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1.
Perioper Med (Lond) ; 13(1): 6, 2024 Jan 23.
Article in English | MEDLINE | ID: mdl-38263053

ABSTRACT

BACKGROUND: Frailty is associated with worse outcomes and higher healthcare costs. The long waiting time for surgery is a potential 'teachable' moment. We examined the feasibility and safety of a pilot prehabilitation programme on high-risk frail patients undergoing major elective surgery. METHODS: A single-centre, retrospective pilot study (Dec 2020-Nov 2021) on a one-stop prehabilitation programme (structured exercise training, nutritional counselling/therapy, and psychological support) in collaboration with geriatricians and allied health professionals. At least 4 weeks before surgery, patients at high risk of frailty or malnutrition, or undergoing major hepatectomy, esophagectomy, pancreaticoduodenectomy, or radical cystectomy, were referred for prehabilitation (2-3 sessions/week). The primary outcomes were the feasibility and safety of prehabilitation. The secondary outcomes were changes in functional, emotional, and nutritional status and days alive and at home within 30 days after surgery (DAH30) associated with prehabilitation. RESULTS: Over a 12-month period, 72 out of 111 patients (64.9%) from the Perioperative Medicine Clinic were eligible for prehabilitation, of which 54 (75%) were recruited. The mean (standard deviation) age was 71.9 (6.9) years. The adherence rate to 3 weeks of prehabilitation was high in 52 (96.3%) participants. Prehabilitation improved exercise capacity (P = 0.08), enhanced some functional mobility measures (P = 0.02), and increased nutritional energy (P = 0.04) and protein intakes (P < 0.01). However, prehabilitation-related changes in muscle strength, cognitive function, and emotional resilience were minimal. The median (interquatile range) DAH30 was 19 (14-23) days. No adverse events were reported. CONCLUSIONS: This outpatient-based, one-stop multidisciplinary prehabilitation programme was feasible, safe, and improved several measures of patient's physiological reserve and functional capacity. CLINICAL TRIAL REGISTRATION: NCT05668221.

2.
Ther Adv Neurol Disord ; 12: 1756286419842698, 2019.
Article in English | MEDLINE | ID: mdl-31007721

ABSTRACT

BACKGROUND: The HAVOC score was previously developed to predict the risk of atrial fibrillation (AF) after cryptogenic stroke (CS) or transient ischemic attack (TIA). The purpose of this study was to apply the HAVOC score to patients who received insertable cardiac monitors (ICMs) in the CRYSTAL AF study. METHODS: All patients from the CRYSTAL AF study who received an ICM were included. HAVOC score (one point each for peripheral vascular disease and obesity with body mass index >30, two points each for hypertension, age ⩾ 75, valvular heart disease, and coronary artery disease, 4 points for congestive heart failure) was computed for all patients. The primary endpoint was AF detection by 12 months of ICM monitoring. RESULTS: A total of 214 patients who received ICM were included. AF was detected in 40 patients while the remaining 174 patients were AF negative. The HAVOC score was significantly higher among patients with AF [median 3.0 with interquartile range (IQR) 2-4] than those without AF [median 2.0 (IQR 0-3)], p = 0.01. AF increased significantly across the three HAVOC score groups: 11% in Group A (score 0-1), 18% in Group B (score 2-3), and 32 % in Group C (score ⩾ 4) with p = 0.02. CONCLUSIONS: The HAVOC score was shown in this post hoc analysis of CRYSTAL AF to successfully stratify AF risk post CS or TIA. The 11% AF rate in the lowest HAVOC score group highlights the significance of nontraditional contributors to AF and ischemic stroke.

3.
JACC Heart Fail ; 6(3): 209-218, 2018 03.
Article in English | MEDLINE | ID: mdl-29496022

ABSTRACT

OBJECTIVES: This study sought to characterize patients with methamphetamine-associated pulmonary arterial hypertension (MA-PAH) and cardiomyopathy (MA-CMP), to compare with MA controls (MA-CTL), users with structurally normal hearts, with the aim of identifying risk factors for these conditions. BACKGROUND: MA-PAH and MA-CMP are 2 poorly understood cardiac complications in MA users. METHODS: We retrospectively studied the clinical characteristics and outcomes of 50 MA-PAH, 296 MA-CMP, and 356 MA-CTL patients, whom we evaluated between 2010 and 2017. RESULTS: After a median follow-up of 20.0 months (interquartile range [IQR]: 7.6 to 42.6 months), all-cause mortality was 18.0% for MA-PAH, 15.2% for MA-CMP, and 4.5% for MA-CTL group (p < 0.001). More women (58%) were in the MA-PAH group than in the MA-CMP (14%; p < 0.001) and MA-CTL (42%; p = 0.028) groups, whereas the MA-CMP group was predominantly male (86% vs. 58% in the MA-CTL group; p < 0.001). More MA-CMP patients had hypertension (p < 0.001) or alcoholism (p < 0.001) than MA-CTL patients. Logistic regression analyses identified male sex, alcoholism, and hypertension as independent factors associated with MA-CMP with the following respective adjusted odds ratios (OR) of 3.791 (95% confidence interval [CI]: 2.508 to 5.730), OR of 2.959 (95% CI: 2.084 to 4.203), and OR of 2.111 (95% CI: 1.486 to 2.999), whereas female sex was the only factor associated with MA-PAH. CONCLUSIONS: Both MA-PAH and MA-CMP patients carried significant disease burden and mortality risk. Male sex, hypertension, and alcoholism were strongly associated with MA-CMP, whereas female sex and other unknown factors may influence development of MA-PAH. This study adds to the understanding of MA-associated cardiac complications and highlights directions for future investigation.


Subject(s)
Amphetamine-Related Disorders/complications , Cardiomyopathy, Dilated/chemically induced , Central Nervous System Stimulants/adverse effects , Hypertension, Pulmonary/chemically induced , Methamphetamine/adverse effects , Adult , Alcoholism/complications , Alcoholism/epidemiology , Amphetamine-Related Disorders/epidemiology , California/epidemiology , Cardiomyopathy, Dilated/epidemiology , Case-Control Studies , Female , Humans , Hypertension, Pulmonary/epidemiology , Male , Middle Aged , Prevalence , Retrospective Studies , Sex Distribution
4.
Cardiology ; 138(3): 133-140, 2017.
Article in English | MEDLINE | ID: mdl-28654919

ABSTRACT

OBJECTIVES: Detection of atrial fibrillation (AF) in post-cryptogenic stroke (CS) or transient ischemic attack (TIA) patients carries important therapeutic implications. METHODS: To risk stratify CS/TIA patients for later development of AF, we conducted a retrospective cohort study using data from 1995 to 2015 in the Stanford Translational Research Integrated Database Environment (STRIDE). RESULTS: Of the 9,589 adult patients (age ≥40 years) with CS/TIA included, 482 (5%) patients developed AF post CS/TIA. Of those patients, 28.4, 26.3, and 45.3% were diagnosed with AF 1-12 months, 1-3 years, and >3 years after the index CS/TIA, respectively. Age (≥75 years), obesity, congestive heart failure, hypertension, coronary artery disease, peripheral vascular disease, and valve disease are significant risk factors, with the following respective odds ratios (95% CI): 1.73 (1.39-2.16), 1.53 (1.05-2.18), 3.34 (2.61-4.28), 2.01 (1.53-2.68), 1.72 (1.35-2.19), 1.37 (1.02-1.84), and 2.05 (1.55-2.69). A risk-scoring system, i.e., the HAVOC score, was constructed using these 7 clinical variables that successfully stratify patients into 3 risk groups, with good model discrimination (area under the curve = 0.77). CONCLUSIONS: Findings from this study support the strategy of looking longer and harder for AF in post-CS/TIA patients. The HAVOC score identifies different levels of AF risk and may be used to select patients for extended rhythm monitoring.


Subject(s)
Atrial Fibrillation/diagnosis , Atrial Fibrillation/epidemiology , Ischemic Attack, Transient/complications , Severity of Illness Index , Stroke/complications , Aged , Aged, 80 and over , California/epidemiology , Coronary Disease/complications , Databases, Factual , Female , Heart Failure/complications , Humans , Hypertension/complications , Logistic Models , Male , Middle Aged , Multivariate Analysis , Retrospective Studies , Risk Factors , Sensitivity and Specificity , Time Factors
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