dose error
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2021 ◽  
Vol 71 (11) ◽  
pp. 2629-2636
Author(s):  
Muhammad Arfat Yameen ◽  
Mubashra Tafseer ◽  
Warda Khan ◽  
Sanaa Anjum ◽  
Raza-E-Mustafa ◽  
...  

Objective: The aim of the study was the evaluation of drug-related problems, including drug-drug interactions, dose error, use of nephrotoxic drugs and polypharmacy with special emphasis on kidney disease patients. Methods: Descriptive cross-sectional study from January to April 2019 was carried out in nephrology ward of Ayub teaching hospital, Abbottabad, Pakistan to review patient’s medication orders for evaluation of drug-related problems. Doses of medicine and drug-drug interactions were evaluated by comparing it with standard protocols given in BNF and Lexicomp software. Prescriptions were also evaluated for polypharmacy and use of nephrotoxic drugs. Results: Out of 131 patients, majority were males 72 (55%). Drug-drug interactions were found in 69 (52.7%) patients among which the highest percentage was of the moderate drug-drug interaction (48.1%) followed by major and minor drug-drug interaction (29.8% and 20.6% respectively). Incidence of polypharmacy (51.9%) and use of nephrotoxic drug (77%) was high while dose error was low up to 10.7%. All the drug-related problems were present with a high percentage in patients with CKD as compare to other kidney diseases. There was significant association of CKD stages with DDIs, polypharmacy, dose error and prescribing drugs. There was significant positive correlation among DDIs-polypharmacy and prescribing drugs was noted in the study. Conclusion: The higher incidence of drug-related problems in our study setting reflects irrational prescribing trends and deficiency of professional staff dealing kidney disease patients. Key Words: kidney disease, drug-drug interactions, polypharmacy, nephrotoxic drugs, dose error. Continuous...


2020 ◽  
Vol 144 (10) ◽  
pp. 1204-1208
Author(s):  
Mark Inman ◽  
Andrew W. Lyon ◽  
Oliver A. S. Lyon ◽  
Martha E. Lyon

Context.— Glycemic control requires accurate blood glucose testing. The extent of hematocrit interference is difficult to assess to assure quality patient care. Objective.— To predict the effect of patient hematocrit on the performance of a glucose meter and its corresponding impact on insulin-dosing error. Design.— Multilevel mixed regression was conducted to assess the extent that patient hematocrit influences Roche Accu-Chek Inform II glucose meters, using the Radiometer ABL 837 as a reference method collected during validation of 35 new meters. Regression coefficients of fixed effects for reference glucose, hematocrit, an interaction term, and random error were applied to 4 months of patient reference method results extracted from the laboratory information system. A hospital inpatient insulin dose algorithm was used to determine the frequency of insulin dose error between reference glucose and meter glucose results. Results.— Fixed effects regression for method and hematocrit predicted biases to glucose meter results that met the “95% within ±12%” for the US Food and Drug Administration goal, but combinations of fixed and random effects exceeded that target in emergency and hospital inpatient units. Insulin dose errors were predicted from the meter results. Twenty-eight percent of intensive care unit, 20.8% of hospital inpatient, and 17.7% of emergency department results were predicted to trigger a ±1 insulin dose error by fixed and random effects. Conclusions.— The current extent of hematocrit interference on glucose meter performance is anticipated to cause insulin error by 1-dose category, which is likely associated with low patient risk.


2020 ◽  
Vol 6 (3) ◽  
pp. 27
Author(s):  
Yang Bo ◽  
Zhang Jing ◽  
Li Lei ◽  
Liu Xiaolong ◽  
Pang Haowen

2019 ◽  
Vol 10 (12) ◽  
pp. 793-799
Author(s):  
Scott Pardo

Aim: Inaccurate blood glucose monitoring system (BGMS) results may lead to insulin dosing errors and adverse clinical outcomes. Results & methodology: This post-hoc analysis used a model to estimate the bolus insulin dose error associated with each of the five BGMSs, for a hypothetical person with diabetes (assuming a standardized meal and target blood glucose of 100 mg/dl). Differences in dose-error distribution between BGMSs were statistically tested. The 95% dose-error range for each BGMS was (insulin units): CONTOUR®PLUS, -1.1–0.7; Accu-Chek® Active, -2.4–0.7; Accu-Chek® Performa, -2.9–0.8; FreeStyle Freedom, from -5.5 to -0.5; OneTouch® SelectSimple™, -4.1−3.0. Conclusion: The CONTOUR®PLUS BGMS was associated with a statistically significantly smaller model-estimated median bolus insulin dose-error and dosing error range, compared with the other BGMSs.


2019 ◽  
Vol 70 ◽  
pp. 30-33 ◽  
Author(s):  
Martha E. Lyon ◽  
Oliver A.S. Lyon ◽  
Nam K. Tran ◽  
Jeffrey A. DuBois ◽  
Andrew W. Lyon

2017 ◽  
Vol 73 (5) ◽  
pp. 382-388
Author(s):  
Hideki Kojima ◽  
Makoto Takigami ◽  
Tomohiro Asano ◽  
Yasuhiro Hatanaka ◽  
Kazuhiro Aizawa ◽  
...  

2016 ◽  
Vol 57 (3) ◽  
pp. 258-264 ◽  
Author(s):  
Keita Kurosu ◽  
Iori Sumida ◽  
Hirokazu Mizuno ◽  
Yuki Otani ◽  
Michio Oda ◽  
...  

Abstract A patient-specific quality assurance (QA) test is conducted to verify the accuracy of dose delivery. It generally consists of three verification processes: the absolute point dose difference, the planar dose differences at each gantry angle, and the planar dose differences by 3D composite irradiation. However, this imposes a substantial workload on medical physicists. The objective of this study was to determine whether our novel method that predicts the 3D delivered dose allows certain patient-specific IMRT QAs to be curtailed. The object was IMRT QA for the pelvic region with regard to point dose and composite planar dose differences. We compared measured doses, doses calculated in the treatment planning system, and doses predicted by in-house software. The 3D predicted dose was reconstructed from the per-field measurement by incorporating the relative dose error distribution into the original dose grid of each beam. All point dose differences between the measured and the calculated dose were within ±3%, whereas 93.3% of them between the predicted and the calculated dose were within ±3%. As for planar dose differences, the gamma passing rates between the calculated and the predicted dose were higher than those between the calculated and the measured dose. Comparison and statistical analysis revealed a correlation between the predicted and the measured dose with regard to both point dose and planar dose differences. We concluded that the prediction-based approach is an accurate substitute for the conventional measurement-based approach in IMRT QA for the pelvic region. Our novel approach will help medical physicists save time on IMRT QA.


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