Association Between Respiratory Event-Specific Oxygen Desaturation Rate and Blood Pressure Surge in Obstructive Sleep Apnea

Association Between Respiratory Event-Specific Oxygen Desaturation Rate and Blood Pressure Surge in Obstructive Sleep Apnea | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Association Between Respiratory Event-Specific Oxygen Desaturation Rate and Blood Pressure Surge in Obstructive Sleep Apnea Yanli Gu, yujiao wan, Jiani Shen, Yujie Yuan, Qiyun Ma, Guihong Wei, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8841930/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 May, 2026 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract To investigate the association between respiratory event-specific oxygen desaturation rate (ODR) and blood pressure (BP) surges in patients with obstructive sleep apnea (OSA). Oxygen desaturation events caused by apnea and hypopnea were analyzed to quantify ODR, representing the rate of oxygen consumption. Beat-to-beat systolic blood pressure was recorded using a pulse transit time (PTT)-based technique synchronized with PSG, and post-hypoxic BP responses (peak, amplitude, surge rate) were extracted. Vascular hypoxic reactivity was defined as the ratio of BP response to ODR. A total of 95,518 respiratory events from 297 patients were analyzed. In adjusted linear models, higher ODR was significantly associated with increased BP amplitude (β = 5.21, 95% CI: 2.90–7.52, p < 0.001) and BP surge rate (β = 0.51, 95% CI: 0.22–0.80, p = 0.001), but not with BP peak. A significant interaction between ODR and hypertension status was observed for both BP amplitude and surge rate. For each unit increase in BP amplitude/ODR, BP peak/ODR, and BP surge rate/ODR, the odds of hypertension increased by 2.3%, 0.2%, and 14.1%, respectively. ODR showed an independent relationship with post-hypoxic BP surge in OSA patients. The ratio of BP surges to ODR, reflecting vascular hypoxic reactivity, was associated with hypertension. Health sciences/Cardiology Health sciences/Diseases Health sciences/Medical research Biological sciences/Physiology Obstructive sleep apnea Oxygen desaturation rate Blood pressure surge Hypertension Figures Figure 1 Figure 2 Introduction Beat-to-beat blood pressure variability (BPV) refers to rapid fluctuations in blood pressure (BP) between consecutive cardiac cycles, reflecting the dynamic regulation of vascular tone by neural and humoral mechanisms [ 1 ] . Evidence shows that beat-to-beat BPV is independently associated with target organ damage, including hypertensive nephropathy [ 2 ] , left ventricular hypertrophy [ 2 ] , and cerebrovascular injury [ 3 ] . Moreover, increased beat-to-beat BPV has been identified as a sensitive and early prognostic indicator of adverse cardiovascular events, independent of average BP levels [ 4 , 5 ] . Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder characterized by recurrent collapse of the upper airway during sleep [ 6 ] , leading to a series of physiological responses that contribute to the exacerbation of nocturnal beat-to-beat BPV [ 7 ] . Among various pathophysiological mechanisms, the periodic decrease in oxygen saturation during sleep, known as intermittent hypoxia (IH), is considered the primary driver of this increased BPV [ 8 ] . Studies employing continuous BP monitoring have demonstrated that the termination of obstructive events is accompanied by transient BP surges lasting only a few seconds, followed by a return to baseline or below baseline levels [ 9 ] . These BP variations are highly correlated with the desaturation depth or duration [ 10 ] . However, these measures inadequately capture the complex dynamics of oxygen transport and utilization that underlie BPV during obstructive episodes. The oxygen desaturation rate (ODR) reflects the oxygen consumption druing IH event, calculated as the percentage change in desaturation per second [ 11 ] . Specifically, extremely rapid desaturation can induce significant ventilation-perfusion mismatch, potentially leading to organ damage [ 12 ] . Short-duration IH events are often characterized by high ODR, associated with the hypoxic sensitivity of the carotid body [ 13 ] . Based on this metric, our previous work has identified that high ODR is closely associated with elevated daytime systolic BP levels [ 11 ] and excessive daytime sleepiness [ 14 ] . However, it remains unclear whether ODR contributes to acute post-hypoxic BP surges and whether this relationship is associated with the risk of hypertension. To better characterize the association between IH metrics and acute BP changes, we analyzed hypoxia-triggered BP surge profiles using continuous beat-to-beat monitoring based on the pulse transit time (PTT) method in a group of OSA patients. Hypoxia-related ODR was quantified using pulse oximetry signals recorded during overnight polysomnography (PSG). This study primarily aimed to evaluate the relationship between ODR and post-hypoxic BP surge metrics. Furthermore, we examined whether vascular hypoxic reactivity, defined as the ratio of BP surge parameters to ODR, was associated with an increased risk of hypertension. Results Study population As shown in Table 1 , 297 patients were included in the study: 80 were normotensive, 127 had treated hypertension, and 90 had untreated hypertension. Of all participants, 83.2% were male, with a median age of 51.0 years and a median AHI of 52.8 events/h. A total of 95,518 IH events were analyzed. Hypertension, diabetes, and CHD were present in 73.1%, 43.4%, and 30.0%. of the patients, respectively. Significant group differences were observed in alcohol consumption (p = 0.027) and CHD prevalence (p = 0.036). In contrast, no statistically significant differences were found among groups in BMI, smoking status, or diabetes, nor in AHI, mean SpO₂, or T90. The normotensive group had a significantly higher median ODR (0.41 [0.29–0.51] %/s) compared with the treated hypertension group (0.35 [0.24–0.43] %/s) and the untreated hypertension group (0.35 [0.23–0.47] %/s). The untreated hypertension group had the longest Δt (18.4 [16.8–27.2] s, p = 0.001), while event duration was longest in the treated hypertension group (16.7 [15.8–18.3] s, p = 0.012). Table 1 Demographic, PSG, oxygen desaturation, BP variability characteristics. Variables Normotensive (n = 80) Treated-hypertensive (n = 127) Untreated-hypertensive (n = 90) P Age, years 43.0 (34.3, 54.0) 54.0 (47.0, 63.0) 47.0 (34.0, 59.3) < 0.001*** Male, n (%) 69 (86.3) 102 (74.5) 76 (84.4) 0.500 BMI, kg/m 2 30.6 (27.4, 33.8) 30.0 (27.0, 33.2) 31.2 (27.6, 34.3) 0.351 Smoking, n (%) 18 (22.5) 30 (21.9) 15 (16.7) 0.442 Alcohol consumption, n (%) 19 (23.8) 16 (11.7) 9 (10.0) 0.027* CHD, n (%) 18 (22.5) 48 (35.0) 23 (25.6) 0.036* Diabetes, n (%) 32 (40.0) 58 (42.3) 39 (43.3) 0.725 TST, hours 6.6 (5.6, 7.5) 7.0 (6.1, 7.8) 6.3 (5.5, 7.2) 0.001** AHI, events/h 57.2 (36.2, 74.9) 50.8 (31.5, 64.5) 52.1 (36.2, 67.3) 0.190 ODI, events/h 48.3 (29.7, 68.6) 46.8 (26.5, 61.7) 46.3 (30.5, 63.2) 0.294 T90, % 18.9 (5.5, 45.9) 17.8 (5.7, 41.0) 15.9 (6.3, 40.3) 0.904 Mean SpO 2 , % 92.0 (89.0, 93.0) 92.0 (89.0, 94.0) 92.0 (90.0, 94.0) 0.805 Lowest SpO 2 , % 72.0 (62.3, 80.0) 74.0 (60.0, 78.0) 73.0 (62.8, 79.3) 0.794 Δt, s 17.4 (16.2, 19.1) 17.7 (16.7, 19.1) 18.4 (16.8, 27.2) 0.001** ΔSpO 2 , % 5.6 (4.7, 6.5) 5.7 (4.9, 6.4) 5.6 (4.8, 7.6) 0.245 Event duration, s 16.2 (15.4, 16.9) 16.7 (15.8, 18.3) 16.5 (15.8, 17.2) 0.012* ODR, %/s 0.41 (0.29, 0.51) 0.35 (0.24, 0.43) 0.35 (0.23, 0.47) 0.012* Awake SBP, mmHg 125.1 (117.5, 132.7) 129.0 (123.0, 134.8) 145.0 (140.0, 150.0) < 0.001*** Awake DBP, mmHg 79.3 (76.1, 84.8) 80.0 (76.8, 82.6) 89.0 (82.5, 95.3) < 0.001*** Nighttime SBP, mmHg 124.0 (116.0, 133.9) 126.0 (115.0, 134.2) 131.0 (124.9, 141.4) < 0.001*** Nighttime DBP, mmHg 80.0 (74.4, 83.8) 79.0 (76.2, 82.7) 80.0 (76.2, 84.8) 0.559 BP surge time, s 11.7 (10.6, 13.6) 12.1 (10.6, 14.1) 10.7 (8.5, 12.7) < 0.001*** BP peak, mmHg 122.4 (115.0, 133.0) 122.3 (113.6, 134.9) 125.1 (118.5, 135.3) 0.157 BP amplitude, mmHg 15.0 (13.6, 18.1) 14.4 (13.0, 16.4) 15.0 (13.1, 17.6) 0.016* BP surge rate, mmHg/s 1.7 (1.4, 2.1) 1.5 (1.3, 1.8) 1.6 (1.3, 1.9) 0.002** Primary outcomes As shown in Fig. 2 , ODR was significantly positively correlated with BMI (r = 0.283), AHI (r = 0.344), and T90 (r = 0.388), and significantly negatively correlated with mean SpO₂ (r =-0.372) and lowest SpO₂ (r =-0.346), while no significant correlation was found with event duration. In the adjusted linear regression model, ODR was significantly associated with increased BP amplitude (β = 5.21, 95% CI: 2.90 to 7.52, p < 0.001) and BP surge rate (β = 0.51, 95% CI: 0.22 to 0.80, p = 0.001). Specifically, for every 1-unit increase in ODR, BP amplitude increased by 5.21 mmHg, and BP surge rate increased by 0.51 mmHg/s. However, no significant association was found between ODR and BP peak (Table 2 ). A significant interaction effect between ODR and hypertension status on BP amplitude was observed (β = 3.91, 95% CI: 1.39 to 6.44, p = 0.002), as well as on BP surge rate (β = 0.33, 95% CI: 0.01 to 0.64, p = 0.045), suggesting that hypertension modifies the association between ODR and BP surges. Table 2 Multiple linear regression analysis with BP surge parameters as dependent variables in the entire population. BP amplitude BP peak BP surge rate Model 1 (unadjusted) Model 2 (adjusted) Model 1 (unadjusted) Model 2 (adjusted) Model 1 (unadjusted) Model 2 (adjusted) β (95% CI) P β (95% CI) P β (95% CI) P β (95% CI) P β (95% CI) P β (95% CI) P ODR, %/s 8.69 (6.57, 10.82) < 0.001*** 5.21 (2.90, 7.52) < 0.001*** 3.53 (-6.68, 13.73) 0.497 -6.20 (-17.93,5.54) 0.300 1.01 (0.74, 1.28) < 0.001*** 0.51 (0.22, 0.80) 0.001** Δt, s -0.01 (-0.09, 0.06) 0.750 0.05 (-0.01, 0.12) 0.113 -0.65 (-0.96, -0.34) < 0.001 -0.71 (-1.03, -0.40) < 0.001 -0.02 (-0.03, -0.01) 0.001 -0.01 (-0.02, 0.00) 0.078 ΔSpO 2 , % 0.10 (-0.06, 0.25) 0.212 -0.00 (-0.14, 0.13) 0.968 0.16 (-0.51, 0.82) 0.640 -0.15 (-0.80, -0.51) 0.660 0.00 (-0.02, 0.02) 0.747 -0.01 (-0.02, 0.01) 0.380 Event duration, s -0.04 (-0.18, 0.10) 0.572 0.05 (-0.07, 0.17) 0.395 -0.41 (-1.01, 0.19) 0.180 -0.35 (-0.95, 0.24) 0.242 -0.01 (-0.03, 0.00) 0.130 0.00 (-0.02, 0.01) 0.890 Hypertension -0.73 (-1.70, 0.24) 0.138 0.26 (-0.73, 1.24) 0.611 3.09 (-1.12, 7.30) 0.149 5.41 (0.55, 10.27) 0.029 -0.19 (-0.31, -0.07) 0.002 -0.08 (-0.20, 0.04) 0.205 ODR*hypertension 2.73 (0.88, 4.57) 0.004** 3.91 (1.39, 6.44) 0.002** 3.46 (-4.67, 11.58) 0.404 -12.10(-24.63,0.44) 0.058 0.14 (-0.10, 0.37) 0.249 0.33 (0.01, 0.64) 0.045* Sensitivity Analyses In sensitive analysis (Table 3 ), ODR was positively associated with BP amplitude in normotensive (β = 7.39, 95% CI: 2.60 to 12.19, p = 0.003), treated hypertensive (β = 5.14, 95% CI: 1.17 to 9.10, p = 0.012), and untreated hypertensive patients (β = 4.99, 95% CI: 0.76 to 9.21, p = 0.021). Significant positive associations between ODR and BP surge rate were observed in normotensive (β = 0.85, 95% CI: 0.28 to 1.43, p = 0.004) and untreated hypertensive (β = 0.69, 95% CI: 0.11 to 1.26, p = 0.020), but not in treated hypertensive patients. Δt was negatively associated with BP peak in treated and untreated hypertensive groups, with no significant association in normotensives. In contrast, neither ΔSpO₂ nor event duration showed a consistent correlation with BP surge parameters. In the stratified analysis, the association between ODR and BP surge rate was more stronger in younger individuals (< 60 years: β = 0.60, 95% CI: 0.25 to 0.95, p = 0.001) and those with more severe OSA (AHI ≥ 50 events/h: β = 0.67, 95% CI: 0.23 to 1.11, p = 0.003) ( Table s1 ). Table 3 Sensitivity analysis of BP surge parameters in hypertensive and normotensive populations. BP amplitude BP peak BP surge rate Model 1 (unadjusted) Model 2 (adjusted) Model 1 (unadjusted) Model 2 (adjusted) Model 1 (unadjusted) Model 2 (adjusted) β (95% CI) P β (95% CI) P β (95% CI) P β (95% CI) P β (95% CI) P β (95% CI) P Normotensive patients (n = 80) ODR, %/s 14.00 (10.02, 17.97) < 0.001*** 7.39 (2.60, 12.19) 0.003** 30.89 (11.17, 50.61) 0.003** 16.04 (-9.60, 41.68) 0.216 1.74 (1.22, 2.27) < 0.001*** 0.85 (0.28, 1.43) 0.004** Δt, s 0.08 (-0.27, 0.42) 0.665 0.14 (-0.15, 0.44) 0.327 -1.01 (-2.41, 0.40) 0.158 -0.42 (-1.90, 1.06) 0.576 -0.03 (-0.08, 0.01) 0.122 -0.03 (-0.07, 0.00) 0.081 ΔSpO 2 , % -0.16 (-0.41, 0.09) 0.200 0.01 (-0.20, 0.21) 0.955 -0.65 (-1.67, 0.37) 0.206 -0.28 (-1.31, 0.75) 0.589 -0.03 (-0.07, -0.00) 0.034* -0.02 (-0.04, 0.01) 0.200 Event duration, s -0.10 (-0.50, 0.31) 0.645 0.16 (-0.16, 0.49) 0.319 -0.21 (-1.89, 1.47) 0.805 0.72 (-0.94, 2.38) 0.390 -0.05 (-0.10, 0.00) 0.050 -0.02 (-0.06, 0.02) 0.266 Treated-hypertensive patients (n = 127) ODR, %/s 8.21 (4.49, 11.94) < 0.001*** 5.14 (1.17, 9.10) 0.012* -7.62 (-27.45, 12.21) 0.449 -19.19 (-41.72, 3.35) 0.094 0.59 (0.16, 1.01) 0.007** 0.18 (-0.27, 0.62) 0.431 Δt, s -0.02 (-0.14, 0.09) 0.676 0.02 (-0.08, 0.13) 0.660 -0.76 (-1.31, -0.21) 0.007** -0.76 (-1.34, -0.18) 0.010* -0.01 (-0.02, 0.00) 0.142 -0.01 (-0.02, 0.01) 0.311 ΔSpO 2 , % 0.28 (-0.03, 0.59) 0.072 0.09 (-0.21, 0.38) 0.569 -1.24 (-2.76, 0.28) 0.109 -1.54 (-3.16, 0.08) 0.063 0.02 (-0.02, 0.05) 0.294 -0.00 (-0.03, 0.03) 0.893 Event duration, s 0.00 (-0.17, 0.17) 0.997 0.06 (-0.10, 0.21) 0.488 -0.47 (-1.31, 0.36) 0.261 -0.44 (-1.31, 0.43) 0.320 -0.01 (-0.03, 0.01) 0.428 -0.00 (-0.02, 0.01) 0.718 Untreated-hypertensive patients (n = 90) ODR, %/s 6.56 (2.90, 10.22) 0.001** 4.99 (0.76, 9.21) 0.021* 0.04 (-15.20, 15.27) 0.996 -2.68 (-21.42, 16.07) 0.777 0.87 (0.38, 1.35) 0.001** 0.69 (0.11, 1.26) 0.020* Δt, s -0.01 (-0.13, 0.10) 0.808 0.08 (-0.03, 0.19) 0.157 -0.82 (-1.25, -0.40) < 0.001** -0.69 (-1.14, -0.24) 0.003* -0.02 (-0.03, -0.00) 0.026* -0.01 (-0.02, 0.01) 0.345 ΔSpO 2 , % 0.19 (-0.08, 0.46) 0.163 -0.06 (-0.32, 0.21) 0.667 1.14 (0.12, 2.16) 0.030* 0.79 (-0.33, 1.91) 0.163 0.03 (-0.01, 0.06) 0.153 0.00 (-0.04, 0.04) 0.993 Event duration, s -0.03 (-0.32, 0.27) 0.867 0.03 (-0.23, 0.30) 0.810 -0.47 (-1.62, 0.67) 0.412 -0.36 (-1.49, 0.77) 0.531 0.00 (-0.04, 0.04) 0.934 0.00 (-0.04, 0.04) 0.993 Exploratory analyses In the binary logistic regression analysis (Table 4 ), vascular hypoxic reactivity, as represented by the BP surge metrics/ODR ratio, was positively associated with hypertension. Specifically, for each 1-unit increase in BP amplitude/ODR, the odds of developing hypertension increased by 2.3% (1.023 [95% CI: 1.005–1.041], p = 0.011). Similarly, each unit increase in BP peak/ODR was associated with a 0.2% increased likelihood of hypertension (1.002 [ 95% CI: 1.000-1.004], p = 0.015). Furthermore, the odds of hypertension increased by 14.1% for every unit increase in BP surge rate/ODR (1.141 [95% CI: 1.001–1.299], p = 0.048). Table 4 Binary logistic regression analysis with hypertension status as a dependent variable. Independent variables Model 1 (unadjusted) Model 2 (adjusted) OR (95% CI) P value OR (95% CI) P AHI, events/h 0.991 (0.980, 1.002) 0.123 0.997 (0.983, 1.011) 0.626 T90, % 0.999 (0.988, 1.010) 0.813 0.998 (0.984, 1.012) 0.811 BP amplitude/ODR 1.021 (1.007, 1.036) 0.003** 1.023 (1.005, 1.041) 0.011* BP peak/ODR 1.002 (1.001, 1.004) 0.002** 1.002 (1.000, 1.004) 0.015* BP surge rate/ODR 1.124 (1.011, 1.249) 0.031* 1.141 (1.001,1.299) 0.048 * Table s2 compared BP parameters among patients taking different antihypertensive medications. The calcium channel blockers (CCBs) group had a significantly lower BP surge rate (1.43 mmHg/s), BP amplitude (13.73 mmHg) and BP peak (120.62 mmHg) compared to both the angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (ACEIs/ARBs) group (1.55 mmHg/s, 14.82 mmHg, 122.77 mmHg) and the CCBs + ACEIs/ARBs group (1.60 mmHg/s, 14.87 mmHg, 129.73 mmHg), with overall p-values of 0.043, 0.019 and 0.048, respectively. No significant differences were found in other BP parameters, including average BP and BP rise time. Discussion In this study, we developed a novel PSG-derived IH metric, the ODR, which showed a significant independent association with post-hypoxic BP variations in the OSA population. This association was more significant among younger patients and those with more severe OSA. Importantly, hypertension significantly modified the association between ODR and BP surges, with hypertensive individuals showing amplified BP responses to comparable ODR levels. Furthermore, the ratio of BP surge metrics to ODR, a surrogate marker of hypoxia-induced vasoconstriction, was significantly associated with the risk of hypertension. Exploratory analyses suggested that CCBs were more effective than ACE inhibitors or ARBs in attenuating post-hypoxic BP elevations, highlighting their potential advantage in managing nocturnal BP variability in OSA. ODR is the rate of decrease in pulse oxygen saturation during a respiratory event, serving as an indicator of oxygen storage and metabolic oxygen consumption [ 15 ] . Our study found a significant positive correlation between ODR and T90, and a negative correlation with mean SpO₂, indicating that a high ODR, reflecting rapid depletion of alveolar oxygen reserves, significantly worsens nocturnal hypoxia severity. Theoretically, lung volume and metabolic rate are key determinants of desaturation rate. Obesity reduces functional residual capacity and expiratory reserve volume [ 16 ] , thus lowering pulmonary oxygen reserves and accelerating oxygen depletion during apnea episodes. Furthermore, obesity impairs the ventilation-perfusion ratio [ 17 ] , contributing to small airway closure [ 18 ] , V/Q mismatch, all of which further accelerate oxygen desaturation. Together, these may likely explain the positive correlation observed between BMI and ODR. Moreover, recurrent apneic events have been shown to induce desaturation rates approximately twice those observed in isolated apneas [ 19 , 20 ] . Consistent with this, our findings indicate that higher AHI is significantly correlated with increased ODR levels. However, no significant correlation was found between ODR and event duration, a finding consistent with Strohl et al [ 15 ] . who demonstrated that the rate of change in arterial oxygen saturation during conscious breath holding is independent of breath-hold duration. Therefore, a high ODR may serve as a comprehensive marker of hypoxia, reflecting multiple pathological features, including recurrent airway obstruction, increased obesity, and diminished pulmonary oxygen reserve, which predispose individuals to more severe oxygen desaturation during sleep. We observed a significant association between the ODR and BP surges during obstructive respiratory events. Additionally, a significant positive interaction between ODR and hypertension was identified, indicating that individuals with hypertension may exhibit an exaggerated hemodynamic response to rapid oxygen desaturation. To better characterize individual variability in vascular reactivity to hypoxia, we proposed a novel metric: the ratio of BP surge to ODR. This parameter normalizes the magnitude of the BP response relative to the severity of oxygen desaturation, serving as a surrogate index of hypoxia-induced vasoconstrictive sensitivity. Notably, higher BP surge/ODR values were consistently and significantly associated with the presence of hypertension. Mechanistically, this phenomenon may be attributed to pathophysiological changes associated with chronic hypertension, including vascular remodeling [ 21 ] , increased arterial stiffness [ 22 ] in this population. These vascular abnormalities may lower the threshold for pressor responses [ 23 ] , thereby contributing to an exaggerated vasoconstrictive response to transient hypoxia. Additionally, sympathetic nervous system overactivity [ 24 ] , which is elevated in both OSA and hypertension, is further potentiated by hypoxia-induced chemoreflex sensitivity, particularly through the carotid body [ 25 ] . This chemosensory hyperresponsiveness triggers excessive catecholamine release [ 26 ] , leading to vasoconstriction mediated by α- and/or β-adrenergic receptors [ 27 ] , which may promote large transient BP surges during hypopnea or apnea termination. Moreover, in OSA patients with normal endothelial function, the endothelial nitric oxide synthase/nitric oxide (eNOS/NO) pathway counteracts the pressor effect of sympathetic nervous system and contributes to BP homeostasis [ 28 ] . However, in hypertensive OSA patients, endothelial dysfunction may impair the eNOS/NO pathway [ 29 – 31 ] , thereby diminishing vascular buffering capacity in response to hypoxia and facilitating abrupt increases in BP. In stratified analyses, the association between ODR and post-hypoxic BP responses was stronger in younger individuals. These findings suggest that age influences cardiovascular responses to hypoxia. Younger individuals appear more sensitive, likely due to greater sympathetic vascular transduction, a key mechanism in beat-to-beat BP regulation [ 32 ] . With aging, this transduction becomes less effective, leading to attenuated pressor and vasoconstrictor responses[ 33 , 34 ], which may reflect a protective adaptation against excessive BP fluctuations in older adults. Therefore, exaggerated vascular responses may represent a pathophysiological mechanism contributing to elevated cardiovascular risk. Characterizing individual vascular reactivity profiles could enhance risk stratification and support more personalized management strategies in patients with OSA. The effect of CCBs on BPV has been widely studied, including on long-term and short-term variability. For example, Frattola et al. reported that the long-acting CCB lacidipine significantly reduced the variation coefficient of 24-hour beat-to-beat BP in patients with type II diabetes and hypertension [ 35 ] . In hypertensive rat models, the CCB nitrendipine was more effective than hydralazine in reducing long-term BPV and end-organ damage [ 36 ] . Analysis of two large-scale clinical studies showed that the CCB amlodipine had greater efficacy than β-blockers in stabilizing visit-to-visit BP variability and lowering the incidence of stroke [ 37 ] . In this study, we compared the effects of different classes of antihypertensive agents on acute BP fluctuations induced by respiratory events and found that CCBs more effectively reduced post-hypoxic BP elevations than ACEIs or ARBs, indicating that CCBs may offer greater benefits in stabilizing both long-term BPV and acute post-hypoxic BP surges. Our study presents several important strengths. Notably, we applied the concept of the ODR as a novel event-based hypoxic marker. Unlike conventional desaturation indices, ODR specifically characterizes the rate of oxygen desaturation during individual respiratory events, thereby capturing the dynamic and transient hypoxic stress experienced by OSA. By utilizing this event-specific parameter, our study enabled a more precise characterization of the association between hypoxia and acute BP responses, which may be inadequately represented by traditional indices. However, our study has several limitations. First, the relatively small sample size may limit generalizability, and larger studies in diverse populations are needed to validate these findings. Second, an observational study design prevents causal inferences and may be subject to residual confounding despite adjustment. Finally, Given the limited information about β-blocker or diuretic monotherapy, our analysis only focused on the effect of exclusively CCBs and ACEIs/ARBs on hypoxia-induced BP oscillations. Conclusion This study provides evidence that ODR during obstructive respiratory events is closely associated with post-hypoxic BP surges. Importantly, hypertension significantly amplifies this relationship, with hypertensive individuals exhibiting greater BP surges at similar ODR levels. Furthermore, vascular hypoxic reactivity, measured by the ratio of BP surge to ODR, was significantly correlated with an increased risk of developing hypertension. Methods Study population Between January 2024 and April 2025, patients who underwent overnight PSG at the Sleep Medicine Center of the Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University were recruited. A detailed questionnaire was designed to evaluate daily BP, comorbidities, medications, smoking and alcohol consumption, clinical history, and anthropometric measurements. Inclusion criteria were: 1) newly diagnosed OSA (apnea-hypopnea index [AHI] ≥ 15 events/h); and 2) age between 18 and 75 years. Exclusion criteria were: 1) comorbid conditions causing nocturnal hypoxia (e.g., heart failure, chronic obstructive pulmonary disease); 2) history of other sleep disorders; 3) refusal to participate; and 4) inadequate study data. A total of 297 individuals were included in the final analysis. The study protocol was approved by the Huaian First People’s Hospital Medical Ethics Committee and conducted in accordance with the Declaration of Helsinki (YX-Z-2022-028-01), with all participants providing written informed consent. Sleep study All patients underwent full-night PSG (SOMNOscreen Plus, SOMNOmedics, Germany) in the sleep laboratory. Recorded signals included electroencephalography, bilateral electrooculograms, chin electromyography, electrocardiogram, nasal pressure, thermistor-based airflow, thoracic and abdominal inductance plethysmography, and fingertip pulse oximetry. Sleep data were scored using standardized protocols [ 38 ] . Apnea was defined as a complete cessation of airflow lasting ≥ 10 seconds. Hypopnea was defined as a ≥ 50% reduction in nasal pressure amplitude, accompanied by either ≥ 3% oxygen desaturation or arousal. AHI was calculated as the number of apneas and hypopneas per hour of sleep, with AHI > 15 events/h used to define OSA [ 39,40 ] . T90 was defined as the percentage of total sleep time spent with SpO 2 < 90%. The oxygen desaturation index (ODI) was calculated as the number of ≥ 3% desaturation events per hour. Definition of IH parameters The occurrence of apnea or hypopnea depletes the body's oxygen reserves, leading to a drop in SpO₂. For each oxygen desaturation event, the following IH parameters were calculated: 1) Δt, defined as the time from the onset of oxygen desaturation to the SpO₂ nadir; 2) ΔSpO 2 , the magnitude of oxygen desaturation from the initial drop to the nadir; 3) event duration, defined as the length of apneas or hypopneas; and 4) ODR, calculated as the ratio of ΔSpO 2 to Δt, representing the rate of oxygen desaturation per second ( Fig. 1 ). BP measurement Cuff BP was measured in the seated position using conventional mercury sphygmomanometry. Hypertension was defined as a systolic BP ≥ 140 mmHg and/or diastolic BP ≥ 90 mmHg, or current use of antihypertensive medication [ 41 ] . Beat-to-beat BP was continuously monitored using a PTT-based method synchronized with PSG (SOMNOscreen plus PSG+), as previously described [ 11 ] . In brief, PTT was defined as the time interval between the ECG R-wave and the arrival of the pulse wave at the fingertip detected by photoplethysmography. Systolic, diastolic, and mean BP values were then automatically calculated using the DOMINO Light software. For each respiratory event, the following BP response metrics were calculated: 1) BP peak, defined as the maximum systolic BP during the post-hypoxic rise; 2) BP amplitude, calculated as the difference between baseline and peak systolic BP; and 3) BP surge rate, representing the rate of systolic BP increase (mmHg/s) during the ascending phase ( Fig. 1 ). Statistical analyses Continuous variables were presented as median (interquartile range [IQR]) and categorical variables as number (percentage). Group comparisons were performed using the Kruskal–Wallis test or the chi-square test. Pearson or Spearman correlation analyses were used to assess associations between ODR and relevant clinical parameters. Multiple linear regression models were used to assess the associations between IH parameters (ODR, Δt, ΔSpO₂, event duration) and post-hypoxic BP surge indices (amplitude, peak, surge rate), using the enter method. Model 1 was unadjusted; Model 2 adjusted for age, gender, body mass index (BMI), smoking, alcohol consumption, AHI, T90, total sleep time (TST), history of hypertension, diabetes, coronary heart disease (CHD), and antihypertensive medication. Interaction terms were included in the model to assess whether hypertension status modified the association between ODR and BP. Sensitivity analyses were conducted in normotensive and hypertensive subgroups using the same models described previously. Additionally, stratified analyses by age, AHI, and BMI were performed to examine population-specific differences. In exploratory analyses, binary logistic regression was used to assess the association between vascular hypoxic reactivity, as represented by the BP surge metrics/ODR ratio, and hypertension. The effects of antihypertensive medications on post-hypoxic BP surges were also assessed. All statistical analyses were performed using SPSS version 29.0 (IBM Corp., Armonk, NY, USA), with a two-sided p-value < 0.05 considered statistically significant. Declarations Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request, [email protected] . Acknowledgements The authors thank all individuals who agreed to participate in this study. Author contributions Yanli Gu and Yujiao Wan: Conceptualization, Methodology, Investigation, Formal Analysis, Writing - Original Draft, Writing - Review & Editing. Jiani Shen and Yujie Yuan: Methodology, Validation, Visualization. Qiyun Ma: Resources, Software . Guihong Wei: Formal analysis, Project administration . Xiaochen Xie: Data Curation, Resources. Fengjuan Xu: Software, Visualization. Xiaoxiao Han: Supervision, Data Curation. Jing Xu: Supervision, Project Management, Supervision, Writing - Review & Editing, Funding acquisition. All authors have given final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work. Competing interests All the authors declare that they have no conflicts of interest. Funding information This study did not receive any funding to assist with the preparation of this manuscript. Ethics declarations This study was approved by the Institutional Review Committee of Huai’an No.1 People’s Hospital and was conducted following the Helsinki Declaration. Additional information References Sheikh, A. B. et al. Blood pressure variability in clinical practice: past, present and the future. J. Am. 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Obstructive sleep apnea and hypertension: updates to a critical relationship. Curr. Hypertens. Rep. 24 , 173–184 (2022). Peng, Y. J. et al. Signal transduction pathway mediating carotid body dependent sympathetic activation and hypertension by chronic intermittent hypoxia. Function 6 , zqaf003 (2025). Bisogni, V., Pengo, M. F., Maiolino, G. & Rossi, G. P. The sympathetic nervous system and catecholamines metabolism in obstructive sleep apnoea. J. Thorac. Dis. 8 , 243–254 (2016). Motiejunaite, J., Amar, L. & Vidal-Petiot, E. Adrenergic receptors and cardiovascular effects of catecholamines. Ann. Endocrinol. 82 , 193–197 (2021). Battault, S. et al. Vascular endothelial function masks increased sympathetic vasopressor activity in rats with metabolic syndrome. Am. J. Physiol. Heart Circ. Physiol. 314 , H497–H507 (2018). Genta-Pereira, D. C., Pedrosa, R. P., Lorenzi-Filho, G. & Drager, L. F. Sleep disturbances and resistant hypertension: association or causality? Curr. Hypertens. Rep. 16 , 459 (2014). Schulz, R. et al. Decreased plasma levels of nitric oxide derivatives in obstructive sleep apnoea: response to CPAP therapy. Thorax 55 , 1046–1051 (2000). Ohike, Y. et al. Amelioration of vascular endothelial dysfunction in obstructive sleep apnea syndrome by nasal continuous positive airway pressure-possible involvement of nitric oxide and asymmetric NG, NG-dimethylarginine. Circ. J. 69 , 221–226 (2005). D'Souza, A. W. et al. Age- and sex-related differences in sympathetic vascular transduction and neurohemodynamic balance in humans. Am. J. Physiol. Heart Circ. Physiol. 325 , H917–H932 (2023). Petterson, J. L. et al. Sympathetic neurohemodynamic transduction is attenuated in older males independent of aerobic fitness. Clin. Auton. Res. 32 , 73–76 (2022). D'Souza, A. W., Klassen, S. A., Badrov, M. B., Lalande, S. & Shoemaker, J. K. Aging is associated with enhanced central but impaired peripheral arms of the sympathetic baroreflex arc. J. Appl. Physiol. 133 , 349–360 (2022). Frattola, A. et al. Lacidipine and blood pressure variability in diabetic hypertensive patients. Hypertension 36 , 622–628 (2000). Liu, J. G., Xu, L. P., Chu, Z. X., Miao, C. Y. & Su, D. F. Contribution of blood pressure variability to the effect of nitrendipine on end-organ damage in spontaneously hypertensive rats. J. Hypertens. 21 , 1961–1967 (2003). Rothwell, P. M. et al. Effects of beta blockers and calcium-channel blockers on within-individual variability in blood pressure and risk of stroke. Lancet Neurol. 9 , 469–480 (2010). Berry, R. B. et al. Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. J. Clin. Sleep. Med. 8 , 597–619 (2012). Kapur, V. K. et al. Clinical Practice Guideline for Diagnostic Testing for Adult Obstructive Sleep Apnea: An American Academy of Sleep Medicine Clinical Practice Guideline. J. Clin. Sleep. Med. 13 , 479–504 (2017). Mangione, C. M. et al. Screening for Obstructive Sleep Apnea in Adults: US Preventive Services Task Force Recommendation Statement. JAMA 328 , 1945–1950 (2022). Whelton, P. K. et al. ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension 71, 1269–1324 (2018). (2017). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8841930","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":610078569,"identity":"38eaff4f-b614-48ac-a1a7-4f7029b16cb9","order_by":0,"name":"Yanli Gu","email":"","orcid":"","institution":"Huaian First People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yanli","middleName":"","lastName":"Gu","suffix":""},{"id":610078576,"identity":"74f344a2-5bc6-468c-8514-596d0c82a059","order_by":1,"name":"yujiao wan","email":"","orcid":"","institution":"Huaian First People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"yujiao","middleName":"","lastName":"wan","suffix":""},{"id":610078578,"identity":"6ddb9d66-a0b5-42e4-82ad-3cd4c896e2be","order_by":2,"name":"Jiani Shen","email":"","orcid":"","institution":"Huaian First People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiani","middleName":"","lastName":"Shen","suffix":""},{"id":610078581,"identity":"ec8758d2-e973-4818-ab4e-2fed469efaba","order_by":3,"name":"Yujie Yuan","email":"","orcid":"","institution":"Huaian First People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yujie","middleName":"","lastName":"Yuan","suffix":""},{"id":610078582,"identity":"a43326a7-f704-472b-aad1-0693fa18a6c2","order_by":4,"name":"Qiyun Ma","email":"","orcid":"","institution":"Huaian First People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qiyun","middleName":"","lastName":"Ma","suffix":""},{"id":610078584,"identity":"7b23aa1c-4dad-4071-a870-a1f45d01f95d","order_by":5,"name":"Guihong Wei","email":"","orcid":"","institution":"Huaian First People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Guihong","middleName":"","lastName":"Wei","suffix":""},{"id":610078587,"identity":"18dc43d0-34ff-4c85-9d80-f829835cecbe","order_by":6,"name":"Xiaochen Xie","email":"","orcid":"","institution":"Huaian First People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaochen","middleName":"","lastName":"Xie","suffix":""},{"id":610078592,"identity":"1931c85e-8583-49bb-b194-fb815678e15e","order_by":7,"name":"Fengjuan Xu","email":"","orcid":"","institution":"Huaian First People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fengjuan","middleName":"","lastName":"Xu","suffix":""},{"id":610078597,"identity":"f29e01b4-be9b-4a88-98b3-93e6840433bc","order_by":8,"name":"Xiaoxiao Han","email":"","orcid":"","institution":"Huaian First People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaoxiao","middleName":"","lastName":"Han","suffix":""},{"id":610078603,"identity":"7d6d09f9-a3d4-4821-91d6-385cc2077885","order_by":9,"name":"Jing Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYFCCwwcfJPyw4eFnZj74gEgtx5INPvakyUm2syUbEKmFR01yBtthY4PzPGYCRGkwOHiG2ZiH53Di5sMMZgwMNTbRBLVINpw9+JjHIj1x22GGtAcMx9JyGwhp4Wc4lwy0xRqk5bgBY8NhwlrYGM6YSfOwMSdubmZskyBKCz9QC9D7zsYGzMxsxGmRbIAGssRhNmaDBGL8YnADFpX95z8++FBjQ1gLg8QBJE4CQeUgwE/Y1FEwCkbBKBjpAABXO0GqcV+oQgAAAABJRU5ErkJggg==","orcid":"","institution":"Huaian First People’s Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jing","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2026-02-10 14:09:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8841930/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8841930/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-026-51395-0","type":"published","date":"2026-05-03T15:58:39+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":105318788,"identity":"24760541-2b29-43b0-875b-939e1c8860e1","added_by":"auto","created_at":"2026-03-24 16:55:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":118026,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIllustration of changes in oxygen desaturation and BP surge related to respiratory events\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e BP, blood pressure; ODR, oxygen desaturation rate; SBP, systolic blood pressure; SpO\u003csub\u003e2\u003c/sub\u003e, peripheral oxygen saturation.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8841930/v1/c3753743d7dcc9785333beb2.png"},{"id":105318715,"identity":"6fccebf9-5130-4ce7-8e1a-65a35d50d6aa","added_by":"auto","created_at":"2026-03-24 16:55:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":205067,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation between ODR and BMI, AHI, T90, mean SpO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, lowest SpO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, event duration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e AHI, apnea-hypopnea index; BMI, body mass index; ODR, oxygen desaturation rate; SpO\u003csub\u003e2\u003c/sub\u003e, peripheral oxygen saturation; T90, percentage of sleep time with SpO\u003csub\u003e2\u003c/sub\u003e \u0026lt; 90%.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8841930/v1/18d2d8cbab882644ec8aec37.png"},{"id":108495318,"identity":"3664d230-f420-42e7-9da7-f9d1a6ba8919","added_by":"auto","created_at":"2026-05-05 10:09:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":841739,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8841930/v1/93bade03-a4ab-4c98-a556-699fa9e87f0a.pdf"},{"id":105318716,"identity":"3ee68044-94a9-41be-b571-4f5ce9f38059","added_by":"auto","created_at":"2026-03-24 16:55:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":118821,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8841930/v1/701f812e24a5ea44c4d70b87.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Respiratory Event-Specific Oxygen Desaturation Rate and Blood Pressure Surge in Obstructive Sleep Apnea","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBeat-to-beat blood pressure variability (BPV) refers to rapid fluctuations in blood pressure (BP) between consecutive cardiac cycles, reflecting the dynamic regulation of vascular tone by neural and humoral mechanisms\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Evidence shows that beat-to-beat BPV is independently associated with target organ damage, including hypertensive nephropathy\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, left ventricular hypertrophy\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, and cerebrovascular injury\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Moreover, increased beat-to-beat BPV has been identified as a sensitive and early prognostic indicator of adverse cardiovascular events, independent of average BP levels\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder characterized by recurrent collapse of the upper airway during sleep\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, leading to a series of physiological responses that contribute to the exacerbation of nocturnal beat-to-beat BPV\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Among various pathophysiological mechanisms, the periodic decrease in oxygen saturation during sleep, known as intermittent hypoxia (IH), is considered the primary driver of this increased BPV\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Studies employing continuous BP monitoring have demonstrated that the termination of obstructive events is accompanied by transient BP surges lasting only a few seconds, followed by a return to baseline or below baseline levels\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. These BP variations are highly correlated with the desaturation depth or duration\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. However, these measures inadequately capture the complex dynamics of oxygen transport and utilization that underlie BPV during obstructive episodes.\u003c/p\u003e \u003cp\u003eThe oxygen desaturation rate (ODR) reflects the oxygen consumption druing IH event, calculated as the percentage change in desaturation per second\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Specifically, extremely rapid desaturation can induce significant ventilation-perfusion mismatch, potentially leading to organ damage\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Short-duration IH events are often characterized by high ODR, associated with the hypoxic sensitivity of the carotid body\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Based on this metric, our previous work has identified that high ODR is closely associated with elevated daytime systolic BP levels\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e and excessive daytime sleepiness\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. However, it remains unclear whether ODR contributes to acute post-hypoxic BP surges and whether this relationship is associated with the risk of hypertension.\u003c/p\u003e \u003cp\u003eTo better characterize the association between IH metrics and acute BP changes, we analyzed hypoxia-triggered BP surge profiles using continuous beat-to-beat monitoring based on the pulse transit time (PTT) method in a group of OSA patients. Hypoxia-related ODR was quantified using pulse oximetry signals recorded during overnight polysomnography (PSG). This study primarily aimed to evaluate the relationship between ODR and post-hypoxic BP surge metrics. Furthermore, we examined whether vascular hypoxic reactivity, defined as the ratio of BP surge parameters to ODR, was associated with an increased risk of hypertension.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy population\u003c/h2\u003e\n \u003cp\u003eAs shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, 297 patients were included in the study: 80 were normotensive, 127 had treated hypertension, and 90 had untreated hypertension. Of all participants, 83.2% were male, with a median age of 51.0 years and a median AHI of 52.8 events/h. A total of 95,518 IH events were analyzed. Hypertension, diabetes, and CHD were present in 73.1%, 43.4%, and 30.0%. of the patients, respectively. Significant group differences were observed in alcohol consumption (p\u0026thinsp;=\u0026thinsp;0.027) and CHD prevalence (p\u0026thinsp;=\u0026thinsp;0.036). In contrast, no statistically significant differences were found among groups in BMI, smoking status, or diabetes, nor in AHI, mean SpO₂, or T90. The normotensive group had a significantly higher median ODR (0.41 [0.29\u0026ndash;0.51] %/s) compared with the treated hypertension group (0.35 [0.24\u0026ndash;0.43] %/s) and the untreated hypertension group (0.35 [0.23\u0026ndash;0.47] %/s). The untreated hypertension group had the longest \u0026Delta;t (18.4 [16.8\u0026ndash;27.2] s, p\u0026thinsp;=\u0026thinsp;0.001), while event duration was longest in the treated hypertension group (16.7 [15.8\u0026ndash;18.3] s, p\u0026thinsp;=\u0026thinsp;0.012).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic, PSG, oxygen desaturation, BP variability characteristics.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNormotensive\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eTreated-hypertensive\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;127)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eUntreated-hypertensive\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;90)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e43.0 (34.3, 54.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e54.0 (47.0, 63.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e47.0 (34.0, 59.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e69 (86.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e102 (74.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e76 (84.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI, kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e30.6 (27.4, 33.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e30.0 (27.0, 33.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e31.2 (27.6, 34.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.351\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e18 (22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e30 (21.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e15 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.442\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol consumption, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e19 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e16 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e9 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.027*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHD, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e18 (22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e48 (35.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e23 (25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.036*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e32 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e58 (42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e39 (43.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.725\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eTST, hours\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e6.6 (5.6, 7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e7.0 (6.1, 7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e6.3 (5.5, 7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAHI, events/h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e57.2 (36.2, 74.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e50.8 (31.5, 64.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e52.1 (36.2, 67.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eODI, events/h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e48.3 (29.7, 68.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e46.8 (26.5, 61.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e46.3 (30.5, 63.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.294\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eT90, %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e18.9 (5.5, 45.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e17.8 (5.7, 41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e15.9 (6.3, 40.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.904\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean SpO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e, \u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e92.0 (89.0, 93.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e92.0 (89.0, 94.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e92.0 (90.0, 94.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eLowest SpO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e, \u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e72.0 (62.3, 80.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e74.0 (60.0, 78.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e73.0 (62.8, 79.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;t, s\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e17.4 (16.2, 19.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e17.7 (16.7, 19.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e18.4 (16.8, 27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;SpO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e, \u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e5.6 (4.7, 6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e5.7 (4.9, 6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e5.6 (4.8, 7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.245\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eEvent duration, s\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e16.2 (15.4, 16.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e16.7 (15.8, 18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e16.5 (15.8, 17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.012*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eODR, %/s\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.41 (0.29, 0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.35 (0.24, 0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.35 (0.23, 0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.012*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAwake SBP, mmHg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e125.1 (117.5, 132.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e129.0 (123.0, 134.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e145.0 (140.0, 150.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAwake DBP, mmHg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e79.3 (76.1, 84.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e80.0 (76.8, 82.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e89.0 (82.5, 95.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eNighttime SBP, mmHg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e124.0 (116.0, 133.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e126.0 (115.0, 134.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e131.0 (124.9, 141.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eNighttime DBP, mmHg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e80.0 (74.4, 83.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e79.0 (76.2, 82.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e80.0 (76.2, 84.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBP surge time, s\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e11.7 (10.6, 13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e12.1 (10.6, 14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e10.7 (8.5, 12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBP peak, mmHg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e122.4 (115.0, 133.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e122.3 (113.6, 134.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e125.1 (118.5, 135.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBP amplitude, mmHg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e15.0 (13.6, 18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e14.4 (13.0, 16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e15.0 (13.1, 17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.016*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBP surge rate, mmHg/s\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e1.7 (1.4, 2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.5 (1.3, 1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.6 (1.3, 1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003ePrimary outcomes\u003c/h3\u003e\n\u003cp\u003eAs shown in Fig. \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e, ODR was significantly positively correlated with BMI (r\u0026thinsp;=\u0026thinsp;0.283), AHI (r\u0026thinsp;=\u0026thinsp;0.344), and T90 (r\u0026thinsp;=\u0026thinsp;0.388), and significantly negatively correlated with mean SpO₂ (r =-0.372) and lowest SpO₂ (r =-0.346), while no significant correlation was found with event duration. In the adjusted linear regression model, ODR was significantly associated with increased BP amplitude (\u0026beta;\u0026thinsp;=\u0026thinsp;5.21, 95% CI: 2.90 to 7.52, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and BP surge rate (\u0026beta;\u0026thinsp;=\u0026thinsp;0.51, 95% CI: 0.22 to 0.80, p\u0026thinsp;=\u0026thinsp;0.001). Specifically, for every 1-unit increase in ODR, BP amplitude increased by 5.21 mmHg, and BP surge rate increased by 0.51 mmHg/s. However, no significant association was found between ODR and BP peak (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). A significant interaction effect between ODR and hypertension status on BP amplitude was observed (\u0026beta;\u0026thinsp;=\u0026thinsp;3.91, 95% CI: 1.39 to 6.44, p\u0026thinsp;=\u0026thinsp;0.002), as well as on BP surge rate (\u0026beta;\u0026thinsp;=\u0026thinsp;0.33, 95% CI: 0.01 to 0.64, p\u0026thinsp;=\u0026thinsp;0.045), suggesting that hypertension modifies the association between ODR and BP surges.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultiple linear regression analysis with BP surge parameters as dependent variables in the entire population.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\n \u003cp\u003eBP amplitude\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\n \u003cp\u003eBP peak\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e\n \u003cp\u003eBP surge rate\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\n \u003cp\u003eModel 1 (unadjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003eModel 2 (adjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\n \u003cp\u003eModel 1 (unadjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\n \u003cp\u003eModel 2 (adjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\n \u003cp\u003eModel 1 (unadjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\n \u003cp\u003eModel 2 (adjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eODR, %/s\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e8.69 (6.57, 10.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e5.21 (2.90, 7.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"−\" colname=\"c6\"\u003e\n \u003cp\u003e3.53 (-6.68, 13.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-6.20 (-17.93,5.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\n \u003cp\u003e1.01 (0.74, 1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\n \u003cp\u003e0.51 (0.22, 0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;t, s\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e-0.01 (-0.09, 0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.05 (-0.01, 0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"−\" colname=\"c6\"\u003e\n \u003cp\u003e-0.65 (-0.96, -0.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-0.71 (-1.03, -0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\n \u003cp\u003e-0.02 (-0.03, -0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\n \u003cp\u003e-0.01 (-0.02, 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;SpO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e, \u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.10 (-0.06, 0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e-0.00 (-0.14, 0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"−\" colname=\"c6\"\u003e\n \u003cp\u003e0.16 (-0.51, 0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-0.15 (-0.80, -0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\n \u003cp\u003e0.00 (-0.02, 0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\n \u003cp\u003e-0.01 (-0.02, 0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\n \u003cp\u003e0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eEvent duration, s\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e-0.04 (-0.18, 0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.05 (-0.07, 0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"−\" colname=\"c6\"\u003e\n \u003cp\u003e-0.41 (-1.01, 0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-0.35 (-0.95, 0.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\n \u003cp\u003e-0.01 (-0.03, 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\n \u003cp\u003e0.00 (-0.02, 0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\n \u003cp\u003e0.890\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e-0.73 (-1.70, 0.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.26 (-0.73, 1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"−\" colname=\"c6\"\u003e\n \u003cp\u003e3.09 (-1.12, 7.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e5.41 (0.55, 10.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\n \u003cp\u003e-0.19 (-0.31, -0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\n \u003cp\u003e-0.08 (-0.20, 0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\n \u003cp\u003e0.205\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eODR*hypertension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e2.73 (0.88, 4.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e3.91 (1.39, 6.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"−\" colname=\"c6\"\u003e\n \u003cp\u003e3.46 (-4.67, 11.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-12.10(-24.63,0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\n \u003cp\u003e0.14 (-0.10, 0.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\n \u003cp\u003e0.33 (0.01, 0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.045*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch3\u003eSensitivity Analyses\u003c/h3\u003e\n\u003cp\u003eIn sensitive analysis (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), ODR was positively associated with BP amplitude in normotensive (\u0026beta;\u0026thinsp;=\u0026thinsp;7.39, 95% CI: 2.60 to 12.19, p\u0026thinsp;=\u0026thinsp;0.003), treated hypertensive (\u0026beta;\u0026thinsp;=\u0026thinsp;5.14, 95% CI: 1.17 to 9.10, p\u0026thinsp;=\u0026thinsp;0.012), and untreated hypertensive patients (\u0026beta;\u0026thinsp;=\u0026thinsp;4.99, 95% CI: 0.76 to 9.21, p\u0026thinsp;=\u0026thinsp;0.021). Significant positive associations between ODR and BP surge rate were observed in normotensive (\u0026beta;\u0026thinsp;=\u0026thinsp;0.85, 95% CI: 0.28 to 1.43, p\u0026thinsp;=\u0026thinsp;0.004) and untreated hypertensive (\u0026beta;\u0026thinsp;=\u0026thinsp;0.69, 95% CI: 0.11 to 1.26, p\u0026thinsp;=\u0026thinsp;0.020), but not in treated hypertensive patients. \u0026Delta;t was negatively associated with BP peak in treated and untreated hypertensive groups, with no significant association in normotensives. In contrast, neither \u0026Delta;SpO₂ nor event duration showed a consistent correlation with BP surge parameters. In the stratified analysis, the association between ODR and BP surge rate was more stronger in younger individuals (\u0026lt;\u0026thinsp;60 years: \u0026beta;\u0026thinsp;=\u0026thinsp;0.60, 95% CI: 0.25 to 0.95, p\u0026thinsp;=\u0026thinsp;0.001) and those with more severe OSA (AHI\u0026thinsp;\u0026ge;\u0026thinsp;50 events/h: \u0026beta;\u0026thinsp;=\u0026thinsp;0.67, 95% CI: 0.23 to 1.11, p\u0026thinsp;=\u0026thinsp;0.003) (\u003cstrong\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003es1\u003c/span\u003e\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSensitivity analysis of BP surge parameters in hypertensive and normotensive populations.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\n \u003cp\u003eBP amplitude\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\n \u003cp\u003eBP peak\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e\n \u003cp\u003eBP surge rate\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\n \u003cp\u003eModel 1 (unadjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003eModel 2 (adjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\n \u003cp\u003eModel 1 (unadjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\n \u003cp\u003eModel 2 (adjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\n \u003cp\u003eModel 1 (unadjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\n \u003cp\u003eModel 2 (adjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e\u0026beta; (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormotensive patients (n\u0026thinsp;=\u0026thinsp;80)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eODR, %/s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e14.00 (10.02, 17.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e7.39 (2.60, 12.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e30.89 (11.17, 50.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e16.04 (-9.60, 41.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e1.74 (1.22, 2.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.85 (0.28, 1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026Delta;t, s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.08 (-0.27, 0.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.14 (-0.15, 0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e-1.01 (-2.41, 0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-0.42 (-1.90, 1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e-0.03 (-0.08, 0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e-0.03 (-0.07, 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026Delta;SpO\u003csub\u003e2\u003c/sub\u003e, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e-0.16 (-0.41, 0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.01 (-0.20, 0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e-0.65 (-1.67, 0.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-0.28 (-1.31, 0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e-0.03 (-0.07, -0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.034*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e-0.02 (-0.04, 0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEvent duration, s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e-0.10 (-0.50, 0.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.16 (-0.16, 0.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e-0.21 (-1.89, 1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.72 (-0.94, 2.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e-0.05 (-0.10, 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e-0.02 (-0.06, 0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreated-hypertensive patients (n\u0026thinsp;=\u0026thinsp;127)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eODR, %/s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e8.21 (4.49, 11.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e5.14 (1.17, 9.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.012*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e-7.62 (-27.45, 12.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-19.19 (-41.72, 3.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.59 (0.16, 1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.18 (-0.27, 0.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.431\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026Delta;t, s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e-0.02 (-0.14, 0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.02 (-0.08, 0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e-0.76 (-1.31, -0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-0.76 (-1.34, -0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.010*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e-0.01 (-0.02, 0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e-0.01 (-0.02, 0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026Delta;SpO\u003csub\u003e2\u003c/sub\u003e, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.28 (-0.03, 0.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.09 (-0.21, 0.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e-1.24 (-2.76, 0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-1.54 (-3.16, 0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.02 (-0.02, 0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e0.294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e-0.00 (-0.03, 0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEvent duration, s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.00 (-0.17, 0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.06 (-0.10, 0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e-0.47 (-1.31, 0.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-0.44 (-1.31, 0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e-0.01 (-0.03, 0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e0.428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e-0.00 (-0.02, 0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.718\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eUntreated-hypertensive patients (n\u0026thinsp;=\u0026thinsp;90)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eODR, %/s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e6.56 (2.90, 10.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e4.99 (0.76, 9.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.021*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.04 (-15.20, 15.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-2.68 (-21.42, 16.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.87 (0.38, 1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.69 (0.11, 1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.020*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026Delta;t, s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e-0.01 (-0.13, 0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.08 (-0.03, 0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e-0.82 (-1.25, -0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-0.69 (-1.14, -0.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e-0.02 (-0.03, -0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.026*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e-0.01 (-0.02, 0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.345\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026Delta;SpO\u003csub\u003e2\u003c/sub\u003e, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.19 (-0.08, 0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-0.06 (-0.32, 0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e1.14 (0.12, 2.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.030*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.79 (-0.33, 1.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.03 (-0.01, 0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.00 (-0.04, 0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.993\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEvent duration, s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e-0.03 (-0.32, 0.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.03 (-0.23, 0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e-0.47 (-1.62, 0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e-0.36 (-1.49, 0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.00 (-0.04, 0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e0.934\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.00 (-0.04, 0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.993\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch3\u003eExploratory analyses\u003c/h3\u003e\n\u003cp\u003eIn the binary logistic regression analysis (Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), vascular hypoxic reactivity, as represented by the BP surge metrics/ODR ratio, was positively associated with hypertension. Specifically, for each 1-unit increase in BP amplitude/ODR, the odds of developing hypertension increased by 2.3% (1.023 [95% CI: 1.005\u0026ndash;1.041], p\u0026thinsp;=\u0026thinsp;0.011). Similarly, each unit increase in BP peak/ODR was associated with a 0.2% increased likelihood of hypertension (1.002 [ 95% CI: 1.000-1.004], p\u0026thinsp;=\u0026thinsp;0.015). Furthermore, the odds of hypertension increased by 14.1% for every unit increase in BP surge rate/ODR (1.141 [95% CI: 1.001\u0026ndash;1.299], p\u0026thinsp;=\u0026thinsp;0.048).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBinary logistic regression analysis with hypertension status as a dependent variable.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eIndependent variables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\n \u003cp\u003eModel 1 (unadjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003eModel 2 (adjusted)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAHI, events/h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.991 (0.980, 1.002)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.997 (0.983, 1.011)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.626\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eT90, %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.999 (0.988, 1.010)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.998 (0.984, 1.012)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.811\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBP amplitude/ODR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e1.021 (1.007, 1.036)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.023 (1.005, 1.041)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.011*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBP peak/ODR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e1.002 (1.001, 1.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.002 (1.000, 1.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.015*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBP surge rate/ODR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e1.124 (1.011, 1.249)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.031*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.141 (1.001,1.299)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.048\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable s2\u003c/strong\u003e compared BP parameters among patients taking different antihypertensive medications. The calcium channel blockers (CCBs) group had a significantly lower BP surge rate (1.43 mmHg/s), BP amplitude (13.73 mmHg) and BP peak (120.62 mmHg) compared to both the angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (ACEIs/ARBs) group (1.55 mmHg/s, 14.82 mmHg, 122.77 mmHg) and the CCBs\u0026thinsp;+\u0026thinsp;ACEIs/ARBs group (1.60 mmHg/s, 14.87 mmHg, 129.73 mmHg), with overall p-values of 0.043, 0.019 and 0.048, respectively. No significant differences were found in other BP parameters, including average BP and BP rise time.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we developed a novel PSG-derived IH metric, the ODR, which showed a significant independent association with post-hypoxic BP variations in the OSA population. This association was more significant among younger patients and those with more severe OSA. Importantly, hypertension significantly modified the association between ODR and BP surges, with hypertensive individuals showing amplified BP responses to comparable ODR levels. Furthermore, the ratio of BP surge metrics to ODR, a surrogate marker of hypoxia-induced vasoconstriction, was significantly associated with the risk of hypertension. Exploratory analyses suggested that CCBs were more effective than ACE inhibitors or ARBs in attenuating post-hypoxic BP elevations, highlighting their potential advantage in managing nocturnal BP variability in OSA.\u003c/p\u003e \u003cp\u003eODR is the rate of decrease in pulse oxygen saturation during a respiratory event, serving as an indicator of oxygen storage and metabolic oxygen consumption\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Our study found a significant positive correlation between ODR and T90, and a negative correlation with mean SpO₂, indicating that a high ODR, reflecting rapid depletion of alveolar oxygen reserves, significantly worsens nocturnal hypoxia severity. Theoretically, lung volume and metabolic rate are key determinants of desaturation rate. Obesity reduces functional residual capacity and expiratory reserve volume\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, thus lowering pulmonary oxygen reserves and accelerating oxygen depletion during apnea episodes. Furthermore, obesity impairs the ventilation-perfusion ratio\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e, contributing to small airway closure\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e, V/Q mismatch, all of which further accelerate oxygen desaturation. Together, these may likely explain the positive correlation observed between BMI and ODR. Moreover, recurrent apneic events have been shown to induce desaturation rates approximately twice those observed in isolated apneas\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Consistent with this, our findings indicate that higher AHI is significantly correlated with increased ODR levels. However, no significant correlation was found between ODR and event duration, a finding consistent with Strohl et al\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. who demonstrated that the rate of change in arterial oxygen saturation during conscious breath holding is independent of breath-hold duration. Therefore, a high ODR may serve as a comprehensive marker of hypoxia, reflecting multiple pathological features, including recurrent airway obstruction, increased obesity, and diminished pulmonary oxygen reserve, which predispose individuals to more severe oxygen desaturation during sleep.\u003c/p\u003e \u003cp\u003eWe observed a significant association between the ODR and BP surges during obstructive respiratory events. Additionally, a significant positive interaction between ODR and hypertension was identified, indicating that individuals with hypertension may exhibit an exaggerated hemodynamic response to rapid oxygen desaturation. To better characterize individual variability in vascular reactivity to hypoxia, we proposed a novel metric: the ratio of BP surge to ODR. This parameter normalizes the magnitude of the BP response relative to the severity of oxygen desaturation, serving as a surrogate index of hypoxia-induced vasoconstrictive sensitivity. Notably, higher BP surge/ODR values were consistently and significantly associated with the presence of hypertension.\u003c/p\u003e \u003cp\u003eMechanistically, this phenomenon may be attributed to pathophysiological changes associated with chronic hypertension, including vascular remodeling\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e, increased arterial stiffness\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e in this population. These vascular abnormalities may lower the threshold for pressor responses\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e, thereby contributing to an exaggerated vasoconstrictive response to transient hypoxia. Additionally, sympathetic nervous system overactivity\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e, which is elevated in both OSA and hypertension, is further potentiated by hypoxia-induced chemoreflex sensitivity, particularly through the carotid body\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. This chemosensory hyperresponsiveness triggers excessive catecholamine release\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e, leading to vasoconstriction mediated by α- and/or β-adrenergic receptors\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e, which may promote large transient BP surges during hypopnea or apnea termination. Moreover, in OSA patients with normal endothelial function, the endothelial nitric oxide synthase/nitric oxide (eNOS/NO) pathway counteracts the pressor effect of sympathetic nervous system and contributes to BP homeostasis\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. However, in hypertensive OSA patients, endothelial dysfunction may impair the eNOS/NO pathway\u003csup\u003e[\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e, thereby diminishing vascular buffering capacity in response to hypoxia and facilitating abrupt increases in BP.\u003c/p\u003e \u003cp\u003eIn stratified analyses, the association between ODR and post-hypoxic BP responses was stronger in younger individuals. These findings suggest that age influences cardiovascular responses to hypoxia. Younger individuals appear more sensitive, likely due to greater sympathetic vascular transduction, a key mechanism in beat-to-beat BP regulation\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. With aging, this transduction becomes less effective, leading to attenuated pressor and vasoconstrictor responses[\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e], which may reflect a protective adaptation against excessive BP fluctuations in older adults. Therefore, exaggerated vascular responses may represent a pathophysiological mechanism contributing to elevated cardiovascular risk. Characterizing individual vascular reactivity profiles could enhance risk stratification and support more personalized management strategies in patients with OSA.\u003c/p\u003e \u003cp\u003eThe effect of CCBs on BPV has been widely studied, including on long-term and short-term variability. For example, Frattola et al. reported that the long-acting CCB lacidipine significantly reduced the variation coefficient of 24-hour beat-to-beat BP in patients with type II diabetes and hypertension\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. In hypertensive rat models, the CCB nitrendipine was more effective than hydralazine in reducing long-term BPV and end-organ damage\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e. Analysis of two large-scale clinical studies showed that the CCB amlodipine had greater efficacy than β-blockers in stabilizing visit-to-visit BP variability and lowering the incidence of stroke\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. In this study, we compared the effects of different classes of antihypertensive agents on acute BP fluctuations induced by respiratory events and found that CCBs more effectively reduced post-hypoxic BP elevations than ACEIs or ARBs, indicating that CCBs may offer greater benefits in stabilizing both long-term BPV and acute post-hypoxic BP surges.\u003c/p\u003e \u003cp\u003eOur study presents several important strengths. Notably, we applied the concept of the ODR as a novel event-based hypoxic marker. Unlike conventional desaturation indices, ODR specifically characterizes the rate of oxygen desaturation during individual respiratory events, thereby capturing the dynamic and transient hypoxic stress experienced by OSA. By utilizing this event-specific parameter, our study enabled a more precise characterization of the association between hypoxia and acute BP responses, which may be inadequately represented by traditional indices.\u003c/p\u003e \u003cp\u003eHowever, our study has several limitations. First, the relatively small sample size may limit generalizability, and larger studies in diverse populations are needed to validate these findings. Second, an observational study design prevents causal inferences and may be subject to residual confounding despite adjustment. Finally, Given the limited information about β-blocker or diuretic monotherapy, our analysis only focused on the effect of exclusively CCBs and ACEIs/ARBs on hypoxia-induced BP oscillations.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides evidence that ODR during obstructive respiratory events is closely associated with post-hypoxic BP surges. Importantly, hypertension significantly amplifies this relationship, with hypertensive individuals exhibiting greater BP surges at similar ODR levels. Furthermore, vascular hypoxic reactivity, measured by the ratio of BP surge to ODR, was significantly correlated with an increased risk of developing hypertension.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween January 2024 and April 2025, patients who underwent overnight PSG at the Sleep Medicine Center of the Affiliated Huaian No. 1 People\u0026rsquo;s Hospital of Nanjing Medical University were recruited. A detailed questionnaire was designed to evaluate daily BP, comorbidities, medications, smoking and alcohol consumption, clinical history, and anthropometric measurements. Inclusion criteria were: 1) newly diagnosed OSA (apnea-hypopnea index [AHI] \u0026ge; 15 events/h); and 2) age between 18 and 75 years. Exclusion criteria were: 1) comorbid conditions causing nocturnal hypoxia (e.g., heart failure, chronic obstructive pulmonary disease); 2) history of other sleep disorders; 3) refusal to participate; and 4) inadequate study data. A total of 297 individuals were included in the final analysis. The study protocol was approved by the Huaian First People\u0026rsquo;s Hospital Medical Ethics Committee and conducted in accordance with the Declaration of Helsinki (YX-Z-2022-028-01), with all participants providing written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSleep study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll patients underwent full-night PSG (SOMNOscreen Plus, SOMNOmedics, Germany) in the sleep laboratory. Recorded signals included electroencephalography, bilateral electrooculograms, chin electromyography, electrocardiogram, nasal pressure, thermistor-based airflow, thoracic and abdominal inductance plethysmography, and fingertip pulse oximetry. Sleep data were scored using standardized protocols\u003csup\u003e[\u003c/sup\u003e\u003csup\u003e38\u003c/sup\u003e\u003csup\u003e]\u003c/sup\u003e. Apnea was defined as a complete cessation of airflow lasting \u0026ge; 10 seconds. Hypopnea was defined as a \u0026ge; 50% reduction in nasal pressure amplitude, accompanied by either \u0026ge; 3% oxygen desaturation or arousal. AHI was calculated as the number of apneas and hypopneas per hour of sleep, with AHI \u0026gt; 15 events/h used to define OSA\u003csup\u003e[\u003c/sup\u003e\u003csup\u003e39,40\u003c/sup\u003e\u003csup\u003e]\u003c/sup\u003e. T90 was defined as the percentage of total sleep time spent with SpO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003e\u0026lt; 90%. The oxygen desaturation index (ODI) was calculated as the number of \u0026ge; 3% desaturation events per hour.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDefinition of IH parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe occurrence of apnea or hypopnea depletes the body\u0026apos;s oxygen reserves, leading to a drop in SpO₂.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eFor each oxygen desaturation event, the following IH parameters were calculated: 1) \u0026Delta;t, defined as the time from the onset of oxygen desaturation to the SpO₂\u0026nbsp;nadir; 2) \u0026Delta;SpO\u003csub\u003e2\u003c/sub\u003e, the magnitude of oxygen desaturation from the initial drop to the nadir; 3) event duration, defined as the length of apneas or hypopneas; and 4) ODR, calculated as the ratio of \u0026Delta;SpO\u003csub\u003e2\u003c/sub\u003e to \u0026Delta;t, representing the rate of oxygen desaturation per second (\u003cstrong\u003eFig. 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBP measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCuff BP was measured in the seated position using conventional mercury sphygmomanometry. Hypertension was defined as a systolic BP \u0026ge; 140 mmHg and/or diastolic BP \u0026ge; 90 mmHg, or current use of antihypertensive medication\u003csup\u003e[\u003c/sup\u003e\u003csup\u003e41\u003c/sup\u003e\u003csup\u003e]\u003c/sup\u003e.\u0026nbsp;Beat-to-beat BP was continuously monitored using a PTT-based method synchronized with PSG (SOMNOscreen plus PSG+), as previously described\u003csup\u003e[\u003c/sup\u003e\u003csup\u003e11\u003c/sup\u003e\u003csup\u003e]\u003c/sup\u003e. In brief, PTT was defined as the time interval between the ECG R-wave and the arrival of the pulse wave at the fingertip detected by photoplethysmography. Systolic, diastolic, and mean BP values were then automatically calculated using the DOMINO Light software. For each respiratory event, the following BP response metrics were calculated: 1) BP peak, defined as the maximum systolic BP during the post-hypoxic rise; 2) BP amplitude, calculated as the difference between baseline and peak systolic BP; and 3) BP surge rate, representing the rate of systolic BP increase (mmHg/s) during the ascending phase (\u003cstrong\u003eFig. 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContinuous variables were presented as median (interquartile range [IQR]) and categorical variables as number (percentage). Group comparisons were performed using the Kruskal\u0026ndash;Wallis test or the chi-square test. Pearson or Spearman correlation analyses were used to assess associations between ODR and relevant clinical parameters. Multiple linear regression models were used to assess the associations between IH parameters (ODR, \u0026Delta;t, \u0026Delta;SpO₂, event duration) and post-hypoxic BP surge indices (amplitude, peak, surge rate), using the enter method. Model 1 was unadjusted; Model 2 adjusted for age, gender, body mass index (BMI), smoking, alcohol consumption, AHI, T90, total sleep time (TST), history of hypertension, diabetes, coronary heart disease (CHD), and antihypertensive medication. Interaction terms were included in the model to assess whether hypertension status modified the association between ODR and BP.\u003c/p\u003e\n\u003cp\u003eSensitivity analyses were conducted in normotensive and hypertensive subgroups using the same models described previously. Additionally, stratified analyses by age, AHI, and BMI were performed to examine population-specific differences. In exploratory analyses, binary logistic regression was used to assess the association between vascular hypoxic reactivity, as represented by the BP surge metrics/ODR ratio, and hypertension. The effects of antihypertensive medications on post-hypoxic BP surges were also assessed. All statistical analyses were performed using SPSS version 29.0 (IBM Corp., Armonk, NY, USA), with a two-sided p-value \u0026lt; 0.05 considered statistically significant.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request, [email protected].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all individuals who agreed to participate in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYanli Gu and Yujiao Wan:\u003c/strong\u003e Conceptualization, Methodology, Investigation, Formal Analysis, Writing - Original Draft, Writing - Review \u0026amp; Editing. \u003cstrong\u003eJiani Shen and Yujie Yuan:\u003c/strong\u003e Methodology, Validation,\u0026nbsp;Visualization. \u003cstrong\u003eQiyun Ma:\u0026nbsp;\u003c/strong\u003eResources, Software\u003cstrong\u003e. Guihong Wei:\u0026nbsp;\u003c/strong\u003eFormal analysis, Project administration\u003cstrong\u003e. Xiaochen Xie:\u003c/strong\u003e Data Curation, Resources.\u003cstrong\u003e\u0026nbsp;Fengjuan Xu:\u003c/strong\u003e Software, Visualization.\u003cstrong\u003e\u0026nbsp;Xiaoxiao Han:\u003c/strong\u003e Supervision, Data Curation. \u003cstrong\u003eJing Xu:\u003c/strong\u003e Supervision, Project Management, Supervision, Writing - Review \u0026amp; Editing, Funding acquisition. All authors have given final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive any funding to assist with the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Committee of Huai\u0026rsquo;an No.1 People\u0026rsquo;s Hospital and was conducted following the Helsinki Declaration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSheikh, A. 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(2017).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Obstructive sleep apnea, Oxygen desaturation rate, Blood pressure surge, Hypertension","lastPublishedDoi":"10.21203/rs.3.rs-8841930/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8841930/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo investigate the association between respiratory event-specific oxygen desaturation rate (ODR) and blood pressure (BP) surges in patients with obstructive sleep apnea (OSA). Oxygen desaturation events caused by apnea and hypopnea were analyzed to quantify ODR, representing the rate of oxygen consumption. Beat-to-beat systolic blood pressure was recorded using a pulse transit time (PTT)-based technique synchronized with PSG, and post-hypoxic BP responses (peak, amplitude, surge rate) were extracted. Vascular hypoxic reactivity was defined as the ratio of BP response to ODR. A total of 95,518 respiratory events from 297 patients were analyzed. In adjusted linear models, higher ODR was significantly associated with increased BP amplitude (β\u0026thinsp;=\u0026thinsp;5.21, 95% CI: 2.90\u0026ndash;7.52, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and BP surge rate (β\u0026thinsp;=\u0026thinsp;0.51, 95% CI: 0.22\u0026ndash;0.80, p\u0026thinsp;=\u0026thinsp;0.001), but not with BP peak. A significant interaction between ODR and hypertension status was observed for both BP amplitude and surge rate. For each unit increase in BP amplitude/ODR, BP peak/ODR, and BP surge rate/ODR, the odds of hypertension increased by 2.3%, 0.2%, and 14.1%, respectively. ODR showed an independent relationship with post-hypoxic BP surge in OSA patients. The ratio of BP surges to ODR, reflecting vascular hypoxic reactivity, was associated with hypertension.\u003c/p\u003e","manuscriptTitle":"Association Between Respiratory Event-Specific Oxygen Desaturation Rate and Blood Pressure Surge in Obstructive Sleep Apnea","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-24 16:53:48","doi":"10.21203/rs.3.rs-8841930/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-06T08:46:47+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-01T09:18:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"77840946658841824319917415450934418822","date":"2026-03-22T08:48:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-20T03:34:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"271119803745718925357129341382232282971","date":"2026-03-19T23:19:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-19T14:27:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-19T14:20:35+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-17T13:09:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-16T08:59:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-02-16T08:55:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2b5d64ab-17ac-48fb-ad63-fca4305c8599","owner":[],"postedDate":"March 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":64915087,"name":"Health sciences/Cardiology"},{"id":64915088,"name":"Health sciences/Diseases"},{"id":64915089,"name":"Health sciences/Medical research"},{"id":64915090,"name":"Biological sciences/Physiology"}],"tags":[],"updatedAt":"2026-05-05T10:02:32+00:00","versionOfRecord":{"articleIdentity":"rs-8841930","link":"https://doi.org/10.1038/s41598-026-51395-0","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-05-03 15:58:39","publishedOnDateReadable":"May 3rd, 2026"},"versionCreatedAt":"2026-03-24 16:53:48","video":"","vorDoi":"10.1038/s41598-026-51395-0","vorDoiUrl":"https://doi.org/10.1038/s41598-026-51395-0","workflowStages":[]},"version":"v1","identity":"rs-8841930","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8841930","identity":"rs-8841930","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}