Intermountain Healthcare Research Articles

Abstract 10083: Cardiovascular Outcomes of Non-ST-Elevation Myocardial Infarction (NSTEMI) Patients Without Standard Modifiable Risk Factors (SMuRF-less): The Intermountain Healthcare Experience

Introduction: Recent interest has focused on STEMI patients (pts) without standard modifiable risk factors (SMuRF-less), noting that they are surprisingly common (14-27%). These studies have reported them to have a worse, or at best similar, in-hospital/short-term prognosis. However, relatively little attention has been paid to the prevalence and prognosis of SMuRF-less patients with non-ST elevation myocardial infarction (NSTEMI). The aim of our study was to identify the proportion and outcomes of SMuRF-less NSTEMI pts in a large US healthcare population. Methods: Pts with NSTEMI between 2001-2021 presenting to Intermountain Healthcare catheterization laboratories were included. SMuRF included a clinical diagnosis of, or treatment for, hypertension, hyperlipidemia, diabetes, and/or smoking. 60-day and long-term major adverse cardiovascular event (MACE) outcomes were defined as death, myocardial infarction, and heart failure hospitalization and were tested using Cox proportional hazard regression. Results: NSTEMI pts totaled 8196, of which1458 (17.8%) were SMuRF-less. SMuRF-less pts were younger, more frequently male, had fewer comorbidities, and were slightly less likely to have PCI/CABG than NSTEMI pts with SMuRF (Table 1). 60-day MACE for SMuRF-less pts were lower (adj HR 0.55, p<0.0001), and this persisted for long-term MACE outcomes (adj HR 0.64, p<0.0001) and for each of its components (Table 2). Conclusions: In this large US healthcare population, SMuRF-less NSTEMI presentation, as with STEMI presentation, was found to be common (17.8%). However, unlike STEMI reports, short- and long-term outcomes were generally more favorable for SMuRF-less status. Further studies to increase understanding of risk factors and preventive measures for NSTEMI in SMuRF-less pts are indicated.

Abstract 11600: Characteristics and Outcomes of Statin Use During Pregnancy: A US Real-World Experience

Introduction: Statins traditionally have been contraindicated during pregnancy because of a theoretical risk of teratogenicity. However, emerging evidence to suggest relative safety and potential harm in contraindicating statins in high cardiovascular (CV)-risk pregnancies have led the FDA in 2021 to remove the “Pregnancy Category X” label. This has placed a heavy burden on physician-patient (pt) shared decision making in that statins “should be discontinued in most pregnant patients or consider the ongoing therapeutic needs of the individual pt, particularly those at very high risk for CV events during pregnancy”. Methods: The objective of this study was to describe the current real-world characteristics of pts prescribed a statin during pregnancy and pregnancy outcomes in a large US healthcare system. Pregnant pts taking a statin were identified by a search of the electronic medical records (eMR) of Intermountain Healthcare, a system of 24 hospitals and 215 clinics in Utah, Idaho, and Nevada, between 1997 and 2021, and pregnancy outcomes determined electronically. Statin pts were matched 1:10 by age (+/- 1 y) with non-statin pts. Characteristics and outcomes were determined, and adjusted odds ratios (aOR) were calculated. Results: A total of 63 statin-user pregnancies were matched to 630 controls. Stain pts had more co-morbidities and higher baseline lipids (Table 1). Adverse pregnancy outcomes were more frequent in statin users (Table 2A). However, statin use did not contribute significantly to multivariable risk prediction of miscarriage or congenital anomalies although possibly it did to eclampsia/preeclampsia (Table 2B). Conclusions: In a current real-world US experience, pts prescribed statins during pregnancy had more comorbidities and more adverse outcomes, including fetal anomalies. However, after adjustment, statin use did not contribute to multivariable risk prediction of miscarriage or congenital anomalies.

Intermountain Healthcare's Hospital-Level Care at Home Program.

Intermountain Healthcare's Hospital-Level Care at Home Program.

A pilot intervention to improve health insurance literacy and financial toxicity among recently diagnosed adolescents and young adults with cancer.

218 Background: Adolescents and young adults (AYAs; ages 18-39) with cancer report worries about costs and feeling uninformed about their insurance, which may impair their ability to navigate the health care system, use their insurance, and manage costs. We conducted a pilot randomized controlled trial (RCT) to assess a virtually delivered health insurance navigation intervention (“CHAT”) to improve health insurance literacy (HIL) and knowledge, increase awareness of insurance protections in the Affordable Care Act (ACA), and reduce financial toxicity and stress. Methods: CHAT is a 4-session program delivered by a patient navigator. Session content included learning about insurance, navigating your plan, insurance-related laws, & managing care costs. Eligible participants had access to a wireless device, were within their first year of cancer diagnosis, and were treated at oncology sites from the University of Utah Healthcare and Intermountain Healthcare systems. We assessed feasibility and preliminary efficacy of CHAT compared to usual navigation care, including HIL (9 items on confidence using insurance), insurance knowledge (13 items on terms such as deductible & copay), ACA protections (8 items), Perceived Stress Scale (PSS; 4 items), and COmprehensive Score for financial Toxicity (COST; 11 items) using t-tests. Results: From November 2020 to January 2022, 86 AYAs enrolled (46.2% approached consented); 68.6% were female, 72.1% white, 18.6% Hispanic, 34.9% age 18-25, 65.1% age 26-39, 83.7% had private insurance, and 10.5% public. Mean baseline HIL scores were 22.6 (range = 9-33, SD = 5.5). At baseline, 65.1% of participants were unaware of the ACA provision allowing appeals for coverage denials. 64.4% of intervention participants completed all 4 sessions; 86.0% completed the 5-month follow-up survey with data collection ongoing (74/86). At follow-up, compared to usual navigation care, CHAT participants had improvements in HIL, knowledge of insurance, and knowledge of ACA provisions (Table). While PSS improved more for CHAT than usual care, COST did not differ. Conclusions: Results support the feasibility and preliminary efficacy of CHAT with related improvements in HIL and knowledge of the ACA. Clinical trial information: NCT04448678. [Table: see text]

Remote Biometric Monitoring of Patients With COVID-19 With Exertional Hypoxia Treated With Supplemental Oxygen

Remote Biometric Monitoring of Patients With COVID-19 With Exertional Hypoxia Treated With Supplemental Oxygen

Unrecognized Severe Anemia in Neonates

Unrecognized Severe Anemia in Neonates

Standard Vocabularies to Improve Machine Learning Model Transferability With Electronic Health Record Data: Retrospective Cohort Study Using Health Care-Associated Infection.

BackgroundWith the widespread adoption of electronic healthcare records (EHRs) by US hospitals, there is an opportunity to leverage this data for the development of predictive algorithms to improve clinical care. A key barrier in model development and implementation includes the external validation of model discrimination, which is rare and often results in worse performance. One reason why machine learning models are not externally generalizable is data heterogeneity. A potential solution to address the substantial data heterogeneity between health care systems is to use standard vocabularies to map EHR data elements. The advantage of these vocabularies is a hierarchical relationship between elements, which allows the aggregation of specific clinical features to more general grouped concepts.ObjectiveThis study aimed to evaluate grouping EHR data using standard vocabularies to improve the transferability of machine learning models for the detection of postoperative health care–associated infections across institutions with different EHR systems.MethodsPatients who underwent surgery from the University of Utah Health and Intermountain Healthcare from July 2014 to August 2017 with complete follow-up data were included. The primary outcome was a health care–associated infection within 30 days of the procedure. EHR data from 0-30 days after the operation were mapped to standard vocabularies and grouped using the hierarchical relationships of the vocabularies. Model performance was measured using the area under the receiver operating characteristic curve (AUC) and F1-score in internal and external validations. To evaluate model transferability, a difference-in-difference metric was defined as the difference in performance drop between internal and external validations for the baseline and grouped models.ResultsA total of 5775 patients from the University of Utah and 15,434 patients from Intermountain Healthcare were included. The prevalence of selected outcomes was from 4.9% (761/15,434) to 5% (291/5775) for surgical site infections, from 0.8% (44/5775) to 1.1% (171/15,434) for pneumonia, from 2.6% (400/15,434) to 3% (175/5775) for sepsis, and from 0.8% (125/15,434) to 0.9% (50/5775) for urinary tract infections. In all outcomes, the grouping of data using standard vocabularies resulted in a reduced drop in AUC and F1-score in external validation compared to baseline features (all P<.001, except urinary tract infection AUC: P=.002). The difference-in-difference metrics ranged from 0.005 to 0.248 for AUC and from 0.075 to 0.216 for F1-score.ConclusionsWe demonstrated that grouping machine learning model features based on standard vocabularies improved model transferability between data sets across 2 institutions. Improving model transferability using standard vocabularies has the potential to improve the generalization of clinical prediction models across the health care system.

Staphylococcal scalded skin syndrome: Clinical features, ancillary testing, and patient management.

The utility of ancillary testing in improving diagnostic precision or improving patient outcomes in staphylococcal scalded skin syndrome (SSSS) is unclear. Similarly, an optimal antibiotic regimen has yet to be established. Our goal was to describe clinical characteristics and ancillary work-up of SSSS, report bacterial resistance patterns, and examine patient outcomes under varying therapeutic strategies with the aim of developing an evidence-based management algorithm. We performed a retrospective review of pediatric patients diagnosed with SSSS at Intermountain Healthcare facilities between 2010 and 2021. A Kruskal-Wallis rank sum test was used to assess median length of stay between different antibiotic regimens. Eighty-five cases were identified. The most common ancillary tests obtained were a complete blood count (88%), followed by chemistry analysis (80%). Blood cultures were collected in more patients (79%) compared to aerobic cultures (60%). No blood culture was positive for Staphylococcus aureus. All S. aureus isolates were methicillin-sensitive. Of those found resistant to clindamycin (36%), all demonstrated macrolide-induced clindamycin resistance. None were constitutively resistant to clindamycin. There was no statistical difference between antibiotic regimen and length of stay (p=.691). Receiving opiate medications was the only risk factor associated with prolonged hospitalization (p=.001). Ancillary testing does not improve diagnostic precision and can be reduced. Clindamycin does not improve patient outcomes, suggesting beta-lactams should be considered first line. Susceptibility patterns in our cohort demonstrate inducible clindamycin resistance as opposed to constitutive.

Severe Anemia at Birth—Incidence and Implications

To identify neonates with severe anemia at birth, defined by a hemoglobin or hematocrit value within the first 6hours after birth that plotted below the 1st percentile according to gestational age. For each patient, we retrospectively determined whether caregivers recognized the anemia within the first 24hours after birth and the probable cause and outcome of anemia. This was a retrospective cohort analysis of Intermountain Healthcare population-based data from neonates born between January 2011 and December 2020 who had a hemoglobin or hematocrit value measured within the first 6hours after birth below the 1st percentile lower reference interval (hematocrit ∼35% in near-term/term neonates). Among 299 927 live births, we identified 344 neonates with severe anemia at birth. In 191 of these neonates (55.5%), the anemia was recognized by caregivers during the first 24hours. Anemia was more likely to be recorded as a problem (85%) if the hemoglobin was ≥2g/dL below the 1st percentile (P<.001). The lowest hemoglobin values occurred in those in whom hemorrhage was the probable cause (P<.013 vs hemolysis and P<.001 vs hypoproduction, mixed cause, or indeterminant.) Treatment was provided to 39.5%. A retrospective review suggested that mixed mechanisms, particularly hemorrhagic plus hemolytic, occurred more commonly than was recognized at the time of occurrence. Severe anemia at birth often went unrecognized on the first day of life. Algorithm-directed retrospective reviews commonly identified causes that were not listed in the medical record. We postulate that earlier recognition and more accurate diagnoses would be facilitated by an electronic medical record-associated hemoglobin/hematocrit gestational age nomogram.

Concordance of MRI-Guided Fusion and Systematic 12-Core Prostate Biopsy for the Detection of Prostate Cancer.

BackgroundMRI-guided fusion biopsy is increasingly utilized over systematic 12-core biopsy for men with MRI-visible prostate lesions.Patients and MethodsPatients with MRI visible lesions who underwent MRI-guided fusion and systematic 12-core biopsy from 2016-2020 in the Intermountain Healthcare (IHC) system were consecutively analyzed. This was in the setting of a continuous quality assurance initiative among the reading radiologists. Primary outcome was prostate cancer (PCa) detection defined by Gleason grade group (GGG) 1 or higher. Clinically significant cancer (CSC) was defined as GGG 2 or higher. Patients were stratified by biopsy date, 2016-2017 and 2018-2021, and lesions were stratified by PI-RADS v2 category.ResultsA total of 184 patients with 324 MRI-detectable lesions underwent both biopsy modalities in the IHC system from 2016 to 2021. CSC was detected in 23.5% of MRI-guided fusion biopsies. Comparing PI-RAD v2 categories 1-3 to categories 4-5, rate of CSC was 10% and 42% respectively. MRI-guided fusion and systematic 12-core biopsies were concordant for PCa in 77% of men and CSC in 83%. MRI-guided fusion biopsy detected PCa in 26/103 and CSC in 20/131 men in whom systematic 12-core biopsy was negative. Systematic 12-core biopsy detected PCa in 17/94 and CSC in 11/122 men in whom MRI-guided fusion was negative.ConclusionsOmitting MRI-guided fusion or systematic 12-core biopsy would have resulted in underdiagnosis of CSC in 11% or 6% of patients respectively. Combining biopsies increased detection rate of CSC. This was in the setting of a continuous quality assurance program at a large community-based hospital.

Rapid streptococcal pharyngitis testing and antibiotic prescribing before and during the COVID-19 pandemic

Background: Pharyngitis is 1 of the most common conditions leading to inappropriate antibiotic prescriptions. When personal protective equipment (PPE) was at first constrained during the COVID-19 pandemic, Intermountain Healthcare recommended limiting rapid group A streptococcal pharyngitis (GAS) testing in urgent-care clinics to preserve PPE. Notably, the percentage of pharyngitis encounters prescribed an antibiotic and that underwent GAS testing is a key Healthcare Effectiveness Data and Information Set (HEDIS) measure. We have described our experience with urgent-care pharyngitis encounters and the impact of temporarily reducing GAS testing on antibiotic prescribing before and during the COVID19 pandemic. Method: We identified all urgent care encounters between July 2018 and August 2021 associated with a primary diagnosis of pharyngitis using ICD-10 CM codes and a validated methodology. Pharyngitis encounters were assessed for antibiotic prescriptions ordered through the electronic health record (EHR) and the use of point-of-care rapid GAS tests. Pharyngitis encounters were analyzed monthly. We assessed the percentage of encounters associated with an antibiotic prescription regardless of testing and the percentage of encounters associated with an antibiotic prescription when a GAS test was or was not performed. We examined 3 periods relating to COVID-19 and GAS testing recommendations: the prepandemic period (July 2018–March 2020), the pandemic onset period (April 2020–June 2020), and the pandemic period (July 2020–August 2021). Results: Prior to the pandemic, the monthly percentage of pharyngitis encounters for which rapid GAS testing was performed was nearly 90% (Fig. 1). The average monthly percentage of urgent-care pharyngitis encounters prescribed an antibiotic was 38.9%, and the average percentage of monthly pharyngitis encounters prescribed an antibiotic that also underwent GAS testing was 90.4%. This HEDIS measure declined from 90.4% during the prepandemic period to 29.8% in the pandemic onset period when GAS testing was limited. Following resumption of routine testing practices the monthly percentage of urgent-care pharyngitis encounters for which rapid GAS testing was performed returned to levels ≥80% by July 2020 (Fig. 1). The average percentage of monthly pharyngitis encounters prescribed an antibiotic that also underwent GAS testing rose to 87.3% during this period. Conclusions: Limited PPE in our urgent care centers during the initial months of the COVID-19 pandemic was associated with a mandated substantial decline in rapid GAS testing. As testing volume decreased, we noted a simultaneous relative increase of &gt;30% in antibiotic prescribing for pharyngitis. These findings suggest that rapid streptococcal testing promotes appropriate antibiotic prescribing.Funding: NoneDisclosures: None

Prognostic Accuracy of Presepsis and Intrasepsis Characteristics for Prediction of Cardiovascular Events After a Sepsis Hospitalization.

OBJECTIVES:Sepsis survivors face increased risk for cardiovascular complications; however, the contribution of intrasepsis events to cardiovascular risk profiles is unclear.SETTING:Kaiser Permanente Northern California (KPNC) and Intermountain Healthcare (IH) integrated healthcare delivery systems.SUBJECTS:Sepsis survivors (2011–2017 [KPNC] and 2018–2020 [IH]) greater than or equal to 40 years old without prior cardiovascular disease.DESIGN:Data across KPNC and IH were harmonized and grouped into presepsis (demographics, atherosclerotic cardiovascular disease scores, comorbidities) or intrasepsis factors (e.g., laboratory values, vital signs, organ support, infection source) with random split for training/internal validation datasets (75%/25%) within KPNC and IH. Models were bidirectionally, externally validated between healthcare systems.INTERVENTIONS:None.MEASUREMENTS AND MAIN RESULTS:Changes to predictive accuracy (C-statistic) of cause-specific proportional hazards models predicting 1-year cardiovascular outcomes (atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation events) were compared between models that did and did not contain intrasepsis factors. Among 39,590 KPNC and 16,388 IH sepsis survivors, 3,503 (8.8%) at Kaiser Permanente (KP) and 600 (3.7%) at IH experienced a cardiovascular event within 1-year after hospital discharge, including 996 (2.5%) at KP and 192 (1.2%) IH with an atherosclerotic event first, 564 (1.4%) at KP and 117 (0.7%) IH with a heart failure event, 2,310 (5.8%) at KP and 371 (2.3%) with an atrial fibrillation event. Death within 1 year after sepsis occurred for 7,948 (20%) KP and 2,085 (12.7%) IH patients. Combined models with presepsis and intrasepsis factors had better discrimination for cardiovascular events (KPNC C-statistic 0.783 [95% CI, 0.766–0.799]; IH 0.763 [0.726–0.801]) as compared with presepsis cardiovascular risk alone (KPNC: 0.666 [0.648–0.683], IH 0.660 [0.619–0.702]) during internal validation. External validation of models across healthcare systems showed similar performance (KPNC model within IH data C-statistic: 0.734 [0.725–0.744]; IH model within KPNC data: 0.787 [0.768–0.805]).CONCLUSIONS:Across two large healthcare systems, intrasepsis factors improved postsepsis cardiovascular risk prediction as compared with presepsis cardiovascular risk profiles. Further exploration of sepsis factors that contribute to postsepsis cardiovascular events is warranted for improved mechanistic and predictive models.

Real-world clinical burden and economic assessment associated with hyperkalaemia in a large integrated healthcare system: a retrospective analysis

BackgroundHyperkalaemia (HK) is a serious and potentially life-threatening condition. Both acute and chronic conditions may alter potassium homeostasis. Our aim is to describe HK incidence, clinical outcomes, and associated resource use within a large, integrated healthcare system.MethodsAdult patients seen at Intermountain Healthcare facilities with a serum potassium (sK) result between January 1, 2003 and December 31, 2018 were retrospectively studied. Descriptive assessment of a population with detected HK, defined by any sK > 5.0 mmol/L and HK frequency and severity to associated resource use and characteristics of HK predictors were made. Multivariable Cox hazard regression was used to evaluate HK to outcomes.ResultsOf 1,208,815 patients included, 13% had HK. Compared to no-HK, HK patients were older (60 ± 18 vs 43 ± 18 years, P < 0.001), male (51% vs 41%, P < 0.001), and had greater disease burden (Charlson Comorbidity Index 3.5 ± 2.8 vs 1.7 ± 1.4, P < 0.001). At 3 years, more HK patients experienced major adverse cardiovascular events (MACEs) (19 vs 3%, P < 0.001), persisting post-adjustment (multivariable hazard ratio = 1.60, P < 0.001). They incurred higher costs for emergency department services ($552 ± 7,574 vs $207 ± 1,930, P < 0.001) and inpatient stays ($10,956 ± 93,026 vs $1,477 ± 21,423, P < 0.001). HyperK Risk Scores for the derivation and validation cohorts were: 44% low-risk, 45% moderate-risk, 11% high-risk. Strongest HK predictors were renal failure, dialysis, aldosterone blockers, diabetes, and smoking.ConclusionWithin this large system, HK was associated with a large clinical burden, affecting over 1 in 10 patients; HK was also associated with increased 3-year MACE risk and higher medical costs. Although risk worsened with more severe or persistently recurring HK, even mild or intermittent HK episodes were associated with significantly greater adverse clinical outcomes and medical costs. The HyperK Score predicted patients who may benefit from closer management to reduce HK risk and associated costs. It should be remembered that our assumptions are valid only for detected HK and not HK per se.

Simple scoring tool to estimate risk of hospitalization and mortality in ambulatory and emergency department patients with COVID-19.

Accurate methods of identifying patients with COVID-19 who are at high risk of poor outcomes has become especially important with the advent of limited-availability therapies such as monoclonal antibodies. Here we describe development and validation of a simple but accurate scoring tool to classify risk of hospitalization and mortality. All consecutive patients testing positive for SARS-CoV-2 from March 25-October 1, 2020 within the Intermountain Healthcare system were included. The cohort was randomly divided into 70% derivation and 30% validation cohorts. A multivariable logistic regression model was fitted for 14-day hospitalization. The optimal model was then adapted to a simple, probabilistic score and applied to the validation cohort and evaluated for prediction of hospitalization and 28-day mortality. 22,816 patients were included; mean age was 40 years, 50.1% were female and 44% identified as non-white race or Hispanic/Latinx ethnicity. 6.2% required hospitalization and 0.4% died. Criteria in the simple model included: age (0.5 points per decade); high-risk comorbidities (2 points each): diabetes mellitus, severe immunocompromised status and obesity (body mass index≥30); non-white race/Hispanic or Latinx ethnicity (2 points), and 1 point each for: male sex, dyspnea, hypertension, coronary artery disease, cardiac arrythmia, congestive heart failure, chronic kidney disease, chronic pulmonary disease, chronic liver disease, cerebrovascular disease, and chronic neurologic disease. In the derivation cohort (n = 16,030) area under the receiver-operator characteristic curve (AUROC) was 0.82 (95% CI 0.81-0.84) for hospitalization and 0.91 (0.83-0.94) for 28-day mortality; in the validation cohort (n = 6,786) AUROC for hospitalization was 0.8 (CI 0.78-0.82) and for mortality 0.8 (CI 0.69-0.9). A prediction score based on widely available patient attributes accurately risk stratifies patients with COVID-19 at the time of testing. Applications include patient selection for therapies targeted at preventing disease progression in non-hospitalized patients, including monoclonal antibodies. External validation in independent healthcare environments is needed.

Effect of COVID 19 pneumonia on hyperglycemia: Is it different from non COVID pneumonia?

Background and aimsGlycemic control in critical illness has been linked to outcomes. We sought to investigate if COVID pneumonia was causing disrupted glycemic control compared to historically similar diseases. MethodsAt Intermountain Healthcare, a 23-hospital healthcare system in the intermountain west, we performed a multicenter, retrospective cohort observational study. We compared 13,268 hospitalized patients with COVID pneumonia to 6673 patients with non -COVID-pneumonia. ResultsPatients with COVID-19 were younger had fewer comorbidities, had lower mortality and greater length of hospital stay. Our regression models demonstrated that daily insulin dose, indexed for weight, was associated with COVID-19, age, diabetic status, HgbA1c, admission SOFA, ICU length of stay and receipt of corticosteroids. There was significant interaction between a diagnosis of diabetes and having COVID-19. Time in range for our IV insulin protocol was not correlated with having COVID after adjustment. It was correlated with ICU length of stay, diabetic control (HgbA1C) and prior history of diabetes. Among patients with subcutaneous (SQ) insulin only percent of glucose checks in range was correlated with diabetic status, having Covid-19, HgbA1c, total steroids given and Elixhauser comorbidity score even when controlled for other factors. ConclusionsHospitalized patients with COVID-19 pneumonia who receive insulin for glycemic control require both more SQ and IV insulin than the non-COVID-19 pneumonia counterparts. Patients with COVID-19 who received SQ insulin only had a lower percent of glucose checks in range.

Economics and outcomes of sotalol in-patient dosing approaches in patients with atrial fibrillation.

IntroductionThere exists variability in the administration of in‐patient sotalol therapy for symptomatic atrial fibrillation (AF). The impact of this variability on patient in‐hospital and 30‐day posthospitalization costs and outcomes is not known. Also, the cost impact of intravenous sotalol, which can accelerate drug loading to therapeutic levels, is unknown.MethodsOne hundred and thirty‐three AF patients admitted for oral sotalol initiation at an Intermountain Healthcare Hospital from January 2017 to December 2018 were included. Patient and dosing characteristics were described descriptively and the impact of dosing schedule was correlated with daily hospital costs/clinical outcomes during the index hospitalization and for 30 days. The Centers for Medicare and Medicaid Services reimbursement for 3‐day sotalol initiation is $9263.51. Projections of cost savings were made considering a 1‐day load using intravenous sotalol that costs $2500.00 to administer.ResultsThe average age was 70.3 ± 12.3 years and 60.2% were male with comorbidities of hypertension (83%), diabetes (36%), and coronary artery disease (53%). The mean ejection fraction was 59.9 ± 7.8% and the median corrected QT interval was 453.7 ± 37.6 ms before sotalol dosing. No ventricular arrhythmias developed, but bradycardia (<60 bpm) was observed in 37.6% of patients. The average length of stay was 3.9 ± 4.6 (median: 2.2) days. Postdischarge outcomes and rehospitalization rates stratified by length of stay were similar. The cost per day was estimated at $2931.55 (1. $2931.55, 2. $5863.10, 3. $8794.65, 4. $11 726.20).ConclusionsIn‐patient oral sotalol dosing is markedly variable and results in the potential of both cost gain and loss to a hospital. In consideration of estimated costs, there is the potential for $871.55 cost savings compared to a 2‐day oral load and $3803.10 compared to a 3‐day oral load.

Insulin Growth Factor Phenotypes in Heart Failure With Preserved Ejection Fraction, an INSPIRE Registry and CATHGEN Study

BackgroundThe insulin-like growth factor (IGF) axis emerged as an important pathway in heart failure with preserved ejection (HFpEF). We aimed to identify IGF phenotypes associated with HFpEF in the context of high-dimensional proteomic profiling. MethodsFrom the INtermountain Healthcare Biological Samples Collection Project and Investigational REgistry for the On-going Study of Disease Origin, Progression and Treatment (Intermountain INSPIRE Registry), we identified 96 patients with HFpEF and matched controls. We performed targeted proteomics, including IGF-1,2, IGF binding proteins (IGFBP) 1–7 and 111 other proteins (EMD Millipore and ELISA). We used partial least square discriminant analysis (PLS-DA) to identify a set of proteins associated with prevalent HFpEF, pulmonary hypertension and 5-year all-cause mortality. K-mean clustering was used to identify IGF phenotypes. ResultsPatients with HFpEF had a high prevalence of systemic hypertension (95%) and coronary artery disease (74%). Using PLS-DA, we identified a set of biomarkers, including IGF1,2 and IGFBP 1,2,7, that provided a strong discrimination of HFpEF, pulmonary hypertension and mortality with an area under the curve of 0.91, 0.77 and 0.83, respectively. Using K mean clustering, we identified 3 IGF phenotypes that were independently associated with all-cause 5-year mortality after adjustment for age, NT-proBNP and kidney disease (P = 0.004). Multivariable analysis validated the prognostic value of IGFBP-1 and 2 in the CATHeterization GENetics (CATHGEN) biorepository. ConclusionIGF phenotypes were associated with pulmonary hypertension and mortality in HFpEF.

A Small but Significantly Greater Incidence of Inflammatory Heart Disease Identified After Vaccination for Severe Acute Respiratory Syndrome Coronavirus 2.

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines are being administered on an unprecedented scale. Assessing the risks of side effects is needed to aid clinicians in early detection and treatment. This study examined the risk of inflammatory heart disease, including pericarditis and myocarditis, after SARS-CoV-2 vaccination.MethodsIntermountain Healthcare patients with inflammatory heart disease from December 15, 2020 to June 15, 2021, and with or without preceding SARS-CoV-2 vaccinations, were studied. Relative rates of inflammatory heart disease were examined for vaccinated patients compared to unvaccinated patients.ResultsOf 67 patients identified with inflammatory heart disease, 21 (31.3%) had a SARS-Cov-2 vaccination within the previous 60 days. Overall, 914 611 Intermountain Healthcare patients received a SARS-CoV-2 vaccine, resulting in an inflammatory heart disease rate of 2.30 per 100 000 vaccinated patients. The relative risk of inflammatory heart disease for the vaccinated patients compared to the unvaccinated patients was 2.05 times higher rate within the 30-day window (P = .01) and had a trend toward increase in the 60-day window (relative rate = 1.63; P = .07). All vaccinated patients with inflammatory heart disease were treated successfully with 1 death related to a pre-existing condition.ConclusionsAlthough rare, the rate of inflammatory heart disease was greater in a SARS-CoV-2-vaccinated population than the unvaccinated population. This risk is eclipsed by the risk of contracting coronavirus disease 2019 and its associated, commonly severe outcomes. Nevertheless, clinicians and patients should be informed of this risk to facilitate earlier recognition and treatment.

The silent and dangerous inequity around access to COVID-19 testing: A call to action.

The silent and dangerous inequity around access to COVID-19 testing: A call to action.

A Novel Program to Provide Drug Recovery Assistance and Outpatient Parenteral Antibiotic Therapy in People Who Inject Drugs.

BackgroundSafe hospital discharge on parenteral antibiotic therapy is challenging for people who inject drugs (PWID) admitted with serious bacterial infections (SBI). We describe a Comprehensive Care of Drug Addiction and Infection (CCDAI) program involving a partnership between Intermountain Healthcare hospitals and a detoxification facility (DF) to provide simultaneous drug recovery assistance and parenteral antibiotic therapy (DRA-OPAT).MethodsThe CCDAI program was evaluated using a pre-/poststudy design. We compared outcomes in PWID hospitalized with SBI during a 1-year postimplementation period (2018) with similar patients from a historical control period (2017), identified by propensity modeling and manual review.ResultsEighty-seven patients were candidates for the CCDAI program in the implementation period. Thirty-five participants (40.2%) enrolled in DRA-OPAT and discharged to the DF; 16 (45.7%) completed the full outpatient parenteral antibiotic therapy (OPAT) duration. Fifty-one patients with similar characteristics were identified as a preimplementation control group. Median length of stay (LOS) was reduced from 22.9 days (interquartile interval [IQI], 9.8–42.7) to 10.6 days (IQI, 6–17.4) after program implementation (P < .0001). Total median cost decreased from $39 220.90 (IQI, $23 300.71–$82 506.66) preimplementation to $27 592.39 (IQI, $18 509.45–$48 369.11) postimplementation (P < .0001). Ninety-day readmission rates were similar (23.5% vs 24.1%; P = .8). At 1-year follow-up, all-cause mortality was 7.1% in the preimplementation group versus 1.2% postimplementation (P = .06).ConclusionsPartnerships between hospitals and community resources hold promise for providing resource-efficient OPAT and drug recovery assistance. We observed significant reductions in LOS and cost without increases in readmission rates; 1-year mortality may have been improved. Further study is needed to optimize benefits of the program.