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Background: Inaccurate documentation of sampling and infusion times is a potential source of error in personalizing busulfan doses using therapeutic drug monitoring (TDM). Planned times rather than the actual times for sampling and infusion time are often documented. Therefore, this study aimed to evaluate the robustness of a limited sampling TDM of busulfan with regard to inaccurate documentation.
Methods: A pharmacometric analysis was conducted in NONMEM® 7.4.3 and "R" by performing stochastic simulation and estimation with four, two and one sample(s) per patient on the basis of a one-compartment- (1CMT) and two-compartment (2CMT) population pharmacokinetic model. The dosing regimens consisted of i.v. busulfan (0.8 mg/kg) every 6 h (Q6H) or 3.2 mg/kg every 24 h (Q24H) with a 2 h- and 3 h infusion time, respectively. The relative prediction error (rPE) and relative root-mean-square error (rRmse) were calculated in order to determine the accuracy and precision of the individual AUC estimation.
Results: A noticeable impact on the estimated AUC based on a 1CMT-model was only observed if uncertain documentation reached ± 30 min (1.60% for Q24H and 2.19% for Q6H). Calculated rPEs and rRmse for Q6H indicate a slightly lower level of accuracy and precision when compared to Q24H. Spread of rPE's and rRmse for the 2CMT-model were wider and higher compared to estimations based on a 1CMT-model.
Conclusions: The estimated AUC was not affected substantially by inaccurate documentation of sampling and infusion time. The calculated rPEs and rRmses of estimated AUC indicate robustness and reliability for TDM of busulfan, even in presence of erroneous records.
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http://dx.doi.org/10.1007/s11095-021-03115-8 | DOI Listing |
Am J Obstet Gynecol
August 2025
Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Eunice Kennedy Shriver National Institute of Child Health and Human Development, 6710B Rockledge Drive, MSC 7002, Rm 2419B, Bethesda, Maryland, 20817 USA. Electronic address: donna.mazloom
Objective: The aim of this manuscript is to describe the quality improvement auditing process developed by the Pelvic Floor Disorders Network of the Eunice Kennedy Shriver NICHD for assessing the primary outcome of pelvic organ prolapse quantification (POP-Q) measurements in their prolapse research trials and provide the reader with the most iterative POP-Q form.
Methods: We reviewed the Pelvic Floor Disorders Network steering committee minutes, data coordinating center audit reports, and the case report forms for studies related to prolapse and summarized findings.
Results: Errors found were related to data entry and documentation of pelvic organ prolapse quantification data with sign errors and inaccurate Ba/Bp point assessments being most common.
Stud Health Technol Inform
August 2025
Medical Data Integration Center, University Hospital Schleswig-Holstein, Germany.
Despite the existence of ICD-O for tumor classification, the broader ICD-10 system is often used in practice. While OncoTree is significant in research and molecular tumor boards, it provides a more detailed classification based on molecular and histological characteristics, crucial for clinical trial enrollment and data comparison. Therefore, a mapping between ICD-10 and OncoTree was developed.
View Article and Find Full Text PDFJ Med Internet Res
August 2025
Department of Health Services, Policy, and Management, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
Background: Electronic health record (EHR) data are widely used in public health research, including in HIV-related studies, but are limited by potential bias due to incomplete and inaccurate information, lack of generalizability, and lack of representativeness.
Objective: This study explores how workflow processes among HIV health care providers (HCPs), data scientists, and state health department professionals may potentially introduce or minimize bias within EHR data.
Methods: One focus group with 3 health department professionals working in HIV surveillance and 16 in-depth interviews (ie, 5 people with HIV, 5 HCPs, 5 data scientists, and 1 health department professional providing retention-in-care services) were conducted with participants purposively sampled in South Carolina from August 2023 to April 2024.
J Am Coll Emerg Physicians Open
October 2025
Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Objectives: Review of self-reported data in the electronic medical record (EMR) is the standard approach to the study of emergency airway management. Despite this, very little research has been done into the accuracy of the laryngoscopic views documented in the EMR during intubation in the emergency department. Complicating matters further, the original Cormack-Lehane (CL) airway grading system and the newer modified CL grading system have overlapping definitions.
View Article and Find Full Text PDFJ Am Med Inform Assoc
July 2025
Quantitative Biomedical Research Center, Department of Health Data Science and Biostatistics, Peter O'Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.
Objective: Social and behavioral determinants of health (SBDH) are increasingly recognized as essential for prognostication and informing targeted interventions. Clinical notes often contain details about SBDH in unstructured format. Conventional extraction methods for these data tend to be labor intensive, inaccurate, and/or unscalable.
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