Analysis of the correlation between body weight, body composition, and factor VIII recovery in paediatric patients with severe haemophilia A – a single-centre study
Bibliographic record
Abstract
Introduction Haemophilia A (HA) is a rare bleeding disorder. Patients with severe HA have a factor VIII activity of < 1%. The clinical picture of severe HA consists of a propensity for spontaneous haemorrhages to the skin, muscles, joints, and internal organs. To prevent severe complications of bleeds, patients with severe HA receive prophylaxis with deficient clotting factor. Obese people have larger absolute fat free mass (FFM) as well as fat mass than non-obese individuals of the same age, gender and height. Factor VIII (FVIII) concentrates are typically confined to the vascular space. Although the pharmacokinetics (PK) based FVIII dosing is becoming a standard in tailoring the prophylaxis for HA patients, the majority of them are still dosed according to total body weight and this may result in an overdose of FVIII. This study aimed to evaluate the PK of FVIII considering patients’ body weight and body composition using electrical bioimpedance. Material and methods Twenty-one boys with severe HA undergoing plasma-derived factor VIII prophylaxis were enrolled in the study. Patients underwent physical examination, body weight and height measurements, had body composition assessed using electrical bioimpedance, FVIII concentration was measured before and 30 min after FVIII administration, and FVIII recovery was evaluated. Patients completed a questionnaire regarding treatment, physical activity, and bleeding. Results Of the patients who underwent the study, 47.6% had a normal body mass index (BMI), 42.8% were overweight, and 9.5% of patients were underweight. There was a correlation between patients’ BMI and FVIII recovery, FFM and FVIII recovery, and fat mass and FVIII recovery. No relationship was found between FVIII recovery and bleeding rate. Conclusions Determining factor VIII dosage according to FFM requires further study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".