G-factor of electrons in gate-defined quantum dots in a strong in-plane magnetic field

We analyze orbital effects of an in-plane magnetic field on the spin structure of states of a gated quantum dot based in a two-dimensional electron gas. Starting with a $k \cdot p$ Hamiltonian, we perturbatively calculate these effects for the conduction band of GaAs, up to the third power of the magnetic field. We quantify several corrections to the g-tensor and reveal their relative importance. We find that for typical parameters, the Rashba spin-orbit term and the isotropic term, $H_{43} \propto {\bf P}^2 {\bf B} \cdot \boldsymbol{\sigma}$, give the largest contributions in magnitude. The in-plane anisotropy of the g-factor is, on the other hand, dominated by the Dresselhaus spin-orbit term. At zero magnetic field, the total correction to the g-factor is typically 5-10% of its bulk value. In strong in-plane magnetic fields, the corrections are modified appreciably.Comment: 24 pages, 8 figures; v2 is in content identical to the version published in PRB. Compared to v1, the minor changes adopted in v2 are reflecting the PRB referees' suggestion

The paradox of verbal autopsy in cause of death assignment: symptom question unreliability but predictive accuracy

Background: We believe that it is important that governments understand the reliability of the mortality data which they have at their disposable to guide policy debates. In many instances, verbal autopsy (VA) will be the only source of mortality data for populations, yet little is known about how the accuracy of VA diagnoses is affected by the reliability of the symptom responses. We previously described the effect of the duration of time between death and VA administration on VA validity. In this paper, using the same dataset, we assess the relationship between the reliability and completeness of symptom responses and the reliability and accuracy of cause of death (COD) prediction. Methods: The study was based on VAs in the Population Health Metrics Research Consortium (PHMRC) VA Validation Dataset from study sites in Bohol and Manila, Philippines and Andhra Pradesh, India. The initial interview was repeated within 3-52 months of death. Question responses were assessed for reliability and completeness between the two survey rounds. COD was predicted by Tariff Method. Results: A sample of 4226 VAs was collected for 2113 decedents, including 1394 adults, 349 children, and 370 neonates. Mean question reliability was unexpectedly low (kappa = 0.447): 42.5 % of responses positive at the first interview were negative at the second, and 47.9 % of responses positive at the second had been negative at the first. Question reliability was greater for the short form of the PHMRC instrument (kappa = 0.497) and when analyzed at the level of the individual decedent (kappa = 0.610). Reliability at the level of the individual decedent was associated with COD predictive reliability and predictive accuracy. Conclusions: Families give coherent accounts of events leading to death but the details vary from interview to interview for the same case. Accounts are accurate but inconsistent; different subsets of symptoms are identified on each occasion. However, there are sufficient accurate and consistent subsets of symptoms to enable the Tariff Method to assign a COD. Questions which contributed most to COD prediction were also the most reliable and consistent across repeat interviews; these have been included in the short form VA questionnaire. Accuracy and reliability of diagnosis for an individual death depend on the quality of interview. This has considerable implications for the progressive roll out of VAs into civil registration and vital statistics (CRVS) systems

Using Verbal Autopsy to Measure Causes of Death: the Comparative Performance of Existing Methods.

Monitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability. We investigated the validity of five automated VA methods for assigning cause of death: InterVA-4, Random Forest (RF), Simplified Symptom Pattern (SSP), Tariff method (Tariff), and King-Lu (KL), in addition to physician review of VA forms (PCVA), based on 12,535 cases from diverse populations for which the true cause of death had been reliably established. For adults, children, neonates and stillbirths, performance was assessed separately for individuals using sensitivity, specificity, Kappa, and chance-corrected concordance (CCC) and for populations using cause specific mortality fraction (CSMF) accuracy, with and without additional diagnostic information from prior contact with health services. A total of 500 train-test splits were used to ensure that results are robust to variation in the underlying cause of death distribution. Three automated diagnostic methods, Tariff, SSP, and RF, but not InterVA-4, performed better than physician review in all age groups, study sites, and for the majority of causes of death studied. For adults, CSMF accuracy ranged from 0.764 to 0.770, compared with 0.680 for PCVA and 0.625 for InterVA; CCC varied from 49.2% to 54.1%, compared with 42.2% for PCVA, and 23.8% for InterVA. For children, CSMF accuracy was 0.783 for Tariff, 0.678 for PCVA, and 0.520 for InterVA; CCC was 52.5% for Tariff, 44.5% for PCVA, and 30.3% for InterVA. For neonates, CSMF accuracy was 0.817 for Tariff, 0.719 for PCVA, and 0.629 for InterVA; CCC varied from 47.3% to 50.3% for the three automated methods, 29.3% for PCVA, and 19.4% for InterVA. The method with the highest sensitivity for a specific cause varied by cause. Physician review of verbal autopsy questionnaires is less accurate than automated methods in determining both individual and population causes of death. Overall, Tariff performs as well or better than other methods and should be widely applied in routine mortality surveillance systems with poor cause of death certification practices

Global and national Burden of diseases and injuries among children and adolescents between 1990 and 2013

Importance The literature focuses on mortality among children younger than 5 years. Comparable information on nonfatal health outcomes among these children and the fatal and nonfatal burden of diseases and injuries among older children and adolescents is scarce. Objective To determine levels and trends in the fatal and nonfatal burden of diseases and injuries among younger children (aged <5 years), older children (aged 5-9 years), and adolescents (aged 10-19 years) between 1990 and 2013 in 188 countries from the Global Burden of Disease (GBD) 2013 study. Evidence Review Data from vital registration, verbal autopsy studies, maternal and child death surveillance, and other sources covering 14 244 site-years (ie, years of cause of death data by geography) from 1980 through 2013 were used to estimate cause-specific mortality. Data from 35 620 epidemiological sources were used to estimate the prevalence of the diseases and sequelae in the GBD 2013 study. Cause-specific mortality for most causes was estimated using the Cause of Death Ensemble Model strategy. For some infectious diseases (eg, HIV infection/AIDS, measles, hepatitis B) where the disease process is complex or the cause of death data were insufficient or unavailable, we used natural history models. For most nonfatal health outcomes, DisMod-MR 2.0, a Bayesian metaregression tool, was used to meta-analyze the epidemiological data to generate prevalence estimates. Findings Of the 7.7 (95% uncertainty interval [UI], 7.4-8.1) million deaths among children and adolescents globally in 2013, 6.28 million occurred among younger children, 0.48 million among older children, and 0.97 million among adolescents. In 2013, the leading causes of death were lower respiratory tract infections among younger children (905 059 deaths; 95% UI, 810 304-998 125), diarrheal diseases among older children (38 325 deaths; 95% UI, 30 365-47 678), and road injuries among adolescents (115 186 deaths; 95% UI, 105 185-124 870). Iron deficiency anemia was the leading cause of years lived with disability among children and adolescents, affecting 619 (95% UI, 618-621) million in 2013. Large between-country variations exist in mortality from leading causes among children and adolescents. Countries with rapid declines in all-cause mortality between 1990 and 2013 also experienced large declines in most leading causes of death, whereas countries with the slowest declines had stagnant or increasing trends in the leading causes of death. In 2013, Nigeria had a 12% global share of deaths from lower respiratory tract infections and a 38% global share of deaths from malaria. India had 33% of the world’s deaths from neonatal encephalopathy. Half of the world’s diarrheal deaths among children and adolescents occurred in just 5 countries: India, Democratic Republic of the Congo, Pakistan, Nigeria, and Ethiopia. Conclusions and Relevance Understanding the levels and trends of the leading causes of death and disability among children and adolescents is critical to guide investment and inform policies. Monitoring these trends over time is also key to understanding where interventions are having an impact. Proven interventions exist to prevent or treat the leading causes of unnecessary death and disability among children and adolescents. The findings presented here show that these are underused and give guidance to policy makers in countries where more attention is needed

Reliability of verbal autopsies and its implications for routine cause of death surveillance

Thesis (Master's)--University of Washington, 2014Background Verbal autopsies (VAs) have been widely used to determine cause of death (COD) for research in developing countries. Understanding the quality of these estimates is essential for research and policy making. Quality of VA surveys can be assessed both in terms of validity and reliability. The former has been extensively researched, but there is not much evidence available for the latter. This study aims to determine if VAs yield consistent results by quantifying the test-retest reliability of verbal autopsies and exploring possible factors associated with reliability in the context of VAs. Methods For this study we collected two VAs for 2,113 decedents in Bohol, Philippines; Manila, Philippines; and Andhra Pradesh, India using the Population Health Metrics Research Consortium (PHMRC) Verbal Autopsy Instrument (VAI). COD was predicted using the Tariff Method for VA analysis. Reliability was measured for question responses, COD predictions for individual deaths, and predicted cause-specific mortality fractions (CSMFs). Factors associated with reliability of VA question responses and COD predictions were examined in a regression framework. Results We found that although responses to specific questions were often unreliable, there was a much greater degree of reliability for cause of death estimates, particularly at the population-level. Both the interviewer and respondent were found to have significant effects on the reliability of VA questions. We also found the reliability of question responses had a significant effect on the reliability of COD predictions. Interpretation Based these results we recommend a greater emphasis be placed on the standardization of VA administration protocols and the training of interviewers. COD estimates derived from VA are essential to informing public health research and policy. Therefore, we must work to ensure that the COD predictions and the survey data underlying them are as reliable as possible

Clinical predictors of early second event in patients with clinically isolated syndrome

This study aimed to determine the predictors of increased risk of a second demyelinating event within the first year of an initial demyelinating event (IDE) suggestive of early multiple sclerosis (MS). Patients with MS or clinically isolated syndrome (CIS) seen at the UCSF MS Center within one year of the IDE were studied. Univariate and multivariate Cox models were used to analyze predictors of having a second event within 1 year of the IDE. Of 330 patients with MS/CIS, 111 had a second event within 1 year. Non-white race/ethnicity (HR = 2.39, 95% CI [1.58, 3.60], p &lt; 0.0001) and younger age (HR for each 10-year decrease in age = 1.51, 95% CI [1.28, 1.80], p &lt; 0.0001) were strongly associated with an increased risk of having a second event within one year of onset. Having a lower number of functional systems affected by the IDE was also associated with an increased risk of early second event (HR for every one less FS involved = 1.31, 95% CI [1.06, 1.61], p = 0.011). These results were similar after adjusting for treatment of the IDE with steroids and disease-modifying therapy. Non-white race/ethnicity, younger age, and a lower number of FS affected by the IDE are associated with a substantially increased hazard ratio for a second demyelinating event within 1 year. Since early relapse is predictive of worse long-term outcome, identifying and treating such patients after the IDE may be of benefit to them

Clinical predictors of early second event in patients with clinically isolated syndrome.

This study aimed to determine the predictors of increased risk of a second demyelinating event within the first year of an initial demyelinating event (IDE) suggestive of early multiple sclerosis (MS). Patients with MS or clinically isolated syndrome (CIS) seen at the UCSF MS Center within one year of the IDE were studied. Univariate and multivariate Cox models were used to analyze predictors of having a second event within 1 year of the IDE. Of 330 patients with MS/CIS, 111 had a second event within 1 year. Non-white race/ethnicity (HR = 2.39, 95% CI [1.58, 3.60], p &lt; 0.0001) and younger age (HR for each 10-year decrease in age = 1.51, 95% CI [1.28, 1.80], p &lt; 0.0001) were strongly associated with an increased risk of having a second event within one year of onset. Having a lower number of functional systems affected by the IDE was also associated with an increased risk of early second event (HR for every one less FS involved = 1.31, 95% CI [1.06, 1.61], p = 0.011). These results were similar after adjusting for treatment of the IDE with steroids and disease-modifying therapy. Non-white race/ethnicity, younger age, and a lower number of FS affected by the IDE are associated with a substantially increased hazard ratio for a second demyelinating event within 1 year. Since early relapse is predictive of worse long-term outcome, identifying and treating such patients after the IDE may be of benefit to them