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Record W2371616582

Efficiency of autologous bone marrow stem cell for ischemic disease of lower extremity in 254 cases

2011· article· en· W2371616582 on OpenAlexaff
Yibin Zhang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicOrgan and Tissue Transplantation Research
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsMedicineGangreneClaudicationSurgeryIntermittent claudicationAnkleAmputationCritical limb ischemiaTransplantationIschemiaLimb ischemiaArterial diseaseVascular diseaseInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Objective To evaluate the efficiency of autologous bone mononuclear cell(ABMC) transplantation in the treatment of ischemic disease of lower extremity.Methods Treatment records of 254 patients with ischemic disease of lower extremity were retrieved.All patients have been followed up for one year from November 2003 to August 2008.The skin temperature,bathesthesia,transcutaneous partial pressure O2(TcPo2) and ankle-brachial index(ABI) were rechecked at 3,6 and 12 months after transplantation,and the symptoms of pain,cold,intermittent claudication and ulcer and gangrene were evaluated.Results A total of 254 patients were evaluated.(1) Alleviation of pain and cold was reported in 61.8﹪(157/254) and 74﹪(188/254) of the patients respectively.Improvement of claudication was noted in 40.2﹪(102/254);Alleviation of ulcer was noted in 59﹪(36/61).Six patients received amputation due to gangrene,5 patients healed by ablation,8 patients were stable and 7 patients have worsened ischemia.(2)The skin temperature of lower extremity increased from 32.89℃±2.19℃ to 35.52℃±2.26℃(t=13.32,P=0.000),TcPo2 increased from(26.46±18.49) mmHg to(34.14±14.99) mmHg(t=5.157,P=0.000).The ABI increased from(0.62±0.36) to(0.84±0.24)(t=8.104,P=0.000).Conclusion ABMC transplantation is effective in the treatment of ischemic disease of lower extremity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

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

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 head0.049
GPT teacher head0.298
Teacher spread0.249 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2011
Admission routes1
Has abstractyes

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