Citations

Abstract Objective : Blood flow waveforms—essential data for hemodynamic modeling—are often in practice unavailable to researchers. The objectives of this work were to assess the variability among the waveforms for a clinically relevant older population, and develop data-based methods for addressing the missing waveform data for hemodynamic studies. Approach : We analyzed 272 flow waveforms from the internal carotid arteries of older patients (73 ± 13 yr) with moderate cardiovascular disease, and used these data to develop methods to guide new approaches for hemodynamic studies. Main results : Profound variations in waveform parameters were found within the aged population that were not seen in published data for young subjects. Common features in the aged population relative to the young included a larger systole-to-diastole flow rate ratio, increased flow during late systole, and absence of a dicrotic notch. Eight waveforms were identified that collectively represent the range of waveforms in the older population. A relationship between waveform shape and flow rate was obtained that, in conjunction with equations relating flow rate to diameter, can be used to provide individualized waveforms for patient-specific geometries. The dependence of flow rate on diameter was statistically different between male and female patients. Significance : It was shown that a single archetypal waveform cannot well-represent the diverse waveforms found within an aged population, although this approach is frequently used in studies of flow in the cerebral vasculature. Motivated by these results, we provided a set of eight waveforms that can be used to assess the hemodynamic uncertainty associated with the lack of patient-specific waveform data. We also provided a methodology for generating individualized waveforms when patient gender, age, and cardiovascular disease state are known. These data-driven approaches can be used to devise more relevant in vitro or in silico intra-cranial hemodynamic studies for older patients.

OBJECTIVE Intensive treatment (INT) of type 1 diabetes reduces the incidence of cardiovascular disease (CVD) events compared with conventional treatment (CONV), but it also results in more weight gain. Our objective was to examine whether excessive weight gain from INT of type 1 diabetes is independently associated with subsequent CVD events. RESEARCH DESIGN AND METHODS Quartiles (Q) of weight gain in 1,213 participants aged 18 years and older at enrollment in the Diabetes Control and Complications Trial (DCCT) were determined within randomized treatment groups (INT vs. CONV) using change in BMI from baseline to the closeout DCCT visits. Effects of this weight gain on CVD risk factors and outcomes during an additional 20 years of observational follow-up were then determined. RESULTS The Q4 INT group experienced greater proportional weight gain (median change in BMI, 6.08 kg/m2), increases in CVD risk factors, and need for medications for hypertension and lipids compared with the Q1–3 INT and comparable CONV groups. Over a mean of 26 years of follow-up, the numbers of major and total CVD events were not statistically different in Q4 compared with Q1–3 of either the INT or CONV group. By year 14, however, the incident CVD event curve became significantly higher in the Q4 INT group than in the Q1–3 INT groups (P = 0.024) and was similar to that for the CONV group. CONCLUSIONS For the first 13 years after DCCT, INT for type 1 diabetes reduced macrovascular events compared with CONV, even when excessive weight gain occurred. After this, total CVD events significantly increased in the Q4 INT group, becoming equivalent to those in the CONV group. Longer follow-up is needed to determine whether this trend continues and results in more major CVD events.

SummaryDue to the introduction of newer, more efficacious treatment options, there is a pressing need for policy makers and public health officials to develop or adapt national hepatitis C virus (HCV) control strategies to the changing epidemiological landscape. To do so, detailed, country‐specific data are needed to characterize the burden of chronic HCV infection. In this study of 17 countries, a literature review of published and unpublished data on HCV prevalence, viraemia, genotype, age and gender distribution, liver transplants and diagnosis and treatment rates was conducted, and inputs were validated by expert consensus in each country. Viraemic prevalence in this study ranged from 0.2% in Hong Kong to 2.4% in Taiwan, while the largest viraemic populations were in Nigeria (2 597 000 cases) and Taiwan (569 000 cases). Diagnosis, treatment and liver transplant rates varied widely across the countries included in this analysis, as did the availability of reliable data. Addressing data gaps will be critical for the development of future strategies to manage and minimize the disease burden of hepatitis C.

SummaryFactors influencing the morbidity and mortality associated with viremic hepatitis C virus (HCV) infection change over time and place, making it difficult to compare reported estimates. Models were developed for 17 countries (Bahrain, Bulgaria, Cameroon, Colombia, Croatia, Dominican Republic, Ethiopia, Ghana, Hong Kong, Jordan, Kazakhstan, Malaysia, Morocco, Nigeria, Qatar and Taiwan) to quantify and characterize the viremic population as well as forecast the changes in the infected population and the corresponding disease burden from 2015 to 2030. Model inputs were agreed upon through expert consensus, and a standardized methodology was followed to allow for comparison across countries. The viremic prevalence is expected to remain constant or decline in all but four countries (Ethiopia, Ghana, Jordan and Oman); however, HCV‐related morbidity and mortality will increase in all countries except Qatar and Taiwan. In Qatar, the high‐treatment rate will contribute to a reduction in total cases and HCV‐related morbidity by 2030. In the remaining countries, however, the current treatment paradigm will be insufficient to achieve large reductions in HCV‐related morbidity and mortality.

SummaryThe hepatitis C virus (HCV) epidemic was forecasted through 2030 for 17 countries in Africa, Asia, Europe, Latin America and the Middle East, and interventions for achieving the Global Health Sector Strategy on viral hepatitis targets—“WHO Targets” (65% reduction in HCV‐related deaths, 90% reduction in new infections and 90% of infections diagnosed by 2030) were considered. Scaling up treatment and diagnosis rates over time would be required to achieve these targets in all but one country, even with the introduction of high SVR therapies. The scenarios developed to achieve the WHO Targets in all countries studied assumed the implementation of national policies to prevent new infections and to diagnose current infections through screening.

Total artificial hearts (TAH) can be used as a bridge to transplant or, occasionally, as destination therapy for patients with severe biventricular dysfunction. Not infrequently TAHs are placed in patients with severe low flow states, in which the lungs of these patients are unable to adjust rapidly to the “normal” right ventricular output of a TAH. These patients may develop variable degrees of pulmonary edema secondary to stress failure of the pulmonary capillaries requiring increased respiratory support, which can occasionally be fatal. In this “how to do it” article, we describe the technique for a pulmonary arteriovenous extracorporeal membrane oxygenation with TAH to avoid sudden pulmonary overflow and gradually expose the lungs to increasing flow.

Purpose We propose a robust treatment planning model that simultaneously considers proton range and patient setup uncertainties and reduces high linear energy transfer (LET) exposure in organs at risk (OARs) to minimize the relative biological effectiveness (RBE) dose in OARs for intensity‐modulated proton therapy (IMPT). Our method could potentially reduce the unwanted damage to OARs. Methods We retrospectively generated plans for 10 patients including two prostate, four head and neck, and four lung cancer patients. The “worst‐case robust optimization” model was applied. One additional term as a “biological surrogate (BS)” of OARs due to the high LET‐related biological effects was added in the objective function. The biological surrogate was defined as the sum of the physical dose and extra biological effects caused by the dose‐averaged LET. We generated nine uncertainty scenarios that considered proton range and patient setup uncertainty. Corresponding to each uncertainty scenario, LET was obtained by a fast LET calculation method developed in‐house and based on Monte Carlo simulations. In each optimization iteration, the model used the worst‐case BS among all scenarios and then penalized overly high BS to organs. The model was solved by an efficient algorithm (limited‐memory Broyden–Fletcher–Goldfarb–Shanno) in a parallel computing environment. Our new model was benchmarked with the conventional robust planning model without considering BS. Dose–volume histograms (DVHs) of the dose assuming a fixed RBE of 1.1 and BS for tumor and organs under nominal and uncertainty scenarios were compared to assess the plan quality between the two methods. Results For the 10 cases, our model outperformed the conventional robust model in avoidance of high LET in OARs. At the same time, our method could achieve dose distributions and plan robustness of tumors assuming a fixed RBE of 1.1 almost the same as those of the conventional robust model. Conclusions Explicitly considering LET in IMPT robust treatment planning can reduce the high LET to OARs and minimize the possible toxicity of high RBE dose to OARs without sacrificing plan quality. We believe this will allow one to design and deliver safer proton therapy.