Abstract 106: A Dedicated Atrial Fibrillation Program Improves Catheter Ablation Outcomes and Electrophysiology Lab Resource Utilization

2016 ◽  
Vol 9 (suppl_2) ◽  
Author(s):  
Donna M Suter ◽  
Lisa J Greenwood ◽  
Kevin C Floyd ◽  
Lawrence S Rosenthal ◽  
Cynthia A Ennis ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Real Time ◽  
Resource Utilization ◽  
Process Improvement ◽  
Intervention Group ◽  
Adverse Outcomes ◽  
Complex Data ◽  
Average Case ◽  
Case Duration ◽  
The Impact

Introduction: Atrial fibrillation (AF) is a common condition that adversely impacts quality of life, reduces survival and requires significant healthcare resource utilization. Catheter-based ablation is an effective tool commonly used in the management of symptomatic AF patients, but it remains technically and logistically complex. Data describing the impact of team-based process improvement initiatives on laboratory resource utilization and outcomes of AF ablation are limited. To address this knowledge gap, we examined the impact of a real-time review of quality indicators and systems-based process improvement (PI) initiative on outcomes and resource utilization over 5 years. Methods: We developed an AF Treatment Program to conduct real-time review of ablation outcomes and lab resource utilization to facilitate PI and promote accountability. Key stakeholders and operational deficiencies were identified, and process changes, when needed, were implemented. Real-time feedback on performance was given and monthly results posted. In this analysis we examine the impact of our AF PI initiative on case start times, case duration, procedural adverse outcomes and ablation success rates. Results: Over the study period, concurrent with PI efforts, the rate of adverse outcomes decreased from 16.7% to 1.9% (p=0.03), average case start time improved by 85% (p=0.04), and the mean case duration decreased by 70 minutes (p=0.11). Maintenance of sinus rhythm at 1 year for the pre-intervention group was 78% versus 83% during the most recent study year (p=0.04). Conclusions: A continuous quality improvement AF program was associated with significant declines in adverse event rates and increased laboratory efficiencies, without adversely affecting long-term ablation outcomes. Although the non-randomized nature of our study precludes assumptions of causality, we hypothesize that real-time review and feedback was a major driver of performance improvement.

Abstract 14499: Impact of Pre-existing and New Incident Atrial Fibrillation on Outcomes of Patients With Acute Pulmonary Embolism: Findings From an International Registry

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Behnood Bikdeli ◽  
David Jimenez ◽  
Jorg Del Toro ◽  
Gregory Piazza ◽  
Augussina Rivas ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Pulmonary Embolism ◽  
Ischemic Stroke ◽  
Acute Pulmonary Embolism ◽  
Adverse Outcomes ◽  
Risk Of Mortality ◽  
Patient Groups ◽  
The Impact ◽  
Related Mortality

Background: Atrial fibrillation (AF) may occur prior to or early in the course of acute pulmonary embolism (PE). The impact of AF on outcomes of patients with PE remains uncertain. Methods: Using the data from a large prospective multicenter registry of patients with objectively-confirmed PE (04/2014 to 01/2020), we identified three patient groups: 1) those with pre-existing AF 2) patients with newly identified AF within 2 days from the index PE (incident AF) and 3) patients without AF. We assessed the 90-day and 1-year risk of mortality and stroke in patients with AF, in unadjusted and multivariable adjusted models considering those without AF as referent. Results: Among 16,497 patients with PE, 792 had pre-existing AF. Compared with those without AF, patients with pre-existing AF, had increased odds of 90-day all-cause (Odds ratio [OR]: 2.81 (95% confidence interval [CI]: 2.33-3.38) and PE-related mortality (OR: 2.38, 95% CI: 1.37-4.14). After multivariable adjustment, pre-existing AF significantly increased the odds of all-cause mortality (OR: 1.91, 95% CI: 1.57-2.32) but not PE-related mortality (OR: 1.50; 95% CI: 0.85-2.66). Pre-existing AF was associated with increased hazard for ischemic stroke at 1-year follow-up (hazard ratio [HR]: 5.48; 95% CI: 3.10-9.69). Among 16,497 patients with PE, 445 developed incident AF within 2 days of acute PE. Incident AF was associated with increased odds of 90-day all-cause (OR: 2.28; 95% CI: 1.75-2.97) and PE-related (OR: 3.64; 95% CI: 2.01-6.59) mortality. Findings were similar in multivariable analyses and at 1-year follow-up (Figure). No patients with incident AF developed ischemic stroke. Conclusion: In patients with acute symptomatic PE, both pre-existing AF and incident AF predict an adverse clinical course, although the type of adverse outcomes may be different depending on the timing of AF onset.

Abstract P369: Polypharmacy, Adverse Outcomes, and Treatment Effectiveness in Elderly Patients With Atrial Fibrillation

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Aniqa Alam ◽  
Nemin Chen ◽  
Pamela L Lutsey ◽  
Richard MacLehose ◽  
J'Neka Claxton ◽  
...  
Keyword(s):  
Heart Failure ◽  
Atrial Fibrillation ◽  
Ischemic Stroke ◽  
Elderly Patients ◽  
Rate Control ◽  
Treatment Effectiveness ◽  
Adverse Outcomes ◽  
Pharmacy Claims ◽  
Increased Risk ◽  
The Impact

Background: Polypharmacy is highly prevalent in elderly individuals with chronic conditions, including atrial fibrillation (AF). The impact of polypharmacy on adverse outcomes and on treatment effectiveness in elderly AF patients remains unaddressed. Methods: We studied 338,810 AF patients ≥75 years of age with 1,761,660 active prescriptions [mean (SD), 5.1 (3.8) per patient] enrolled in the MarketScan Medicare Supplemental database in 2007-2015. Polypharmacy was defined as ≥5 active prescriptions at AF diagnosis based on outpatient pharmacy claims. AF treatments (oral anticoagulation, rhythm and rate control) and cardiovascular endpoints (ischemic stroke, bleeding, heart failure) were defined based on inpatient, outpatient and pharmacy claims. Multivariable Cox models were used to estimate associations of polypharmacy with cardiovascular endpoints and the interaction between polypharmacy and AF treatments in relation to cardiovascular endpoints. Results: Prevalence of polypharmacy was 52% (176,007 of 338,810). Patients with polypharmacy had increased risk of major bleeding [hazard ratio (HR) 1.16, 95% confidence interval (CI) 1.12, 1.20] and heart failure (HR 1.33, 95%CI 1.29, 1.36), but not of ischemic stroke (HR 0.96, 95%CI 0.92, 1.00), compared to those not with polypharmacy (Table). Polypharmacy status did not consistently modify the effectiveness of oral anticoagulants. However, rhythm control (vs. rate control) was more effective in preventing heart failure hospitalization in patients not with polypharmacy (HR 0.87, 95%CI 0.76, 0.99) than among those with polypharmacy (HR 0.98, 95%CI 0.91, 1.07, p for interaction = 0.02). Conclusion: Polypharmacy is frequent among elderly patients with AF, associated with adverse outcomes, and potentially affecting the effectiveness of AF treatments. Optimizing management of polypharmacy in elderly AF patients may lead to improved outcomes.

scholarly journals Atrial fibrillation and clinical outcomes 1 to 3 years after myocardial infarction

Open Heart ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. e001726
Author(s):  
Anthony P Carnicelli ◽  
Ruth Owen ◽  
Stuart J Pocock ◽  
David B Brieger ◽  
Satoshi Yasuda ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Myocardial Infarction ◽  
Atrial Fibrillation ◽  
Clinical Outcomes ◽  
Oral Anticoagulants ◽  
Adverse Outcomes ◽  
Increased Risk ◽  
History Of ◽  
The Impact

ObjectiveAtrial fibrillation (AF) and myocardial infarction (MI) are commonly comorbid and associated with adverse outcomes. Little is known about the impact of AF on quality of life and outcomes post-MI. We compared characteristics, quality of life and clinical outcomes in stable patients post-MI with/without AF.Methods/resultsThe prospective, international, observational TIGRIS (long Term rIsk, clinical manaGement and healthcare Resource utilization of stable coronary artery dISease) registry included 8406 patients aged ≥50 years with ≥1 atherothrombotic risk factor who were 1–3 years post-MI. Patient characteristics were summarised by history of AF. Quality of life was assessed at baseline using EQ-5D. Clinical outcomes over 2 years of follow-up were compared. History of AF was present in 702/8277 (8.5%) registry patients and incident AF was diagnosed in 244/7575 (3.2%) over 2 years. Those with AF were older and had more comorbidities than those without AF. After multivariable adjustment, patients with AF had lower self-reported quality-of-life scores (EQ-5D UK-weighted index, visual analogue scale, usual activities and pain/discomfort) than those without AF. CHA2DS2-VASc score ≥2 was present in 686/702 (97.7%) patients with AF, although only 348/702 (49.6%) were on oral anticoagulants at enrolment. Patients with AF had higher rates of all-cause hospitalisation (adjusted rate ratio 1.25 [1.06–1.46], p=0.008) over 2 years than those without AF, but similar rates of mortality.ConclusionsIn stable patients post-MI, those with AF were commonly undertreated with oral anticoagulants, had poorer quality of life and had increased risk of clinical outcomes than those without AF.Trial registration numberClinicalTrials: NCT01866904.

scholarly journals Artificial intelligence prediction of adverse outcomes in emergency department patients with hyperglycemic crises in real-time

2020 ◽  
Author(s):  
Chin-Chuan Hsu ◽  
Yuan Kao ◽  
Chien-Chin Hsu ◽  
Chia-Jung Chen ◽  
Shu-Lien Hsu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Septic Shock ◽  
Logistic Regression ◽  
Prediction Model ◽  
Real Time ◽  
Adverse Outcomes ◽  
Support Vector ◽  
Icu Admission ◽  
All Cause Mortality ◽  
The Impact

Abstract Background Hyperglycemic crises are associated with high morbidity and mortality. Previous studies proposed methods for predicting adverse outcome in hyperglycemic crises, artificial intelligence (AI) has however never been tried. We implemented an AI prediction model integrated with hospital information system (HIS) to clarify this issue. Methods We included 3,715 patients with hyperglycemic crises from emergency departments (ED) between 2009 and 2018. Patients were randomized into a 70%/30% split for AI model training and testing. Twenty-two feature variables from their electronic medical records were collected, and multilayer perceptron (MLP) was used to construct an AI prediction model to predict sepsis or septic shock, intensive care unit (ICU) admission, and all-cause mortality within 1 month. Comparisons of the performance among random forest, logistic regression, support vector machine (SVM), K-nearest neighbor (KNN), Light Gradient Boosting Machine (LightGBM), and MLP algorithms were also done. Results Using the MLP model, the areas under the curves (AUCs) were 0.808 for sepsis or septic shock, 0.688 for ICU admission, and 0.770 for all-cause mortality. MLP had the best performance in predicting sepsis or septic shock and all-cause mortality, compared with logistic regression, SVM, KNN, and LightGBM. Furthermore, we integrated the AI prediction model with the HIS to assist physicians for decision making in real-time. Conclusions A real-time AI prediction model is a promising method to assist physicians in predicting adverse outcomes in ED patients with hyperglycemic crises. Further studies on the impact on clinical practice and patient outcome are warranted.

Outcome Disparities and Resource Utilization Among Limited English Proficient Patients After Tonsillectomy

2021 ◽  
pp. 000348942110619
Author(s):  
Michal Plocienniczak ◽  
Batsheva R. Rubin ◽  
Alekha Kolli ◽  
Jessica Levi ◽  
Lauren Tracy
Keyword(s):  
Emergency Department ◽  
Resource Utilization ◽  
Limited English Proficiency ◽  
English Proficiency ◽  
Surgical Care ◽  
Adverse Outcomes ◽  
Utilization Rate ◽  
Increased Risk ◽  
Significant Difference ◽  
The Impact

Objective: There is evidence to suggest adverse outcomes on patients’ medical and surgical care when there is language discordance in patient-physician relationships. No studies have evaluated the impact of limited English proficiency (LEP) on complications after common surgical procedures in otolaryngology. Furthermore, no studies have evaluated how patients with LEP utilize remote resources to connect with otolaryngology providers to better triage such complications. The purpose was to evaluate the incidence of post-tonsillectomy hemorrhage (PTH) comparing patients with LEP to those with English proficiency (EP). Patients with PTH were retrospectively evaluated to identify preceding telephone encounters, a marker of resource utilization. Methods: Demographics, English proficiency, and PTH management (surgical vs non-surgical) were evaluated in addition to PTH-associated triage telephone encounters with otolaryngology providers. Results: Of 2466 tonsillectomies, there were 141 episodes of reported hemorrhage (50 LEP vs 91 EP) in the 5 years studied. Rates were not significantly different between LEP and EP patients (4.9% vs 6.3%, P = .127). There was no statistically significant difference in rate of preceding telephone encounters between LEP and EP patients (24% vs 40%, P = .062). Of patients presenting directly to the Emergency Department without a triage telephone encounter, there was no difference in operative versus non-operative management when comparing LEP versus EP patients. However, patients presenting directly to the Emergency Department were nearly twice as likely to undergo operative intervention compared to patients with preceding telephone encounters (RR = 1.79). Conclusion: Patients with limited English proficiency are not at increased risk for developing PTH. There is equitable access to remote otolaryngologic triage care, although overall the utilization rate of this resource was low for both cohorts.

Increasing age as a major determinant of major adverse outcomes in patients with atrial fibrillation: the EURObservational research programme in atrial fibrillation general long-term registry

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
G Boriani ◽  
M Proietti ◽  
C Laroche ◽  
O Piot ◽  
D.A Lane ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Adverse Events ◽  
Adverse Outcomes ◽  
Major Determinant ◽  
Funding Source ◽  
Ageing Population ◽  
Kaplan Meier ◽  
The Impact ◽  
Major Adverse Events

Abstract Introduction Increasing age is a well-known determinant for incident atrial fibrillation (AF) as well as for adverse outcomes. With a progressively ageing population in Europe (and elsewhere), contemporary data are needed to investigate the impact of age in relation to major adverse events in AF patients. Purpose To evaluate the impact of increasing age on major adverse outcomes in a contemporary European AF cohort. Methods Patients enrolled in the EORP-AF Long Term General Registry were categorized by age: <65, 65–74, 75–84, and ≥85 years. Any thromboembolic event (TE)/acute coronary syndrome (ACS)/cardiovascular (CV) death, CV death, all-cause mortality were considered as outcomes. Results Among the 9762 patients included in this analysis, 2946 (30.2%) were <65 years, 3288 (33.7%) were 65–74 years, 2954 (30.3%) were 75–84 years and 574 (5.9%) were ≥85 years. With increasing age categories, there was a progressively higher prevalence of most risk factors and comorbidities. Accordingly, both mean CHA2DS2-VASc and HAS-BLED scores were progressively higher across the age categories (both p<0.0001). At discharge, use of any oral anticoagulant (OAC) drug was lower in patients ≥85 years compared to those aged 65–74 or 75–84 years (83.6% vs. 89.4% and 88.8%, respectively) but significantly higher than in those <65 years (80.2%) [p<0.001]. Rate of all major adverse events progressively increased across the age categories, being higher in those aged ≥85 (all p<0.001). Kaplan-Meier curves showed an increasing cumulative risk across the age groups for all the outcomes (p<0.0001) (Figure 1). A fully adjusted Cox regression analysis demonstrated a progressively increasing association between age categories and the risk of all major adverse outcomes (Table 1). Conclusions In a large contemporary cohort of European AF patients, increasing age was a major determinant of major adverse outcomes. Figure 1. Kaplan-Meier Curves for All-Cause Death Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Since the start of EORP programme, several companies supported its activities with unrestricted grants.

scholarly journals Real-Time Foot Clearance Biofeedback to Assist Gait Rehabilitation Following Stroke: a Randomised Controlled Trial Protocol

2018 ◽  
Author(s):  
Rezaul Begg ◽  
Mary Galea ◽  
Lisa James ◽  
Tony Sparrow ◽  
Pazit Levinger ◽  
...  
Keyword(s):  
Real Time ◽  
Controlled Trial ◽  
Intervention Group ◽  
Training Session ◽  
Sensory Information ◽  
Gait Training ◽  
Gait Pattern ◽  
Falls Prevention ◽  
Visual Biofeedback ◽  
The Impact

Abstract Background: The risk of falling is significantly higher in people with chronic stroke and it is, therefore, important to design interventions to improve mobility and decrease falls risk. Minimum Toe Clearance (MTC) is the key gait cycle event for predicting tripping-falls because it occurs mid-swing during the walking cycle where forward velocity of the foot is maximum. High forward velocity coupled with low MTC increases the probability of unanticipated foot-ground contacts. Training procedures to increase toe-ground clearance (MTC) have potential, therefore, as a falls prevention intervention. The aim of this project is to determine whether augmented sensory information via real-time visual biofeedback during gait training can increase MTC. Methods: Participants will be over 18 years, have sustained a single stroke (ischaemic or hemorrhagic) at least 6 months previously, able to walk 50 metres independently and capable of informed consent. Using a secure web-based application (REDCap) 150 participants will be randomly assigned to either no-feedback (Control) or feedback (Experimental) groups, all will receive 10 sessions of treadmill training for up to 10 minutes at a self-selected speed over five to six weeks. The intervention group will receive real-time, visual biofeedback of MTC during training and will be asked to modify their gait pattern to match a required “target” criterion. Biofeedback is continuous for the first six sessions then progressively reduced (faded) across the remaining four sessions. Control participants will walk on the treadmill without biofeedback. Gait assessments are conducted at baseline, immediately following the final training session and then during follow-up, at 1, 3 and 6 months. The primary outcome measure is MTC. Monthly falls calendars will also be collected for 12 months from enrolment. Discussion: This project will evaluate the impact of augmented sensory information, via visually presented biofeedback, for improving gait function in people with stroke. This has implications for the rehabilitation of gait disorders following stroke and may have the potential to reduce falls in this population.

scholarly journals Hospital hyperglycemia: Status Investigation and Effect of a Real-time Glycemic Alert System

2021 ◽  
Author(s):  
Chenxiang Cao ◽  
Victor Bernet ◽  
Zhaoxiang Liu ◽  
Caihong Li ◽  
Chongyang Bi ◽  
...  
Keyword(s):  
Real Time ◽  
Glucose Monitoring ◽  
Serum Glucose ◽  
Adverse Outcomes ◽  
Team Physician ◽  
Alert System ◽  
Consultation Rate ◽  
Warning Messages ◽  
Total Glucose ◽  
The Impact

BACKGROUND Hospital hyperglycemia is common and associated with potential adverse outcomes. A Hospital-wide Mobile Phone Alert (HMA) system was built to achieve real time glucose monitoring with warnings for glucose excursions. This study investigated the status of glucose control and evaluated the impact of HMA system on inpatient glycemia management. METHODS Inpatients with hyperglycemia hospitalized between 1 January, 2017 and 31 December, 2018 were identified excluding those < 18 years of age. The HMA system was activated on 1 October, 2017. It sent real time cellphone warning messages to the patient’s designated team physician whenever glucose levels > 10 mmol/L or < 3 mmol/L were detected. A serum glucose > 7.8 mmol/L was defined as hospital hyperglycemia (HH), and > 10 mmol/L was defined as significant HH (SHH). Glucose excursions before and after the HMA system was instituted were compared. RESULTS The incidence of HH, SHH and hypoglycemia was 26.1%, 12.8% and 2.5%, respectively. With the HMA system, the monthly glucose related consultation rate for all inpatients increased 65.9%. The rate of HH glucose amount/ total glucose amount improved with the HMA system, being lower than pre HMA system activation for the surgical wards (15.8 ± 4.7% vs 21.1 ± 6.1%，p<0.05). CONCLUSIONS In this study, one third of inpatients were noted to experience hyperglycemia. Real time cellphone warning messages to the patient’s designated team physician can improve consultation utilization for blood glucose excursions. The alert system was found to reduce the incidence of hyperglycemia on surgical wards.

scholarly journals Towards Efficient Resource Utilization Exploiting Collaboration between HPF and 5G Enabled Energy Management Controllers in Smart Homes

2018 ◽  
Vol 10 (10) ◽  
pp. 3592 ◽  
Author(s):  
Rasool Bakhsh ◽  
Nadeem Javaid ◽  
Itrat Fatima ◽  
Majid Khan ◽  
Khaled. Almejalli
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Resource Utilization ◽  
Virtual Machines ◽  
Smart Homes ◽  
System Delay ◽  
Real Time Control ◽  
Home Energy Management ◽  
Efficient Processing ◽  
The Impact

The influence of Information Communication and Technology (ICT) in power systems necessitates Smart Grid (SG) with monitoring and real-time control of electricity consumption. In SG, huge requests are generated from the smart homes in residential sector. Thus, researchers have proposed cloud based centralized and fog based semi-centralized computing systems for such requests. The cloud, unlike the fog system, has virtually infinite computing resources; however, in the cloud, system delay is the challenge for real-time applications. The prominent features of fog are; awareness of location, low latency, wired and wireless connectivity. In this paper, the impact of longer delay of cloud in SG applications is addressed. We proposed a cloud-fog based system for efficient processing of requests coming from the smart homes, their quick response and ultimately reduced cost. Each smart home is provided with a 5G based Home Energy Management Controller (HEMC). Then, the 5G-HEMC communicates with the High Performance Fog (HPF). The HPFs are capable of processing energy consumers’ huge requests. Virtual Machines (VMs) are installed on physical systems (HPFs) to entertain the requests using First Come First Service (FCFS) and Ant Colony Optimization (ACO) algorithms along with Optimized Response Time Policy (ORTP) for the selection of potential HPF for efficient processing of the requests with maximum resource utilization. It is analysed that size and number of virtual resources affect the performance of the computing system. In the proposed system model, micro grids are introduced in the vicinity of energy consumers for uninterrupted and cost optimized power supply. The impact of the number of VMs on the performance of HPFs is analysed with extensive simulations with three scenarios.

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