Incidence of Inborn Errors of Metabolism in British Columbia, 1969–1996
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To determine how many children with specific types of inborn errors of metabolism are born each year in British Columbia, Canada. This population provides a relatively unique setting for collection of accurate and uniform incidence data because the diagnoses are all made through one laboratory in a population with universal access to government-funded medical care. METHODOLOGY: We used the records of the Biochemical Diseases Laboratory, Children's Hospital, Vancouver (the central referral point for all metabolic diagnoses in British Columbia) to identify all patients diagnosed with the metabolic diseases defined below. We obtained incidence figures by including only the children diagnosed with the diseases covered in this article who were confirmed as having been born within the province for the years 1969 to 1996. The diseases covered were diseases of amino acids, organic acids, the urea cycle, galactosemia, primary lactic acidoses, glycogen storage diseases, lysosomal storage diseases, and diseases involving specifically peroxisomal and mitochondrial respiratory chain dysfunction. Because the technology needed for diagnosis of specific disease groups was in place at different times our data for the different disease groups correspond to different time frames. We have also adjusted the time frames used to allow for the likelihood that some diseases may not come to medical attention for some time after birth. For instance the incidence of amino acid diseases was assessed throughout the whole of this time frame but the incidence of peroxisomal diseases was restricted to 1984 to 1996 because this was the time frame during which the technology needed for diagnosis was in place and reliable. Most disease group statistics included at least 400 000 births. RESULTS: The overall minimum incidence of the metabolic diseases surveyed in children born in British Columbia is approximately 40 cases per 100 000 live births. This includes phenylketonuria (PKU) and galactosemia which are detected by a newborn screening program. Metabolic diseases, which were not screened for at birth, ie, those with PKU and galactosemia subtracted from the total, have a minimal incidence of approximately 30 cases per 100 000 live births. This diagnostic dilemma group would present to pediatricians for diagnosis. Not all metabolic diseases have been surveyed and our data are restricted to the following metabolic disease groups. Approximately 24 children per 100 000 births (approximately 60% of the total disease groups surveyed) have a disease involving amino acids (including PKU), organic acids, primary lactic acidosis, galactosemia, or a urea cycle disease. These children all have metabolic diseases involving small molecules. Approximately 2.3 children per 100 000 births ( approximately 5%) have some form of glycogen storage disease. Approximately 8 per 100 000 births (20%) have a lysosomal storage disease; approximately 3 per 100 000 births (7%-8%) have a respiratory chain-based, mitochondrial disease and approximately 3 to 4 per 100 000 (7%-8%) of births have a peroxisomal disease. The diseases involving subcellular organelles represent approximately half of the diagnostic dilemma group. The incidence of each of the specific diseases diagnosed, including apparently rare diseases such as nonketotic hyperglycinemia, is to be found in the text. The metabolic diseases reported in this survey represent over 10% of the total number of single gene disorders in our population. CONCLUSIONS: Our data provide a good estimate of metabolic disease incidence, for the disease groups surveyed, in a predominantly Caucasian population. Incidence data for metabolic diseases are hard to collect because in very few centers are diagnoses centralized for a population with uniform access to modern health care and this has been the case for our population during the course of the study. (ABSTRACT TRUNCATED)
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it