Abstract P112: Orthostatic Hypotension, Orthostatic Hypertension And Ambulatory Blood Pressure In Patients With Chronic Kidney Disease: Findings From The Chronic Renal Insufficiency Cohort Study

Background: We recently demonstrated how orthostatic hypotension might be used to identify out-of-office blood pressure phenotypes, including white coat effects and nocturnal non-dipping patterns. However, these findings have not been replicated in a population with chronic kidney disease (CKD). Objective: To examine the association between orthostatic hypotension (OH) or hypertension (OHTN) with ambulatory BP in adults with CKD. Methods: CRIC is a prospective multicenter observation cohort study of participants with CKD. Standing BP at 1 minute and ABPM were obtained on 1467 participants. OH was defined as a 20mmHg drop in systolic BP (SBP) or 10 mmHg drop in diastolic BP (DBP) when changing from seated to standing positions. OHTN was defined as a 20 mmHg or 10mmHg rise in SBP or DBP respectively when changing from seated to standing position. White coat effects, based on ABPM, was defined as the difference between seated clinic and ambulatory BP. Systolic and diastolic night to day ratio was also calculated. Results: Of the 1467 participants (age: 58 ± 10 yrs, 44% female, 39% black) 73 had OH and 165 had OHTN). OH was positively associated with systolic and diastolic white coat effect (β=5.9 [0.9, 10.9] and 4.2 [1.3, 7.1]). OHTN was negatively associated with diastolic white coat effect (-4.9 [-6.9, -3]). OH was positively associated with systolic and diastolic night-to-day ratio (0.03 [0.01, 0.05] and 0.03 [0.01, 0.06] respectively). Conclusions: Clinic-based assessments of OH and OHTN may be useful for identifying BP phenotypes often missed with seated office BP measurements in CKD patients.

Examining the effectiveness of telemonitoring with routinely acquired blood pressure data in primary care: challenges in the statistical analysis

Background Scale-up BP was a quasi-experimental implementation study, following a successful randomised controlled trial of the roll-out of telemonitoring in primary care across Lothian, Scotland. Our primary objective was to assess the effect of telemonitoring on blood pressure (BP) control using routinely collected data. Telemonitored systolic and diastolic BP were compared with surgery BP measurements from patients not using telemonitoring (comparator patients). The statistical analysis and interpretation of findings was challenging due to the broad range of biases potentially influencing the results, including differences in the frequency of readings, ‘white coat effect’, end digit preference, and missing data. Methods Four different statistical methods were employed in order to minimise the impact of these biases on the comparison between telemonitoring and comparator groups. These methods were “standardisation with stratification”, “standardisation with matching”, “regression adjustment for propensity score” and “random coefficient modelling”. The first three methods standardised the groups so that all participants provided exactly two measurements at baseline and 6–12 months follow-up prior to analysis. The fourth analysis used linear mixed modelling based on all available data. Results The standardisation with stratification analysis showed a significantly lower systolic BP in telemonitoring patients at 6–12 months follow-up (-4.06, 95% CI -6.30 to -1.82, p < 0.001) for patients with systolic BP below 135 at baseline. For the standardisation with matching and regression adjustment for propensity score analyses, systolic BP was significantly lower overall (− 5.96, 95% CI -8.36 to − 3.55 , p < 0.001) and (− 3.73, 95% CI− 5.34 to − 2.13, p < 0.001) respectively, even after assuming that − 5 of the difference was due to ‘white coat effect’. For the random coefficient modelling, the improvement in systolic BP was estimated to be -3.37 (95% CI -5.41 to -1.33 , p < 0.001) after 1 year. Conclusions The four analyses provide additional evidence for the effectiveness of telemonitoring in controlling BP in routine primary care. The random coefficient analysis is particularly recommended due to its ability to utilise all available data. However, adjusting for the complex array of biases was difficult. Researchers should appreciate the potential for bias in implementation studies and seek to acquire a detailed understanding of the study context in order to design appropriate analytical approaches.

Impact of Sex on Office White Coat Effect Tail: A Review

Office white-coat effect tail (OWCET) is defined as a decrease of ≥10 mmHg in systolic blood pressure (SBP) between successive measurements after its waxing during an office visit. The influence of sex on the incidence of long-term major fatal and non-fatal cardiovascular events was studied in two Italian populational cohorts [from the Gubbio Study and the Italian Rural Areas of the Seven Countries Study (IRA)]. OWCET increased risk of cardiovascular disease (CVD) [HR: 1.591 (95%CI: 1.204-2.103)], coronary heart disease (CHD) [HR: 1.614 (95%CI: 1.037-2.512)] and stroke (STR) [HR: 1.696 (95%CI: 1.123-2.563)] events independently of age, serum and high density lipoprotein (HDL) cholesterol, cigarettes, body mass index (BMI) and SBP in women included in Gubbio study over an almost 20-year follow-up. However, risks of CVD, CHD or STR increased in men with OWCET neither in the Gubbio 20-year follow-up nor in the IRA 50-year follow-up. The correction of the regression dilutions bias between the first and the subsequent SBP measurements did not significantly change these outcomes. Primary care physicians should evaluate OWCET, especially in women, to improve stratification of long-term CVD, CHD and STR risks.

Examining the effectiveness of telemonitoring with routinely acquired blood pressure data in primary care: challenges in the statistical analysis

Background Scale-up BP was a quasi-experimental implementation study, following a successful randomised controlled trial of the roll-out of telemonitoring in primary care across Lothian, Scotland. Our primary objective was to assess the effect of telemonitoring on blood pressure (BP) control using routinely collected data. Telemonitored systolic and diastolic BP were compared with surgery BP measurements from patients not using telemonitoring (comparator patients). The statistical analysis and interpretation of findings was challenging due to the broad range of biases potentially influencing the results, including differences in the frequency of readings, ‘white coat effect’, end digit preference, and missing data. Methods Four different statistical methods were employed in order to minimise the impact of these biases on the comparison between telemonitoring and comparator groups. These methods were “standardisation with stratification”, “standardisation with matching”, “regression adjustment for propensity score” and “random coefficient modelling”. The first three methods standardised the groups so that all participants provided exactly two measurements at baseline and 6-12 months follow-up prior to analysis. . The fourth analysis used linear mixed modelling based on all available data. Results The standardisation with stratification analysis showed a significantly lower systolic BP in telemonitoring patients at 6-12 months follow-up (-3.42, 95% CI -1.72 to -5.11, p<0.001). For the standardisation with matching and regression adjustment for propensity score analyses systolic BP was also significantly lower (-5.96, 95% CI -3.55 to -8.36, p<0.001) and (-3.73, -5.34 to -2.13, p<0.001) respectively, even after assuming that -5 of the difference was due to ‘white coat effect’. For the random coefficient modelling, the improvement in systolic BP was estimated to be -4.68 (95% CI -3.12 to -6.24, p<0.001) after one year.Conclusions The four analyses provide additional evidence for the effectiveness of telemonitoring in controlling BP in routine primary care. The random coefficient analysis is particularly recommended due to its ability to utilise all available data. However, adjusting for the complex array of biases was difficult. Researchers should appreciate the potential for bias in implementation studies and seek to acquire a detailed understanding of the study context in order to design appropriate analytical approaches.

Haemodynamic characteristics and blood pressure evolution of hypertension subtypes in young to middle age adults

Aim The prognostic significance of different hypertension subtypes in young hypertensives, in particular of isolated systolic hypertensives (ISHs) is still debated. The aim of the present study was to investigate clinical and haemodynamic characteristics and blood pressure (BP) evolution of different hypertension subtypes in young stage I hypertensives. Methods We investigated 1206 young subjects from the HARVEST study: 81 normotensives (NTs), 146 ISHs, 281 isolated diastolic hypertensives (IDHs) and 698 systolic-diastolic hypertensives (SDHs) according to office BP values at baseline. Data on baseline haemodynamic and metabolic characteristics, BP and heart rate changes during follow-up (mean 7 years) were collected. ANCOVA analysis was used for all comparisons adjusting for age and sex. Results Males were more frequent among ISHs (90.4%) compared to other categories (70.4, 67.3, 71.5% among NTs, IDHs, SHDs). Moreover, ISHs were younger compared to the others (25.6±6.6 years, p&lt;0.001) and thinner compared to SDHs (24.6±.2.6 vs 25.8±3.6 kg/m2, p=0.028). Heart rate was higher among ISHs (75.7±9.4 bpm) and SDHs (75.8±9.7) compared to other categories (p&lt;0.001). Metabolic characteristics were not significantly different among groups. ISHs were more active in sports (55.5%) and drank less alcohol compared to others (p&lt;0.001, p=0.05 respectively). Systolic white coat effect was higher among ISH (17.6±12.4 mmHg) compared to others (p&lt;0.001), as was cardiac output ISH (6.3±1.2 ml/min) compared to NTs and IDHs (p&lt;0.001); Peripheral resistances were similar in ISHs and NTs and were lower than in IDHs and SDHs (p&lt;0.001). Small and large artery compliance was higher, central systolic BP and augmentation index were lower among NTs and ISHs compared to IDHs and SDHs, even if these differences were not statistically significant. During follow-up systolic BP decreased (−7.6±14.4 mmHg) among ISHs, while it increased among NTs and IDHs (p&lt;0.001). Heart rate decreased in all categories but to a higher extent among ISHs (−3.8±10.9 bpm) and SDHs (−3.4±10.8 bpm) (p=0.002 vs others). Changes in diastolic BP were similar among ISHs and NTs and higher than those observed among IDHs and SDHs (p&lt;0.001). The percent of patients who started pharmacological treatment during follow-up was 70.6% among SDHs, 54.1% among IDHs, 41.1% among ISHs, and 39.5% among NTs (p&lt;0.001). Conclusions ISHs had increased cardiac output and white coat effect and lower peripheral resistances compared to other hypertension subtypes while distensibility parameters did not differ significantly among groups. The percent of patients who developed hypertension needing treatment was lower among ISHs than other hypertensives. This was due to a favourable time course of BP during follow-up. Longer follow-ups are needed to confirm the lower risk profile of ISH of the young Funding Acknowledgement Type of funding source: None

Effects of Intensive Versus Standard Office-Based Hypertension Treatment Strategy on White-Coat Effect and Masked Uncontrolled Hypertension

Guidelines recommend using out-of-office blood pressure (BP) measurements to confirm the diagnoses of hypertension and in the titration of antihypertensive medication. The prevalence of out-of-office BP phenotypes for an office systolic/diastolic BP goal <140/90 mm Hg has been reported. However, the prevalence of these phenotypes when targeting an office systolic/diastolic BP goal <120/80 is unknown. The SPRINT (Systolic Blood Pressure Intervention Trial) Ambulatory BP Ancillary study evaluated out-of-office BP using ambulatory BP monitoring in 897 participants 27 months after randomization to intensive versus standard BP targets (office systolic BP <120 versus <140 mm Hg). We used office and daytime BP to assess the proportion of participants with white-coat effect (standard target: office BP ≥140/90 mm Hg and daytime BP <135/85 mm Hg versus intensive target: office BP ≥120/80 mm Hg and daytime BP <120/80 mm Hg) and masked uncontrolled hypertension (standard target: office BP <140/90 mm Hg and daytime BP ≥135/85 mm Hg versus intensive target: office BP <120/80 mm Hg and daytime BP ≥120/80 mm Hg) in each treatment arm. The prevalence of white-coat effect and masked uncontrolled hypertension was 9% and 34%, in both treatment groups. Among participants with uncontrolled office BP, white-coat effect was present in 20% and 23% in the intensive and standard groups, respectively. Among participants with controlled office BP, masked uncontrolled hypertension was present in 62% and 56% in the intensive and standard groups, respectively. In conclusion, a more intensive BP target resulted in a similar proportion of patients with white-coat effect and masked uncontrolled hypertension compared with a standard target.

Examining the Effectiveness of Telemonitoring with Routinely Acquired Blood Pressure Data in Primary Care: Challenges in the Statistical Analysis

BackgroundScale-up BP was a quasi-experimental implementation study, following a successful randomised controlled trial of the roll-out of telemonitoring in primary care across Lothian, Scotland. Our primary objective was to assess the effect of telemonitoring on blood pressure (BP) control using routinely collected data. Telemonitored systolic and diastolic BP were compared with surgery BP measurements from patients not using telemonitoring (comparator patients). The statistical analysis and interpretation of findings was challenging due to the broad range of biases potentially influencing the results, including differences in the frequency of readings, ‘white coat effect’, end digit preference, and missing data.MethodsThree different statistical methods were employed in order to minimise the impact of these biases on the comparison between telemonitoring and comparator groups. These methods were “standardisation with stratification”, “standardisation with matching”, and “random coefficient modelling”. The first two methods standardised the groups so that all participants provided exactly two measurements at baseline and 6-12 months follow-up before using stratification or matched cohort analysis to compare the groups. The third analysis used linear mixed modelling based on all available data. ResultsThe standardisation with stratification analysis showed a significantly lower systolic BP in telemonitoring patients at 6-12 months follow-up (-3.42, 95% CI -1.72 to -5.11, p<0.001). For the standardisation with matching analysis, systolic BP was also significantly lower (-5.96, 95% CI -3.55 to -8.36, p<0.001), even after assuming that -5 of the difference was due to ‘white coat effect’. For the random coefficient modelling, the improvement in systolic BP was estimated to be -4.68 (95% CI -3.12 to -6.24, p<0.001) after one year. ConclusionsThe three analyses provide additional evidence for the effectiveness of telemonitoring in controlling BP in routine primary care. However, adjusting for the complex array of biases was difficult. Researchers should appreciate the potential for bias in implementation studies and seek to acquire a detailed understanding of the study context in order to design appropriate analytical approaches.