IntroductionCalculating drug infusions in neonatal unit for sick infants can be challenging, unnerving and time consuming, especially in a neonatal emergency, and especially for junior medical and ...nursing staff. If done incorrectly, it can lead to untoward side effects or lack of desired effect.Our trust contains a level 3 and a level 1 unit. In our level 1 unit- investigation of two clinical incidents revealed undue delay in prescription and preparation of the above infusions in the crisis event. In our level 3 unit, there were drug errors due to heavy workload related to the number and complexity of patients.Aimsand Methods We designed a microsoft excel based neonatal drug infusion calculator (NDIC) for key infusions used in neonatal emergencies. Once patient’s weight was entered, NDIC calculated the amount and volume of drug to be drawn up and the volume and nature of diluent to provide the required infusion. The sheet containing calculated drug infusions (dopamine, dobutamine, adrenaline, noradrenaline, vecuronium, and prostin) could then be printed off and signed by the medical prescriber and administering nurse and the printed copy stapled to the actual drug chart as a supplementary chart. We then performed a user-survey and time analysis one year after its implementation to evaluate its impact.ResultsWe found that it took between 1.08–5.41 min to manually prescribe various infusions as compared to 37.8 s-2.22 min with NDIC to complete a prescription. The major delay in manual prescription was during checking the formulary. In the survey, prescribers found NDIC to be useful and time saving. They felt that it makes prescribing complex and scary drugs very easy. An inexperienced prescriber said, she wouldn’t know what to do without NDIC. Nurses found it very efficient and easy to use. The staff in level 1 unit found it most useful due to being inexperienced prescribers and it enabled them to accomplish other tasks quicker.ConclusionInfusion calculators are user friendly and time-efficient and may reduce drug errors until e-prescribing becomes universal.
AtheroEdge Composite Risk Score (AECRS1.010yr) is an integrated stroke/cardiovascular risk calculator that was recently developed and computes the 10-year risk of carotid image phenotypes by ...integrating conventional cardiovascular risk factors (CCVRFs). It is therefore important to understand how closely AECRS1.010yr is associated with the ten other currently available conventional cardiovascular risk calculators (CCVRCs).
The Institutional Review Board of Toho University approved the examination of the left/right common carotid arteries of 202 Japanese patients. Step 1 consists of measurement of AECRS1.010yr, given current image phenotypes and CCVRFs. Step 2 consists of computing the risk score using ten different CCVRCs given CCVR factors: QRISK3, Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study (UKPDS) 56, UKPDS60, Reynolds Risk Score (RRS), Pooled cohort Risk Score (PCRS or ASCVD), Systematic Coronary Risk Evaluation (SCORE), Prospective Cardiovascular Munster Study (PROCAM) calculator, NIPPON, and World Health Organization (WHO) risk. Step 3 consists of computing the closeness factor between AECRS1.010yr and ten CCVRCs using cumulative ranking index derived using eight different statistically derived metrics.
AECRS1.010yr reported the highest area-under-the-curve (0.927;P < 0.001) among all the risk calculators. The top three CCVRCs closest to AECRS1.010yr were QRISK3, FRS, and UKPDS60 with cumulative ranking scores of 2.1, 3.0, and 3.8, respectively.
AECRS1.010yr produced the largest AUC due to the integration of image-based phenotypes with CCVR factors, and ranked at first place with the highest AUC. Cumulative ranking of ten CCVRCs demonstrated that QRISK3 was the closest calculator to AECRS1.010yr, which is also consistent with the industry trend.
Abstract
Background
Although books and articles guiding the methods of sample size calculation for prevalence studies are available, we aim to guide, assist and report sample size calculation using ...the present calculators.
Results
We present and discuss four parameters (namely level of confidence, precision, variability of the data, and anticipated loss) required for sample size calculation for prevalence studies. Choosing correct parameters with proper understanding, and reporting issues are mainly discussed. We demonstrate the use of a purposely-designed calculators that assist users to make proper informed-decision and prepare appropriate report.
Conclusion
Two calculators can be used with free software (Spreadsheet and RStudio) that benefit researchers with limited resources. It will, hopefully, minimize the errors in parameter selection, calculation, and reporting. The calculators are available at: (
https://sites.google.com/view/sr-ln/ssc
).
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
MDCalc offers all healthcare professionals a quick and well-designed tool to look up for popular clinical calculators that are supported by evidence-based medicine. The app allows you to select your ...speciality and have related calculations at a press of a button. The app offers hundreds of clinical decision tools including risk scores, algorithms, equations, diagnostic criteria, formulas, classifications, dosing calculators, and more at your fingertips.
Carbon Footprint (CF) calculations have recently drawn considerable attention in order to limit greenhouse gas (GHG) emissions. Adapting to environmental consequences of climate change will require ...collaborative action, which involves every stakeholder, particularly libraries. CF calculators are digital tools for revealing and reducing CF. This paper introduces the concepts of “carbon footprint” and “carbon footprint calculator” by reviewing relevant library and information science literature.
UFO – The Universal FeynRules Output Degrande, Céline; Duhr, Claude; Fuks, Benjamin ...
Computer physics communications,
June 2012, 2012-6-00, Letnik:
183, Številka:
6
Journal Article
Recenzirano
Odprti dostop
We present a new model format for automatized matrix-element generators, the so-called Universal FeynRules Output (UFO). The format is universal in the sense that it features compatibility with more ...than one single generator and is designed to be flexible, modular and agnostic of any assumption such as the number of particles or the color and Lorentz structures appearing in the interaction vertices. Unlike other model formats where text files need to be parsed, the information on the model is encoded into a Python module that can easily be linked to other computer codes. We then describe an interface for the Mathematica package FeynRules that allows for an automatic output of models in the UFO format.
To evaluate the accuracy of multiple risk calculators for 30-day mortality on patients undergoing major lower extremity amputation.
The actual 30-day mortality at a single Veterans Affairs ...institution was compared to the predicted outcome from the following risk calculators: ACS-NSQIP, VASQIP, amputation scoring tool (AST), and POTTER elective.
The overall calculated 30-day mortality was similar to the actual mortality with the VASQIP and POTTER elective risk calculators, while the NSQIP and AST over-estimated the 30-day mortality. The predictive accuracy of the POTTER and NSQIP risk calculators were moderate (AUC >0.7), and fair for the VASQIP and AST.
Risk assessment tools can provide adjunctive data on predicted 30-day mortality in patients undergoing major lower extremity amputation. In our study, there were differences in predictability of the risk calculators for lower extremity amputation that should be considered when utilizing a risk assessment tool to improve physician-patient shared decision-making.
•Risk calculators provide adjunctive data on 30-day mortality for veterans undergoing major lower extremity amputation.•Optimal Classification Tree risk calculator was more accurate compared to NSQIP or VASQIP in our amputation population.•Risk assessment tools should be considered to improve physician-patient shared decision-making.
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