Prediction Methods for Antimicrobial Resistance Trends in China.

Zhengyang Wu, Ning Zhang, Bohan Zhang, Haiwei Wang, Jiaqi Yan, Xingyu Wan, Ming Cheng, Junming Bu, Yinan Du

Abstract read

In one paragraph

Article in Indian journal of microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

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

9 authors.

Zhengyang Wu *School of Basic Medical Sciences, Anhui Medical University, Hefei, 230032 China.

Ning Zhang *School of Basic Medical Sciences, Anhui Medical University, Hefei, 230032 China.

Bohan Zhang *Department of Computer Science and Technology, School of Information, Renmin University of China, Beijing, 100872 China.

Haiwei WangSchool of Basic Medical Sciences, Anhui Medical University, Hefei, 230032 China.

Jiaqi YanSchool of Clinical Medicine, Bengbu Medical College, Bengbu, 233000 China.

Xingyu WanSchool of Basic Medical Sciences, Anhui Medical University, Hefei, 230032 China.

Ming ChengSchool of Basic Medical Sciences, Anhui Medical University, Hefei, 230032 China.

Junming BuSchool of Basic Medical Sciences, Anhui Medical University, Hefei, 230032 China.

Yinan DuSchool of Basic Medical Sciences, Anhui Medical University, Hefei, 230032 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our objective in this study was to develop robust and accurate prediction models for assessing the trends of antimicrobial resistance in China. Data for our study were derived from the China Antimicrobial Resistance Surveillance System, spanning the period from 2014 to 2021. Utilizing these data, we constructed prediction models by GM (1,1), support vector machine, polynomial fitting, and time series. Of all the antibiotics investigated in this study, the resistance rates of carbapenem-resistant Supplementary Information: The online version contains supplementary material available at 10.1007/s12088-024-01442-z.

Indexed as

Antibiotic drug resistanceAntimicrobial resistance trendsGM (1,1)Machine learningPrediction method

Identifiers

PMID40655330

DOI10.1007/s12088-024-01442-z

PMCPMC12246353

What OpenQuestion holds

Textmetadata

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 OpenQuestion graph.