Can Quality of Life Tests Be Useful in Patients Affected by Alpha-1 Antitrypsin Deficiency?

J Clin Med

Evaluation Service of the Canarian Health Service, Research Network on Chronicity, Primary Care and Health Promotion (RICAPPS), 38001 Santa Cruz de Tenerife, Spain.

Published: December 2024

Alpha-1 antitrypsin deficiency (AATD) is a genetic condition that predisposes a person to certain diseases over their lifetime, mainly including lung disease (in the form of emphysema) and liver disease (liver cirrhosis). Quality of life questionnaires are instruments designed to quantify the deterioration of a patient's health. : This study aimed to assess whether certain quality of life tests that are routinely used in clinical practice can be useful for patients with AATD. : A sample of AATD patients, with various genotypes, but with the common characteristic that they must have both altered alleles (Pi* ≠ M), participated in the study. Different quality of life tests were used, including the COPD Assessment Test (CAT), COPD and Asthma Sleep Impact Scale, the short form of the Short Form Health Survey, and EuroQol 5 dimensions, and were related to differing clinical and functional characteristics. : The sample was composed of 54 patients, and slightly more than half of the participants were women (57.4%), with a mean age of 51.5 ± 13.7. The main genotypes were Pi*SZ (43.4%) and Pi*ZZ (34%). In patients under 65 years of age ( = 47), those who were actively working could walk a greater distance in the walking test, namely, 573 m (511-629), compared to those who were not actively working, namely, 415.5 m (392-469; < 0.001). Active non-workers had a worse CAT (13.6 ± 7.8 vs. 4.6 ± 4.3; < 0.001). In total, 80% of non-working patients had exacerbations, but only 46. 9% of those who were active, although the association did not reach statistical significance ( = 0.068). Having a lower score in the physical component of SF-12 was related to suffering from lung disease (46.0 ± 11.4 vs. 38.4 ± 11.1 ( = 0.026)). : Quality of life tests were able to detect differences and relate them to functional factors such as the distance covered in the walking test, being sensitive and specific in this regard.

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http://dx.doi.org/10.3390/jcm13247711DOI Listing

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