China. scorpiojing@139.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHelicobacter pylori (HP) infection is associated with various diseases. Early detection can prevent the onset of illness. We constructed a nomogram to predict groups at high risk of HP infection.

methodsPatients who underwent regular medical check-ups at hospital in Chaoshan, China from March to September 2022 were randomly allocated to the training and validation cohorts. Risk factors including basic characteristics and lifestyle habits associated with HP infection were analyzed by logistic regression analyses. The independent varieties were calculated and plotted into a nomogram. The nomogram was internally validated by receiver operating characteristic curve, calibration, and decision curve analyses (DCAs).

resultsOf the 945 patients, 680 were included in the training cohort and 265 in the validation cohort. 356 patients in training cohort with positive 13 C-UBT results served as the infected group, and 324 without infection were the control group. The multivariate regression analyses showed that the risk factors for HP infection included alcohol consumption (OR = 1.29, 95%CI = 0.78-2.13, P = 0.03), family history of gastric disease (OR = 4.35, 95%CI = 1.47-12.84, P = 0.01), living with an HP-positive individual (OR = 18.09, 95%CI = 10.29-31.82, P < 0.0001), drinking hot tea (OR = 1.58, 95%CI = 1.05-2.48, P = 0.04), and infection status of co-drinkers unknown (OR = 2.29, 95%CI = 1.04-5.06, P = 0.04). However, drinking tea > 3 times per day (OR = 0.56, 95%CI = 0.33-0.95, P = 0.03), using serving chopsticks (OR = 0.30, 95%CI = 0.12-0.49, P < 0.0001) were protective factors for HP infection. The nomogram had an area under the curve (AUC) of 0.85 in the training cohort. The DCA was above the reference line within a large threshold range, indicating that the model was better. The calibration analyses showed the actual occurrence rate was basically consistent with the predicted occurrence rate. The model was validated in the validation cohort, and had a good AUC (0.80), DCA and calibration curve results.

conclusionsThis nomogram, which incorporates basic characteristics and lifestyle habits, is an efficient model for predicting those at high risk of HP infection in the Chaoshan region.

Indexed as

Helicobacter InfectionsHelicobacter pyloriChinaHumansLife StyleNomogramsTeaTeaChaoshan regionHelicobacter pylori infectionNomogramRisk factor

Identifiers

PMID37853349
PMCPMC10585980

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.