Guidelines for the Management of Transfusion Dependent Thalassaemia (TDT) [Internet]
Bibliographic record
Abstract
The full costs of treating patients with inherited disorders of haemoglobin is extremely variable among countries depending on different health care systems, varying methods of obtaining blood, different practices in screening for blood pathogens and different costs of drugs and equipment. It is evident that all countries would benefit from the sharing of experience and expertise in order to harmonize and optimize the quality of treatment as much as possible. The need for management guidelines for Transfusion Dependent Thalassaemias (TDT) is clear. Throughout the past four years, six major TDT management guidelines became available for use by thalassaemia care givers (TIF, US, Canadian, UK, Italian and Australian Guidelines). A comparison among those guidelines has been recently published (Musallam KM et al. Acta Haematologica 2013). In light of a swiftly evolving evidence, the need for revisiting and updating TDT management recommendations remains crucial. More importantly, ensuring access to such guidelines and careful application and implementation should only help arriving at early diagnosis of morbidity to allow prompt and effective management. It would also allow early prediction of risk and would enable preventive measures to be set in place saving unnecessary health care costs.This updated third edition of the TIF guidelines will offer valuable information to all allied healthcare professionals involved in the treatment of patients with TDT. It includes updated information on new approaches for more effective, safe and less laborious treatment, and an overview of the progress achieved to date towards a total cure using methods such as gene therapy and stem cell transplantation.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".