Evidence map›Paper›PMID 31219499›Full record

ArticleSaudi medical journal2019

Effect of wet cupping on reducing bone pain for patients in King Abdulaziz University Hospital, Saudi Arabia. A retrospective study.

Lamya A Baharith, Samiha A Mourad, Hanan M Alghamdi, Soad K Al Jaouni

Open access · diamondAbstract read
In one paragraph

Article in Saudi medical journal, 2019. 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
0.9field-weighted citation impact, top 23% of its field
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, 7 citations in OpenAlex.

  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

4 authors at 1 institution in 1 country.

Lamya A BaharithDepartment of Statistics, Faculty Science, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia. E-mail. lbaharith@kau.edu.sa.
Samiha A Mourad
Hanan M Alghamdi
Soad K Al Jaouni
King Abdulaziz Hospital · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate the effectiveness of wet cupping as alternative treatment on reducing bone pain and built a model that predicts the level of improvement for patients who suffer from bone pain.

methodsThis retrospective study was conducted on 289 patients referred from specialty clinics to Prophetic Medicine Clinics (PMC) between September 2013 and August 2015. The effectiveness of cupping is assessed on patients with bone pain who were redirected to PMC, King Abdulaziz University Hospital, Jeddah, Saudi Arabia. An artificial neural network (ANN) method was used to propose a model that predicts levels of improvement for patients suffering from bone pain. Therefore, a random sample of 90% of the data was used to build the ANN model and tested by the remaining 10%. Inferential statistics were conducted to study relations and compare blood tests before and after treatment.

resultsOut of 289 patients suffering from bone pain, more than 11% were completely cured, and 55% improved after wet cupping treatment sessions. The proposed ANN model showed a good performance with more than 72% accuracy. In addition, the statistical analysis showed a significant improvement for most blood tests.

conclusionWet cupping has positive effects on reducing bone pain. We recommend the use of an ANN model in PMC to predict whether patients will benefit from the treatment to reduce pain. This is a recommendation for further study not a conclusion.

Indexed as

Bone and BonesAdolescentAdultAgedComplementary TherapiesFemaleHospitals, UniversityHumansMaleMiddle AgedModels, AnatomicNerve NetPain ManagementRetrospective StudiesSaudi ArabiaYoung Adult

Identifiers

PMID31219499
PMCPMC6778763
OpenAlexW2947372459

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.