Assessing Health-Related Quality of Life, Morbidity, and Survival Status for Individuals With Down Syndrome in Pakistan (DS-Pak): Protocol for a Web-Based Collaborative Registry
Bibliographic record
Abstract
BACKGROUND: Down syndrome is the most common chromosomal disorder, with a global incidence of 1 in 700 live births. However, the true prevalence, associated morbidities, and health-related quality of life (HRQOL) of these individuals and their families are not well documented, especially in low- and middle-income countries such as Pakistan. Disease-specific documentation in the form of a collaborative registry is required to better understand this condition and the associated health outcomes. This protocol paper describes the aims and processes for developing the first comprehensive, web-based collaborative registry for Down syndrome in a Pakistani cohort. OBJECTIVE: This study aims to assess the HRQOL, long-term survival, and morbidity of individuals with Down syndrome by using a web-based collaborative registry. METHODS: The registry data collection will be conducted at the Aga Khan University Hospital and at the Karachi Down Syndrome Program. Data will be collected by in-person interviews or virtually via telephone or video interviews. Participants of any age and sex with Down syndrome (trisomy 21) will be recruited. After receiving informed consent and assent, a series of tablet-based questionnaires will be administered. The questionnaires aim to assess the sociodemographic background, clinical status, and HRQOL of the participants and their families. Data will be uploaded to a secure cloud server to allow for real-time access to participant responses by the clinicians to plan prompt interventions. Patient safety and confidentiality will be maintained by using multilayer encryption and unique coded patient identifiers. The collected data will be analyzed using IBM SPSS Statistics for Windows, Version 22.0 (IBM Corporation), with the mean and SD of continuous variables being reported. Categorical variables will be analyzed with their percentages being reported and with a P value cutoff of .05. Multivariate regression analysis will be conducted to identify predictors related to the HRQOL in patients with Down syndrome. Survival analysis will be reported using the Kaplan-Meier survival curves. RESULTS: The web-based questionnaire is currently being finalized before the commencement of pilot testing. This project has not received funding at the moment (ethical review committee approval reference ID: 2020-3582-11145). CONCLUSIONS: This registry will allow for a comprehensive understanding of Down syndrome in low- and middle-income countries. This can provide the opportunity for data-informed interventions, which are tailored to the specific needs of this patient population and their families. Although this web-based registry is a proof of concept, it has the potential to be expanded to national, regional, and international levels. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/24901.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.033 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".