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Record W4385751828 · doi:10.1177/20543581231191836

Transition From Pediatric to Adult Nephrology Care: Program Report of a Single-Center Experience

2023· article· en· W4385751828 on OpenAlexafffund
Andrey V. Cybulsky, Leonor Cercena, Paul Goodyer, Rita S. Suri

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2023
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsMcGill University Health Centre
FundersAmgen CanadaMcGill UniversityAmgen
KeywordsMedicineNephrologyYoung adultAdult careFamily medicineHealth careKidney diseaseInternal medicinePediatrics

Abstract

fetched live from OpenAlex

Purpose of program: Adolescents and young adults with chronic disease face many personal and systemic barriers that may impede their successful transition from pediatric to adult care, putting them at risk for treatment nonadherence, loss to follow-up, and poor health outcomes. Such barriers include impaired socioemotional functioning, overreliance on adult caregivers, lack of disease-specific knowledge, and poor coordination between pediatric and adult health care services. In 2007, we established a specialized youth to adult nephrology transition clinic at a tertiary care center to address these barriers and provide adolescents and young adults with renal disease followed at the affiliated children's hospital with a seamless transition to adult care. Sources of information: The attending clinic nephrologist collected data prospectively for this quality improvement report. Methods: The features of this specialized clinic included (1) single point of entry and single triage adult nephrologist, (2) ongoing follow-up with a single adult nephrologist who communicated with the pediatric nephrologists, and (3) a single specialized clinic nurse who provided disease-specific education and helped to ensure ongoing patient engagement and follow-up. Importantly, the transition patients were booked into regular appointment slots in the adult nephrologist's general clinic, which facilitated regular follow-up without additional resources. The salary of the transition clinic nurse was covered by an unrestricted grant. Patient visits were in-person, except between 2020 and 2021 when visits were by telephone due to the pandemic. Key findings: A total of 213 patients were referred and assessed in the transition clinic from February 2007 until October 2022. Most referrals were from pediatric nephrologists. Among the patients, 29% had a hereditary kidney disease; in 71%, the disease was acquired. The most common disease was glomerulonephritis and ~30% of the patients suffered from a "rare" disease. Of the 213 patients, 123 (58%) continue to be followed up (mean follow-up: 4.8 years), 27 (13%) were transferred to other physicians, in part to accommodate treatment closer to patients' homes, and 29 (14%) without ongoing care needs were discharged. Only 33 (15%) were lost to follow-up. There were several advantages to the clinic, including the maintenance of accurate records, a process to minimize loss to follow-up, and a "critical mass" of patients with rare diseases, which facilitated development of special expertise in rare disease pathogenesis, diagnosis, treatment, and management of complications. Patients with glomerulonephritis demonstrated a stable serum creatinine over 3 to 15 years, and morbidity (as reflected by emergency room visits and hospitalizations) was low. Limitations: Due to the relatively small numbers of patients in the disease categories, it was not possible to determine conclusively whether attendance of patients in the transition clinic reduced the rate of progression of kidney disease or morbidity. Implications: A dedicated referral, triage, and follow-up process post-transition with only modest financial resources and personnel can result in accurate tracking of clinic data, as well as consistent and reliable follow-up and expert patient care.

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)0.003
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 score0.989
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.383
Teacher spread0.336 · 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

Citations11
Published2023
Admission routes2
Has abstractyes

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