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Book: Child and adolescent psychiatry

Turk, Jeremy / Graham, P. J. / Verhulst, Frank C.

a developmental approach

2007

Author's details	Jeremy Turk ; Philip Graham ; Frank C. Verhulst
Keywords	Mental Disorders ; Child Development ; Adolescent Development ; Infant ; Child ; Adolescent ; Child psychiatry ; Adolescent psychiatry
Subject code	618.9289
Language	English
Size	IX, 456 S. : Ill., 25cm
Edition	4. ed.
Publisher	Oxford Univ. Press
Publishing place	Oxford
Publishing country	Great Britain
Document type	Book
Old title	3. Aufl. u.d.T. Graham, Philip J.: Child psychiatry
HBZ-ID	HT014875180
ISBN	0-19-921669-X ; 0-19-852612-1 ; 978-0-19-921669-7 ; 978-0-19-852612-4
Database	Catalogue ZB MED Medicine, Health

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Article ; Online: Estimating contact network properties by integrating multiple data sources associated with infectious diseases.

Goyal, Ravi / Carnegie, Nicole / Slipher, Sally / Turk, Philip / Little, Susan J / De Gruttola, Victor

Statistics in medicine

2023 Volume 42, Issue 20, Page(s) 3593–3615

Abstract: To effectively mitigate the spread of communicable diseases, it is necessary to understand the interactions that enable disease transmission among individuals in a population; we refer to the set of these interactions as a contact network. The structure ... ...

Abstract	To effectively mitigate the spread of communicable diseases, it is necessary to understand the interactions that enable disease transmission among individuals in a population; we refer to the set of these interactions as a contact network. The structure of the contact network can have profound effects on both the spread of infectious diseases and the effectiveness of control programs. Therefore, understanding the contact network permits more efficient use of resources. Measuring the structure of the network, however, is a challenging problem. We present a Bayesian approach to integrate multiple data sources associated with the transmission of infectious diseases to more precisely and accurately estimate important properties of the contact network. An important aspect of the approach is the use of the congruence class models for networks. We conduct simulation studies modeling pathogens resembling SARS-CoV-2 and HIV to assess the method; subsequently, we apply our approach to HIV data from the University of California San Diego Primary Infection Resource Consortium. Based on simulation studies, we demonstrate that the integration of epidemiological and viral genetic data with risk behavior survey data can lead to large decreases in mean squared error (MSE) in contact network estimates compared to estimates based strictly on risk behavior information. This decrease in MSE is present even in settings where the risk behavior surveys contain measurement error. Through these simulations, we also highlight certain settings where the approach does not improve MSE.
MeSH term(s)	Humans ; Bayes Theorem ; Information Sources ; SARS-CoV-2 ; COVID-19/epidemiology ; Communicable Diseases/epidemiology ; HIV Infections/epidemiology
Language	English
Publishing date	2023-07-01
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ZDB-ID	843037-8
ISSN	1097-0258 ; 0277-6715
ISSN (online)	1097-0258
ISSN	0277-6715
DOI	10.1002/sim.9816
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Article ; Online: Publisher Correction: A predictive internet-based model for COVID-19 hospitalization census.

Turk, Philip J / Tran, Thao P / Rose, Geoffrey A / McWilliams, Andrew

Scientific reports

2021 Volume 11, Issue 1, Page(s) 17182

Language	English
Publishing date	2021-08-19
Publishing country	England
Document type	Published Erratum
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-96363-y
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Forecasting COVID-19 Hospital Census: A Multivariate Time-Series Model Based on Local Infection Incidence.

Nguyen, Hieu M / Turk, Philip J / McWilliams, Andrew D

JMIR public health and surveillance

2021 Volume 7, Issue 8, Page(s) e28195

Abstract: Background: COVID-19 has been one of the most serious global health crises in world history. During the pandemic, health care systems require accurate forecasts for key resources to guide preparation for patient surges. Forecasting the COVID-19 hospital ...

Abstract	Background: COVID-19 has been one of the most serious global health crises in world history. During the pandemic, health care systems require accurate forecasts for key resources to guide preparation for patient surges. Forecasting the COVID-19 hospital census is among the most important planning decisions to ensure adequate staffing, number of beds, intensive care units, and vital equipment. Objective: The goal of this study was to explore the potential utility of local COVID-19 infection incidence data in developing a forecasting model for the COVID-19 hospital census. Methods: The study data comprised aggregated daily COVID-19 hospital census data across 11 Atrium Health hospitals plus a virtual hospital in the greater Charlotte metropolitan area of North Carolina, as well as the total daily infection incidence across the same region during the May 15 to December 5, 2020, period. Cross-correlations between hospital census and local infection incidence lagging up to 21 days were computed. A multivariate time-series framework, called the vector error correction model (VECM), was used to simultaneously incorporate both time series and account for their possible long-run relationship. Hypothesis tests and model diagnostics were performed to test for the long-run relationship and examine model goodness of fit. The 7-days-ahead forecast performance was measured by mean absolute percentage error (MAPE), with time-series cross-validation. The forecast performance was also compared with an autoregressive integrated moving average (ARIMA) model in the same cross-validation time frame. Based on different scenarios of the pandemic, the fitted model was leveraged to produce 60-days-ahead forecasts. Results: The cross-correlations were uniformly high, falling between 0.7 and 0.8. There was sufficient evidence that the two time series have a stable long-run relationship at the .01 significance level. The model had very good fit to the data. The out-of-sample MAPE had a median of 5.9% and a 95th percentile of 13.4%. In comparison, the MAPE of the ARIMA had a median of 6.6% and a 95th percentile of 14.3%. Scenario-based 60-days-ahead forecasts exhibited concave trajectories with peaks lagging 2 to 3 weeks later than the peak infection incidence. In the worst-case scenario, the COVID-19 hospital census can reach a peak over 3 times greater than the peak observed during the second wave. Conclusions: When used in the VECM framework, the local COVID-19 infection incidence can be an effective leading indicator to predict the COVID-19 hospital census. The VECM model had a very good 7-days-ahead forecast performance and outperformed the traditional ARIMA model. Leveraging the relationship between the two time series, the model can produce realistic 60-days-ahead scenario-based projections, which can inform health care systems about the peak timing and volume of the hospital census for long-term planning purposes.
MeSH term(s)	COVID-19/epidemiology ; COVID-19/therapy ; Censuses ; Forecasting/methods ; Hospitals ; Humans ; Incidence ; Models, Theoretical ; Multivariate Analysis ; North Carolina/epidemiology
Language	English
Publishing date	2021-08-04
Publishing country	Canada
Document type	Journal Article
ISSN	2369-2960
ISSN (online)	2369-2960
DOI	10.2196/28195
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Assessing Platelet Mitochondrial Dysfunction in a Murine Model of Acute Acetaminophen Toxicity.

Fox, Carolyn / Ekaney, Michael L / Runyon, Michael / Nguyen, Hieu M / Turk, Philip J / McKillop, Iain H / Murphy, Christine M

Journal of medical toxicology : official journal of the American College of Medical Toxicology

2023 Volume 19, Issue 4, Page(s) 341–351

Abstract: Introduction: Acetaminophen (APAP) toxicity remains a significant cause of adult and pediatric liver failure in North America and Europe. Previous research has evaluated the impaired mitochondrial function associated with APAP toxicity. The primary aim ... ...

Abstract	Introduction: Acetaminophen (APAP) toxicity remains a significant cause of adult and pediatric liver failure in North America and Europe. Previous research has evaluated the impaired mitochondrial function associated with APAP toxicity. The primary aim of this study was to evaluate the effects of APAP toxicity on platelet mitochondrial function using platelet oxygen consumption in a murine model in vivo. Our secondary objectives were to determine the effect of 4-MP on platelet mitochondrial function and hepatic toxicity in the setting of APAP overdose, and to correlate platelet mitochondrial function with other markers of APAP toxicity. Methods: Male C57Bl/6 mice were randomized to receive APAP (300 or 500 mg/kg) or vehicle followed 90 minutes later by either 4-MP (50 mg/kg) or vehicle via intraperitoneal injection. Mice were euthanized 0, 12, or 24 hours later and platelets isolated from cardiac blood and counted. Platelet oxygen consumption (POC) was determined using a closed-system respirometer. Liver injury was assessed by measuring alanine transferase (ALT) and histological evaluation. Results: Injection of 500 mg/kg APAP led to increased POC versus pair-matched control (vehicle) (p < 0.001). Administration of 4-MP did not affect POC in control or 300 mg/kg APAP mice. In mice receiving 500 mg/kg APAP and 4-MP, POC decreased significantly compared to mice receiving 500 mg/kg APAP alone (p < 0.01). Serum and histological analysis confirmed APAP-induced hepatic damage in mice receiving 500 mg/kg APAP and these effects blunted by treatment with 4-MP. Conclusions: Platelet oxygen consumption as a measure of mitochondrial function may be useful as a biomarker of hepatic APAP toxicity in the setting of moderate to severe overdose. Treatment with 4-MP decreases hepatic necrosis and may mitigate the harmful effects of APAP on platelet mitochondrial function detected via POC.
MeSH term(s)	Animals ; Male ; Mice ; Acetaminophen ; Chemical and Drug Induced Liver Injury/etiology ; Disease Models, Animal ; Mitochondria
Chemical Substances	Acetaminophen (362O9ITL9D)
Language	English
Publishing date	2023-08-29
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2435016-3
ISSN	1937-6995 ; 1556-9039
ISSN (online)	1937-6995
ISSN	1556-9039
DOI	10.1007/s13181-023-00964-0
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A quantitative assessment of the effectiveness of USDA's AgrAbility project.

Fetsch, Robert J / Turk, Philip

Disability and health journal

2017 Volume 11, Issue 2, Page(s) 249–255

Abstract: Background: There is evidence that the combination of assistive technology and education increases ability to live and work independently, which in turn increases the quality of life (QOL) levels of adults with disabilities. No previously published ... ...

Abstract	Background: There is evidence that the combination of assistive technology and education increases ability to live and work independently, which in turn increases the quality of life (QOL) levels of adults with disabilities. No previously published treatment-comparison group intervention studies were found with adult farmers and ranchers with disabilities. Knowing how effective USDA's AgrAbility Project is at increasing this population's QOL and independent living and working (ILW) levels will reinforce and inform change in AgrAbility and will provide outcomes for stakeholders and public decision makers to better address agricultural communities' needs. Objectives: To assess whether or not AgrAbility is effective for enhancing QOL and ILW levels of agricultural producers with functional limitations and to assess intervention-comparison group differences. Methods: Intervention group participants (N = 225) included ranchers and farmers from 12 states with various disabilities who participated in AgrAbility. Comparison group participants (N = 100) from 17 states also included farmers and ranchers with various disabilities; they received no on-site visits or other AgrAbility services. Results: In this 10-year, 27-state study, AgrAbility participants reported statistically significant presurvey-postsurvey improvements in QOL levels (mean presurvey = 5.56; mean postsurvey = 7.13) while comparison group participants reported no change in QOL (mean presurvey = 5.10; mean postsurvey = 4.91). AgrAbility group mean ILW scores rose from 2.86 to 3.71 while comparison group mean ILW scores rose slightly from 3.24 to 3.50. Conclusions: These results suggest that AgrAbility was effective as compared with a no-treatment comparison group on improving QOL and ILW levels.
MeSH term(s)	Aged ; Agriculture ; Animal Husbandry ; Disabled Persons ; Farmers ; Female ; Humans ; Independent Living ; Male ; Middle Aged ; Patient Education as Topic ; Program Evaluation ; Quality of Life ; Self-Help Devices ; United States ; United States Department of Agriculture ; Work
Language	English
Publishing date	2017-10-16
Publishing country	United States
Document type	Evaluation Studies ; Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2414615-8
ISSN	1876-7583 ; 1936-6574
ISSN (online)	1876-7583
ISSN	1936-6574
DOI	10.1016/j.dhjo.2017.10.004
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Publisher Correction

Philip J. Turk / Thao P. Tran / Geoffrey A. Rose / Andrew McWilliams

Scientific Reports, Vol 11, Iss 1, Pp 1-

A predictive internet-based model for COVID-19 hospitalization census

2021 Volume 1

Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2021-08-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A predictive internet-based model for COVID-19 hospitalization census.

Turk, Philip J / Tran, Thao P / Rose, Geoffrey A / McWilliams, Andrew

Scientific reports

2021 Volume 11, Issue 1, Page(s) 5106

Abstract: The COVID-19 pandemic has strained hospital resources and necessitated the need for predictive models to forecast patient care demands in order to allow for adequate staffing and resource allocation. Recently, other studies have looked at associations ... ...

Abstract	The COVID-19 pandemic has strained hospital resources and necessitated the need for predictive models to forecast patient care demands in order to allow for adequate staffing and resource allocation. Recently, other studies have looked at associations between Google Trends data and the number of COVID-19 cases. Expanding on this approach, we propose a vector error correction model (VECM) for the number of COVID-19 patients in a healthcare system (Census) that incorporates Google search term activity and healthcare chatbot scores. The VECM provided a good fit to Census and very good forecasting performance as assessed by hypothesis tests and mean absolute percentage prediction error. Although our study and model have limitations, we have conducted a broad and insightful search for candidate Internet variables and employed rigorous statistical methods. We have demonstrated the VECM can potentially be a valuable component to a COVID-19 surveillance program in a healthcare system.
MeSH term(s)	COVID-19/epidemiology ; Forecasting/methods ; Hospitalization/statistics & numerical data ; Hospitalization/trends ; Humans ; Models, Statistical ; Pandemics ; Resource Allocation ; SARS-CoV-2/pathogenicity ; Search Engine/statistics & numerical data ; Search Engine/trends ; Time Factors
Language	English
Publishing date	2021-03-03
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-84091-2
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: First Monte Carlo beam model for ultra-high dose rate radiotherapy with a compact electron LINAC.

Dai, Tianyuan / Sloop, Austin M / Rahman, Mahbubur R / Sunnerberg, Jacob P / Clark, Megan A / Young, Ralph / Adamczyk, Sebastian / Von Voigts-Rhetz, Philip / Patane, Chris / Turk, Michael / Jarvis, Lesley / Pogue, Brian W / Gladstone, David J / Bruza, Petr / Zhang, Rongxiao

Medical physics

2024

Abstract: Background: FLASH radiotherapy based on ultra-high dose rate (UHDR) is actively being studied by the radiotherapy community. Dedicated UHDR electron devices are currently a mainstay for FLASH studies.: Purpose: To present the first Monte Carlo (MC) ... ...

Abstract	Background: FLASH radiotherapy based on ultra-high dose rate (UHDR) is actively being studied by the radiotherapy community. Dedicated UHDR electron devices are currently a mainstay for FLASH studies. Purpose: To present the first Monte Carlo (MC) electron beam model for the UHDR capable Mobetron (FLASH-IQ) as a dose calculation and treatment planning platform for preclinical research and FLASH-radiotherapy (RT) clinical trials. Methods: The initial beamline geometry of the Mobetron was provided by the manufacturer, with the first-principal implementation realized in the Geant4-based GAMOS MC toolkit. The geometry and electron source characteristics, such as energy spectrum and beamline parameters, were tuned to match the central-axis percentage depth dose (PDD) and lateral profiles for the pristine beam measured during machine commissioning. The thickness of the small foil in secondary scatter affected the beam model dominantly and was fine tuned to achieve the best agreement with commissioning data. Validation of the MC beam modeling was performed by comparing the calculated PDDs and profiles with EBT-XD radiochromic film measurements for various combinations of applicators and inserts. Results: The nominal 9 MeV electron FLASH beams were best represented by a Gaussian energy spectrum with mean energy of 9.9 MeV and variance (σ) of 0.2 MeV. Good agreement between the MC beam model and commissioning data were demonstrated with maximal discrepancy < 3% for PDDs and profiles. Hundred percent gamma pass rate was achieved for all PDDs and profiles with the criteria of 2 mm/3%. With the criteria of 2 mm/2%, maximum, minimum and mean gamma pass rates were (100.0%, 93.8%, 98.7%) for PDDs and (100.0%, 96.7%, 99.4%) for profiles, respectively. Conclusions: A validated MC beam model for the UHDR capable Mobetron is presented for the first time. The MC model can be utilized for direct dose calculation or to generate beam modeling input required for treatment planning systems for FLASH-RT planning. The beam model presented in this work should facilitate translational and clinical FLASH-RT for trials conducted on the Mobetron FLASH-IQ platform.
Language	English
Publishing date	2024-03-17
Publishing country	United States
Document type	Journal Article
ZDB-ID	188780-4
ISSN	2473-4209 ; 0094-2405
ISSN (online)	2473-4209
ISSN	0094-2405
DOI	10.1002/mp.17031
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Book: Child psychiatry

Graham, Philip J. / Turk, Jeremy / Verhulst, Frank C.

a developmental approach

1999

Author's details	Philip Graham ; Jeremy Turk and Frank C. Verhulst
Keywords	Entwicklungspsychologie ; Kinderpsychiatrie
Subject	Kind ; Genetische Psychologie ; Psychogenese
Language	English
Size	XI, 554 S.
Edition	3. ed.
Publisher	Oxford Univ. Press
Publishing place	Oxford
Publishing country	Great Britain
Document type	Book
New title	4. Aufl. u.d.T. Turk, Jeremy: Child and adolescent psychiatry
HBZ-ID	HT010722369
ISBN	0-19-262864-X ; 978-0-19-262864-0
Database	Catalogue ZB MED Medicine, Health

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1999 A 3931	order for loan	Magazin

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