Showing 20 of total 20 results (show query)
dewittpe
pedbp:Pediatric Blood Pressure
Data and utilities for estimating pediatric blood pressure percentiles by sex, age, and optionally height (stature) as described in Martin et.al. (2022) <doi:10.1001/jamanetworkopen.2022.36918>. Blood pressure percentiles for children under one year of age come from Gemelli et.al. (1990) <doi:10.1007/BF02171556>. Estimates of blood pressure percentiles for children at least one year of age are informed by data from the National Heart, Lung, and Blood Institute (NHLBI) and the Centers for Disease Control and Prevention (CDC) <doi:10.1542/peds.2009-2107C> or from Lo et.al. (2013) <doi:10.1542/peds.2012-1292>. The flowchart for selecting the informing data source comes from Martin et.al. (2022) <doi:10.1542/hpeds.2021-005998>.
Maintained by Peter DeWitt. Last updated 2 months ago.
blood-pressuregrowth-standardspediatriccpp
38.3 match 6 stars 6.43 score 45 scripts
annaseffernick
BEAMR:Bootstrap Evaluation of Association Matrices
A bootstrap-based approach to integrate multiple forms of high dimensional genomic data with multiple clinical endpoints. This method is used to find clinically meaningful groups of genomic features, such as genes or pathways. A manuscript describing this method is in preparation.
Maintained by Anna Eames Seffernick. Last updated 8 months ago.
37.4 match 5 stars 4.00 score 1 scripts
cu-dbmi-peds
phoenix:The Phoenix Pediatric Sepsis and Septic Shock Criteria
Implementation of the Phoenix and Phoenix-8 Sepsis Criteria as described in "Development and Validation of the Phoenix Criteria for Pediatric Sepsis and Septic Shock" by Sanchez-Pinto, Bennett, DeWitt, Russell et al. (2024) <doi:10.1001/jama.2024.0196> (Drs. Sanchez-Pinto and Bennett contributed equally to this manuscript; Dr. DeWitt and Mr. Russell contributed equally to the manuscript), "International Consensus Criteria for Pediatric Sepsis and Septic Shock" by Schlapbach, Watson, Sorce, Argent, et al. (2024) <doi:10.1001/jama.2024.0179> (Drs Schlapbach, Watson, Sorce, and Argent contributed equally) and the application note "phoenix: an R package and Python module for calculating the Phoenix pediatric sepsis score and criteria" by DeWitt, Russell, Rebull, Sanchez-Pinto, and Bennett (2024) <doi:10.1093/jamiaopen/ooae066>.
Maintained by Peter DeWitt. Last updated 13 days ago.
pediatricphoenixpythonsepsisseptic-shocksql
13.8 match 3 stars 5.78 score 20 scripts
ngiangre
kidsides:Download, Cache, and Connect to 'KidSIDES'
Caches and then connects to a 'sqlite' database containing half a million pediatric drug safety signals. The database is part of a family of resources catalogued at <https://nsides.io>. The database contains 17 tables where the description table provides a map between the fields the field's details. The database was created by Nicholas Giangreco during his PhD thesis which you can read in Giangreco (2022) <doi:10.7916/d8-5d9b-6738>. The observations are from the Food and Drug Administration's Adverse Event Reporting System. Generalized additive models estimated drug effects across child development stages for the occurrence of an adverse event when exposed to a drug compared to other drugs. Read more at the methods detailed in Giangreco (2022) <doi:10.1016/j.medj.2022.06.001>.
Maintained by Nicholas Giangreco. Last updated 2 years ago.
databasedruggeneralized-additive-modelsinformaticspediatricspharmacovigilancepkgdownsafety
17.1 match 5 stars 4.40 score 5 scripts
pharmaverse
pharmaversesdtm:SDTM Test Data for the 'Pharmaverse' Family of Packages
A set of Study Data Tabulation Model (SDTM) datasets from the Clinical Data Interchange Standards Consortium (CDISC) pilot project used for testing and developing Analysis Data Model (ADaM) datasets inside the pharmaverse family of packages. SDTM dataset specifications are described in the CDISC SDTM implementation guide, accessible by creating a free account on <https://www.cdisc.org/>.
Maintained by Edoardo Mancini. Last updated 2 days ago.
7.8 match 15 stars 7.40 score 143 scripts
boehringer-ingelheim
tipmap:Tipping Point Analysis for Bayesian Dynamic Borrowing
Tipping point analysis for clinical trials that employ Bayesian dynamic borrowing via robust meta-analytic predictive (MAP) priors. Further functions facilitate expert elicitation of a primary weight of the informative component of the robust MAP prior and computation of operating characteristics. Intended use is the planning, analysis and interpretation of extrapolation studies in pediatric drug development, but applicability is generally wider.
Maintained by Christian Stock. Last updated 12 months ago.
bayesian-borrowingbayesian-methodsclinical-trialevidence-synthesisextrapolationpediatricspharmaceutical-developmentprior-elicitationtipping-pointweighting
10.5 match 2 stars 4.38 score 12 scripts
cud2v
pccc:Pediatric Complex Chronic Conditions
An implementation of the pediatric complex chronic conditions (CCC) classification system using R and C++.
Maintained by Seth Russell. Last updated 5 months ago.
6.8 match 5 stars 5.93 score 38 scripts
abichat
scimo:Extra Recipes Steps for Dealing with Omics Data
Omics data (e.g. transcriptomics, proteomics, metagenomics...) offer a detailed and multi-dimensional perspective on the molecular components and interactions within complex biological (eco)systems. Analyzing these data requires adapted procedures, which are implemented as steps according to the 'recipes' package.
Maintained by Antoine BICHAT. Last updated 9 months ago.
7.5 match 4 stars 4.90 score 4 scripts
bioc
MethPed:A DNA methylation classifier tool for the identification of pediatric brain tumor subtypes
Classification of pediatric tumors into biologically defined subtypes is challenging and multifaceted approaches are needed. For this aim, we developed a diagnostic classifier based on DNA methylation profiles. We offer MethPed as an easy-to-use toolbox that allows researchers and clinical diagnosticians to test single samples as well as large cohorts for subclass prediction of pediatric brain tumors. The current version of MethPed can classify the following tumor diagnoses/subgroups: Diffuse Intrinsic Pontine Glioma (DIPG), Ependymoma, Embryonal tumors with multilayered rosettes (ETMR), Glioblastoma (GBM), Medulloblastoma (MB) - Group 3 (MB_Gr3), Group 4 (MB_Gr3), Group WNT (MB_WNT), Group SHH (MB_SHH) and Pilocytic Astrocytoma (PiloAstro).
Maintained by Helena Carén. Last updated 5 months ago.
immunooncologydnamethylationclassificationepigenetics
7.9 match 4.00 score 1 scripts
smouksassi
coveffectsplot:Produce Forest Plots to Visualize Covariate Effects
Produce forest plots to visualize covariate effects using either the command line or an interactive 'Shiny' application.
Maintained by Samer Mouksassi. Last updated 1 months ago.
4.0 match 32 stars 7.86 score 40 scripts
alwinw
epocakir:Clinical Coding of Patients with Kidney Disease
Clinical coding and diagnosis of patients with kidney using clinical practice guidelines. The guidelines used are the evidence-based KDIGO guidelines, see <https://kdigo.org/guidelines/> for more information. This package covers acute kidney injury (AKI), anemia, and chronic kidney disease (CKD).
Maintained by Alwin Wang. Last updated 1 years ago.
kdigokdigo-guidelineskidney-diseasemedical
5.7 match 5 stars 5.00 score 5 scriptsbioc
cypress:Cell-Type-Specific Power Assessment
CYPRESS is a cell-type-specific power tool. This package aims to perform power analysis for the cell-type-specific data. It calculates FDR, FDC, and power, under various study design parameters, including but not limited to sample size, and effect size. It takes the input of a SummarizeExperimental(SE) object with observed mixture data (feature by sample matrix), and the cell-type mixture proportions (sample by cell-type matrix). It can solve the cell-type mixture proportions from the reference free panel from TOAST and conduct tests to identify cell-type-specific differential expression (csDE) genes.
Maintained by Shilin Yu. Last updated 5 months ago.
softwaregeneexpressiondataimportrnaseqsequencing
6.6 match 1 stars 3.70 score 2 scripts
christianroever
bayesmeta:Bayesian Random-Effects Meta-Analysis and Meta-Regression
A collection of functions allowing to derive the posterior distribution of the model parameters in random-effects meta-analysis or meta-regression, and providing functionality to evaluate joint and marginal posterior probability distributions, predictive distributions, shrinkage effects, posterior predictive p-values, etc.; For more details, see also Roever C (2020) <doi:10.18637/jss.v093.i06>, or Roever C and Friede T (2022) <doi:10.1016/j.cmpb.2022.107303>.
Maintained by Christian Roever. Last updated 1 years ago.
3.6 match 3 stars 5.40 score 73 scripts 1 dependents
bemts-hhs
nemsqar:National Emergency Medical Service Quality Alliance Measure Calculations
Designed to automate the calculation of Emergency Medical Service (EMS) quality metrics, 'nemsqar' implements measures defined by the National EMS Quality Alliance (NEMSQA). By providing reliable, evidence-based quality assessments, the package supports EMS agencies, healthcare providers, and researchers in evaluating and improving patient outcomes. Users can find details on all approved NEMSQA measures at <https://www.nemsqa.org/measures>. Full technical specifications, including documentation and pseudocode used to develop 'nemsqar', are available on the NEMSQA website after creating a user profile at <https://www.nemsqa.org>.
Maintained by Nicolas Foss. Last updated 3 days ago.
4.0 match 5 stars 4.70 score
gunhanb
MetaStan:Bayesian Meta-Analysis via 'Stan'
Performs Bayesian meta-analysis, meta-regression and model-based meta-analysis using 'Stan'. Includes binomial-normal hierarchical models and option to use weakly informative priors for the heterogeneity parameter and the treatment effect parameter which are described in Guenhan, Roever, and Friede (2020) <doi:10.1002/jrsm.1370>.
Maintained by Burak Kuersad Guenhan. Last updated 2 years ago.
3.6 match 8 stars 5.08 score 7 scripts
jhchou
peditools:Pediatric Clinical Data Science Tools
A collection of tools for newborn and pediatric anthropometric calculations and data abstraction from Vermont Oxford Network registry exports. Includes charts based on Lambda, Mu, Sigma (LMS) parameters, including: Fenton 2003, Olsen 2010, Olsen BMI, CDC infant, CDC pediatric, CDC BMI, CDC (Addo) skin, WHO infant, WHO skin, Abdel-Rahman 2017, Mramba 2017, Zemel Down Syndrome, Brooks cerebral palsy, WHO expanded, Cappa 2024 (except BMI). Includes functions to take a Vermont Oxford Network XML or CSV data file export read into a data frame, converting the coded variables into human readable factors.
Maintained by Joseph Chou. Last updated 2 months ago.
3.8 match 5 stars 3.00 score 2 scripts
nlsy-links
NlsyLinks:Utilities and Kinship Information for Research with the NLSY
Utilities and kinship information for behavior genetics and developmental research using the National Longitudinal Survey of Youth (NLSY; <https://www.nlsinfo.org/>).
Maintained by S. Mason Garrison. Last updated 8 days ago.
behavior-geneticskinship-informationnational-longitudinal-surveynlsy
1.5 match 7 stars 7.49 score 185 scripts
certara-jcraig
Certara.RsNLME:Pharmacometric Modeling
Facilitate Pharmacokinetic (PK) and Pharmacodynamic (PD) modeling and simulation with powerful tools for Nonlinear Mixed-Effects (NLME) modeling. The package provides access to the same advanced Maximum Likelihood algorithms used by the NLME-Engine in the Phoenix platform. These tools support a range of analyses, from parametric methods to individual and pooled data analysis <https://www.certara.com/app/uploads/2020/06/BR_PhoenixNLME-v4.pdf>. Execution is supported both locally or on remote machines.
Maintained by James Craig. Last updated 4 months ago.
3.3 match 3.01 score 34 scripts 2 dependents
mvogel78
childsds:Data and Methods Around Reference Values in Pediatrics
Calculation of standard deviation scores and percentiles adduced from different standards (WHO, UK, Germany, Italy, China, etc). Also, references for laboratory values in children and adults are available, e.g., serum lipids, iron-related blood parameters, IGF, liver enzymes. See package documentation for full list.
Maintained by Mandy Vogel. Last updated 2 months ago.
2.9 match 2.83 score 51 scriptsdewittpe
pedalfast.data:PEDALFAST Data
Data files and documentation for PEDiatric vALidation oF vAriableS in TBI (PEDALFAST). The data was used in "Functional Status Scale in Children With Traumatic Brain Injury: A Prospective Cohort Study" by Bennett, Dixon, et al (2016) <doi:10.1097/PCC.0000000000000934>.
Maintained by Peter DeWitt. Last updated 6 months ago.
3.5 match 2.30 score 5 scripts