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Record W2559985332 · doi:10.25011/cim.v39i6.27526

Effect of Ankaferd Blood Stopper on muscle healing

2016· article· en· W2559985332 on OpenAlexvenueno aff
Murat Uygun, Osman Yüksel Yavuz, İsmail Uraş, İbrahim Gökhan Duman, Hacer Haltaş, Mahmut Kömürcü

Bibliographic record

VenueClinical and investigative medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicHemostasis and retained surgical items
Canadian institutionsnot available
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

PURPOSE: Ankaferd Blood Stopper (ABS), which is a standardized mixture of herbal extracts obtained from five plants, has been proven as an efficient hemostatic agent and is still used in emergency situations. It is not known exactly if decreased bleeding has positive or negative effects on muscle healing and fibrosis, so the purpose of this study was to test the effect of ABS on muscle healing and morphology. METHODS: A total of 66 outbred Wistar rats were divided into three control and three experimental subgroups. In the experimental groups, ABS was sprayed on the cut surface of the soleus. In the control groups, a saline solution was sprayed on the cut surface of the soleus. Subgroups were euthanized after 2 weeks, 3 weeks and 4 weeks, respectively. In each subgroup, eight rats were used for the biomechanical study to determine muscle healing and three rats were used for the histopathological investigation. RESULTS: Although muscle strength in the control groups was lower than that of the experimental groups in early weeks, no differences were found between the control and the experimental groups at 4 weeks. CONCLUSIONS: ABS has no negative effect on muscle healing. We also observed that ABS accelerated muscle healing compared to the control group. ABS could be used in hemostasis of open fractures and elective orthopedic surgeries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.007
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.139
GPT teacher head0.384
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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