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Record W4405038512 · doi:10.1182/blood-2024-210205

How Does Cognition Impact Healthcare Transition Skills, Engagement and Utilization in Young Adults Living with Sickle Cell Disease?

2024· article· en· W4405038512 on OpenAlexaffabout
Sophie Marsolais, Chrystelle Charles, Amer Yassine Hafsaoui, J. A. Colin Bergeron, Bárbara Fritz, Nancy Van Synghel, Valérie Fraïle, Natalie Fournier, Lauren Arena, Serge Sultan, Nancy Robitaille, Léandra Desjardins, Nathalie Gaucher, Yves Pastore, Stéphanie Forté

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineCentre Hospitalier de l’Université de MontréalUniversité de Montréal
Fundersnot available
KeywordsDiseaseCognitionGerontologyMedicineYoung adultPsychologyPsychiatry

Abstract

fetched live from OpenAlex

Background The adolescent and young adult period is a time of increased risk of acute complications and mortality in patients with sickle cell disease (SCD). Transfer of care from pediatric to adult healthcare setting presents several challenges. Attention difficulties, lower IQ and other cognitive deficits may negatively impact transfer success and adherence to adult health maintenance appointments. Cognitive screening is available since 2021 at the CHUM, an adult SCD centre. The main aims of this study are to 1) describe the results obtained by young adults (YA) with SCD in different cognitive screening tests, and 2) to explore if these results are associated with different measures of transition skills, healthcare engagement and utilization. Methods A retrospective study was conducted at the CHUM (Montréal, Canada), a tertiary care centre treating adults with SCD. Patients with SCD between the ages of 18-25 who had undergone cognitive screening between August 2021 and December 2023, and who had a follow-up period of at least 12 months were included. Cognitive screening was conducted using the Montreal Cognitive Assessment Test (MoCA), the Rowland Universal Dementia Assessment Scale (RUDAS) and a standard neurological examination. Electronic medical records were used to extract baseline characteristics including demographics, pre-existing intellectual disability (ID) or attention disorder (AD), as well as variables pertaining to transition skills (Transition Readiness Assessment Questionnaire [TRAQ] score), health care engagement (appointment attendance, interactions with clinic nurses), and acute care utilization (ED visits, hospitalizations). Patients were identified as having a cognitive comorbidity (CC) if they had a documented ID or AD, a RUDAS score of <28 or a MoCA score of <27. Mann-Whitney U test was used for comparison of transition success measures between those with and without CC and Spearman's ρ to find correlations between those same measures. Results Thirty patients fulfilling the inclusion criteria were identified. The median age at the time of cognitive assessment was 20 years [range: 18-23]. Nineteen (63%) patients were female and 20 (67%) had the SS/Sβ0 genotype. Most patients (28, 93%) were followed at a pediatric centre with expertise in SCD prior to the transfer. Three (10%) patients had a previous diagnosis of stroke, 8 (27%) were diagnosed with AD and 1 (3%) patient had a diagnosis of ID. As part of the cognitive screening, 28 (93%) patients completed the MoCA and 28 (93%) the RUDAS. The median RUDAS score was 30 (23-30) and the median MoCA score was 27 (22-30). RUDAS and MoCA scores were suggestive of a mild cognitive disorder in 7 (23%) and 10 (33%) patients, respectively, and overall, 15 (50%) patients were identified as having a CC. With regards to transition success, mean TRAQ scores were similar between patients with and without a CC (74±8 vs. 72±7, p=0.69). No differences were noted in attendance of ophthalmology (72±32% vs 68±29, p=0.69) or imaging appointments (86±22% vs 87±22%, p=0.85) between those with and without CC, however attendance of hematology appointments was noted to be higher in patients with a CC (88±10% vs. 81±13%, p=0.04). Numbers of formal communications per year in the form of emails or phone calls between patients and the care team were similar between groups, regardless if initiated by the patient's family or the patient themselves. No significant differences were noted in the mean number of ED visits per year (1.0±1.1 vs. 0.8±0.6, p=0.95), day hospital visits per year (0.3±0.7 vs. 0.3±0.4, p=0.37) nor hospitalizations per year (0.4±0.5 vs. 0.5±0.6, p=0.54) between those with and without CC. Conclusion In our study, YA with SCD and cognitive comorbidity demonstrated similarly favourable transition skills, good healthcare engagement and limited acute care utilization when compared to their peers. While this study is limited in size, we hypothesize that the potentially negative effect of cognitive vulnerabilities on health outcomes in youth with SCD could be mitigated with appropriate support throughout the transition period.

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)0.004
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 score0.112
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.007
GPT teacher head0.238
Teacher spread0.231 · 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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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