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Low Dose Secondary/Tertiary Prophylaxis Is Feasible and Effective in Resource Limited Setting in South India for Children with Hemophilia

2016· article· en· W2616327563 on OpenAlexaff
Neeraj Sidharthan, Vijayakumar Narayana Pillai, Sheena Mathew, Remya Sudevan, Dinkar Viswam, Cilla Joseph, Sumi Soman, Archana Vijay, Adrienne Lee, Man‐Chiu Poon

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineCryoprecipitateClotting factorPediatricsPopulationFactor IXHemarthrosisSurgeryInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Prophylaxis for Hemophilia is globally accepted as a treatment strategy compared to on-demand therapy in the care of persons with hemophilia (PwH) . Prophylaxis is rarely practized in low and middle income countries due to several reasons such as ill-affordability of clotting factor concentrates ( CFCs), lack of awareness, absence of comprehensive / home care infrastructure and misconcepts regarding treatment among general population. The South Indian state of Kerala had been providing CFCs free of cost for on-demand treatment. A recent initiative was started in Hemophilia Treatment Centre(HTC), Aluva , Ernakulam district to provide secondary/tertiary prophylaxis free of cost to children with severe hemophilia (Factor level <1%, aged 5-15 yrs) as a joint effort from HTC and the local government. A clinical audit was done in 11 children at this center for a period of twelve months (6 months retrospectively for on-demand treatment and 6 months prospectively for prophylactic treatment). Among all patients with severe hemophilia, eight have Hemophilia A and the remaining three have Hemophilia B. They were previously treated with CFCs/plasma/cryoprecipitate, a few of them had established joint disease and all of them had absence of inhibitors. These children were initiated on low dose prophylaxis with plasma derived CFCs. Factor VIII concentrate was given at a dose of 20-40 U/kg in 2 divided doses per week for Hemophilia A and Factor IX concentrate at 25-40 U/Kg once a week for Hemophilia B. Outcomes were measured at two time points - at the end of secondary/tertiary prophylactic treatment period and at the end of preceding six months of on-demand treatment. The variables taken as outcome measures were changes in bleed rates, Hemophilia joint health score (HJHS), Functional independence score in Hemophilia (FISH), hospitalization rates and school absenteeism. A reduction in the bleed rate was seen from the transition of on demand treatment to secondary/tertiary prophylactic treatment (14.9 vs 0.91, p 0.005). Similar reductions were seen for hospitalization rates (12.45 vs 2.36 days, p 0.005) and school absenteeism (78.55 vs 1.27 days, p 0.01) respectively(Fig 1 a). FISH and HJHS scores were either maintained or improved during the prophylaxis period.(Fig 1b, 1c). None of the children developed inhibitors during the study period. The estimated cost of CFCs for on demand treatment per patient was 1314.4 USD and 1691.8USD during prophylaxis. The factor consumption for on demand treatment for 6 months was 968.24 IU/Kg and that of secondary/tertiary prophylaxis was 1077.96 IU/Kg respectively. We conclude that low dose prophylaxis for severe Hemophilia in a developing economy is feasible and has marked clinical benefits with greater well-being when compared to on demand therapy. In countries with resource constraints low dose secondary/tertiary prophylaxis should be considered as a therapeutic option over on demand therapy for children with severe Hemophilia in the light of its potential benefits . Disclosures No relevant conflicts of interest to declare.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.008
GPT teacher head0.245
Teacher spread0.237 · 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 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".

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Citations5
Published2016
Admission routes1
Has abstractyes

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