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Developing prediction models for electrolyte abnormalities in patients indicated for antihypertensive therapy: evidence-based treatment and monitoring recommendations.
OBJECTIVES: Evidence from clinical trials suggests that antihypertensive treatment is associated with an increased risk of common electrolyte abnormalities. We aimed to develop and validate two clinical prediction models to estimate the risk of hyperkalaemia and hyponatraemia, respectively, to facilitate targeted treatment and monitoring strategies for individuals indicated for antihypertensive therapy. DESIGN AND METHODS: Participants aged at least 40 years, registered to an English primary care practice within the Clinical Practice Research Datalink (CPRD), with a systolic blood pressure reading between 130 and 179 mmHg were included the study. The primary outcomes were first hyperkalaemia or hyponatraemia event recorded in primary or secondary care. Model development used a Fine-Gray approach with death from other causes as competing event. Model performance was assessed using C-statistic, D-statistic, and Observed/Expected (O/E) ratio upon external validation. RESULTS: The development cohort included 1 773 224 patients (mean age 59 years, median follow-up 6 years). The hyperkalaemia model contained 23 predictors and the hyponatraemia model contained 29 predictors, with all antihypertensive medications associated with the outcomes. Upon external validation in a cohort of 3 805 366 patients, both models calibrated well (O/E ratio: hyperkalaemia 1.16, 95% CI 1.13-1.19; hyponatraemia 1.00, 95% CI 0.98-1.02) and showed good discrimination at 10 years (C-statistic: 0.69, 95% CI 0.69-0.69; 0.80, 95% CI 0.80-0.80, respectively). CONCLUSION: Current clinical guidelines recommend monitoring serum electrolytes after initiating antihypertensive treatment. These clinical prediction models predicted individuals' risk of electrolyte abnormalities associated with antihypertensive treatment and could be used to target closer monitoring for individuals at a higher risk, where resources are limited.
Withdrawal of antihypertensive drugs in older people
Background: Hypertension is an important risk factor for subsequent cardiovascular events, including ischaemic and haemorrhagic stroke, myocardial infarction, and heart failure, as well as chronic kidney disease, cognitive decline, and premature death. Overall, the use of antihypertensive medications has led to a reduction in cardiovascular disease, morbidity rates, and mortality rates. However, the use of antihypertensive medications is also associated with harms, especially in older people, including the development of adverse drug reactions and drug-drug interactions, and can contribute to increasing medication-related burden. As such, discontinuation of antihypertensives may be considered appropriate in some older people. Objectives: To evaluate the effects of withdrawal of antihypertensive medications used for hypertension or primary prevention of cardiovascular disease in older adults. Search methods: For this update, we searched the Cochrane Hypertension Specialised Register, CENTRAL (2022, Issue 9), Ovid MEDLINE, Ovid Embase, the WHO ICTRP, and ClinicalTrials.gov up to October 2022. We also conducted reference checking and citation searches, and contacted study authors to identify any additional studies when appropriate. There were no language restrictions on the searches. Selection criteria: We included randomised controlled trials (RCTs) of withdrawal versus continuation of antihypertensive medications used for hypertension or primary prevention of cardiovascular disease in older adults (defined as 50 years of age and over). Eligible participants were living in the community, residential aged care facilities, or based in hospital settings. We included trials evaluating the complete withdrawal of all antihypertensive medication, as well as those focusing on a dose reduction of antihypertensive medication. Data collection and analysis: We compared the intervention of discontinuing or reducing the dose of antihypertensive medication to continuing antihypertensive medication using mean differences (MD) and 95% confidence intervals (95% CIs) for continuous variables, and Peto odds ratios (ORs) and 95% CI for binary variables. Our primary outcomes were mortality, myocardial infarction, and the development of adverse drug reactions or adverse drug withdrawal reactions. Secondary outcomes included hospitalisation, stroke, blood pressure (systolic and diastolic), falls, quality of life, and success in withdrawing from antihypertensives. Two review authors independently, and in duplicate, conducted all stages of study selection, data extraction, and quality assessment. Main results: We identified no new studies in this update. Six RCTs from the original review met the inclusion criteria and were included in the review (1073 participants). Study duration and follow-up ranged from 4 weeks to 56 weeks. Meta-analysis of studies showed that discontinuing antihypertensives, compared to continuing, may result in little to no difference in all-cause mortality (OR 2.08, 95% CI 0.79 to 5.46; P = 0.14, I2 = 0%; 4 studies, 630 participants; low certainty of evidence), and that the evidence is very uncertain about the effect on myocardial infarction (OR 1.86, 95% CI 0.19 to 17.98; P = 0.59, I2 = 0%; 2 studies, 447 participants; very low certainty of evidence). Meta-analysis was not possible for the development of adverse drug reactions and withdrawal reactions; the evidence is very uncertain about the effect of antihypertensive discontinuation on the risk of adverse drug reactions (very low certainty of evidence), and the included studies did not assess adverse drug withdrawal reactions specifically. One study reported on hospitalisations; discontinuing antihypertensives may result in little to no difference in hospitalisation (OR 0.83, 95% CI 0.33 to 2.10; P = 0.70; 1 study, 385 participants; low certainty of evidence). Meta-analysis showed that discontinuing antihypertensives may result in little to no difference in stroke (OR 1.44, 95% CI 0.25 to 8.35; P = 0.68, I2 = 6%; 3 studies, 524 participants; low certainty of evidence). Blood pressure may be higher in the discontinuation group than the continuation group (systolic blood pressure: MD 9.75 mmHg, 95% CI 7.33 to 12.18; P < 0.001, I2 = 67%; 5 studies, 767 participants; low certainty of evidence; and diastolic blood pressure: MD 3.5 mmHg, 95% CI 1.82 to 5.18; P < 0.001, I2 = 47%; 5 studies, 768 participants; low certainty of evidence). No studies reported falls. The sources of bias included selective reporting (reporting bias), lack of blinding of outcome assessment (detection bias), incomplete outcome data (attrition bias), and lack of blinding of participants and personnel (performance bias). Authors' conclusions: The main conclusions from the 2020 review still apply. Discontinuing antihypertensives may result in little to no difference in mortality, hospitalisation, and stroke. The evidence is very uncertain about the effect of discontinuing antihypertensives on myocardial infarction and adverse drug reactions and adverse drug withdrawal reactions. Discontinuing antihypertensives may result in an increase in blood pressure. There was no information about the effect on falls. The evidence was of low to very low certainty, mainly due to small studies and low event rates. These limitations mean that we cannot draw any firm conclusions about the effect of deprescribing antihypertensives on these outcomes. Future research should focus on populations with the greatest uncertainty of the benefit:risk ratio for the use of antihypertensive medications, such as those with frailty, older age groups, and those taking polypharmacy, and measure clinically important outcomes such as adverse drug events, falls, and quality of life.
Understanding Measurement of Postural Hypotension (UMPH): a nationwide survey of general practice in England.
Background Postural hypotension (PH) is associated with excess mortality, falls and cognitive decline. PH is poorly recorded in routine general practice (practice) records. Few practice studies have explored measurement and diagnosis of PH. Aim To understand how PH is measured, diagnosed and managed in practice. Design and setting Online survey of practice staff in England. Method Clinical Research Networks distributed the survey to practices, seeking individual responses from any clinical staff involved in routine blood pressure (BP) measurement. Responses were analysed according to role and demographic data using descriptive statistics. Multivariable modelling of undertaking postural BP measurements was performed. Results 703 responses were received from 243 practices (mean practice-level response rate 17%). Half (362; 51%) of respondents were doctors, 196 (28%) practice nurses and 77 (11%) healthcare assistants (HCAs). Eight percent did not routinely check for PH, usually citing time constraints. For the remaining 92%, postural symptoms were the predominant reason for checking (97% respondents); only 24% cited any other guideline indication for PH testing. 77% used sit-to-stand BP measurements; only 25% measured standing BP for more than one minute. On regression modelling, other professionals tested less for PH than doctors (Odds ratios: nurses 0.323 (95% confidence interval 0.117 to 0.894), HCAs 0.102 (0.032 to 0.325), pharmacists 0.986 (0.024 to 0.412)). Conclusion Awareness of reasons, besides symptoms, and adherence to guidelines for PH testing, are low. Time is the key barrier to improved testing for PH. Clarity on pragmatic methods of measuring PH in practice would also facilitate measurement uptake.
How, why and when are delayed (back-up) antibiotic prescriptions used in primary care? A realist review integrating concepts of uncertainty in healthcare
Background: Antimicrobial resistance is a global patient safety priority and inappropriate antimicrobial use is a key contributing factor. Evidence have shown that delayed (back-up) antibiotic prescriptions (DP) are an effective and safe strategy for reducing unnecessary antibiotic consumption but its use is controversial. Methods: We conducted a realist review to ask why, how, and in what contexts general practitioners (GPs) use DP. We searched five electronic databases for relevant articles and included DP-related data from interviews with healthcare professionals in a related study. Data were analysed using a realist theory-driven approach – theorising which context(s) influenced (mechanisms) resultant outcome(s) (context-mechanism-outcome-configurations: CMOCs). Results: Data were included from 76 articles and 41 interviews to develop a program theory comprising nine key and 56 related CMOCs. These explain the reasons for GPs’ tolerance of risk to different uncertainties and how these may interact with GPs’ work environment, self-efficacy and perceived patient concordance to make using DP as a safety-net or social tool more or less likely, at a given time-point. For example, when a GP uses clinical scores or diagnostic tests: a clearly high or low score/test result may mitigate scientific uncertainty and lead to an immediate or no antibiotic decision; an intermediary result may provoke hermeneutic (interpretation-related) uncertainty and lead to DP becoming preferred and used as a safety net. Our program theory explains how DP can be used to mitigate some uncertainties but also provoke or exacerbate others. Conclusion: This review explains how, why and in what contexts GPs are more or less likely to use DP, as well as various uncertainties GPs face which DP may mitigate or provoke. We recommend that efforts to plan and implement interventions to optimise antibiotic prescribing in primary care consider these uncertainties and the contexts when DP may be (dis)preferred over other interventions to reduce antibiotic prescribing. We also recommend the following and have included example activities for: (i) reducing demand for immediate antibiotics; (ii) framing DP as an ‘active’ prescribing option; (iii) documenting the decision-making process around DP; and (iv) facilitating social and system support.
Excess burden of antibiotic-resistant bloodstream infections: evidence from a multicentre retrospective cohort study in Chile, 2018–2022
Background: Antibiotic-resistant bloodstream infections (ARB BSI) cause an enormous disease and economic burden. We assessed the impact of ARB BSI caused by high- and critical-priority pathogens in hospitalised Chilean patients compared to BSI caused by susceptible bacteria. Methods: We conducted a retrospective cohort study from 2018 to 2022 in three Chilean hospitals and measured the association of ARB BSI with in-hospital mortality, length of hospitalisation (LOS), and intensive care unit (ICU) admission. We focused on BSI caused by Acinetobacter baumannii, Enterobacterales, Staphylococcus aureus, Enterococcus species, and Pseudomonas aeruginosa. We addressed confounding using propensity scores, inverse probability weighting, and multivariate regressions. We stratified by community- and hospital-acquired BSI and assessed total hospital and productivity costs. Findings: We studied 1218 adult patients experiencing 1349 BSI episodes, with 47.3% attributed to ARB. Predominant pathogens were Staphylococcus aureus (33% Methicillin-resistant ‘MRSA’), Enterobacterales (50% Carbapenem-resistant ‘CRE’), and Pseudomonas aeruginosa (65% Carbapenem-resistant ‘CRPA’). Approximately 80% of BSI were hospital-acquired. ARB was associated with extended LOS (incidence risk ratio IRR = 1.14, 95% CI = 1.05–1.24), increased ICU admissions (odds ratio OR = 1.25; 1.07–1.46), and higher mortality (OR = 1.42, 1.20–1.68) following index blood culture across all BSI episodes. In-hospital mortality risk, adjusted for time-varying and fixed confounders, was 1.35-fold higher (1.16–1.58) for ARB patients, with higher hazard ratios for hospital-acquired MRSA and CRE at 1.37 and 1.48, respectively. Using a societal perspective and a 5% discount rate, we estimated excess costs for ARB at $12,600 per patient, with an estimated annual excess burden of 2270 disability-adjusted life years (DALYs) and $9.6 (5.0–16.4) million. Interpretation: It is urgent to develop and implement interventions to reduce the burden of ARB BSIs, particularly from MRSA and CRE. Funding: Agencia Nacional de Investigación y Desarrollo ANID, Chile.
Implementation framework for AI deployment at scale in healthcare systems
Artificial intelligence (AI) and digital health technologies are increasingly used in the medical field. Despite promises of leading the future of personalized medicine and better clinical outcomes, implementation of AI faces barriers for deployment at scale. We introduce a novel implementation framework that can facilitate digital health designers, developers, patient groups, policymakers, and other stakeholders, to co-create and solve issues throughout the life cycle of designing, developing, deploying, monitoring, and maintaining algorithmic models. This framework targets health systems that integrate multiple machine learning (ML) models with various modalities. This design thinking approach promotes clinical utility beyond model prediction, combining privacy preservation with clinical parameters to establish a reward function for reinforcement learning, ranking competing models. This allows leveraging explainable AI (xAI) methods for clinical interpretability. Governance mechanisms and orchestration platforms can be integrated to monitor and manage models. The proposed framework guides users toward human-centered AI design and developing AI-enhanced health system solutions.