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Record W2915034290 · doi:10.21926/obm.icm.1901008

Integrated Oncology in an Integrated Medicine Hospital in Pitigliano (Grosseto, Italy)

2019· article· en· W2915034290 on OpenAlexaboutno aff
Ferreri Rosaria, Simonetta Bernardini, Cracolici Franco, Francesca Bechini

Bibliographic record

VenueOBM Integrative and Complementary Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHomeopathyQuality of life (healthcare)AcupunctureAdverse effectCancerRadiation therapyDiseaseAlternative medicineTraditional Chinese medicineInternal medicinePhysical therapyIntensive care medicineNursing

Abstract

fetched live from OpenAlex

Background: Complementary medicines (CM), including homeopathy, acupuncture, and traditional Chinese medicine, have been introduced for cancer patients undergoing chemotherapy and radiotherapy treatment in the Pitigliano Hospital Centre of Integrated Medicine in order to minimize the side effects of these treatments, which improves quality of life and adherence to conventional therapies. Methods: Cancer patients (240) were enrolled in an integrated care model offering a comprehensive protocol including homeopathy and acupuncture, provided in line with the stage of the disease as well as in consideration of any comorbidities in individual patients. The following data were collected upon enrollment and also after 1-2 months of the integrated therapies:SF-12 quality of life (QoL) questionnaire;Edmonton symptom assessment scale (ESAS);and a questionnaire on the use of conventional medications. Results: There was a 92.4% reduction in symptoms (as monitored by ESAS) caused by the patient’s disease or by comorbidities. The SF-12 revealed reduced fatigue and increased wellness, as well as good adherence to the cancer treatments. Additionally, a reduction in the use of conventional medications for side effects, good control of cancer symptoms, and an improved QoL was also observed. Conclusions: This study suggests the use of complementary medicines to reduce therapy-related symptoms in oncologic patients without any adverse effects and to reduce the use of conventional drugs in this case.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.000

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 head0.042
GPT teacher head0.366
Teacher spread0.324 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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