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Institution

State University of New York System

EducationAlbany, New York, United States
About: State University of New York System is a education organization based out in Albany, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 54077 authors who have published 78070 publications receiving 2985160 citations.
Topics: Population, Poison control, RNA, Gene, Receptor


Papers
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Journal ArticleDOI
Hmwe H Kyu1, Christine Pinho1, Joseph Wagner1, Jonathan C Brown1  +199 moreInstitutions (118)
TL;DR: 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 and give guidance to policy makers in countries where more attention is needed.
Abstract: 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 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.

486 citations

Journal ArticleDOI
TL;DR: As a novice qualitative researcher, the author had little idea of the significant and vital role of transcription in the qualitative research process until she undertook her own transcription tasks as mentioned in this paper, and had little understanding of the importance of the transcription in qualitative research.
Abstract: As a novice qualitative researcher, the author had little idea of the significant and vital role of transcription in the qualitative research process until she undertook her own transcription tasks...

486 citations

Journal ArticleDOI
TL;DR: A recursive equation is derived to combine a variable number of family history reports, wherein the probabilities associated with a single report are computed from the logistic analysis, which permits the use offamily history information both as a proxy for an uninterviewed relative, as well as a second source of information to be used in the analysis of genetic family data.
Abstract: Using data from The Collaborative Study on the Genetics of Alcoholism, we compare direct interview diagnoses of alcohol dependence to those obtained by history from family members. Using a requirement of three or more positive implications by history, the specificity, sensitivity, and positive predictive values are 98%, 39%, and 45%, respectively. A logistic analysis found the gender of the relative and alcoholism in the informant to be significant, but not the gender of the informant. The partial odds ratio of a diagnosis at interview associated with a positive family history diagnosis was 13.6. The relationship between the informant and relative was significant, with negative reports from an offspring or mate more influential than a negative report from a parent or second-degree relative. We derived a recursive equation to combine a variable number of family history reports, wherein the probabilities associated with a single report are computed from the logistic analysis. This permits the use of family history information both as a proxy for an uninterviewed relative, as well as a second source of information to be used in the analysis of genetic family data.

485 citations

Journal ArticleDOI
TL;DR: Patients who believed they could not control the CO2 administration were significantly more likely to report panic attacks and psychologic factors to laboratory induction of panic attacks through inhalation of 5.5% CO2-enriched air.
Abstract: The current study tested the notion that a sense of control can mitigate anxiety and panic attacks caused by the inhalation of 5.5% carbon dioxide (CO2)-enriched air. Twenty patients with panic disorder inhaled a mixture of 5.5% CO2-enriched air for 15 minutes. All patients were instructed that illumination of a light directly in front of them would signal that they could decrease the amount of CO2 that they were receiving, if desired, by turning a dial attached to their chair. For ten patients, the light was illuminated during the entire administration of CO2. For the remaining ten patients, the light was never illuminated. In fact, all patients experienced the full CO2 mixture, and the dial was ineffective. When compared with patients who believed they had control, patients who believed they could not control the CO2 administration (1) reported a greater number of DSM-III-revised panic attack symptoms, (2) rated the symptoms as more intense, (3) reported greater subjective anxiety, (4) reported a greater number of catastrophic cognitions, (5) reported a greater resemblance of the overall inhalation experience to a naturally occurring panic attack, and (6) were significantly more likely to report panic attacks. These data illustrate the contribution of psychologic factors to laboratory induction of panic attacks through inhalation of 5.5% CO2-enriched air.

485 citations

Journal ArticleDOI
TL;DR: The use of Gaussian particle filters and Gaussian sum particle filters are extended to dynamic state space (DSS) models with non-Gaussian noise and problems involving heavy-tailed densities can be conveniently addressed.
Abstract: We use the Gaussian particle filter to build several types of Gaussian sum particle filters. These filters approximate the filtering and predictive distributions by weighted Gaussian mixtures and are basically banks of Gaussian particle filters. Then, we extend the use of Gaussian particle filters and Gaussian sum particle filters to dynamic state space (DSS) models with non-Gaussian noise. With non-Gaussian noise approximated by Gaussian mixtures, the non-Gaussian noise models are approximated by banks of Gaussian noise models, and Gaussian mixture filters are developed using algorithms developed for Gaussian noise DSS models. As a result, problems involving heavy-tailed densities can be conveniently addressed. Simulations are presented to exhibit the application of the framework developed herein, and the performance of the algorithms is examined.

484 citations


Authors

Showing all 54162 results

NameH-indexPapersCitations
Meir J. Stampfer2771414283776
Bert Vogelstein247757332094
Zhong Lin Wang2452529259003
Peter Libby211932182724
Robert M. Califf1961561167961
Stephen V. Faraone1881427140298
David L. Kaplan1771944146082
David Baker1731226109377
Nora D. Volkow165958107463
David R. Holmes1611624114187
Richard J. Davidson15660291414
Ronald G. Crystal15599086680
Jovan Milosevic1521433106802
James J. Collins15166989476
Mark A. Rubin14569995640
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202325
2022168
20212,825
20202,891
20192,528
20182,456