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Record W1544050247 · doi:10.4238/vol9-1gmr722

Case Report Benefits of kinesiotherapy and aquatic rehabilitation on sickle cell anemia. A case report

2010· article· en· W1544050247 on OpenAlexaboutno aff
G. Tinti, R. Somera, Flávia Mariana Valente, Cláudia R. Bonini-Domingos

Bibliographic record

VenueGenetics and Molecular Research · 2010
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsMedicineSickle cell anemiaRehabilitationQuality of life (healthcare)AnemiaPhysical therapyHemoglobinDiseaseInternal medicine

Abstract

fetched live from OpenAlex

The process of hemoglobin polymerization and the consequent sickling of red blood cells that occurs in patients with sickle cell disease shortens the half-life of red blood cells. It causes vaso-occlusive complications, as well as pain and pulmonary and cardiovascular dysfunction. We evaluated an aquatic rehabilitation program used for patients with sickle cell anemia and examined the possible benefits that exercise in warm water has for the circulatory system, for relieving pain, and for increasing lung capacity. The patient was a 32-year-old female. The parameters that we used in this study include respiratory muscle strength (which was calculated by measuring maximum inspiratory pressures and maximum expiratory pressures), the McGill and Wisconsin pain questionnaires (in order to evaluate the patients' characterizations and descriptions of their pain), and the SF-36 Health Survey. The treatment included warm water exercises, stretching, aerobic exercise, and relaxation, during two sessions of 45 min per week for 5 weeks. The patient experienced a significant decrease in pain, a significant increase in the strength of respiratory muscles, and improved quality of life. We conclude that aquatic rehabilitation can be used to improve the clinical condition of sickle cell anemia patients, and we encourage more research on this new treatment regime, in comparison with other types of therapies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.001
Science and technology studies0.0040.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0070.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.019
GPT teacher head0.331
Teacher spread0.312 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations23
Published2010
Admission routes1
Has abstractyes

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