Comparing the Predictive Power of Heart Failure Hospitalisation Risk Scores in the Diabetic Outpatient Clinic and Primary Care Settings

Abstract Objective Neck pain is a leading cause of years lived with disability and is often managed with opioid medications in primary care settings, though this is contraindicated by national guidelines. The aim of this study was to determine the prevalence of opioid prescription for neck pain at a primary care visit and to analyze the geographic variation and trends in opioid prescriptions between 2011 and 2017. Methods Using a prescription drug claims database, we identified 591,961 adult patients who presented for neck pain in primary care settings between 2011 and 2017. Patients who had outpatient specialty visits within 1 year before presentation, a concomitant diagnosis of a non-musculoskeletal cause of neck pain, or preexisting chronic opioid use were excluded. Results The mean age of the patients was 45 ± 12 years, and 64% were female. Fifteen percent of patients were prescribed opioids within 30 days of their encounter. Eleven percent of patients were prescribed moderate- to high-dose opioids (>20 morphine milligram equivalents). From 2011–2017, the proportion of both overall opioid prescriptions and moderate- to high-dose prescriptions given to first time presenters to an outpatient clinic for neck pain was highest in Mississippi (20%) and lowest in New Mexico (6%) (P < 0.001). In 2017, the proportion of both overall opioid prescriptions and moderate- to high-dose prescriptions was highest in the Midwest (10.4%) and lowest in the Northeast (4.9%). The proportion of patients with filled opioid prescriptions declined between 2011 (19%) and 2017 (13%) (P < 0.001), and the proportion of patients with moderate- to high-dose prescriptions declined from 2011 (13%) to 2017 (8%) (P < 0.001). first-time presenters of neck pain to an outpatient clinic Conclusions Opioid medication use for neck pain in the primary care setting is significant. Although opioid prescriptions are declining, there remains a need for further standardization in prescription practices.

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Introducing nurse-led heart failure clinics in Swedish primary care settings

European Journal of Heart Failure ◽

10.1002/ejhf.1329 ◽

2018 ◽

Vol 21 (1) ◽

pp. 103-109 ◽

Cited By ~ 16

Author(s):

Maria Liljeroos ◽

Anna Strömberg

Keyword(s):

Heart Failure ◽

Primary Care ◽

Primary Care Settings

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MO498INSIDE CKD: MODELLING THE CLINICAL AND ECONOMIC IMPACTS OF TARGETED URINARY ALBUMIN-TO-CREATININE RATIO SCREENING IN EUROPEAN COUNTRIES

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfab087.0018 ◽

2021 ◽

Vol 36 (Supplement_1) ◽

Author(s):

Juan Jose Garcia Sanchez ◽

Alyshah Abdul Sultan ◽

Johan Ärnlöv ◽

Claudia Cabrera ◽

Joshua Card-Gowers ◽

...

Keyword(s):

Heart Failure ◽

Primary Care ◽

Clinical Practice ◽

Economic Impacts ◽

Urinary Albumin ◽

European Countries ◽

Current Clinical Practice ◽

Creatinine Ratio ◽

Primary Care Settings ◽

The Uk

Abstract Background and Aims With an estimated global prevalence of 10% or more, chronic kidney disease (CKD) and its associated complications constitute a major challenge for healthcare systems worldwide, which is worsened by the burden of undiagnosed CKD. Early diagnosis of CKD followed by guideline-recommended interventions can improve patient outcomes, particularly by delaying or preventing progression to kidney failure. This may result in a reduction in the costs associated with managing CKD. Elevated albuminuria is a strong predictor of risk of complications and death in patients with CKD, and measurement of urinary albumin-to-creatinine ratio (UACR) is an important diagnostic and prognostic tool. However, adherence to screening recommendations is suboptimal in routine care. Inside CKD aims to model the global clinical and economic burden of CKD using country-specific, patient-level microsimulation models. We used the Inside CKD microsimulation to model the potential clinical and economic impacts of routine UACR measurement with appropriate intervention in primary care settings in UK patients aged 45 years and over. This analysis is being expanded to further European countries. Method We used the Inside CKD microsimulation to model the clinical and economic impacts of measuring UACR with subsequent appropriate intervention during routine primary care visits in all individuals aged 45 years and over, versus current practice (i.e. screening in patients with diabetes, hypertension or cardiovascular disease). The model covers the period 2020–2025. First, a virtual population representing the general population of the UK was constructed using data from the 2016 Health Survey for England, covering demographics, prevalence of CKD and comorbidities (type 2 diabetes, uncontrolled hypertension and heart failure) and incidence of complications (heart failure, myocardial infarction, stroke and acute kidney injury). The model also included parameters relating to the direct and indirect costs associated with CKD (e.g. cost of renal replacement therapy), the proportion of patients who visit a primary care physician at least once a year, the proportion of patients who agree to UACR measurements, and the diagnostic sensitivity and specificity of UACR measurements. Results Preliminary results from the UK show that over the 2020–2025 period, routinely measuring UACR in all patients aged 45 years and over during primary care visits could prevent progression to CKD stages 3b–5 in approximately 327 000 patients, compared with current clinical practice, with a linear increase in the cumulative number of prevented cases over the 5 years (Figure). Associated savings in costs related to the management of CKD and its complications are projected to be approximately £300M in 2025, corresponding to a 1.9% reduction from current clinical practice. Conclusion Preliminary results from this Inside CKD microsimulation model show that implementation of routine measurement of UACR in primary care settings in the UK could prevent a substantial number of patients progressing to CKD stages 3b–5 and has the potential to reduce the associated healthcare-related costs considerably. This analysis is being extended to other European countries.

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KAsH score beyond myocardial infarction: a new risk stratification tool for myocardial injury?

European Heart Journal ◽

10.1093/ehjci/ehaa946.2915 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

J Sousa ◽

J.P Monteiro ◽

F Mendonca ◽

M Santos ◽

M Temtem ◽

...

Keyword(s):

Myocardial Infarction ◽

Heart Failure ◽

Multivariate Analysis ◽

Hospital Mortality ◽

Myocardial Injury ◽

Predictive Power ◽

Risk Scores ◽

Hemodynamic Variables ◽

Risk Stratification Tool

Abstract Introduction Our group has recently validated and published a new score - KAsH score. KAsH consists of a continuous, multiplicative score based on 4 simple clinical variables available at first medical contact, proven to be a robust predictor of in-hospital mortality and all-cause mortality at 1 year follow-up in patients with myocardial infarction, putting it next to other well established risk scores. However, the role of KAsH in patients with myocardial injury (Mi), a largely uncharacterized group in the literature, remains unknown. Purpose We aim to assess the predictive power of KAsH in patients with myocardial injury (Mi), regarding in-hospital mortality and at 1 year follow-up. Methods Prospective registry of 250 patients admitted consecutively through the emergency department from January 2018 onward, with higher than P99th high-sensitive troponin assay. The kit used was Roche's Elecsys hsSTAT, and the P99th appointed by the manufacturer was 14 ng/L. All patients with chronic kidney disease ClCr<15ml/min and myocardial infarction, were excluded from the analysis. We were left with 236 patients diagnosed with Mi. KAsH = (Killip Kimbal × Age × Heart Rate) / Systolic BP We used a simplified Killip classification: without heart failure (1 point), with heart failure (2 points) and in shock (3 points). We assessed the score's association to mortality and its predictive value through ROC curves and their respective area under the curve (AUC). Results Both Killip and KAsH had a significant and positive association with in-hospital mortality (KK: p=0.02; KAsH: p<0.001) and cumulative mortality (KK: p=0.002; KAsH: p=0.008). In multivariate analysis, KAsH score as a continuous variable proved to be an independent predictor of in-hospital mortality (p=0.004) but not KK classification (p=0.96). We then categorized KAsH in its 4 different strata (1–4). Multivariate analysis indentified categorized KAsH as the only significant predictor of in-hospital mortality (OR 4.1, CI 2.1–8.1, p<0.001), with the predictive power of KAsH being even mildly superior (AUCs: KAsHcont 0.767, KAsHcat 0.743, KK 0.685). However, the same trend was not observed during follow-up, as none of them were significant predictors of mortality (all p>0.1). Conclusions KAsH seems to maintain its in-hospital predictive value even in patients with Mi. To our knowledge, this is the first study that tries to apply risk scores and stratification tools to such a heterogeneous group of patients. By comprising hemodynamic variables, KAsH may actually be a better risk stratification tool than just the severity of heart failure on admission. However, unlike previously proven in myocardial infarction (MI), KAsH score and its hemodynamic variables do not seem to justify the high mortality on the long run behind these patients. More studies will be needed to address the complex causes behind long-term mortality of Mi patients. KASH table graph Funding Acknowledgement Type of funding source: None

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