Effect of alcohol septal ablation in patients with hypertrophic cardiomyopathy on the electrocardiographic pattern

Alcohol septal ablation (ASA) of patients with hypertrophic cardiomyopathy (HC) allows study of the electrocardiographic effects of myocardial necrosis confined to the base of the interventricular septum, a rare event in atherothrombotic coronary artery disease. Eighty-four consecutive patients were studied after ASA for HC. After excluding 20 with pacing before ASA and 6 with no available preprocedure electrocardiograms, the electrocardiograms of the remaining 58 patients were compared with those of 58 consecutive patients with anterior ST elevation myocardial infarctions who underwent primary intervention for left anterior descending coronary artery (LAD) occlusions. In 25 patients, the occlusions were proximal to the first septal perforator, and in 33 patients, the occlusions were more distal. All electrocardiograms were analyzed with respect to conduction abnormalities and ST-segment changes. Patients with HC developed right bundle branch block significantly more often than those with LAD occlusions (50% vs 14%, p = 0.001) Moreover, patients with HC required postprocedure pacing more frequently (14% vs 2%, p <0.05). A distinctive pattern of ST displacement was found. There was more frequent ST depression in leads I and aVF and greater ST elevation in lead V(1) in patients who underwent ASA, indicating a greater tendency toward a rightward direction than was true in patients with LAD occlusions. In conclusion, in addition to more frequent right bundle branch block after ASA, a distinctive a characteristic pattern of ST-segment deviation similar to but distinct from that produced by proximal LAD occlusion appeared.     

Evaluating sustainable development policies in rural coastal economies

Sustainable development (SD) policies targeting marine economic sectors, designed to alleviate poverty and conserve marine ecosystems, have proliferated in recent years. Many developing countries are providing poor fishing households with new fishing boats (fishing capital) that can be used further offshore as a means to improve incomes and relieve fishing pressure on nearshore fish stocks. These kinds of policies are a marine variant of traditional SD policies focused on agriculture. Here, we evaluate ex ante economic and environmental impacts of provisions of fishing and agricultural capital, with and without enforcement of fishing regulations that prohibit the use of larger vessels in nearshore habitats. Combining methods from development economics, natural resource economics, and marine ecology, we use a unique dataset and modeling framework to account for linkages between households, business sectors, markets, and local fish stocks. We show that the policies investing capital in local marine fisheries or agricultural sectors achieve income gains for targeted households, but knock-on effects lead to increased harvest of nearshore fish, making them unlikely to achieve conservation objectives in rural coastal economies. However, pairing an agriculture stimulus with increasing enforcement of existing fisheries’ regulations may lead to a win–win situation. While marine-based policies could be an important tool to achieve two of the United Nations Sustainable Development Goals (alleviate poverty and protect vulnerable marine resources), their success is by no means assured and requires consideration of land and marine socioeconomic linkages inherent in rural economies.

Coastal and island nations are adopting “blue growth” sustainable development (SD) policies to alleviate poverty and conserve vulnerable ocean resources. Generally speaking, SD policies manage resources and direct investments in order to meet current and future human needs and aspirations, without endangering the natural systems (1). The feasibility and potential of SD has been the focus of decades of academic research; many regard the consideration of economic, social, environmental, and institutional needs and linkages as fundamental to successful policy design and implementation (2–6). Given their novelty, what constitutes a blue growth policy is not universal (7), but like traditional SD policies that focus on land-based sectors such as agriculture, manufacturing, and energy sectors (8, 9), blue growth policies seek to achieve social, economic, and environmental goals simultaneously (10). Blue growth policies attempt to achieve these goals by supporting marine-based industries such as offshore fishing, aquaculture, shipping, and tourism (11, 12). The marine focus has reinvigorated SD efforts of international organizations (including the Global Environmental Facility, United Nations Food and Agriculture Organization, the European Union, and The World Bank) that have collectively invested hundreds of millions of dollars into the development and monitoring of blue growth programs (12–16).While small-scale artisanal fishers consider a variety of factors when making fishing decisions (17), evidence suggests allocation of time is, in part, based on relative returns to labor (18–21). Thus, some blue growth policies attempt to alter returns to fishing relative to alternative income-generating activities as a way to achieve both poverty alleviation and conservation objectives. For example, if poor fishing households are incentivized to participate in offshore fishing, it may lead to increased household incomes and reduced fishing pressure on overexploited nearshore fish stocks (22, 23). Policies enforcing and increasing the regulation of fishing activities are also considered important to achieving blue growth objectives (10, 24).Many SD policies are designed to reduce upfront costs of switching to more sustainable livelihoods. Historically, large-scale fisheries receive the majority of subsidy benefits (25), arguably to the detriment of small-scale fisheries who are often outcompeted by industrialized operations (26). Recently, however, developing countries including Kenya, the Philippines, India, Tanzania, Vietnam, and Indonesia have been investing in programs that bolster the fishing capacity of small-scale and artisanal fishermen (27–33). These programs are designed to help small-scale fishers access larger or better vessels and gear, allowing them to reach more plentiful fishing grounds, compete with commercial vessels, and relieve pressure on vulnerable nearshore fisheries.Despite the recent surge in popularity, we lack evidence that these marine-based SD policies will achieve both poverty reduction and conservation objectives when implemented in rural economies. The complexity of coupled natural–human systems makes it difficult to measure the ex post performance of SD policies, especially in marine environments (34, 35). Additionally, local market failures due to high transportation costs and poorly developed marketing infrastructure (36) can lead to locally defined prices that fluctuate with changes in local supply and demand; local prices may distort household responses to policies, leading to unintended environmental consequences (37–40). Because local market failures are more common in rural economies in developing countries, methods and lessons learned from studies of industrialized fisheries in developed countries may not be relevant. Rather, management of fisheries in rural coastal economies may be more successful if market imperfections, alternative livelihood options, and ecological feedback are considered (20, 41–47).Recent studies explore the causal impacts of land-based SD policy instruments in developing countries (48–56). A key finding of these studies is that community heterogeneity is an important factor in policy performance. However, findings from forestry research do not necessarily carry over to marine settings because fish resources are mobile and regenerate relatively quickly, and, typically, access rights to fisheries are not well defined. This study begins to address the need for research examining responses to SD policy in rural coastal economies.We use a coupled natural–human modeling framework to estimate the ex ante impacts of common SD policies. Our ex ante mechanistic approach that includes a general equilibrium local economy model captures important dynamic feedback between the economy and health of the fish stocks. Indeed, other researchers have studied the correlations between markets and ecosystems in coastal communities in developing countries (44, 57–59). However, the theoretical structure of our analysis approach allows us to examine the causal mechanisms between policy and its outcomes. Our model captures the feedback between economic sectors and households within the economy (Fig. 1, details in SI Appendix). This broad scope is necessary to estimate the extent to which policies targeting poor households in a community also impact nontargeted households (knock-on effects). For example, a policy supporting a subset of fishing households could be detrimental to other households that harvest from the same fish stocks and compete in the same input and output markets.Open in a separate windowFig. 1.A conceptual framework for the bioeconomic local general equilibrium model. Households are represented by four representative groups and may produce goods and services (e.g., agricultural, offshore and nearshore fish, retail, and restaurants) available in local, and possibly global, markets. The simulated policies provide different types of capital to poor households and may also restrict use of fishing capital.Here, we estimate the impacts of two common marine fisheries policies (provision of offshore fishing vessels and increased enforcement of fishing regulations) and an alternative agricultural policy (provision of agricultural capital) in a rural coastal economy. To estimate the impacts of these SD policies in coastal economies, we use a modeling approach that has been developed using theory from development economics, natural resource economics, and marine ecology (37, 60). Introducing new features to the framework, we develop a model of a rural economy capable of disentangling fisher participation in two distinct fishing activities and household consumption of two fish goods. We use microeconomic data collected from household and business surveys to parameterize and calibrate our model, allowing us to realistically estimate policy impacts. An inherent strength to our methodology is the ability to adjust the structure of the model to represent alternative economies. We demonstrate how the model can be used to predict policy outcomes for a typology of rural coastal economies.Although combining policies that simultaneously target marine and agricultural sectors is currently not part of the dialogue on the adoption of blue SD policies around the world (e.g., see The World Bank’s strategy document for its Blue Economy Program and PROBLUE (13)), we find that pairing policy instruments that target both sectors—increased enforcement of vessel regulations and capital investments in the agricultural sector—is better able to achieve both conservation and poverty reduction goals.Why is an agricultural policy combined with enforcement capabilities of marine fishing regulations able to achieve a win–win while marine-focused SD policies are not? Our coupled natural–human modeling framework highlights the mechanisms leading to this counterintuitive outcome. That is, investing in the agricultural sector increases the returns to agricultural labor, which in turn creates upward pressure on wages and encourages a reduction in labor allocated to nearshore fishing. At the same time, the increased wealth in the local economy due to greater agricultural productivity drives up demand for nearshore fish. Although higher prices of fish draw some labor back into the fishery, increased enforcement of vessel regulations prevents fishers from illegally using larger boats in the nearshore habitat as a means to increase harvests. Without coupling increased enforcement and agricultural subsidy, the higher demand for fish would lead to increased harvests in the nearshore environment and lower fish stocks over time.     

Impact of radiation dose on late clinical outcome after intracoronary radiation therapy: three-year follow-up of Long WRIST.

To determine the safety and efficacy, including the impact, on the late recurrence rate of an incremental gamma-radiation dose from 15 to 18 Gy, we report the 3-year clinical outcome of Washington Radiation for In-Stent Restenosis Trial for Long Lesions (Long WRIST). One hundred eighty patients with recurrent in-stent restenosis (ISR) were enrolled in the Long WRIST series and treated with (192)Ir with 1 month of antiplatelet therapy. Between 6 months and 3 years, the need for repeat revascularization was low and similar among the three groups. At 3 years, target lesion revascularization (TLR) and major adverse cardiac events (MACE) were less frequent in the 18 Gy group than in the 15 Gy group (P = 0.12 for TLR, P < 0.05 for MACE) and less frequent in the 15 Gy group as compared to the placebo group (P < 0.05 for TLR and MACE). At 3 years, a higher dose of 18 Gy with (192)Ir continues to improve the outcome of patients treated for ISR when compared to patients treated with 15 Gy or placebo.     

Pilot Validation of a New Wireless Patch System as an Ambulatory,Noninvasive Tool That Measures Gut Myoelectrical Signals: Physiologic and Disease Correlations

Digestive Diseases and Sciences - Limited means exist to assess gastrointestinal activity in a noninvasive, objective way that is highly predictive of underlying motility disorders. The aim of this...     

False-Positive Rates of Reliable Change Indices for Concussion Test Batteries: A Monte Carlo Simulation

Background Neurocognitive testing is widely performed for the assessment of concussion. Athletic trainers can use preseason baselines with reliable change indices (RCIs) to ascertain whether concussed athletes'' cognitive abilities are below preinjury levels. Although the percentage of healthy individuals who show decline on any individual test is determined by its RCI''s confidence level (eg, 10% false-positive rate using an RCI with an 80% confidence interval), the expected rate of 1 or more significant RCIs across multiple indices is unclear.Objective To use a Monte Carlo simulation procedure to estimate the normal rate (ie, base rate) of significant decline on 1 or more RCIs in multitest batteries.

Results & Conclusion

 For batteries producing 7 or more uncorrelated RCIs (80% confidence intervals), the majority of normal individuals would show significant declines on at least 1 RCI. Expected rates are lower for tests with fewer indices, higher inter-RCI correlations, and more stringent impairment criteria. These reference points can help testers interpret RCI output for multitest batteries.Key Words: neurocognitive assessment, base rates, impairment

Key Points

• Clinicians evaluating concussed athletes often rely on the results of multiple tests or subtests to determine whether the athletes remain impaired.
• Base rates (ie, false-positive rates) of impairment are higher across multiple tests than for single tests, yet joint base rates of impairment are often not published.
• This simulation study illustrates how the properties of a test battery affect the expected base rates of impairment on 1 or more indices within the test battery.
• These data can be referenced when making decisions about how to set cut scores for determining impairment in the context of postconcussive evaluations.

Formal assessment of concussed athletes is commonplace in sports medicine, and a number of assessment tools are available to quantify symptoms, cognitive impairments, and other injury sequelae.^1–4 Computerized neurocognitive tests (CNTs) are especially popular for assessing neuropsychological abilities,^5,6 with nearly 40% of athletic trainers reporting use of a CNT in their concussion-management protocols in 2009–2010.⁵ The vast majority (85.9% to 94.7%) of athletic trainers who use CNTs perform preseason assessments so that concussed athletes'' postinjury scores can be compared with their individual premorbid estimates of ability.^5,7 The CNT programs facilitate the comparison of postinjury scores with baseline scores using output about the significance of reliable change indices (RCIs), which estimate the extent to which changes in athletes'' performance are statistically unusual after taking into account measurement error inherent to a test. In addition to CNTs, RCI cutoffs have been published for other concussion tests, including the Sport Concussion Assessment Tool 3 (SCAT3)^8,9 and paper-and-pencil tests of psychomotor speed.¹⁰Yet there is little published guidance about how to interpret RCI output for batteries with multiple indices. For any RCI, the expected false-positive rate is determined by the confidence interval (CI) applied to that RCI. For example, an RCI with a 90% confidence level should classify 5% of normal, healthy individuals as significantly declined from baseline (and, likewise, 5% as significantly improved). Similarly, 80% and 95% CIs should classify 10% and 2.5%, respectively, of normal individuals as significantly declined on average. Clinicians should select thresholds for significance according to their preferences for balancing sensitivity and specificity, with more lenient criteria expected to identify more impairment in concussed athletes (ie, increasing sensitivity) while inevitably also falsely identifying more healthy individuals as impaired (ie, diminishing specificity).Although the specificity for 1 RCI is predictable, the base rates (ie, rates of abnormal scores in the normal population) of significant decline across sets of RCIs have not been well documented. This is a problem because clinical decisions usually involve interpreting the results of multiple indices simultaneously, and the base rates of impairment for 1 or more RCIs considered together should be higher than the rate for individual RCIs. Knowing the joint probability of producing various numbers of significant indices in a set is critical to making informed clinical decisions for any test battery, as the neuropsychology literature has documented. For example, among community participants who completed a comprehensive neuropsychological assessment (comprising an average of 24 tests producing 43 scores), 71.9% of individuals showed at least 1 impaired score using a 1-standard deviation cutoff for impairment.¹¹ For a shorter neuropsychological battery (Wechsler Adult Intelligence Scale–III) with only 4 composite (index) scores, 24% of healthy individuals produced at least 1 abnormal index score (below the 10th percentile).¹² These rates depend on a number of factors, including the number of indices in the battery, their intercorrelations, and the impairment threshold for each measure. Supporting this principle in the context of concussion testing, 2 published studies on the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) battery demonstrated that 22.2% to 46% of healthy individuals produced at least 1 significantly declined RCI out of 5.^13,14The aim of our study was to estimate the base rates of significant decline in 1 or more of a set of RCIs simulating a range of conditions that match most concussion-assessment batteries. This was achieved using a Monte Carlo simulation method that has been found to accurately estimate overall impairment base rates in other neuropsychological batteries.^11,12,15 By varying the number of indices per battery, the correlations among indices, and the criteria for significance, the relationship between these factors and test specificity was illustrated. I discuss these data in the context of the advantages and costs of applying different impairment criteria for concussion-management decisions.     

Kinesio Tape and Shoulder-Joint Position Sense

Context

Joint position sense (JPS) is a key neuromuscular factor for developing and maintaining control of muscles around a joint. It is important when performing specialized tasks, especially at the shoulder. No researchers have studied how Kinesio Tape (KT) application affects JPS.

Objective

To investigate the effects of KT application and no tape on shoulder JPS at increasing shoulder elevations in athletes.

Design

Cross-sectional study.

Setting

University laboratory.

Patients or Other Participants

A total of 27 healthy athletes who did not participate in overhead sports (age = 20.44 ± 1.05 years, height = 175.02 ± 11.67 cm, mass = 70.74 ± 9.65 kg) with no previous pathologic shoulder conditions volunteered for the study. All participants were from 1 university.

Intervention(s)

Shoulder JPS was assessed at increasing elevations with and without KT application. Participants attempted to actively replicate 3 target positions with and without the KT and without visual guidance.

Main Outcome Measure(s)

We examined absolute and variable repositioning errors at increasing shoulder-elevation levels with and without KT application.

Results

Data revealed an interaction between tape and position for absolute error (F_2,52 = 4.07, P = .02); simple effects revealed an increase in error, with KT demonstrating a 2.65° increase in error at 90° of elevation compared with no tape (t₂₆ = 2.65, P = .01). The effect size was medium (ω² = .135). Variable error showed no interaction of tape and position (F_2,52 = .709, P = .50). Further analysis of simple effects was not needed. However, we still calculated the effect size and observed small effect sizes for tape (ω² = .002), position (ω² = .072), and tape by position (ω² = .027).

Conclusions

At 90° of elevation, shoulder JPS was impaired by the application of KT.Key Words: proprioception, taping, shoulder, neuromuscular, rehabilitation

Key Points

• Short-term Kinesio-Tape application to the shoulder reduced joint position sense acuity at 90° of elevation but did not affect JPS at 50° or 110°.
• Kinesio Tape may negatively affect shoulder joint position sense, especially as the shoulder position approaches 90° of elevation.

Athletes, especially those who participate in overhead activities, place much stress on their shoulder joints during activity, so they are at increased risk for developing shoulder injuries. Given that the shoulder allows for much mobility, stability is sacrificed; therefore, the shoulder is considered one of the most vulnerable joints in the body.¹ Numerous factors within the shoulder complex contribute to this lack of stability, including limited glenohumeral bony congruity, limited ligamentous support, and joint capsular laxity. However, stability is still needed to perform precise tasks for activities of daily living or sporting events.² Factors that provide stability to the joint include support of surrounding muscles, the intra-articular pressure of the joint, and the integration of the central nervous system with peripheral mechanoreceptors, a sensory system termed proprioception.³Proprioception is a specialized sensory capability that includes a person''s sense of movement, joint position, and tension.⁴ Joint position sense (JPS) consists of both static and dynamic abilities to detect the position of the joint in space.⁵ Researchers⁶ have suggested that increased muscle activation leads to increased afferent feedback from muscle spindles, resulting in enhanced JPS. The JPS is enabled via sensory feedback from peripheral receptors in sites such as skin, muscles, ligaments, and tendons that the central nervous system processes, and JPS is a key factor for controlling joint movement.⁴Investigators⁷ have observed that shoulder JPS improves as the shoulder-elevation angle approaches 90°. These results may indicate that as the elevation angle increases, the amount of gravitational torque increases, which increases muscle activation. Suprak et al⁷ hypothesized that this increase in muscle activation and the increase in activity from the musculotendinous mechanoreceptors contributed to improved JPS. Suprak et al⁸ supported these results, demonstrating that as resistance increased (via wrist weights) at a given shoulder position, shoulder repositioning error decreased. However, other authors⁵ have suggested that this effect of elevation on shoulder JPS may also be related to intrinsic factors of joint position, such as muscle-spindle and cutaneous-receptor activation.Researchers⁹ believe the application of tape may improve proprioceptive abilities by increasing stimulation of cutaneous mechanoreceptors within the skin, which increases pressure on underlying muscles and, therefore, affects the joint''s proprioception. Robbins et al¹⁰ reported that the application of ankle tape enhanced JPS when a person was on a surface with a slope greater than 10°. Traditional athletic tape can constrict joint range of motion (ROM) but can be a beneficial preventive measure; however, the integrity of the tape is not maintained for extended periods because of such extraneous factors as sweat, lotion, dirt, and hair. Therefore, the development of more specialized tapes that have longer-lasting effects and limit impairments has advanced in recent years. Effective tape application can last up to 1 to 2 days, and some of these specialty tapes can resist extraneous factors.Kinesio Tape (KT; Kinesio Precut, Albuquerque, NM) is a specialized elastic tape that mimics the elasticity of skeletal muscle as it stretches up to 140% of its original length, allowing for no ROM restrictions.^2,11 According to KT creator Kenzo Kase, it can strengthen an already weakened muscle by correcting the muscle''s function, improving circulation of blood and lymph, decreasing pain, repositioning subluxed joints, and improving joint position and kinesthetic awareness.¹² These effects allow the fascia and muscle to return to normal function by relieving the buildup of abnormal muscle tension and can improve joint function by increasing sensory mechanisms.^11,13The constant shear force produced by KT application against the skin leads to increased stimulation of the cutaneous mechanoreceptors.¹⁴ Murray¹⁴ observed an increase in electromyographic measurements after the application of KT to the thigh. He hypothesized that this increased mechanoreceptor activity would result in increased JPS acuity. His research also supported the claim that KT application to the thigh can improve active ROM of a joint compared with no tape.¹⁴ Murray¹⁴ asserted that KT can positively affect proprioception. However, other investigators¹¹ have demonstrated no effect of KT application on the ability to actively replicate a passive ankle position. This discrepancy in observations warrants further investigation given the popularity of KT use in athletics and rehabilitation. No one has examined how KT affects shoulder JPS. Therefore, the purpose of our study was to assess the effects of KT application on shoulder JPS at increasing shoulder elevations in athletes. We hypothesized that the application of KT (1) would result in enhanced shoulder JPS at all elevation angles tested and (2) would not alter the effect of increased JPS acuity with elevation.     

The development of an instrument to evaluate interprofessional student team competency

Healthcare institutions, accreditation agencies for higher learning, and organizations such as the National Academy of Medicine in the United States, support interprofessional education (IPE) opportunities. However, incorporating IPE opportunities into academic settings remains difficult. One challenge is assessing IPE learning and practice outcomes, especially at the level of student performance to ensure graduates are “collaboration-ready”. The Creighton-Interprofessional Collaborative Evaluation (C-ICE) instrument was developed to address the need for a measurement tool for interprofessional student team performance. Four interprofessional competency domains provide the framework for the C-ICE instrument. Twenty-six items were identified as essential to include in the C-ICE instrument. This instrument was found to be both a reliable and a valid instrument to measure interprofessional interactions of student teams. Inter-rater reliability as measured by Krippendorff’s nominal alpha (nKALPHA) ranged from .558 to .887; with four of the five independent assessments achieving nKALPHA greater than or equal to 0.796. The findings indicated that the instrument is understandable (Gwet’s alpha coefficient (gAC) 0.63), comprehensive (gAC = 0.62), useful and applicable (gAC = 0.54) in a variety of educational settings. The C-ICE instrument provides educators a comprehensive evaluation tool for assessing student team behaviors, skills, and performance.