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Record W2754917390 · doi:10.1002/ppul.23788

Quality of life outcomes following pediatric lung transplantation

2017· article· en· W2754917390 on OpenAlexafffundabout
Tanya Lazor, Hartmut Grasemann, Melinda Solomon, Samantha J. Anthony

Bibliographic record

VenuePediatric Pulmonology · 2017
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsCNIB FoundationUniversity of TorontoInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick Children
FundersCanadian Institutes of Health ResearchHospital for Sick Children
KeywordsMedicineQuality of life (healthcare)Lung transplantationTransplantationPediatricsProxy (statistics)PopulationInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: Compared to other solid organs, survival after lung transplantation (LTx) is still poor. Discussions on survival benefits following LTx in children, however, have largely concentrated on medical outcome data. Little research describes quality of life (QoL) of pediatric LTx recipients, which is partly due to the small number of pediatric LTxs performed. Only two centers worldwide performed >10 pediatric LTxs in 2013, making data on QoL in this population difficult to obtain. The primary objective was to examine the impact of LTx on QoL of pediatric recipients. METHODS: LTx recipients aged 8-17 years and their parents were recruited from a Canadian pediatric transplant centre. Participants completed the PedsQL 4.0 Generic Core Scales, a validated health-related QoL patient-reported outcome measure for children and adolescents, pre-transplant and two times post-transplant. Pre-LTx QoL scores were compared with initial assessment scores post-LTx and changes in QoL over time were described. Correlations between self- and proxy-reports were also discussed. RESULTS: Ten pediatric LTx recipients (six male, mean age = 13.3 years) and their parents were enrolled. Assessments were completed pre-LTx (mean months = 4.8) and two times post-LTx (mean months 8.7 and 24.6, respectively). Pre- and post-transplant total scores differed significantly for both self- and proxy-report, which remained consistent at a second assessment post-transplant (P = 0.018 and 0.028, respectively). CONCLUSIONS: Findings highlight the importance of QoL outcomes when exploring LTx as a treatment option. Future research should explore long-term QoL outcomes post-LTx and examine standardized integration of patient-reported outcomes into clinical practice.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.003
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.052
GPT teacher head0.388
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 teacher head, 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
Published2017
Admission routes3
Has abstractyes

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