Pulsed transit time in predicting the symptoms and complications of patients with obstructive SLEEP apnea syndrome

Aims: In current practice, although the severity of Obstructive Sleep Apnea Syndrome (OSAS) is determined by the Apnea Hypopnea Index (AHI), a linear relationship cannot always be determined between AHI and the symptoms and complications of the disease. The aim of this study is to investigate the role of Pulse Transit Time (PTT) in the prediction of symptoms and complications in patients with a preliminary diagnosis of OSAS who applied to the sleep laboratory of our hospital. Materials and Methods: Patients who applied to the sleep outpatient clinic of our hospital and accepted to join in to the study were included in the study. Demographic and clinical characteristics of the patients were recorded with using standard clinical research forms. According to the patients' AHI; Those with AHI<5 were classified as the control group, and those with AHI≥5 were classified as the OSAS group. Full night polysomnography (PSG) recordings were re-viewed and PTT was scored manually by the same investigator. A PTT drop was defined as a decrease of at least 15 ms from the average PTT in the immediately preceding 60 seconds and lasting at least 5 seconds. Results: 114 patients were included in the study, 7 of them had insufficient sleep time and 4 of them were excluded from the study because PTT values were not suitable for calculation, and analyzes were performed with 103 cases. Of these, 46 (44.7%) were female and 57 (55.3%) were male, with a mean age of 48.69±15.62 years. While 81 of the cases were diagnosed with OSAS (24 mild, 23 moderate, 34 severe OSAS), 22 were found to be the control group. Up to 25.2% (26 people) of the participants had increased daytime sleepiness according to the Epworth score (≥10 points). While additional comorbidity was detected in 72 (69.9%) people, cardiovascular diseases were the most common subgroup (39 people, 37.9%). The mean EUS was found to be statistically significantly higher in the severe OSAS group (p=0.021), and nocturia in the whole OSAS group (p=0.009). Although PTTi was higher in the OSAS group, it was not statistically significant (p=0.576). While significant values were obtained with EUS≥10 in the analyzes performed in terms of predicting complications of PTTi (p=0.009), no statistically significant results could be obtained despite the increase in cardiovascular diseases, RSI, and nocturia. A significant correlation was found between AHI and complications in terms of cardiovascular diseases (p=0.032), hypertension (p=0.05), nocturia (p=0.009). There was no significant correlation between AHI and PTTi (p=0.123). A weak correlation was found between AHI and EUS (rho=0.248, p=0.025), and between PTTi and EUS (rho=0.239, p=0.032). Correlation was also found between AHI and RSI, and between VAS and EUS. When EUS was ≥10, the cut-off value calculated by ROC analysis for VAS was ≥4.5, sensitivity: 81%, specificity: 78% (p=0.0001, AUC=0.806). When logistic regression analysis was performed for PTTi and AHI to predict symptoms and complications, the case predictive value of PTTi for EUS ≥10 was found to be more than one-fold increased. When ROC analysis was performed for the PTTi value predicting EUS≥10 in OSAS patients, when the cut-off value was taken as 50.43, the sensitivity was calculated as 63% and specificity: 64.4% (p=0.008, AUC=0.69). Conclusion: In our study, the prevalence of cardiovascular complications, hypertension and nocturia was found to be significantly higher in OSAS cases. However, no statistically significant correlation could be obtained between AHI value and PTTi, and no significant superiority of PTT over AHI was found in detecting OSAS-related symptoms and complications. KeyWords: Obstructive Sleep Apnea Syndrome, Pulse Transit Time, AHI