ABSTRACT
We explored the relationship between obstructive sleep apnea (OSA) patients' anthropometric measures and the CPAP treatment response. To that end, we processed three non-overlapping cohorts (D1, D2, D3) with 1046 patients from four sleep laboratories in Western Romania, including 145 subjects (D1) with one-night CPAP therapy. Using D1 data, we created a CPAP-response network of patients, and found neck circumference (NC) as the most significant qualitative indicator for apnea-hypopnea index (AHI) improvement. We also investigated a quantitative NC cutoff value for OSA screening on cohorts D2 (OSA-diagnosed) and D3 (control), using the area under the curve. As such, we confirmed the correlation between NC and AHI (ρ=0.35, p<0.001) and showed that 71% of diagnosed male subjects had bigger NC values than subjects with no OSA (area under the curve is 0.71, with 95% CI 0.63-0.79, p<0.001); the optimal NC cutoff is 41 cm, with a sensitivity of 0.8099, a specificity of 0.5185, positive predicted value (PPV) = 0.9588, negative predicted value (NPV) = 0.1647, and positive likelihood ratio (LR+) = 1.68. Our NC =41 cm threshold classified the D1 patients' CPAP responses-measured as the difference in AHI prior to and after the one-night use of CPAP-with a sensitivity of 0.913 and a specificity of 0.859.
ABSTRACT
BACKGROUND: In this study the authors present an update to the CFTR mutation profile in Hungary, utilizing data from a selected cohort of 45 cystic fibrosis (CF) patients from different regions of the country. METHODS: Depending on the preceding analysis, four different mutation detection methods were used. A commercial assay targeting the most common CF-causing mutations was performed as the first test followed by an allele specific PCR for CFTRdele2,3(21kb), Sanger sequencing and MLPA analysis of the coding region of the CFTR gene. RESULTS: In our recent study 27 different mutations were detected, including 2 novel ones (c.1037_1038insA and c.1394C>T). Besides F508del (c.1521_1523delCTT), the following mutations were found at a frequency of ≥ 4.0%: W1282X (c.3846G>A), N1303K (c.3909C>G), CFTRdele2,3(21kb) (c.54-5940_273+10250del21kb) and 2184insA (c.2052_2053insA). In addition, four mutations (G542X, Y1092X, 621+1G>T, and 2143delT) were found in more than one allele. CONCLUSIONS: The updated database of Hungarian mutations not only enables to increase the efficiency of the existing diagnostic approach, but also provides a further refined basis for the introduction of the molecular newborn screening (NBS) program in Hungary.
