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Objectives: The MetabQoL 1.0 is the first disease-specific health related quality of life (HrQoL) questionnaire for patients with intoxication-type inherited metabolic disorders. Our aim was to assess the validity and reliability of the MetabQoL 1.0, and to investigate neuropsychiatric burden in our patient population. Methods: Data from 29 patients followed at a single center, aged between 8 and 18 years with the diagnosis of methylmalonic acidemia (MMA), propionic acidemia (PA) or isovaleric acidemia (IVA), and their parents were included. The Pediatric Quality of Life Inventory (PedsQoL) was used to evaluate the validity and reliability of MetabQoL 1.0.
Results: The MetabQoL 1.0 was shown to be valid and reliable (Cronbach's alpha: 0.64–0.9). Fourteen out of the 22 patients (63.6%) formally evaluated had neurological findings. Of note, 17 out of 20 patients (85%) had a psychiatric disorder when evaluated formally by a child and adolescent psychiatrist. The median mental scores of the MetabQoL 1.0 proxy report were significantly higher than those of the self report (p = 0.023). Patients with neonatal-onset disease had higher MetabQoL 1.0 proxy physical (p = 0.008), mental (p = 0.042), total scores (p = 0.022); and self report social (p = 0.007) and total scores (p = 0.043) than those with later onset disease.
Conclusions: This study continues to prove that the MetabQoL 1.0 is an effective tool to measure what matters in intoxication-type inherited metabolic disorders. Our results highlight the importance of clinical assessment complemented by patient reported outcomes which further expands the evaluation toolbox of inherited metabolic diseases.
In this paper, we consider the question of data aggregation using the practical example of emissions data for economic activities for the sustainability assessment of regional bank clients. Given the current scarcity of company-specific emission data, an approximation relies on using available public data. These data are reported in different standards in different sources. To determine a mapping between the different standards, an adaptation to the Covariance Matrix Self-Adaptation Evolution Strategy is proposed. The obtained results show that high-quality mappings are found. Nevertheless, our approach is transferable to other data compatibility problems. These can be found in the merging of emissions data for other countries, or in bridging the gap between completely different data sets.