Evidence map›Paper›PMID 34506009›Full record

Observational studyAdvances in therapy2021

Effectiveness of the 10 cm

Chiung-Chih Chang, Lung Chan, Hsi-Hsien Chou, Yu-Wan Yang, Ta-Fu Chen, Ting-Bin Chen, Chin-I Chen, Audrey Yang, Chaur-Jong Hu

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Advances in therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

9 authors.

Chiung-Chih ChangDepartment of Neurology, Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.
Lung ChanDepartment of Neurology and Dementia Center, Shung Ho Hospital, School of Medicine, College of Medicine, Taipei Medical University, New Taipei, Taiwan.
Hsi-Hsien ChouDepartment of Neurology, Chung Shan Medical University Hospital, Taichung, Taiwan.
Yu-Wan YangDepartment of Neurology, China Medical University Hospital, Taichung, Taiwan.
Ta-Fu ChenDepartment of Neurology, National Taiwan University Hospital, Taipei, Taiwan.
Ting-Bin ChenDepartment of Neurology, Taichung Veterans General Hospital, Taichung, Taiwan.
Chin-I ChenDepartment of Neurology, Wan Fang Hospital, Taipei, Taiwan.
Audrey YangNovartis (Taiwan) Co., Ltd., Taipei, Taiwan.
Chaur-Jong HuDepartment of Neurology and Dementia Center, Shung Ho Hospital, School of Medicine, College of Medicine, Taipei Medical University, New Taipei, Taiwan. chaurjongh@tmu.edu.tw.ORCID http://orcid.org/0000-0002-4900-5967

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe current study aimed to provide data on the effectiveness of the 10 cm

methodsThis was a 48-week, single-arm, open-label, observational, and post-marketing study conducted across seven centers in Taiwan between May 5, 2016 and July 10, 2017. Eligible patients (aged 55-95 years) treated with the 10 cm

resultsOf the 285 eligible patients [full analysis set (FAS)], 216 (75.8%) completed the study protocol while 180 (63.2%) persisted on the 10 cm

conclusionsThe use of the 10 cm

Indexed as

Alzheimer DiseaseAgedAged, 80 and overCholinesterase InhibitorsCognitionHumansMiddle AgedRivastigmineTreatment OutcomeCholinesterase InhibitorsRivastigmineAlzheimer’s diseaseCognitive functionRivastigmine patch

Identifiers

PMID34506009
PMCPMC8478746

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.