Trends in type 1 diabetes diagnosis in Ghana
Bibliographic record
Abstract
BACKGROUND: Despite the fact that the rate of type 1 diabetes (T1D) is increasing worldwide, there exists a dearth of information on the disease in most sub-Saharan African countries. The goal of this study was to determine the enrolment trend of T1D using data compiled over 28 y from a teaching hospital in Kumasi, Ghana. METHODS: Information collected included sex, age at diagnosis and date of T1D diagnosis. We identified trends from 1992 to 2018, divided into 3 y intervals. RESULTS: From 1992 to 2018, 1717 individuals with T1D were enrolled in the diabetes clinic at the Komfo Anokye Teaching Hospital. The male:female ratio was 1:1.2. The number of individuals diagnosed with T1D decreased among the 10-19 y age group during the 1992-1994 period, followed by a progressive increase within the same age group during the subsequent period (from 35.4% in 1995-1997 to 63.2% in 2016-2018). There was a decline in the proportion of children 0-9 y of age diagnosed during the study period (from 5.1% in 1992-1994 to 3.6% in 2016-2018). CONCLUSIONS: In our study population, a decreasing trend of T1D enrolments was observed in general while among adolescents an increasing trend was observed.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".