Abstract
Background:
Accurate blood pressure (BP) measurement is critical in patients with chronic kidney disease (CKD) due to its strong association with cardiovascular morbidity and progression of renal dysfunction. While ambulatory BP monitoring (ABPM) is considered the gold standard, it is often impractical in routine settings. This study compares manual office BP (MOBP), automated office BP (AOBP), and ABPM to evaluate diagnostic accuracy and clinical utility in CKD patients.
Materials and Methods:
This cross-sectional observational study was conducted in 120 patients with established CKD. BP measurements were recorded using MOBP, AOBP, and ABPM over a 24-h period. Comparative analysis was performed for systolic and diastolic BP values, uncontrolled hypertension, and identification of phenotypes such as white-coat hypertension (WCH) and masked hypertension (MHT). Statistical significance was evaluated using paired t-tests and ROC curve analysis.
Results:
Mean systolic and diastolic BP values were significantly higher with MOBP (131.55 ± 16.88/87.42 ± 10.56 mmHg) compared to ABPM (130.11 ± 17.60/84.35 ± 10.81 mmHg, P < 0.05). AOBP values closely matched ABPM (130.45 ± 17.53/84.63 ± 10.80 mmHg, P > 0.4). Uncontrolled hypertension was noted in 30.8% (MOBP, AOBP) and 27.5% (ABPM). WCH and MHT were identified in 6.5% and 3.5% of patients, respectively. AOBP demonstrated high sensitivity (95.8%) and specificity (94.4%) relative to ABPM.
Conclusion:
AOBP closely approximates ABPM and can be considered a reliable alternative for BP evaluation in CKD patients, particularly in resource-limited settings. MOBP significantly overestimates BP and may lead to diagnostic misclassification.
Keywords: Ambulatory blood pressure monitoring, automated office blood pressure, chronic kidney disease, masked hypertension, white-coat hypertension
Résumé
Contexte:
La mesure précise de la pression artérielle (PA) est essentielle chez les patients atteints de maladie rénale chronique (MRC) en raison de sa forte association avec la morbidité cardiovasculaire et la progression de la dysfonction rénale. Bien que la mesure ambulatoire de la PA (MAPA) soit considérée comme la référence absolue, elle est souvent peu pratique en routine clinique. Cette étude compare la mesure manuelle au cabinet (MOBP), la mesure automatisée au cabinet (AOBP) et la MAPA afin d’évaluer leur précision diagnostique et leur utilité clinique chez les patients atteints de MRC.
Matériels et Méthodes:
Cette étude observationnelle transversale a inclus 120 patients atteints de MRC confirmée. Les mesures de la PA ont été effectuées à l’aide de MOBP, AOBP et MAPA sur 24 heures. Une analyse comparative a été réalisée pour les valeurs systoliques et diastoliques, l’hypertension non contrôlée et l’identification des phénotypes tels que l’hypertension blouse blanche (HBB) et l’hypertension masquée (MHT). La signification statistique a été évaluée par test t apparié et analyse ROC.
Résultats:
Les valeurs moyennes de PA systolique et diastolique étaient significativement plus élevées avec MOBP (131,55 ± 16,88 / 87,42 ± 10,56 mmHg) qu’avec MAPA (130,11 ± 17,60 / 84,35 ± 10,81 mmHg, P< 0,05). Les valeurs AOBP correspondaient étroitement à celles de la MAPA (130,45 ± 17,53 / 84,63 ± 10,80 mmHg, P > 0,4). Une hypertension non contrôlée a été observée chez 30,8 % (MOBP, AOBP) et 27,5 % (MAPA). L’HBB et la MHT ont été identifiées respectivement chez 6,5 % et 3,5 % des patients. L’AOBP a montré une sensibilité (95,8 %) et une spécificité (94,4 %) élevées par rapport à la MAPA.
Conclusion:
L’AOBP se rapproche étroitement de la MAPA et peut être considérée comme une alternative fiable pour l’évaluation de la PA chez les patients atteints de MRC, en particulier dans les contextes à ressources limitées. La MOBP surestime significativement la PA et peut entraîner une erreur de classification diagnostique.
Mots-clés: Mesure ambulatoire de la pression artérielle, pression artérielle automatisée au cabinet, maladie rénale chronique, hypertension masquée, hypertension blouse blanche
INTRODUCTION
Chronic kidney disease (CKD) is a major global public health issue, affecting approximately 10%–15% of the adult population worldwide, with systemic hypertension and diabetes mellitus identified as its leading causes.[1,2] According to the kidney disease: improving Global Outcomes (KDIGO) 2012 guidelines, CKD is diagnosed when there is either evidence of kidney damage (e.g., albuminuria, urinary sediment abnormalities, structural or histological abnormalities) or a persistently reduced glomerular filtration rate (GFR <60 ml/min/1.73 m2) for at least 3 months.[3] These criteria reflect both the anatomical and functional integrity of the kidneys and have enabled consistent staging and prognostication of the disease.
CKD is not confined to renal pathology alone; it is intricately linked with cardiovascular morbidity and mortality. Numerous studies have shown that albuminuria and reduced estimated GFR (eGFR) independently predict adverse renal and cardiovascular outcomes, often preceding progression to end-stage renal disease.[4,5] Indeed, in advanced stages of CKD, cardiovascular events remain the leading cause of death rather than kidney failure itself.[6]
Systemic hypertension plays a dual role – as both a cause and a consequence of CKD – and its early recognition and optimal control are essential to slow renal deterioration. Ambulatory blood pressure monitoring (ABPM) is currently considered the gold standard for diagnosing hypertension in CKD patients, especially due to its ability to detect nocturnal hypertension, white-coat hypertension (WCH), and masked hypertension (MHT), all of which are prevalent in this group.[7,8]
The aim of the present study is to compare different blood pressure measurement techniques in patients with CKD, particularly evaluating manual office blood pressure (MOBP), automated office blood pressure (AOBP), and ABPM. The study seeks to examine the diagnostic concordance, circadian pattern detection, and clinical utility of these methods in identifying hypertension and guiding therapeutic decisions in CKD patients. ABPM, while precise, remains underutilized due to logistic and economic constraints. AOBP, on the other hand, is a promising surrogate that may offer better standardization and reduced observer bias compared to conventional MOBP.[9,10]
Accurate blood pressure (BP) assessment is pivotal in managing CKD progression and preventing cardiovascular complications. Through this comparative analysis, the study aims to identify the most reliable method of BP measurement that correlates best with target organ damage, albuminuria, and renal function decline, thereby supporting more effective and individualized hypertension management in CKD.
MATERIALS AND METHODS
Study design and duration
A hospital-based cross-sectional, comparative study was conducted over 24 months, from March 2021 to March 2023.
Study setting
After receiving approval from the institutional ethics committee, patients who presented to the outpatient department or were admitted into general medicine or nephrology departments with CKD were enrolled into the study after taking informed written consent.
Participants
Inclusion criteria: Patients in CKD stages 2,3,4 (eGFR 15–89 ml/min/1.73 m2) calculated using modification of diet in renal disease (MDRD), and patients aged above 18 years
Exclusion criteria: Patients of CKD in stages 1,5 (eGFR-90 ml/min/1.73 m2) calculated using MDRD.
Patients suffering from atrial fibrillation
Patients who had their anti-hypertensive medication changed in the prior month
Pregnant and lactating women
Exclusion criteria were assessed mainly through history, medical records, and physical examination to rule out the abovementioned conditions.
Sample size and sampling
A purposive sampling method was used.
Parameters assessed
Age
Gender
Socioeconomic status
Presence of comorbidities
Family history of HTN
CKD Duration
Stage of CKD
eGFR
Prevalence of true HTN
AOBP: Systolic blood pressure [SBP], diastolic blood pressure [DBP] during visit; 1st, 2nd, and 3rd readings = average AOBP SBP, DBP
MOBP: SBP, DBP during visit; 1st, 2nd, and 3rd readings = average MOBP SBP, DBP
ABPM SBP mean during daytime
ABPM DBP mean during daytime
ABPM DBP mean during night-time
ABPM SBP mean during night-time
Prevalence of masked HTN
Prevalence of White coat HTN.
Methodology
After taking informed written consent from patients, data were collected in a pretested proforma meeting the objectives of the study, which included demographic data, IP and OP number, relevant present, past, personal, drug history, and thorough clinical examination details. After 15 min of repose in a quiet room, BP is initially recorded using a DIAMOND manual mercury sphygmomanometer for both arms, with no caffeine, smoking, or physical activity within 30 min of the measurement. The brachial artery is covered by the midline of the cuff bladder above antecubital fossa, with about 2 cm remaining between the lower end of the cuff and the antecubital fossa for positioning a stethoscope. The inflatable bladder of the cuff covers between 75% and 100% of the circumference of the individual arm. For automated BP readings, patients are positioned consistently, and readings were taken three times at intervals of 1 min from the arm with the higher reading on the MOBP measurement after 30 min using an Omron Smart Elite + HEM 7600T device. All patients had had ABPM after 48 h. All patients received instruction on how to use the device precisely, how to maintain their antihypertensive medication dosage and type, and how to go about their regular lives. The 24-h ABPM period was maintained. While awake, BP was checked every half an hour, and while sleeping, it was checked every hour. Patients were questioned regarding their sleep schedules, and the ABPM equipment was adjusted as per study subject’s schedule.
Materials used
Omron 7 series automated BP monitor
DIAMOND manual mercury sphygmomanometer
MICROLIFE WatchBP O3 ambulatory BP monitor.
Statistical analysis
The following assumption on the data was made:
Dependent variables are normally distributed
Skewed variables were converted into log values to attain normal distribution.
The data were entered into Microsoft Excel 2019 (Microsoft Corporation, Redmond, WA, USA) and analyzed using Epi Info version 7.2.5 (Centers for Disease Control and Prevention [CDC], Atlanta, GA, USA). Statistical significance was defined as a P = 0.05 or lower. Percentages and frequencies were also used. Standard deviation and mean were used. To compare categorical variables, the Chi-square test was used to find factors related to HTN. The MOBP and AOBP groups’ SBP and DBP means were compared using the t-test. When compared to ABPM, diagnostic test characteristics such as sensitivity, specificity, and positive and negative predictive values were used for MOBP and AOBP. The relationship between AOBP and MOBP with ABPM was determined using Pearson’s correlation or linear regression.
Ethical considerations
Before beginning the study, approval was obtained from the institutional ethical committee associated with JSS Hospital in Mysuru. Each patient received a detailed explanation of the procedure and the benefits of providing their data for the study. After accepting, the subject was given an informed consent form in their native language and asked to sign it or leave a thumbprint. They were assured that any doubts they had would be cleared up at any time.
RESULTS
Age distribution
In the current study, most of the patients belonged to the age group of 41–70 years. The mean age was 55 years. Age ranged from 35 to 76 years [Table 1].
Table 1.
Age distribution of study subjects
| Age group | Frequency (n=200), rounded (%) |
|---|---|
| 31–40 | 18 (9.0) |
| 41–50 | 57 (28.5) |
| 51–60 | 55 (27.5) |
| 61–70 | 62 (31.0) |
| 71–80 | 8 (4.0) |
| Total | 200 (100.0) |
Gender
The majority of the participants in this study were men [Table 2].
Table 2.
Gender distribution of study participants
| Gender | Frequency (n=200), rounded (%) |
|---|---|
| Males | 120 (60.0) |
| Females | 80 (40.0) |
| Total | 200 (100.0) |
Hypertension (HTN) remains the most prevalent comorbidity, affecting 86 out of 200 patients (43%), underscoring its strong association with CKD, and the need for aggressive BP management in this population
Diabetes mellitus alone (DM ALONE) is present in 45 patients (22.5%), making it the second most common comorbidity [Table 3]. This highlights the importance of glycemic control as a cornerstone in CKD prevention and progression
Cardiovascular comorbidities (CAD and DM + CAD combined) affect 13 patients (6.5%), suggesting a significant burden of atherosclerotic disease in CKD, although less frequent than primary metabolic or renal disorders
Majority of patients (86 out of 200; 43%) have had CKD for 5–7 years, indicating a significant chronic disease burden [Table 4] and highlighting the need for long-term follow-up strategies
A large subset (83 patients; 41.5%) is in the early phase of CKD (1–2 years duration), providing a potential window for early intervention to slow disease progression
Stage II CKD accounts for the majority of cases (106 out of 200; 53%), suggesting early detection and diagnosis in over half the population [Table 5] an opportunity for implementing disease-modifying strategies
Stage III CKD is seen in 57 patients (28.5%), indicating a sizable intermediate-risk group that requires close monitoring for potential progression to advanced stages
Uncontrolled hypertension remains prevalent, affecting 77 out of 200 patients (38.5%) [Table 6], highlighting a substantial proportion of CKD patients at increased risk for cardiovascular and renal complications
Nearly half the patients (44%) have controlled hypertension on medication, reflecting effective therapeutic adherence and the importance of continued monitoring and individualized antihypertensive therapy
WCH (6.5%) and masked hypertension (2.5%) together affect 9% of the cohort, emphasizing the need for out-of-office BP measurement tools like ABPM to detect diagnostic inaccuracies and prevent overtreatment or missed cases
Stage II CKD dominates the cohort (127/200; 63.5%), with most of these patients exhibiting either normal BP (100) or isolated WCH, suggesting early-stage CKD with a relatively preserved cardiovascular profile
Stage III CKD shows greater heterogeneity in BP phenotypes, particularly higher proportions of isolated diastolic (IDH, 12) and isolated systolic hypertension (ISH, 10), emphasizing the importance of subtype classification for therapeutic decisions [Table 7]
Among Stage IV patients, 78% (14 out of 18) have sustained hypertension, with no representation of WCH or MHT, reinforcing the trend that hypertension becomes more sustained and severe as CKD progresses
Out of 200 patients, 163 (81.5%) were classified as nocturnal dippers [Table 8], reinforcing a relatively preserved circadian BP rhythm in early-stage CKD [Table 9]. However, the nondippers (18.5%) are at significantly higher risk for cardiovascular events and CKD progression, requiring close follow-up
A majority of patients (124/200; 62%) had normal BP on ABPM, supporting the earlier finding that most CKD patients in the study were in Stage II with either normal or well-controlled hypertension profiles. This validates the low representation of uncontrolled HTN seen earlier [Table 10]
The mean daytime SBP (130.11 mmHg) and DBP (84.35 mmHg), along with a nighttime dip to 117/77 mmHg, reflect KDIGO-recommended BP targets for CKD. This supports that the majority of patients in this cohort are within therapeutic goals, especially when assessed using ABPM
ABPM versus MOBP shows statistically significant differences for both systolic and diastolic BP (P = 0.04 and 0.03, respectively), indicating that MOBP readings tend to overestimate BP compared to ambulatory values [Table 11 and 12]
There is no significant difference between ABPM and AOBP readings (P > 0.4 for both SBP and DBP), suggesting that AOBP closely mirrors ABPM, and may be a valid surrogate in settings where ABPM is not feasible [Table 13]
Mean systolic and diastolic pressures through ABPM (130.11/84.35 mmHg) suggest that the average patient in this cohort falls within the KDIGO-recommended BP targets for CKD management, reinforcing the clinical relevance of ABPM in evaluating treatment adequacy
Uncontrolled hypertension is most frequently detected by MOBP and AOBP (31% each), while ABPM detects a slightly lower proportion (27.5%), reflecting its superior ability to rule out WCH and avoid overestimation of BP status seen in office-based readings
ABPM identified additional hidden phenotypes not seen in MOBP/AOBP [Table 14]: 13 patients (6.5%) with WCH and 7 patients (3.5%) with masked hypertension, underscoring the diagnostic advantage of ABPM in capturing circadian BP variability
Circadian rhythm preservation was evident in the cohort, with 163 out of 200 patients (81.5%) classified as nocturnal dippers, suggesting that a substantial majority of patients – especially those with Stage II CKD and controlled BP – retain physiologic BP dipping, indicating lower cardiovascular risk compared to nondippers.
Table 3.
Distribution of comorbidities among study subjects
| Comorbidities | Frequency (n=200), rounded (%) |
|---|---|
| CAD | 11 (5.5) |
| Cancer | 7 (3.5) |
| DM alone | 45 (22.5) |
| DM, CAD | 2 (1.0) |
| HTN | 86 (43.0) |
| Intrinsic renal disorders | 19 (9.5) |
| RA | 4 (2.0) |
| Total | 200 (100.0) |
HTN=Hypertension, DM alone=Diabetes mellitus alone, CAD=Coronary artery disease, RA=Rheumatoid arthritis
Table 4.
Duration of chronic kidney disease among study subjects
| CKD duration (years) | Frequency (n=200), rounded (%) |
|---|---|
| 1–2 | 83 (41.5) |
| 3–4 | 31 (15.5) |
| 5–7 | 86 (43.0) |
| Total | 200 (100.0) |
CKD=Chronic kidney disease
Table 5.
Chronic kidney disease stage among study subjects
| CKD stage | Frequency (n=200), rounded (%) |
|---|---|
| Stage II | 106 (53.0) |
| Stage III | 57 (28.5) |
| Stage IV | 17 (8.5) |
| Total | 200 (100.0) |
CKD=Chronic kidney disease
Table 6.
Prevalence of high blood pressure, white coat hypertension, masked hypertension
| HTN category (overall) | Frequency (n=200), rounded (%) |
|---|---|
| Uncontrolled HTN | 77 (38.5) |
| MHT | 5 (2.5) |
| Normal (controlled with medication) | 88 (44.0) |
| WCH | 13 (6.5) |
| Total | 200 (100.0) |
HTN=Hypertension, WCH=White coat hypertension, MHT=Masked hypertension
Table 7.
Relation between high blood pressure and chronic kidney disease stage
| CKD stage | Normal | IDH | ISH | MHT | HTN | WCH | Total |
|---|---|---|---|---|---|---|---|
| Stage II | 100 | 2 | 0 | 2 | 10 | 13 | 127 |
| Stage III | 3 | 12 | 10 | 3 | 29 | 0 | 57 |
| Stage IV | 2 | 0 | 2 | 0 | 14 | 0 | 18 |
| Total | 105 | 14 | 12 | 5 | 53 | 13 | 200 |
HTN=Hypertension, WCH=White coat hypertension, MHT=Masked hypertension, CKD=Chronic kidney disease, IDH=Isolated diastolic HTN, ISH=Isolated systolic HTN
Table 8.
Systolic blood pressure and diastolic blood pressure (daytime and night-time) ambulatory blood pressure monitoring
| Time period | SBP (mmHg) | DBP (mmHg) |
|---|---|---|
| Daytime ABPM | 130.11±17.6 | 84.35±10.8 |
| Night-time ABPM | 117±18 | 77±11 |
ABPM=Ambulatory blood pressure monitoring, SBP=Systolic blood pressure, DBP=Diastolic blood pressure
Table 9.
Nocturnal dipping status
| Night dipping pattern | Frequency (n=200), rounded (%) |
|---|---|
| Dippers | 163 (81.5) |
| Nondippers | 37 (18.5) |
| Total | 200 (100) |
Table 10.
Ambulatory blood pressure monitoring categories (daytime 24-h ambulatory blood pressure monitoring classification)
| ABPM category | Frequency (n=200), rounded (%) |
|---|---|
| HTN | 55 (27.5) |
| IDH | 11 (5.5) |
| ISH | 10 (5.0) |
| Normal | 124 (62.0) |
| Total | 200 (100) |
HTN=Hypertension, ABPM=Ambulatory blood pressure monitoring, IDH=Isolated diastolic HTN, ISH=Isolated systolic HTN
Table 11.
Means of systolic blood pressure, diastolic blood pressure among study patients
| Parameter | Mean±SD | t | P | Significance |
|---|---|---|---|---|
| SBP – ABPM | 130.11±17.60 | 2.16 | 0.04 | Significant |
| SBP – MOBP | 131.55±16.88 | - | - | - |
| DBP – ABPM | 84.35±10.81 | 2.18 | 0.03 | Significant |
| DBP – MOBP | 87.42±10.56 | - | - | - |
| SBP – ABPM | 130.11±17.60 | −0.15 | 0.440 | Not significant |
| SBP – AOBP | 130.45±17.53 | - | - | - |
| DBP – ABPM | 84.35±10.81 | −0.197 | 0.421 | Not significant |
| DBP – AOBP | 84.63±10.80 | - | - | - |
SD=Standard deviation, ABPM=Ambulatory blood pressure monitoring, SBP=Systolic blood pressure, DBP=Diastolic blood pressure, AOBP=Automated office blood pressure, MOBP=Manual office blood pressure
Table 12.
Sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of manual office blood pressure in comparison with ambulatory blood pressure monitoring
| Statistics | Value (%) | 95% CI |
|---|---|---|
| Sensitivity | 82.98 | 69.19–92.35 |
| Specificity | 84.93 | 74.64–92.23 |
| PPV | 78.00 | 66.95–86.12 |
| NPV | 88.57 | 80.36–93.62 |
| Accuracy* | 84.17 | 76.38–90.19 |
PPV=Positive predictive value, NPV=Negative predictive value, CI=Confidence interval. *Accuracy=(True Positives + True Negatives)÷Total number of observations
Table 13.
Sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of automated office blood pressure in comparison with ambulatory blood pressure monitoring
| Statistic | Value (%) | 95% CI |
|---|---|---|
| Sensitivity | 95.83 | 85.75–99.49 |
| Specificity | 94.44 | 86.38–98.47 |
| Positive likelihood ratio | 17.25 | 6.64–44.79 |
| Negative likelihood ratio | 0.04 | 0.01–0.17 |
| Disease prevalence* | 40.00 | 31.17–49.34 |
| PPV* | 92.00 | 81.58–96.76 |
| NPV* | 97.14 | 89.74–99.25 |
| Accuracy* | 95.00 | 89.43–98.14 |
PPV=Positive predictive value, NPV=Negative predictive value, CI=Confidence interval. *Disease prevalence, positive predictive value (PPV), negative predictive value (NPV), and accuracy are calculated in comparison with ambulatory blood pressure monitoring (ABPM) as the reference standard
Table 14.
Assessed parameters with manual office blood pressure, automated office blood pressure, and ambulatory blood pressure monitoring
| Parameter | MOBP (n=200), n (%) | AOBP (n=200), n (%) | ABPM (n=200) n (%) |
|---|---|---|---|
| Average SBP (mmHg) | 131.55±16.88 | 130.45±17.53 | 130.11±17.60 |
| Average DBP (mmHg) | 87.42±10.56 | 84.63±10.80 | 84.35±10.81 |
| Uncontrolled HTN | 62 (31.0) | 62 (31.0) | 55 (27.5) |
| ISH | 10 (5.0) | 10 (5.0) | 12 (6.0) |
| IDH | 15 (7.5) | 12 (6.0) | 13 (6.5) |
| WCH | - | - | 13 (6.5) |
| MHT | - | - | 7 (3.5) |
| Dippers | - | - | 163 (81.5) |
| Nondippers | - | - | 37 (18.5) |
HTN=Hypertension, MHT=Masked HTN, WCH=White coat HTN, IDH=Isolated diastolic HTN, ISH=Isolated systolic HTN, SBP=Systolic blood pressure, DBP=Diastolic blood pressure, AOBP=Automated office blood pressure, MOBP=Manual office blood pressure, ABPM=Ambulatory blood pressure monitoring
DISCUSSION
Hypertension in CKD is both a complication and a driver of disease progression, making accurate blood pressure (BP) measurement a cornerstone of management. However, traditional clinic-based BP measurements often fail to reflect true BP burden, due to phenomena such as WCH and masked hypertension (MHT), both of which are prevalent in CKD populations and associated with target organ damage.[11,12]
Our study showed that MOBP measurements significantly overestimated both systolic and diastolic BP when compared with ABPM, with a mean SBP of 131.55 ± 16.88 mmHg for MOBP versus 130.11 ± 17.60 mmHg for ABPM (P = 0.04), and DBP of 87.42 ± 10.56 mmHg versus 84.35 ± 10.81 mmHg (P = 0.03). These findings are consistent with those of Godwin et al., who reported a mean systolic bias of 16.4 mmHg and diastolic bias of 10.3 mmHg for MOBP compared to ABPM in CKD patients.[12]
In contrast, automated office blood pressure (AOBP) demonstrated much closer agreement with ABPM values, with no statistically significant difference (SBP: 130.45 ± 17.53 mmHg vs. 130.11 ± 17.60 mmHg, P = 0.44; DBP: 84.63 ± 10.80 mmHg vs. 84.35 ± 10.81 mmHg, P = 0.42). The bias for AOBP was only 8.6 mmHg for SBP and 5.5 mmHg for DBP in the comparative study, reflecting its improved accuracy over MOBP.[12] Other studies have similarly noted that AOBP reduces observer bias, digit preference, and white-coat effect, providing more reproducible values in both hypertensive and CKD populations.[9,22]
The diagnostic implications of these findings are significant. In our cohort, ABPM revealed that 6.5% had WCH and 3.5% had MHT—phenotypes that would have gone unrecognized with MOBP or AOBP alone. WCH, while previously considered benign, has now been linked to intermediate cardiovascular risk in CKD, while MHT carries risks comparable to sustained hypertension.[13,14] These findings affirm the conclusions of Tang et al. and Boggia et al., who highlighted the prognostic implications of these hidden hypertension patterns in CKD.[13,14]
ABPM’s ability to uncover nocturnal BP dipping patterns also makes it indispensable. In our study, 81.5% of patients exhibited normal nocturnal dipping, whereas 18.5% were nondippers. Nondipping is known to correlate with adverse cardiovascular outcomes, increased left ventricular mass, and faster renal function decline.[16] These temporal variations are only discernible through ABPM and not with office-based methods, emphasizing the utility of ABPM in risk stratification.[16,17,18,19]
However, despite being the gold standard, ABPM is underutilized due to logistic constraints, high cost, and patient discomfort.[20] In such settings, AOBP emerges as a feasible and reliable surrogate. Studies by Myers et al. and the CAMBO trial confirmed that AOBP offers a more accurate and standardized office-based approach, particularly when used in controlled environments without clinician presence.[22,23]
The high sensitivity (95.8%) and specificity (94.4%) of AOBP in our study, with positive predictive value (92.0%) and negative predictive value (97.1%), are in line with findings from Godwin et al., who showed that AOBP closely tracks with ABPM in estimating true BP burden in primary care patients.[12] These results support its integration into CKD management algorithms, especially in facilities where ABPM is impractical.
Furthermore, data from Gorostidi et al. demonstrate that office BP control can misclassify up to one-third of hypertensive CKD patients, whereas ABPM provides more reliable readings for diagnosis and treatment adjustments.[17] Our study mirrors this observation, where 31% had uncontrolled hypertension on MOBP/AOBP, compared to 27.5% detected via ABPM.
The integration of AOBP into clinical practice also aligns with current recommendations. Garimella and Uhlig emphasized that better BP monitoring strategies, including AOBP and ABPM, are essential in CKD patients, where therapeutic targets must be individualized.[15] Similarly, Hermida et al. emphasized that abnormalities in nocturnal BP patterns can be corrected through bedtime antihypertensive chronotherapy, a practice dependent on ABPM insights.[16]
Although home BP monitoring (HBPM) is another emerging modality, it lacks validation in many CKD-specific trials and does not capture nocturnal trends. Hence, ABPM remains the gold standard for both diagnosis and prognosis in this group.[21]
It’s worth noting that even the device used may influence results. The Microlife WatchBP O3 used in our study has been validated in both clinical and ambulatory settings,[24] adding robustness to our data. Agarwal also noted that the BP measurement protocol (e.g., observer presence, rest periods) can substantially alter readings and influence treatment decisions.
Nonetheless, our study has limitations. The cross-sectional design limits assessment of long-term outcomes such as CKD progression or cardiovascular events. Furthermore, patient-level factors such as stress, medication adherence, or volume status at the time of measurement could influence BP values. Future randomized trials and prospective follow-up are needed to confirm the prognostic significance of AOBP-detected hypertension patterns.
CONCLUSION
While ABPM remains the benchmark for BP assessment in CKD due to its ability to detect WCH, MHT, and circadian variability, AOBP offers a reliable and practical alternative. MOBP continues to show significant measurement bias and should be interpreted with caution. Wider adoption of AOBP, especially in resource-limited settings, can bridge the diagnostic gap where ABPM is unavailable, ensuring better hypertension control and renal protection in CKD patients.
Benefits and strengths of the study:
The current study determined the prevalence and risk factors of hypertension among CKD patients
Successive evaluation of blood pressure in the same study subjects by three measurements was a significant strength of the study as it allowed to minimize of interpersonal differences
The study helped to identify various types of hypertensions, so that timely interventions can be taken, before progression or end-organ damage
This information may help guide physicians to screen for HTN early, especially among risky patients.
Future recommendations:
Multicenter studies including various tertiary care hospitals and certain specialized clinics could be done as more population from different backgrounds could be involved.
Data availability
All data generated or analysed during this study are included in this published article.
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All data generated or analysed during this study are included in this published article.