Impact of cumulative SBP and serious adverse events on efficacy of intensive blood pressure treatment: a randomized clinical trial

Elucidating the complex interplay between chronic kidney disease and hypertension

Chronic kidney disease (CKD) and hypertension share a complex relationship, each exacerbating the progression of the other. CKD contributes to hypertension by decreasing renal function, leading to fluid retention and increased plasma volume, whereas hypertension exacerbates CKD by increasing glomerular pressure and causing renal damage. This review examines the intertwined nature of CKD and hypertension, exploring the factors driving hypertension in CKD and how hypertension accelerates CKD progression. It discusses the role of the renin-angiotensin system and inflammatory cytokines in this relationship, as well as the potential of blood pressure management to slow renal decline. While studies suggest that meticulous blood pressure control can help attenuate CKD progression, optimal management strategies remain unclear and require further investigation. This review also evaluates the evidence surrounding strict antihypertensive therapy in patients with CKD, considering both diabetic and non-diabetic cases. It recommends blood pressure targets based on CKD stage and presence of diabetes, emphasizing the importance of individualized treatment approaches. Renin-angiotensin system inhibitors are highlighted as a key pharmacological intervention due to their renal protective effects, particularly in patients with CKD with proteinuria. However, evidence regarding their efficacy in patients with CKD but without proteinuria is inconclusive. This review underscores the need for comprehensive approaches to effectively address the intertwined nature of CKD and hypertension and calls for further research to optimize clinical management strategies in this complex interplay.

Reduction in blood pressure for people with isolated diastolic hypertension and cardiovascular outcomes

AIMS

Isolated diastolic hypertension (IDH) is a largely underrated risk factor for cardiovascular disease (CVD). It is currently unclear whether a reduction in blood pressure (BP) is associated with CVD events among adults with IDH. We aimed to elucidate the relationship between BP reduction and incident CVD in individuals with IDH.

METHODS AND RESULTS

We retrospectively analysed the data of 71 297 individuals with IDH. Isolated diastolic hypertension was defined as systolic BP of < 140 mmHg and diastolic BP (DBP) of ≥90 mmHg (median age, 48 years; 83.1% men; median DBP, 92 mmHg). None of the participants took BP-lowering medications or had a history of CVD at baseline. Blood pressure was measured at baseline and 1-year follow-up, and participants were categorized into two groups based on DBP at 1 year (≥90 or < 90 mmHg). The primary outcome was a composite endpoint that included myocardial infarction, stroke, and all-cause death. Over a mean follow-up period of 1100 ± 859 days, 1317 composite CVD endpoints were recorded. Participants with DBP of < 90 mmHg at 1 year were at a lower risk of composite CVD events [hazard ratio (HR): 0.75, 95% confidence interval (CI): 0.67-0.83] than those with DBP of ≥90 mmHg at 1 year. A reduction in DBP per 5 mmHg during the 1-year follow-up was associated with a lower composite CVD event risk (HR: 0.92, 95% CI: 0.89-0.95). The results remained consistent across a multitude of sensitivity analyses.

CONCLUSION

Our analysis of a large-scale epidemiological dataset demonstrated a relationship of reduction in DBP with a reduced risk for CVD events in individuals with IDH.

Dynamic prediction of renal survival among deeply phenotyped kidney transplant recipients using artificial intelligence: an observational, international, multicohort study

BACKGROUND

Kidney allograft failure is a common cause of end-stage renal disease. We aimed to develop a dynamic artificial intelligence approach to enhance risk stratification for kidney transplant recipients by generating continuously refined predictions of survival using updates of clinical data.

METHODS

In this observational study, we used data from adult recipients of kidney transplants from 18 academic transplant centres in Europe, the USA, and South America, and a cohort of patients from six randomised controlled trials. The development cohort comprised patients from four centres in France, with all other patients included in external validation cohorts. To build deeply phenotyped cohorts of transplant recipients, the following data were collected in the development cohort: clinical, histological, immunological variables, and repeated measurements of estimated glomerular filtration rate (eGFR) and proteinuria (measured using the proteinuria to creatininuria ratio). To develop a dynamic prediction system based on these clinical assessments and repeated measurements, we used a Bayesian joint models-an artificial intelligence approach. The prediction performances of the model were assessed via discrimination, through calculation of the area under the receiver operator curve (AUC), and calibration. This study is registered with ClinicalTrials.gov, NCT04258891.

FINDINGS

13 608 patients were included (3774 in the development cohort and 9834 in the external validation cohorts) and contributed 89 328 patient-years of data, and 416 510 eGFR and proteinuria measurements. Bayesian joint models showed that recipient immunological profile, allograft interstitial fibrosis and tubular atrophy, allograft inflammation, and repeated measurements of eGFR and proteinuria were independent risk factors for allograft survival. The final model showed accurate calibration and very high discrimination in the development cohort (overall dynamic AUC 0·857 [95% CI 0·847-0·866]) with a persistent improvement in AUCs for each new repeated measurement (from 0·780 [0·768-0·794] to 0·926 [0·917-0·932]; p<0·0001). The predictive performance was confirmed in the external validation cohorts from Europe (overall AUC 0·845 [0·837-0·854]), the USA (overall AUC 0·820 [0·808-0·831]), South America (overall AUC 0·868 [0·856-0·880]), and the cohort of patients from randomised controlled trials (overall AUC 0·857 [0·840-0·875]).

INTERPRETATION

Because of its dynamic design, this model can be continuously updated and holds value as a bedside tool that could refine the prognostic judgements of clinicians in everyday practice, hence enhancing precision medicine in the transplant setting.

FUNDING

MSD Avenir, French National Institute for Health and Medical Research, and Bettencourt Schueller Foundation.

Application of the American College of Cardiology (ACC/AHA) 2017 Guideline for the Management of Hypertension in Adults and Comparison with the 2014 Eighth Joint National Committee Guideline

Objectives

This study aims to compare the 2017-ACC/AHA hypertension guideline with 2014-JNC-8 guideline in regard to the number of patients who are eligible for treatment and to determine the physicians’ adherence and the financial impact of implementing the new guideline.

Methods

A cross-sectional observational study was conducted on adult patients who attended the hospital outpatient setting in UAE during January 1, 2018 till February 28, 2018. Adults who are diagnosed with hypertension and those with blood pressure (BP) levels based on two or more readings obtained on two or more different occasions were screened for inclusion into this study and cardiovascular diseases (CVD) risk was calculated. The two guidelines were compared with respect to the number of patients diagnosed with hypertension and eligible for treatment. Results were extrapolated to the UAE population. Financial impact of applying the 2017-ACC/AHA guideline was also evaluated.

Results

In comparison with the JNC-8, the 2017-ACC/AHA guideline would increase the proportion of patients diagnosed with hypertension among UAE adults from 40.8% to 76.3% and the number of UAE adults recommended for antihypertensive medications would rise from 2.42 million (32.1%) to 4.71 million (62.5%). Among UAE adults, almost 4.42 million (58.6%) and 0.76 million (10.1%) would have BP above the target according to the 2017-ACC/AHA and JNC-8 guidelines, respectively. The expected increase in the cost of anti-hypertension medications prescribed for the new labeled cases according to 2017-ACC/AHA but not JNC-8 would reach 1.8 billion AED/year. For those who were recommended for antihypertensive medications, who had BP above target, the additional cost would reach 3.5 billion AED/year.

Conclusions

The current study reveals marked increase in the proportion of patients diagnosed with hypertension in concordance with the 2017-ACC/AHA guideline. This is also will be associated with almost double the number of UAE adults recommended for antihypertensive medications. The poor compliance with the 2017-ACC/AHA reflects the concern regarding the increase risk of adverse events.

Serious Adverse Events Cluster in Participants Experiencing the Primary Composite Cardiovascular Endpoint: A Post Hoc Analysis of the SPRINT Trial

BACKGROUND

Intensively treated participants in the SPRINT study experienced fewer primary cardiovascular composite study endpoints (CVD events) and lower mortality, although 38% of participants experienced a serious adverse event (SAE). The relationship of SAEs with CVD events is unknown.

METHODS

CVD events were defined as either myocardial infarction, acute coronary syndrome, decompensated heart failure, stroke, or death from cardiovascular causes. Cox models were utilized to understand the occurrence of SAEs with CVD events according to baseline atherosclerotic cardiovascular disease (ASCVD) risk.

RESULTS

SAEs occurred in 96% of those experiencing a CVD event but only in 34% (P < 0.001) of those not experiencing a CVD event. Occurrence of SAEs monotonically increased across the range of baseline ASCVD risk being approximately twice as great in the highest compared with the lowest risk category. SAE occurrence was strongly associated with ASCVD risk but was similar within risk groups across treatment arms. In adjusted Cox models, experiencing a CVD event was the strongest predictor of SAEs in all risk groups. By the end of year 1, the hazard ratios for the low, middle, and high ASCVD risk tertiles, and baseline clinical CVD group were 2.56 (95% CI = 1.39-4.71); 2.52 (1.63-3.89); 3.61 (2.79-4.68); 1.86 (1.37-2.54), respectively-a trend observed in subsequent years until study end. Intensive treatment independently predicted SAEs only in the second ASVCD risk tertile.

CONCLUSIONS

The occurrence of SAEs is multifactorial and mostly related to prerandomization patient characteristics, most prominently ASCVD risk, which, in turn, relates to in-study CVD events.

An introduction to joint models-applications in nephrology

In nephrology, a great deal of information is measured repeatedly in patients over time, often alongside data on events of clinical interest. In this introductory article we discuss how these two types of data can be simultaneously analysed using the joint model (JM) framework, illustrated by clinical examples from nephrology. As classical survival analysis and linear mixed models form the two main components of the JM framework, we will also briefly revisit these techniques.