Age-specific Models Research Articles

Effects of temperature on the development, reproduction and population growth of Anaphothrips obscurus (Thysanoptera: Thripidae)

Anaphothrips obscurus is a cosmopolitan pest feeding on cereals and other grasses. The effects of constant temperatures on the biology of A. obscurus are not well known. Laboratory studies were conducted to assess the effects of temperature on the development, survival, longevity, fecundity and population parameter of A. obscurus at six constant temperatures (15, 20, 25, 30, 32, 35°C). The hatchability was the lowest at 15°C, the highest at 25°C and no eggs hatched at 35°C. Developmental rates increased linearly as the temperature increased. The lower developmental threshold temperature was 10.6°C and 200 degree-days were required to complete development from egg to adult. Adult longevity decreased with increasing temperature, and ranged from 68.87 d at 15°C to 16.41 d at 32°C. The highest total fecundity occurred at 20°C with 162 eggs per female. The temperature-dependent total fecundity, age-specific oviposition rate, and age-specific survival rate models were described. The intrinsic rate of increase (rm) was significantly higher at 30 and 32°C (0.239 and 0.250) than at other temperatures. This study suggests that optimal developmental and reproductive temperatures for A. obscurus ranges between 25 and 30°C and this may help this species adapt to warmer areas and widen its distribution and potential for damage in response to global warming. These findings will also be useful in developing monitoring programs, population dynamic models, and timing of control measures for A. obscurus.

Determinants of age-specific undernutrition in children aged less than 2years-the Bangladesh context.

Globally, undernutrition affects nearly half of all children aged less than 5years. It is more prominent in low- and middle-income countries. This study aimed to identify the age-specific risk factors for different categories of undernutrition among Bangladeshi children aged less than 2years. Data of 10,291 children aged less than 2years were collected between October 2011 to November 2013 through the Food Security Nutritional Surveillance Project in Bangladesh. Simple logistic regression established bivariate relationships between the categories of undernutrition and the relevant risk factors. Multiple logistic regression constructed the age-specific regression models depicting the independent association and effect size of the risk factors contributing to the various categories of undernutrition among study population. Stunting was prevalent among 30.9% of the study children, whereas 9.7% were wasted and 24.9% were underweight. Being a male child, increase in age, maternal body mass index and education, and household food insecurity were the strongest predictors for all categories of undernutrition in terms of effect size. Our study shows that the different categories of childhood undernutrition have different age-specific risk factors. Maternal body mass index and household food insecurity were the common age-specific risk factors for all categories of undernutrition. We expect our findings to enhance the existing evidence base for the risk factors of undernutrition among children aged less than 2 years.

Seedling survival responses to conspecific density, soil nutrients, and irradiance vary with age in a tropical forest.

Understanding processes that promote species coexistence is integral to diversity maintenance. In hyperdiverse tropical forests, local conspecific density (LCD) and light are influential to woody seedling recruitment and soil nutrients are often limiting, yet the simultaneous effects of these factors on seedling survival across time remain unknown. We fit species- and age-specific models to census and resource data of seedlings of 68 woody species from a Costa Rican wet tropical forest. In decreasing order of prevalence, seedling survivorship was related to LCD, soil base cations, irradiance, nitrogen, and phosphorus. Species-specific responses to factors did not covary, providing evidence that species life history strategies have not converged to one continuum of high-surviving stress tolerant to low-surviving stress intolerant species. Survival responses to all factors varied over the average seedling's lifetime, indicating seedling requirements change with age and conclusions drawn about processes important to species coexistence depend on temporal resolution.

Creation of a paediatric head voxel model database for dosimetric applications

Introduction CBCT is a recently introduced imaging modality in dentomaxillofacial radiology with increasing applications to paediatric cohorts. To accurately estimate the radiation induced risk via Monte Carlo (MC) simulations, age and gender specific head and neck voxel models should be built. These models will enable organ dose calculations and accurate risk estimation via effective dose (ED) or Life Attributable risk (LAR). Purpose To design a head and neck voxel model database for MC dosimetry. Methods and materials Our voxel models were based on organ segmentation of CT image datasets with following characteristics: represent a complete head; have a good low contrast resolution (as the many soft tissues are close in density), have the thyroid included in the scan. Using our PACS database, 13 datasets of paediatric patients from 5 to 14 years old were found to meet the requirements for further processing. From each CT scan, 22 organs were manually segmented on an organ by organ using ImageJ, Matlab tools and human atlases (example: http://headneckbrainspine.com/Neck-CT.php ). Organ masses were compared to ICRP reference values. Results 13 paediatric voxel phantoms were created and compared favourably with ICRP values: 7 males and 6 females. The in-plane resolution of the phantoms, determined by the axial voxel size dimensions, ranges from 0.21 × 0.21 mm 2 to 0.48 × 0.48 mm 2 ; the z resolution ranges from 0.6 mm to 3.22 mm. Conclusion The database for paediatric CBCT applications can now be used for detailed dose and risk applications.

Effect of Temperature on the Fecundity and Longevity of Ascotis selenaria (Lepidoptera: Geometridae): Developing an Oviposition Model.

The fecundity and longevity of Ascotis selenaria (Denis & Schiffermüller 1775) female adults were examined at constant temperatures ranging from 13-35°C. Adult longevity decreased as the temperature increased and ranged from 26.2 d at 13.1°C to 5.2 d at 34.3°C. The maximum observed fecundity of A. selenaria was 2,420 eggs per female at 19.4°C, which decreased to ca 100 eggs per female at 34.3°C. Female adult aging rates (one per median longevity) were well described by a sigmoid equation in the range of 13-35°C used to calculate the physiological age of adults. The relationship between total fecundity and temperature was well described by an extreme value function. Age-specific cumulative oviposition rate and age-specific survival rate curve were fitted to a three-parameter Weibull function. An oviposition model for A. selenaria was developed using the estimated three temperature-dependent submodels: total fecundity, age-specific cumulative oviposition, and age-specific survival rate models. The oviposition model was simulated using pheromone catches of A. selenaria females as input value. Simulated egg populations were subjected to egg stage emergence model to project first-instar populations. Overall, the output of our simulation described the field occurrence pattern of A. selenaria first-instar populations in 2009 and 2010.

Development and Validation of an Older Occupant Finite Element Model of a Mid-Sized Male for Investigation of Age-related Injury Risk.

The aging population is a growing concern as the increased fragility and frailty of the elderly results in an elevated incidence of injury as well as an increased risk of mortality and morbidity. To assess elderly injury risk, age-specific computational models can be developed to directly calculate biomechanical metrics for injury. The first objective was to develop an older occupant Global Human Body Models Consortium (GHBMC) average male model (M50) representative of a 65 year old (YO) and to perform regional validation tests to investigate predicted fractures and injury severity with age. Development of the GHBMC M50 65 YO model involved implementing geometric, cortical thickness, and material property changes with age. Regional validation tests included a chest impact, a lateral impact, a shoulder impact, a thoracoabdominal impact, an abdominal bar impact, a pelvic impact, and a lateral sled test. The second objective was to investigate age-related injury risks by performing a frontal US NCAP simulation test with the GHBMC M50 65 YO and the GHBMC M50 v4.2 models. Simulation results were compared to the GHBMC M50 v4.2 to evaluate the effect of age on occupant response and risk for head injury, neck injury, thoracic injury, and lower extremity injury. Overall, the GHBMC M50 65 YO model predicted higher probabilities of AIS 3+ injury for the head and thorax.

A longitudinal population-based analysis of relationship status and mortality in KwaZulu-Natal, South Africa 2001–2011

BackgroundMortality risk is lower in married than in unmarried men and women. However, little is known about the association between mortality and relationship status in South Africa where marriage rates...

Estimated hospitalizations attributed to norovirus and rotavirus infection in Canada, 2006–2010

Enteric viruses including norovirus and rotavirus are leading causes of gastroenteritis in Canada. However, only a small number of clinical cases are actually tested for these pathogens leading to systematic underestimation of attributed hospitalizations in administrative databases. The objective of this analysis was to estimate the number of hospitalizations due to norovirus and rotavirus in Canada. Hospitalization records for acute gastroenteritis-associated discharges at all acute-care hospitals in Canada between 2006 and 2011 were analysed. Cause-unspecified gastroenteritis hospitalizations were modelled using age-specific negative binomial models with cause-specified gastroenteritis admissions as predictors. The coefficients from the models were used to estimate the number of norovirus and rotavirus admissions. The total annual hospitalizations for rotavirus were estimated to be between 4500 and 10 000. Total annual hospitalizations for norovirus were estimated to be between 4000 and 11 000. The mean total annual cost associated with these hospitalizations was estimated to be at least $16 million for rotavirus and $21 million for norovirus (all figures in Canadian dollars). This study is the first comprehensive analysis of norovirus and rotavirus hospitalizations in Canada. These estimates provide a more complete assessment of the burden and economic costs of these pathogens to the Canadian healthcare system.

Age-related differences in factors associated with cervical spine injuries in children.

The Pediatric Emergency Care Applied Research Network (PECARN) investigators previously identified risk factors associated with cervical spine injuries (CSIs) in children. Anatomic maturation and age-related variation in mechanisms of injury suggested the need to explore factors separately for younger versus older children. The purpose of this substudy was to investigate CSI risk factors in age subgroups within the PECARN study cohort. This was an age-stratified case-control analysis of children younger than 16 years presenting to 17 PECARN hospitals following blunt trauma between January 1, 2000 and December 31, 2004. Data were abstracted for children with CSIs and randomly selected CSI-free children. Age-stratified multivariable logistic regression was performed to identify factors associated with CSI within three age groups: younger than 2, 2 to 7, and 8 to 15 years. Sensitivity and specificity for CSI were estimated for both the age-specific and original (altered mental status, focal neurologic findings, neck pain, torticollis, substantial torso injury, predisposing conditions, diving, and high-risk motor vehicle crash [MVC]) models. Among 540 children with CSIs, 27 were younger than 2 years, 140 were 2 to 7 years, and 373 were 8 to 15 years. Focal neurologic deficits and high-risk MVC were associated with CSIs in all age-specific models. Other age-specific factors included the following: younger than 2 years, none; 2 to 7 years, altered mental status, neck pain, torticollis; and 8 to 15 years, altered mental status, neck pain, diving. Age-specific models had comparable sensitivity to the original model among the older groups, but had lower sensitivity and higher specificity among the youngest children. While this analysis supports the original PECARN model for CSI, there were subtle age variations in factors associated with CSIs in children that warrant future investigation.

The Differential Effects of Beverage Type on Stroke Mortality

Background: Stroke is one of the major causes of death in the developed world and a top ten contributor to the global burden of disease. Russia has one of the world’s highest stroke incidence and mortality rates. Several studies have emphasized the role of binge drinking as important determinant of high stroke mortality rate in Russia. Objective: The aim of this study was to examine the relation between the consumption of different beverage types and stroke mortality rates in Russia. Method: Age-standardized male and female stroke mortality data for the period 1980-2005 and data on beverage-specific alcohol sales were obtained from Russian State Statistical Committee. Time-series analytical modelling techniques (ARIMA) were used to examine the relation between the sale of different alcoholic beverages (vodka, wine, beer) and stroke mortality rates. Result: Vodka consumption as measured by sale was significantly associated with both male and female stroke mortality rate. The consumption of beer and wine were not associated with stroke mortality rate. The estimates of the age specific models for men were positive (except for the 75+ age group) and ranging from 0.038 (60-74 age group) to 0.98 (30-44 age group). The estimates for women were positive for the 30-44 age groups (0.074) and 45-59 age groups (0.053). Conclusion: The findings from this study suggest that public health efforts should focus on both reducing overall consumption and changing beverage preference away from distilled spirits in order to reduce cerebrovascular mortality rates in Russia.

Cortical Source Analysis of High-Density EEG Recordings in Children

EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3. In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.

Cortical source analysis of high-density EEG recordings in children.

EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited, because the composition and spatial configuration of head tissues changes dramatically over development. In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.

Predicting mortality from burns: The need for age-group specific models

Traditional burn mortality models are derived using all age groups. We hypothesized that age variably impacts mortality after burn and that age-specific models for children, adults, and seniors will more accurately predict mortality than an all-ages model. We audited data from the American Burn Association (ABA) National Burn Repository (NBR) from 2000 to 2009 and used mixed effect logistic regression models to assess the influence of age, total body surface area (TBSA) burn, and inhalation injury on mortality. Mortality models were constructed for all ages and age-specific models: children (<18 years), adults (18–60 years), and seniors (>60 years). Model performance was assessed by area under the receiver operating curve (AUC). Main effect and two-way interactions were used to construct age-group specific mortality models. Each age-specific model was compared to the All Ages model. Of 286,293 records 100,051 had complete data. Overall mortality was 4% but varied by age (17% seniors, <1% children). Age, TBSA, and inhalation injury were significant mortality predictors for all models (p<0.05). Differences in predicted mortality between the All Ages model and the age-specific models occurred in children and seniors. In the age-specific pediatric model, predicted mortality decreased with age; inhalation injury had greater effect on mortality than in the All Ages model. In the senior model mortality increased with age. Seniors had greater increase in mortality per 1% increment in burn size and 1 year increase in age than other ages. The predicted mortality in seniors using the senior-specific model was higher than in the All Ages model. “One size fits all” models for predicting burn outcomes do not accurately reflect the outcomes for seniors and children. Age-specific models for children and seniors may be advisable.

Abstract P054: The CUORE Project: The Predictive Role Of Cardiovascular Risk Factors Among Elderly Persons

Background: The number of elderly persons with cardiovascular disease (CVD) is rapidly increasing, mainly due to worldwide aging population. All CVD risk scores consider age as risk factor but most of them assume that the etiological role of other established risk factors is similar at all ages. This analyses aimed to assess the predictive role of cardiovascular risk factors in elderly persons. Methods: We considered 10,979 men and 16,533 women aged 35-74 years from cohorts in North, Centre and South of Italy with 10 years median follow-up time for fatal and non fatal coronary and cerebrovascular events (819 in men and 467 in women) validated according to MONICA criteria. In all cohorts risk factors were assessed by using standardized procedures. Two age groups were defined: adult 35-54 years of age (6,353 men and 10,358 women) and elderly 55-74 years (4,626 men and 6,175 men). Cox models were implemented including age, systolic blood pressure (SBP), total (TC) and HDL cholesterol (HDL-C), smoking, diabetes (DM - fasting blood glucose &gt;=126 mg/dl or under glucose treatment) and hypertension treatment (HT). For continuous variables, hazard ratios (HR) were reported at 1 standard deviation higher level and for dichotomized variables, yes vs no. Results: For adult men SBP resulted having a stronger impact on CVD risk than for elderly even if not statistically significant: adult HR 1.32, 95% confidence interval 1.18-1.48, vs elderly HR 1.25, 1.15-1.36; similar results for TC (HR 1.47 vs 1.25), smoking (HR 1.91, vs 1.52), DM (HR 1.76 vs 1.56), HT (HR 2.30 vs 1.25). HDL-C resulted not significantly associated with CVD risk in elderly men. Among adult women a stronger impact was found than in elderly for SBP (HR 1.59 vs 1.26), HDL-C (0.65 vs 0.84), smoking (2.43 vs 1.99), and HT (2.34 vs 1.45); the opposite for TC (1.19 vs 1.27). DM resulted not significantly associated with CVD risk in adult women. Age resulted having a stronger impact in elderly persons both in men and women (HR 1.22, 1.07-1.39, vs 1.44, 1.29-1.61; 1.45, 1.17-1.80, vs 1.63, 1.42-1.86 respectively). Conclusions: SBP and HT resulted having a pronounced lower impact on CVD risk in elderly than in adult as well as HDL-C for men; age shows a stronger impact in elderly than in adult. Further analyses are recommended to study the reliability of risk scores based on age-specific risk models, evaluating the introduction of different risk factors and considering survival probability derived from data in elderly population.

Development of forecasting models for fatal road traffic injuries

To develop the forecasting models for fatal road traffic injuries and to provide evidence for predicting the future trends on road traffic injuries. Data on the mortality of road traffic injury including factors as gender and age in different countries, were obtained from the World Health Organization Mortality Database. Other information on GDP per capita, urbanization, motorization and education were collected from online resources of World Bank, WHO, the United Nations Population Division and other agencies. We fitted logarithmic models of road traffic injury mortality by gender and age group, including predictors of GDP per capita, urbanization, motorization and education. Sex- and age-specific forecasting models developed by WHO that including GDP per capita, education and time etc. were also fitted. Coefficient of determination(R(2)) was used to compare the performance between our modes and WHO models. 2 626 sets of data were collected from 153 countries/regions for both genders, between 1965 and 2010. The forecasting models of road traffic injury mortality based on GDP per capita, motorization, urbanization and education appeared to be statistically significant(P < 0.001), and the coefficients of determination for males at the age groups of 0-4, 5-14, 15-24, 25-34, 35-44, 45-54, 55-64, 65+ were 22.7% , 31.1%, 51.8%, 52.3%, 44.9%, 41.8%, 40.1%, 25.5%, respectively while the coefficients for these age groups in women were 22.9%, 32.6%, 51.1%, 49.3%, 41.3%, 35.9%, 30.7%, 20.1%, respectively. The WHO models that were based on the GDP per capita, education and time variables were statistically significant (P < 0.001)and the coefficients of determination were 14.9% , 22.0%, 31.5%, 33.1% , 30.7%, 28.5%, 27.7% and 17.8% for males, but 14.1%, 20.6%, 30.4%, 31.8%, 26.7%, 24.3%, 17.3% and 8.8% for females, respectively. The forecasting models that we developed seemed to be better than those developed by WHO.

Predictive performance of comorbidity measures in administrative databases for diabetes cohorts

BackgroundThe performance of comorbidity measures for predicting mortality in chronic disease populations and using ICD-9 diagnosis codes in administrative health data has been investigated in several studies, but less is known about predictive performance with ICD-10 data and for other health outcomes. This study investigated predictive performance of five comorbidity measures for population-based diabetes cohorts in administrative data. The objectives were to evaluate performance for: (a) disease-specific and general health outcomes, (b) data based on the ICD-9 and ICD-10 diagnoses, and (c) different age groups.MethodsPerformance was investigated for heart attack, stroke, amputation, renal disease, hospitalization, and death in all-age and age-specific cohorts. Hospital records, physician billing claims, and prescription drug records from one Canadian province were used to identify diabetes cohorts and measure comorbidity. The data were analysed using multiple logistic regression models and summarized using measures of discrimination, accuracy, and fit.ResultsIn Cohort 1 (n = 29,058), for which only ICD-9 diagnoses were recorded in administrative data, the Elixhauser index showed good or excellent prediction for amputation, renal disease, and death and performed better than the Charlson index. Number of diagnoses was a good predictor of hospitalization. Similar results were obtained for Cohort 2 (n = 41,925), in which both ICD-9 and ICD-10 diagnoses were recorded in administrative data, although predictive performance was sometimes higher. For age-specific models of mortality, the Elixhauser index resulted in the largest improvement in predictive performance in all but the youngest age group.ConclusionsCohort age and the health outcome under investigation, but not the diagnosis coding system, may influence the predictive performance of comorbidity measure for studies about diabetes populations using administrative health data.

An economic evaluation for prevention of diabetes mellitus in a developing country: a modelling study.

BackgroundThe serious consequences of diabetes mellitus, and the subsequent economic burden, call for urgent preventative action in developing countries. This study explores the clinical and economic outcomes of strategies that could potentially prevent diabetes based on Chinese circumstances. It aims to provide indicators for the long-term allocation of healthcare resources for authorities in developing countries.MethodsA representative sample of Chinese adults was used to create a simulated population of 20,000 people aged 25 years and above. The hybrid decision tree Markov model was developed to compare the long-term clinical and economic outcomes of four simulated diabetes prevention strategies with a control group, where no prevention applied. These preventive strategies were the following: (i) one-off screening for undiagnosed diabetes and impaired glucose tolerance (IGT), with lifestyle interventions on diet, (ii) on exercise, (iii) on diet combined exercise (duo-intervention) respectively in those with IGT, and (iv) one-off screening alone. Independent age-specific models were simulated based on diverse incidences of diabetes, mortalities and health utilities. The reported outcomes were the following: the remaining survival years, the quality-adjusted life years (QALYs) per diabetes or IGT subjects, societal costs per simulated subject and the comparisons between preventions and control over 40 years. Sensitivity analyses were performed based on variations of all assumptions, in addition to the performance and the compliance of screening.ResultsCompared with the control group, all simulated screening programmes prolonged life expectancy at the initiation ages of 25 and 40 years, postponed the onset of diabetes and increased QALYs at every initiation age. Along with an assumption of six years intervention, prevention programmes were associated with cost-saving compared with the control group, especially in the population aged 25 years. The savings were at least US$2017 per subject, but no statistically significant difference was observed among the intervention strategies within each age groups. The cost savings were reduced when screening was affected by poor performance and noncompliance.ConclusionsDeveloping countries have few effective strategies to manage the prevention of diabetes. One-off screening for undiagnosed diabetes and IGT, with appropriate lifestyle interventions for those with IGT are cost saving in China, especially in young adults.

Basis and Implications of the CAP88 Age-Specific Dose Coefficients

Recent versions of CAP88 incorporate age-specific dose coefficients based on biokinetic and dosimetric models applied in Federal Guidance Report 13, "Cancer Risk Coefficients for Environmental Exposure to Radionuclides." With a few exceptions the models are those recommended in a series of reports by the International Commission on Radiological Protection (ICRP) on estimation of doses to the public from environmental radionuclides. This paper describes the basis for the ICRP's age-specific biokinetic and dosimetric models and examines differences with age in dose coefficients derived from those models.

High tidal volume ventilation does not exacerbate acid-induced lung injury in infant rats

The impact of mechanical ventilation with high VT-low PEEP in infant rats with preinjured lungs is unknown. After tracheal instillation of saline or acid, two week old rats were ventilated with VT 7mL/kg and PEEP 5cm H2O or VT 21mL/kg and PEEP 1cm H2O for 4h. Airway resistance and the coefficient of tissue elastance, measured via low-frequency forced-oscillation technique, and quasi-static pressure-volume curves deteriorated less with high VT-low PEEP when compared with low VT-high PEEP. IL-6 concentration in bronchoalveolar lavage fluid (BALF) did not differ between all ventilated groups. Moreover, differences in BALF protein concentration and histological lung injury scores were independent of applied ventilation strategies. In contrast to experimental studies with adult rats, short-term mechanical ventilation with high VT-low PEEP is not deleterious when compared to low VT-high PEEP in both healthy and pre-injured infant rat lungs. Our results call for caution when extrapolating data from adult studies and highlight the need for age-specific animal models.

Using Enriched Observational Data to Develop and Validate Age-specific Mortality Risk Adjustment Models for Hospitalized Pediatric Patients

Growth and development in early childhood are associated with rapid physiological changes. We sought to develop and validate age-specific mortality risk adjustment models for hospitalized pediatric patients using objective physiological variables on admission in addition to administrative variables. Age-specific laboratory and vital sign variables were crafted for neonates (up to 30 d old), infants/toddlers (1-23 mo), and children (2-17 y). We fit 3 logistic regression models, 1 for each age group, using a derivation cohort comprising admissions from 2000-2001 in 215 hospitals. We validated the models with a separate validation cohort comprising admissions from 2002-2007 in 62 hospitals. We used the c statistic to assess model fit. The derivation cohort comprised 93,011 neonates (0.55% mortality), 46,152 infants/toddlers (0.37% mortality), and 104,010 children (0.40% mortality). The corresponding numbers of admissions (mortality rates) for the validation cohort were 162,131 (0.50%), 33,818 (0.09%), and 73,362 (0.20%), respectively. The c statistics for the 3 models were 0.94, 0.91, and 0.92, respectively, for the derivation cohort and 0.91, 0.86, and 0.93, respectively, for the validation cohort. The relative contributions of physiological versus administrative variables to the model fit were 52% versus 48% (neonates), 93% versus 7% (infants/toddlers), and 82% versus 18% (children). The thresholds for physiological determinants varied by age. Common physiological variables assessed on admission contributed significantly to predicting mortality for hospitalized pediatric patients. These models may have practical utility in risk adjustment for pediatric outcomes and comparative effectiveness research when physiological data are captured through the electronic medical record.