scholarly journals Trajectory Modelling to Assess Trends in Long-Term Readmission Rate among Abdominal Aortic Aneurysm Patients

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Ahsan Rao ◽  
Alex Bottle ◽  
Collin Bicknell ◽  
Ara Darzi ◽  
Paul Aylin
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Readmission Rate ◽  
High Impact ◽  
Short Term ◽  
Readmission Rates ◽  
Abdominal Aortic ◽  
High Readmission Rate ◽  
Trajectory Modelling

Introduction. The aim of the study was to use trajectory analysis to categorise high-impact users based on their long-term readmission rate and identify their predictors following AAA (abdominal aortic aneurysm) repair. Methods. In this retrospective cohort study, group-based trajectory modelling (GBTM) was performed on the patient cohort (2006-2009) identified through national administrative data from all NHS English hospitals. Proc Traj software was used in SAS program to conduct GBTM, which classified patient population into groups based on their annual readmission rates during a 5-year period following primary AAA repair. Based on the trends of readmission rates, patients were classified into low- and high-impact users. The high-impact group had a higher annual readmission rate throughout 5-year follow-up. Short-term high-impact users had initial high readmission rate followed by rapid decline, whereas chronic high-impact users continued to have high readmission rate. Results. Based on the trends in readmission rates, GBTM classified elective AAA repair (n=16,973) patients into 2 groups: low impact (82.0%) and high impact (18.0%). High-impact users were significantly associated with female sex (P=0.001) undergoing other vascular procedures (P=0.003), poor socioeconomic status index (P<0.001), older age (P<0.001), and higher comorbidity score (P<0.001). The AUC for c-statistics was 0.84. Patients with ruptured AAA repair (n=4144) had 3 groups: low impact (82.7%), short-term high impact (7.2%), and chronic high impact (10.1%). Chronic high impact users were significantly associated with renal failure (P<0.001), heart failure (P = 0.01), peripheral vascular disease (P<0.001), female sex (P = 0.02), open repair (P<0.001), and undergoing other related procedures (P=0.05). The AUC for c-statistics was 0.71. Conclusion. Patients with persistent high readmission rates exist among AAA population; however, their readmissions and mortality are not related to AAA repair. They may benefit from optimization of their medical management of comorbidities perioperatively and during their follow-up.

scholarly journals Common Sequences of Emergency Readmissions among High-Impact Users following AAA Repair

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Ahsan Rao ◽  
Alex Bottle ◽  
Colin Bicknell ◽  
Ara Darzi ◽  
Paul Aylin
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Readmission Rate ◽  
High Impact ◽  
Aortic Graft ◽  
Abdominal Aortic ◽  
Number Of Patients ◽  
Common Causes ◽  
High Readmission Rate

Introduction. The aim of the study was to examine common sequences of causes of readmissions among those patients with multiple hospital admissions, high-impact users, after abdominal aortic aneurysm (AAA) repair and to focus on strategies to reduce long-term readmission rate. Methods. The patient cohort (2006–2009) included patients from Hospital Episodes Statistics, the national administrative data of all NHS English hospitals, and followed up for 5 years. Group-based trajectory modelling and sequence analysis were performed on the data. Results. From a total of 16,973 elective AAA repair patients, 18% (n=3055) were high-impact users. The high-impact users among ruptured abdominal aortic aneurysm (rAAA) repair constituted 17.3% of the patient population (n=4144). There were 2 subtypes of high-impact users, short-term (7.2%) with initial high readmission rate following by rapid decline and chronic high-impact (10.1%) with persistently high readmission rate. Common causes of readmissions following elective AAA repair were respiratory tract infection (7.3%), aortic graft complications (6.0%), unspecified chest pain (5.8%), and gastrointestinal haemorrhage (4.8%). However, high-impact users included significantly increased number of patients with multiple readmissions and distinct sequences of readmissions mainly consisting of COPD (4.7%), respiratory tract infection (4.7%), and ischaemic heart disease (3.3%). Conclusion. A significant number of patients were high-impact users after AAA repair. They had a common and distinct sequence of causes of readmissions following AAA repair, mainly consisting of cardiopulmonary conditions and aortic graft complications. The common causes of long-term mortality were not related to AAA repair. The quality of care can be improved by identifying these patients early and focusing on prevention of cardiopulmonary diseases in the community.

scholarly journals 763. 30 Day Readmission Outcomes in Patients Over 80 Years of Age Enrolled in an Outpatient Parenteral Antibiotic Therapy (OPAT) Program

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S339-S340
Author(s):  
Kathleen R Sheridan ◽  
Joshua Wingfield ◽  
Lauren McKibben ◽  
Natalie Clouse
Keyword(s):  
Readmission Rate ◽  
Chart Review ◽  
Age Groups ◽  
Retrospective Chart Review ◽  
Model Of Care ◽  
Readmission Rates ◽  
Parenteral Antibiotic ◽  
Patient Demographics

Abstract Background OPAT is a well-established model of care for the monitoring of patients requiring long-term IV antibiotics1. We have previously reported a reduction in the 30-day readmission rate to our facility for patients managed in our OPAT program. However, little has been published to date regarding outcomes in OPAT patients over 80 years of age 2–3. Our OPAT program was established in 2013. Patients can be discharged to a facility or home to complete their course of antibiotics. Methods We conducted a retrospective chart review of all OPAT patients discharged from our facility from 2015 to 2018. Patients were divided into two groups based on age, <80 (n = 4618) and >80 (n = 562). Results Patient demographics are listed in Table 1. The overall 30-day readmission rate for patients older than 80 was 27.8%. For patients over 80 that had a follow-up ID clinic appointment, the 30-day readmission rate decreased to 15.7%. For patients younger than 80, the 30-day readmission rate was 36.0% with a decrease to 16.2% if patients were evaluated in the outpatient clinic. Figure 1. Staphylococcus Aureus was the predominant organism in both age categories. Vancomycin was the most common antibiotic used in both age groups followed by β lactams. Conclusion In general, patients aged over 80 years were more likely to be discharged to a facility to complete their antibiotic course than younger patients. These patients also were more likely to have other comorbidities. The 30-day readmission rate in each age group was relatively similar. OPAT in patients over age 80 can have similar 30-day readmission rates as for patients less than 80 years of age Disclosures All authors: No reported disclosures.

Long-Term Follow-Up of Men Invited to Participate in a Population-Based Abdominal Aortic Aneurysm Screening Program

Angiology ◽  
2020 ◽  
Vol 71 (7) ◽  
pp. 641-649
Author(s):  
Rebecka Hultgren ◽  
K. Miriam Elfström ◽  
Daniel Öhman ◽  
Anneli Linné
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Screening Program ◽  
Dropout Rate ◽  
Rupture Rate ◽  
Aortic Repair ◽  
Abdominal Aortic ◽  
Long Term Follow Up

A screening program for abdominal aortic aneurysm (AAA), inviting 65-year-old men, was started in Stockholm in 2010 (2.3 million inhabitants). The aim was to present a long-term follow-up of men participating in screening, as well as AAA repair and ruptures among nonparticipants. Demographics were collected for men with screening detected with AAA 2010 to 2016 (n = 672) and a control group with normal aortas at screening (controls, n = 237). Medical charts and regional Swedvasc (Swedish Vascular registry) data were analyzed for aortic repair for men born 1945 to 1951. Ultrasound maximum aortic diameter (AD) as well as Aortic Size Index (ASI) was recorded. Participation was 78% and prevalence of AAA was 1.2% (n = 672). Aortic repair rates correlated with high ASI and AD. During the study period, 22% of the AAA patients were treated with the elective repair; 35 men in surveillance died (5.2%), non-AAA-related causes (82.9%) dominated, followed by unknown causes among 4 (11.4%), and 2 (5.7%) possibly AAA-related deaths. Abdominal aortic aneurysm rupture rate was higher among nonparticipants (0.096% vs 0.0036%, P < .001). The low dropout rate confirms acceptability of follow-up after screening. The efficacy is shown by the much higher rupture rate among the nonparticipating men.

Abdominal Aortic Aneurysm Wall Stresses After Endovascular Repair

2002 ◽  
Author(s):  
Elena S. Di Martino ◽  
Michel S. Makaroun ◽  
David A. Vorp
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Endovascular Repair ◽  
Careful Consideration ◽  
Aneurysm Wall ◽  
Abdominal Aortic ◽  
Long Term Follow Up ◽  
Endovascular Approach

The early benefits of an endovascular approach to abdominal aortic aneurysm (AAA) treatment has been reported by many authors [1,2]. One of the major advantages is that endovascular repair of AAA (EVAR) as opposed to traditional open surgery, is not a major abdominal surgery. EVAR has been shown to be associated with a death rate comparable to that of surgical repair [3]. In short term follow-up, EVAR is associated with fewer complications and a more rapid recovery [2]. On the contrary very limited data is available on long term follow-up of EVAR patients. Graft-related secondary interventions affect a consistent percentage of the treated cases. The EUROSTAR study [4] recently reported 13% of reintervention in 15.4 months. Our surgical unit reported 20.6% across 48 months in a recent review of 242 cases [3]. The frequence and type of reintervention, whose principal cause is endoleak or perigraft flow, requires careful consideration.

Effects of Abdominal Aortic Aneurysm Size on Mid- and Long-term Mortality After Endovascular Aneurysm Repair

2019 ◽  
Vol 26 (2) ◽  
pp. 231-237 ◽  
Author(s):  
Haekyung Jeon-Slaughter ◽  
Harish Krishnamoorthi ◽  
David Timaran ◽  
Amanda Wall ◽  
Bala Ramanan ◽  
...  
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Endovascular Aneurysm Repair ◽  
Optimal Cutoff ◽  
Term Survival ◽  
Abdominal Aortic ◽  
All Cause Mortality ◽  
Aneurysm Repair

Purpose: To investigate the effect of abdominal aortic aneurysm (AAA) size on mid- and long-term survival after endovascular aneurysm repair (EVAR). Materials and Methods: Retrospective data were collected from 325 consecutive patients (mean age 69.7 ± 8.5 years; 323 men) who underwent EVAR for intact AAA at a single institution between January 2003 and December 2013. The primary endpoint was death at 3, 5, and 10 years after EVAR. Optimal cutoff points for AAA size and age were determined using receiver operating characteristics (ROC) curves. Time to event analyses (Kaplan-Meier curves and Cox proportional hazard models) were employed to determine any differences in all-cause mortality outcomes between AAA size groups. Cox models were adjusted for age and other comorbidities (hypertension, hyperlipidemia, coronary artery disease, smoking status, symptomatic status, and creatinine); the outcomes are reported as the hazard ratio (HR) with 95% confidence interval (CI). Results: The cohort was dichotomized according to the ROC analysis, which defined an optimal cutoff point of 5.6 cm for AAA size and >70 years for age. The mean follow-up period post EVAR was 45.5±29.2 months. In total, 134 (41.2%) patients died during the 10-year follow-up. Thirty-day mortality was 1.1% (2/184) in the patients with AAA <5.6 cm and 2.1% (3/141) in patients with AAA ≥5.6 cm (p=0.45). All-cause mortality was not significantly affected by comorbidities. However, AAA size ≥5.6 cm was associated with increased 3-year mortality risk (HR 1.59, 95% CI 1.001 to 2.52, p<0.049) but not 5-year (HR 1.44, 95% CI 0.98 to 2.10, p=0.062) or 10-year mortality (HR 1.28, 95% CI 0.91 to 1.80, p=0.149). After adjusting for comorbidities, AAA size ≥5.6 cm was no longer significantly associated with morality at any time point. Using a larger size cutoff (AAA size ≥6.0 cm) resulted in improved statistical significance in the unadjusted model. In the adjusted Cox model, AAA size ≥6.0 cm was significantly associated with increased risk of mortality at 3 years (HR 1.67, 95% CI 1.01 to 2.77, p<0.047), but not at longer time points. Conclusion: Our study demonstrates that midterm survival after EVAR is significantly and independently associated with AAA size even after correcting for comorbidities. However, in the long term, preoperative AAA size is not an independent predictor of mortality.

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