Prevalence of Huntington Disease in Italy: a systematic review and meta-analysis.
Bibliographic record
Abstract
INTRODUCTION: Parkinson's disease (PD) is a common disease of unknown etiology. Even though accurate information on the epidemiology of PD is critical for defining appropriate health policies, epidemiological data on Parkinson's disease (PD) in Italy are often defined as scant or conflicting. Our study attempted to provide an overview on the prevalence of (PD) by means of a systematic review and metanalysis of existing data. Material and methods. We searched into two different databases (PubMed and EMBASE), focusing on studies reporting the prevalence of PD in Italy. Data were extracted using a standardized assessment form, and results of such analyses were systematically reported, summarized and compared. Results. A total of 16 studies were eventually included in the analyses, with a prevalence rate of 193.7/100,000. Available reports were heterogeneous both in design and in eventual figures, and also prevalence estimates were affected by substantial heterogeneity. Interestingly, prevalence rates ranged from 37.8/100,000 inhabitants in subjects aged 0 to 64 years, to 578.7 in age group 65 to 75 years, and 1235.7 in age group 75 years or older. PD was significantly associated with male sex, but only in older age groups (i.e. Odds Ratio, OR 1.37 95%CI 1.22-1.53, and OR 1.31, 95%CI 1.21-1.42 for age groups 65-74 years and 75 years or more, respectively). Discussion and conclusion. While the observed variations in prevalence rates may result from environmental or genetic factors, differences in methodologies for case ascertainment and diagnostic criteria may have significantly affected our estimates. As a consequence, the comparability of existing studies is limited.
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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 | 0.019 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.026 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".