Mohammad Alrawashdeh

A Randomized Controlled Trial of a Mobile Health Intervention to Promote Self-Management After Lung Transplantation

Lung transplant recipients are encouraged to perform self‐management behaviors, including (i) monitoring health indicators, (ii) adhering to their regimen, and (iii) reporting abnormal health indicators to the transplant coordinator, yet performance is suboptimal. When hospital discharge was imminent, this two‐group trial randomized 201 recipients to use either the mobile health (mHealth) intervention (n = 99) or usual care (n = 102), to compare efficacy for promoting self‐management behaviors (primary outcomes) and self‐care agency, rehospitalization, and mortality (secondary outcomes) at home during the first year after transplantation. The mHealth intervention group performed self‐monitoring (odds ratio [OR] 5.11, 95% confidence interval [CI] 2.95–8.87, p < 0.001), adhered to medical regimen (OR 1.64, 95% CI 1.01–2.66, p = 0.046), and reported abnormal health indicators (OR 8.9, 95% CI 3.60–21.99, p < 0.001) more frequently than the usual care group. However, the two groups did not differ in rehospitalization (OR 0.78, 95% CI 0.36–1.66, p = 0.51) or mortality (hazard ratio 1.71, 0.68–4.28, p = 0.25). The positive impact of the mHealth intervention on self‐management behaviors suggests that the intervention holds promise and warrants further testing.

Rationale, development, and implementation of the Electrocardiographic Methods for the Prehospital Identification of Non-ST Elevation Myocardial Infarction Events (EMPIRE)

BACKGROUND The serum rise of cardiac troponin remains the gold standard for diagnosing non-ST elevation (NSTE) myocardial infarction (MI) despite its delayed response. Novel methods for real-time detection of NSTEMI would result in more immediate initiation of definitive medical therapy and faster transport to facilities that can provide specialized cardiac care. METHODS EMPIRE is an ongoing prospective, observational cohort study designed to quantify the magnitude of ischemia-induced repolarization dispersion for the early detection of NSTEMI. In this ongoing study, prehospital ECG data is gathered from patients who call 9-1-1 with a chief complaint of non-traumatic chest pain. This data is then analyzed using the principal component analysis (PCA) technique of 12-lead ECGs to fully characterize the spatial and temporal qualities of STT waveforms. RESULTS Between May and December of 2013, Pittsburgh EMS obtained and transmitted 351 prehospital ECGs of the 1149 patients with chest pain-related emergency dispatches transported to participating hospitals. After excluding those with poor ECG signal (n=40, 11%) and those with pacing or LBBB (n=50, 14%), there were 261 eligible patients (age 57±16years, 45% female, 45% Black). In this preliminary sample, there were 19 STEMI (7%) and 33 NSTEMI (12%). More than 50% of those with infarction (STEMI or NSTEMI) had initially negative troponin values upon presentation. We present ECG data of such NSTEMI case that was identified correctly using our methods. CONCLUSIONS Concrete ECG algorithms that can quantify NSTE ischemia and allow differential treatment based on such ECG changes could have an immediate clinical impact on patient outcomes. We describe the rationale, development, design, and potential usefulness of the EMPIRE study. The findings may provide insights that can influence guidelines revisions and improve public health.

Patterns and Predictors of Sleep Quality Within the First Year After Lung Transplantation

Context: Sleep quality affects health and self-management in chronic illness. Limited research has examined patterns and predictors of sleep quality and its impact on self-management and health-related quality of life (HRQOL) among lung transplant recipients (LTRs). Objective: The aims of this study were to identify the patterns, predictors, and impact of poor sleep quality on self-management behaviors and HRQOL the first year after lung transplantation. Methods: Secondary analysis of 75 LTRs who participated in a randomized controlled trial. Pittsburgh Sleep Quality Index (PSQI) was administered at baseline, 2, 6, and 12 months after transplant; 12-month PSQI was dichotomized categorizing good versus poor sleepers. Predictors were measured at the time of transplant; self-management and HRQOL were measured at 12 months. Logistic regression identified predictors of poor sleep. Correlations examined poor sleep quality, self-management behaviors, and HRQOL. Results: Sleep quality was relatively stable during the first year, and 24 of the 75 (32%) of the sample met criteria for poor sleep quality at 12 months. The only multivariate predictor of poor sleep was female gender (odds ratio = 3.421; P = .026); the mental component of HRQOL was the only outcome associated with poor sleep (r = −.348; P < .01). Conclusion: Nearly one-third of LTRs reported persistent poor sleep through year 1. More females reported poor sleep quality, and sleep quality was inversely related to mental HRQOL by 12 months. Knowledge of these relationships may help identify LTRs at the greatest risk for poor sleep and guide strategies to promote sleep and optimize HRQOL.

Pattern and Predictors of Hospital Readmission During the First Year After Lung Transplantation.

Hospital readmission after lung transplantation negatively affects quality of life and resource utilization. A secondary analysis of data collected prospectively was conducted to identify the pattern of (incidence, count, cumulative duration), reasons for and predictors of readmission for 201 lung transplant recipients (LTRs) assessed at 2, 6, and 12 mo after discharge. The majority of LTRs (83.6%) were readmitted, and 64.2% had multiple readmissions. The median cumulative readmission duration was 19 days. The main reasons for readmission were other than infection or rejection (55.5%), infection only (25.4%), rejection only (9.9%), and infection and rejection (0.7%). LTRs who required reintubation (odds ratio [OR] 1.92; p = 0.008) or were discharged to care facilities (OR 2.78; p = 0.008) were at higher risk for readmission, with a 95.7% cumulative incidence of readmission at 12 mo. Thirty‐day readmission (40.8%) was not significantly predicted by baseline characteristics. Predictors of higher readmission count were lower capacity to engage in self‐care (incidence rate ratio [IRR] 0.99; p = 0.03) and discharge to care facilities (IRR 1.45; p = 0.01). Predictors of longer cumulative readmission duration were older age (arithmetic mean ratio [AMR] 1.02; p = 0.009), return to the intensive care unit (AMR 2.00; p = 0.01) and lower capacity to engage in self‐care (AMR 0.99; p = 0.03). Identifying LTRs at risk may assist in optimizing predischarge care, discharge planning and long‐term follow‐up.

Evaluation of beat-to-beat ventricular repolarization lability from standard 12‐lead ECG during acute myocardial ischemia

BACKGROUND Acute myocardial ischemia is a common cause of ventricular arrhythmias, yet recent ECG methods predicting susceptibility to ventricular tachyarrhythmia have not been fully evaluated during spontaneous ischemia. We sought to evaluate the clinical utility of alternans and non-alternans components of repolarization variability from the standard 10-second 12-lead ECG signals to risk stratify patients with acute chest pain. METHODS We enrolled consecutive, non-traumatic, chest pain patients transported through Emergency Medical Services (EMS) to three tertiary care hospitals with cardiac catheterization lab capabilities in Pittsburgh, PA. ECG signals were manually annotated by an electrophysiologist, then automatically processed using a custom-written software. Both T wave alternans (TWA) and non-alternans repolarization variability (NARV) were calculated using the absolute RMS differences over the repolarization window between odd/even averaged beats and between consecutive averaged pairs, respectively. The primary study outcome was the presence of acute myocardial infarction (AMI) documented by cardiac angiography. RESULTS After excluding patients with secondary repolarization changes (n=123) and those with excessive noise (n=90), our final sample included 537 patients (age 57±16years, 56% males). Patients with AMI (n=47, 9%) had higher TWA and NARV values (p<0.01). Mean RR correlated with TWA, and noise measures correlated with TWA and NARV, after adjusting for potential confounders. There was a high collinearity between TWA and NARV, and each was separately predictive of AMI after controlling for number of analyzed beats, noise measures, and other clinical variables. CONCLUSIONS Despite limitations imposed by signal quality, TWA and NARV are higher in patients with AMI, even after correction for potential confounders. The clinical value of TWA and NARV derived from standard ECG using our time-domain RMS method is questionable due to the small number of beats and significant noise.

Nonspecific electrocardiographic abnormalities are associated with increased length of stay and adverse cardiac outcomes in prehospital chest pain

Background: Nonspecific ST‐T repolarization (NST) abnormalities alter the ST‐segment for reasons often unrelated to acute myocardial ischemia, which could contribute to misdiagnosis or inappropriate treatment. We sought to define the prevalence of NST patterns in patients with chest pain and evaluate how such patterns correlate with the eventual etiology of chest pain and course of hospitalization. Methods: This was a prospective observational study that included consecutive prehospital chest pain patients from three tertiary care hospitals in the U.S. Two independent reviewers blinded from clinical data audited the prehospital 12‐lead ECG for the presence or absence of NST patterns (i.e., right or left bundle branch block, left ventricular hypertrophy with strain pattern, ventricular pacing, ventricular rhythm, or coarse atrial fibrillation). The primary outcome was 30‐day major adverse cardiac events (MACE) defined as cardiac arrest, acute heart failure, post‐discharge infarction, or all‐cause death. Results: The final sample included 750 patients (age 59 ± 17, 58% males). A total of 40 patients (5.3%) experienced 30‐MACE and 131 (17.5%) had NST patterns. The presence of NST patterns was an independent multivariate predictor of 30‐day MACE (9.9% vs. 4.4%, OR = 2.2 [95% CI = 1.1–4.5]. Patients with NST patterns had increased median length of stay (1.0 [IQR 0.5–3] vs. 2.0 [IQR 1–4] days, p < 0.05) independent of the etiology of chest pain. Conclusions: One in six prehospital ECGs of patients with chest pain has NST patterns. This pattern is associated with increased length of stay and adverse cardiac outcomes, suggesting the need of preventive measures and close follow up in such patients.

Comparison of clinical risk scores for triaging high-risk chest pain patients at the emergency department

Background Many of the clinical risk scores routinely used for chest pain assessment have not been validated in patients at high risk for acute coronary syndrome (ACS). We performed an independent comparison of HEART, TIMI, GRACE, FRISC, and PURSUIT scores for identifying chest pain due to ACS and for predicting 30‐day death or re‐infarction in patients arriving through Emergency Medical Services (EMS). Methods and results We enrolled consecutive EMS patients evaluated for chest pain at three emergency departments. A reviewer blinded to outcome data retrospectively reviewed patient charts to compute each risk score. The primary outcome was ACS diagnosed during the primary admission, and the secondary outcome was death or re‐infarction within 30‐days of initial presentation. Our sample included 750 patients (aged 59 ± 17 years, 42% female), of whom 115 (15.3%) had ACS and 33 (4.4%) had 30‐day death or re‐infarction. The c‐statistics of HEART, TIMI, GRACE, FRISC, and PURSUIT for identifying ACS were 0.87, 0.86, 0.73, 0.84, and 0.79, respectively, and for predicting 30‐day death or re‐infarction were 0.70, 0.73, 0.72, 0.72, and 0.62, respectively. Sensitivity/negative predictive value of HEART ≥ 4 and TIMI ≥ 3 for ACS detection were 0.94/0.98 and 0.87/0.97, respectively. Conclusions In chest pain patients admitted through EMS, HEART and TIMI outperform other scores for identifying chest pain due to ACS. Although both have similar negative predictive value, HEART has better sensitivity and lower rate of false negative results, thus it can be used preferentially over TIMI in the initial triage of this population.

Predictors and influence of goal orientation on self-management and health-related quality of life after lung transplant.

Context— Lung transplant recipients are encouraged to perform self-management behaviors to maximize health outcomes; however, performance is often less than ideal. Goal orientation is known to influence achievement of academic goals, but the influence of goal orientation on performance of self-management is unknown. Objectives— To identify characteristics at transplant that are predictive of higher goal orientation and examine relationships between Goal Orientation Index (GOI) subscores (Acting, Planning, Reflecting), self-management behaviors (adhering, self-monitoring, and communicating critical changes), and health-related quality of life (HRQOL) at 1 year after transplant. Design— A descriptive, secondary analysis of data from 33 lung transplant recipients who were assessed at transplant and followed for 1 year as part of a clinical trial. GOI subscores were dichotomized at the median to categorize recipients with high and low goal orientation. Logistic regression was used to identify predictors of higher GOI subscores. Correlations between higher GOI subscores, self-management, and HRQOL were examined. Results— Lung transplant recipients reported relatively high mean GOI subscores (Acting, Planning, and Reflecting) and the 3 subscores were correlated (r = 0.31–0.86). Self-care agency was the only significant predictor (P = .04) of higher GOI (Reflecting). Lung transplant recipients with higher Planning and Reflecting subscores were more likely to adhere (r = 0.36 and 0.46, respectively). Recipients with higher GOI subscores reported significantly better mental HRQOL (r = 0.42–0.36). Recipients with higher GOI Planning or Acting subscores reported significantly less anxiety (r = −0.39–0.46) and fewer depressive symptoms (r = −0.40–0.43). Conclusion— Assessing goal orientation may offer a novel approach for promoting adherence and HRQOL after lung transplant.