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Record W2918466418 · doi:10.1016/j.ejpn.2019.02.014

Burden-of-illness and cost-driving factors in Dravet syndrome patients and carers: A prospective, multicenter study from Germany

2019· article· en· W2918466418 on OpenAlexaff
Adam Strzelczyk, Malin Kalski, Thomas Bast, Adelheid Wiemer‐Kruel, U Bettendorf, Lara Kay, Matthias Kieslich, Gerhard Kluger, Gerhard Kurlemann, Bernd A. Neubauer, Tilman Polster, Arne Herting, Sarah von Spiczak, Regina Trollmann, Markus Wolff, John Irwin, Joe Carroll, Daniel Macdonald, Clive Pritchard, Karl Martin Klein, Felix Rosenow, Susanne Schubert‐Bast

Bibliographic record

VenueEuropean Journal of Paediatric Neurology · 2019
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of Calgary
FundersUCB PharmaDesitin ArzneimittelEisaiZogenixDeutsche ForschungsgemeinschaftPfizerLivaNovaViropharmaGW PharmaceuticalsVitafloEuropean CommissionBiocodex FranceMedtronicSage TherapeuticsBiogen
KeywordsMedicineDravet syndromeProspective cohort studyQuality of life (healthcare)Indirect costsPediatricsUnivariate analysisPopulationEpilepsyInternal medicinePsychiatryMultivariate analysisEnvironmental health

Abstract

fetched live from OpenAlex

INTRODUCTION: Dravet syndrome (DS) is a rare developmental and epileptic encephalopathy. This study estimated cost, cost-driving factors and quality of life (QoL) in patients with Dravet syndrome and their caregivers in a prospective, multicenter study in Germany. METHODS: A validated 3-12-month retrospective questionnaire and a prospective 3-month diary assessing clinical characteristics, QoL, and direct, indirect and out-of-pocket (OOP) costs were administered to caregivers of patients with DS throughout Germany. RESULTS: Caregivers of 93 patients (mean age 10.1 years, ±7.1, range 15 months-33.7 years) submitted questionnaires and 77 prospective diaries. The majority of patients (95%) experienced at least one seizure during the previous 12 months and 77% a status epilepticus (SE) at least once in their lives. Over 70% of patients had behavioural problems and delayed speech development and over 80% attention deficit symptoms and disturbance of motor skills and movement coordination. Patient QoL was lower than in the general population and 45% of caregivers had some form of depressive symptoms. Direct health care costs per three months were a mean of €6,043 ± €5,825 (median €4054, CI €4935-€7350) per patient. Inpatient costs formed the single most important cost category (28%, €1,702 ± €4,315), followed by care grade benefits (19%, €1,130 ± €805), anti-epileptic drug (AED) costs (15%, €892 ± €1,017) and ancillary treatments (9%, €559 ± €503). Total indirect costs were €4,399 ±€ 4,989 (median €0, CI €3466-€5551) in mothers and €391 ± €1,352 (median €0, CI €195-€841) in fathers. In univariate analysis seizure frequency, experience of SE, nursing care level and severe additional symptoms were found to be associated with total direct healthcare costs. Severe additional symptoms was the single independently significant explanatory factor in a multivariate analysis. CONCLUSIONS: This study over a period up to 15 months revealed substantial direct and indirect healthcare costs of DS in Germany and highlights the relatively low patient and caregiver QoL compared with the general population.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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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Citations79
Published2019
Admission routes1
Has abstractno

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