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Journal articles on the topic 'Weight-based'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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1

s, Tharani, G. Arutchelvan, and G. Arulanandam. "Weight Based Backbone Clustering Implemented for Multicast MANET." International Journal of Trend in Scientific Research and Development Volume-1, Issue-4 (June 30, 2017): 698–704. http://dx.doi.org/10.31142/ijtsrd2216.

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2

Umscheid, Craig A., Rajender Agarwal, and Gene Gibson. "Weight-Based Low-Molecular-Weight Heparin versus Weight-Based Intravenous Unfractionated Heparin." Annals of Internal Medicine 147, no. 6 (September 18, 2007): 433. http://dx.doi.org/10.7326/0003-4819-147-6-200709180-00020.

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3

Segal, Jodi B., Michael B. Streiff, and Eric B. Bass. "Weight-Based Low-Molecular-Weight Heparin versus Weight-Based Intravenous Unfractionated Heparin." Annals of Internal Medicine 147, no. 6 (September 18, 2007): 434. http://dx.doi.org/10.7326/0003-4819-147-6-200709180-00021.

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4

Craddock, Nadia. "Weight bias, weight-based discrimination and weighty consequences." Journal of Aesthetic Nursing 6, no. 10 (December 2, 2017): 548–51. http://dx.doi.org/10.12968/joan.2017.6.10.548.

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5

Susla, Gregory M. "Weight-based heparin dosing." Critical Care Medicine 25, no. 9 (September 1997): 1451–52. http://dx.doi.org/10.1097/00003246-199709000-00005.

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6

Lashkaripour, Ahmad. "Weight-based quality specialization." Journal of International Economics 127 (November 2020): 103380. http://dx.doi.org/10.1016/j.jinteco.2020.103380.

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7

Shuster, Shirley, Caitlyn Vlasschaert, and Sara Awad. "Weight Loss-Based Nutraceuticals." Canadian Journal of General Internal Medicine 16, no. 2 (June 21, 2021): 49–54. http://dx.doi.org/10.22374/cjgim.v16i2.470.

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Thyrotoxic periodic paralysis (TPP) is characterized by muscle weakness, areflexia, and hypokalemia in the setting of thyrotoxicosis. We present the case of a 32-year-old male with multiple presentations to the emergency department for lower limb weakness, tremors, diaphoresis, and tachycardia. His initial blood work revealed T3-toxicosis and hypokalemia, and he was treated for TPP with intravenous fluids and potassium supplementation. He had been ingesting weight loss supplements containing iodine, kelp, licorice, and likely undeclared thyroid hormones or mimics. Following discontinuation of supplements, all laboratory investigations normalized and thyrotoxicosis symptoms resolved. This case illustrates that ingestion of thyroid hormone-based nutraceuticals should be considered as a cause of thyrotoxicosis and TPP. RésuméLa paralysie périodique thyréotoxique (PPT) se caractérise par de la faiblesse musculaire, une aréflexie et une hypokaliémie dans le contexte de la thyréotoxicose. Nous exposons le cas d’un homme de 32 ans qui s’est présenté au service des urgences pour de multiples symptômes, soit une faiblesse des membres inférieurs, des tremblements, une diaphorèse et une tachycardie. Son bilan sanguin initial a révélé une toxicose-T3 et une hypokaliémie, et il a été traité contre la PPT par des solutés intraveineux et une recharge en potassium. Il ingérait des suppléments pour la perte de poids contenant de l’iode, de la laminaire, de la réglisse et probablement des hormones thyroïdiennes ou leurs analogues non déclarés. Après l’arrêt des suppléments, tous les examens de laboratoire sont revenus à la normale et les symptômes de thyréotoxicose ont disparu. Ce cas montre que l’ingestion de nutraceutiques à base d’hormones thyroïdiennes devrait être considérée comme une cause de la thyréotoxicose et de la PPT.

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8

Anouassi, Zohour, Rania M. El Lababidi, Nouran Salem, Wasim S. El Nekidy, and Mohamad Mooty. "1622. Outcomes of Colistin Weight-Based Dosing Versus The Non-Weight-Based Dosing." Open Forum Infectious Diseases 7, Supplement_1 (October 1, 2020): S803—S804. http://dx.doi.org/10.1093/ofid/ofaa439.1802.

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Abstract Background The use of colistin is currently the mainstay antimicrobial for several multi-drug resistant organisms (MDROs). New guidelines were recently published recommending non-weight-based (NWB) dosing of colistin. There is limited data on outcomes with this new dosing strategy. The purpose of this study was to investigate the outcomes of the new NWB dosing strategy in comparison to the previously used weight-based (WB) dosing strategy. Methods A retrospective study was conducted at our quaternary care hospital between January 2016 and April 2020. Adults (≥ 18 years), who received intravenous (IV) colistin for ≥ 72 hours were included. Documented clinical cure was the primary endpoint, which was defined as having at least two of the following: normalization of white blood cell count or ≥ 25% reduction, defervescence, hemodynamic stability, normalization of inflammatory markers (C-reactive protein and procalcitonin values) or ≥ 25% reduction, or the resolution of signs and symptoms of infection by the end of the therapy. Secondary outcomes were microbiological cure, incidence of acute kidney injury (AKI), time to AKI, outcomes of AKI, time to AKI recovery, new infection while on IV colistin, recurrence of infection, and all-cause mortality. Results A total of 104 primarily male (57.7%) patients with a mean age of 63 ± 20.23 years and weight of 70.24 ± 19.46 kg met the inclusion criteria. At baseline for both groups, the estimated creatinine clearance was 74.23 ± 70.86 mL/min and renal replacement therapy was observed in 34.62%. There was no statistically significant difference observed in clinical cure rate in the WB was 77.03% while 83.33% in the NWB (p-value 0.48). However, a higher rate of AKI was observed in NWB was 84.21% while 53.33% in WB (p-value 0.02). Amongst those who had AKI, NWB had better AKI recovery status with 60.00% while 17.95% in WB (p-value 0.00). A higher all-cause mortality rate was observed in the WB group with 55.41% while 20.00% in NWB (p-value 0.02). Conclusion The study showed no statistical difference in the primary outcome between the two groups, however, higher AKI rates, AKI recovery and all-cause mortality was observed in non-weight-based dosing when compared to the weight-based dosing. Our data needs to be validated in a larger study. Disclosures All Authors: No reported disclosures

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9

Raihan, W., R. M. Tessar, C. O. S. Ernest, W. R. E. Byan, and A. Winda. "Vehicle Maximum Weight Limitation Based on Intelligent Weight Sensor." IOP Conference Series: Materials Science and Engineering 187 (March 2017): 012040. http://dx.doi.org/10.1088/1757-899x/187/1/012040.

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10

Walsh, R. M., B. Chand, J. Brodsky, and B. T. Heniford. "Determination of intact splenic weight based on morcellated weight." Surgical Endoscopy 17, no. 8 (August 1, 2003): 1266–68. http://dx.doi.org/10.1007/s00464-001-8223-6.

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11

DEVEAUX, R. "Comparison between actual birth weight, ultrasonographic fetal weight, and formula-based birth weight." Obstetrics & Gynecology 101, no. 4 (April 2003): S117. http://dx.doi.org/10.1016/s0029-7844(02)03039-9.

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12

DeVeaux, Richard, Stanley Swaby, Prabhudas Palan, and Magdy Mikhail. "Comparison Between Actual Birth Weight, Ultrasonographic Fetal Weight, and Formula-Based Birth Weight." Obstetrics & Gynecology 101, Supplement (April 2003): 117S. http://dx.doi.org/10.1097/00006250-200304001-00278.

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13

Wang, Zhao-Yu, Shie-Jue Lee, and Shing-Tai Pan. "A Weight-Based Clustering Method." ITM Web of Conferences 12 (2017): 05007. http://dx.doi.org/10.1051/itmconf/20171205007.

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14

Miller, Alicia S. "Pharmacy Issues: Weight-Based Dosing." Hospital Pharmacy 36, no. 7 (July 2001): 790–91. http://dx.doi.org/10.1177/001857870103600714.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting prescriber computer order entry (PCOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of PCOE at the Medical Center.

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15

Kraig, KA, and PK Keel. "Weight-based stigmatization in children." International Journal of Obesity 25, no. 11 (November 2001): 1661–66. http://dx.doi.org/10.1038/sj.ijo.0801813.

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16

Meisl, Claus J. "Non-Weight-Based Cost Modeling." Journal of Parametrics 15, no. 1 (April 1995): 37–62. http://dx.doi.org/10.1080/10157891.1995.10462544.

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17

Powroznik, Karen M. "Healthism and Weight-Based Discrimination." Work and Occupations 44, no. 2 (December 8, 2016): 139–70. http://dx.doi.org/10.1177/0730888416682576.

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Health promotion programs have become increasingly common in U.S. workplaces, yet little research has examined the unintended and potentially negative consequences of these initiatives. Overweight and obese employees face widespread prejudice and pervasive discrimination in employment settings, and this study investigates whether workplace health promotion may lead to more negative outcomes for these workers. Using an experimental design, the author finds that overweight and obese employees are rated more negatively and receive lower hiring recommendations when evaluated for companies with health promotion programs. These findings suggest that health promotion increases the salience and perceived legitimacy of negative fat stereotypes that facilitate weight-based discrimination.

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18

Browne, Nancy T., and Beverly B. Haynes. "Weight-Based Victimization in Youth." Journal of Pediatric Surgical Nursing 5, no. 3 (2016): 65–66. http://dx.doi.org/10.1097/jps.0000000000000106.

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19

Yuan, Yi Fan, Jun Ping Du, Jun Zhou, Cheng Lu, Er Wei Bai, and Ya Wen Li. "Weight Calculation Based Image Recognition." Applied Mechanics and Materials 303-306 (February 2013): 1577–80. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.1577.

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The method to recognize facial expression in images quickly has been widely applied in many areas, but there is no way to take into account the accuracy and speed of recognition. This paper presents a method based on the weight calculation for fast expression recognition. It first calculates facial features based on active shape model, and then matches the features to the standard expression vector got by large number of image training and recognizes the expression in the static image. The experiments show that the system can provide fast, universal expression recognizing function under the premise of guaranteeing an ideal accuracy.

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20

Erstad, Brian L. "Which weight for weight-based dosage regimens in obese patients?" American Journal of Health-System Pharmacy 59, no. 21 (November 1, 2002): 2105–10. http://dx.doi.org/10.1093/ajhp/59.21.2105.

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21

Yee, William P., and Linda L. Norton. "Optimal weight base for a weight-based heparin dosing protocol." American Journal of Health-System Pharmacy 55, no. 2 (January 15, 1998): 159–62. http://dx.doi.org/10.1093/ajhp/55.2.159.

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22

Kotecha, Aditya, Nabeel Haider, Prabhash Kakarla, Rushi Surati, Robert Sherwin, Camelia Arsene, Geetha Krishnamoorthy, and Hicham Krayem. "1446: CLINICAL OUTCOMES OF WEIGHT-BASED VERSUS NON-WEIGHT-BASED NOREPINEPHRINE DOSING IN SEPTIC SHOCK." Critical Care Medicine 46, no. 1 (January 2018): 707. http://dx.doi.org/10.1097/01.ccm.0000529448.04122.64.

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23

Patel, Vishal, and Joseph Cavanaugh. "343: Weight-Based Versus Non-Weight-Based Diltiazem for Atrial Fibrillation in an Emergency Department." Critical Care Medicine 49, no. 1 (December 11, 2020): 160. http://dx.doi.org/10.1097/01.ccm.0000727260.93926.18.

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24

Johnston, Craig, S. Rost, K. Miller-Kovach, J. P. Moreno, and J. P. Foreyt. "Comparison of Weight Loss by Weight Classification in a Commercial, Community-based Weight Loss Program." Journal of Nutrition Education and Behavior 45, no. 4 (July 2013): S31—S32. http://dx.doi.org/10.1016/j.jneb.2013.04.086.

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25

Jin, Mi Hwa, Seung Hun Park, Boc Nam Park, Jin Oh Lee, Jong Seon Park, and Hiye Ja Lee. "Effect of Feedback-Based Weight Management System on Body Weight Change." Journal of Korean Society of Medical Informatics 14, no. 3 (2008): 221. http://dx.doi.org/10.4258/jksmi.2008.14.3.221.

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26

Puhl, R. M., J. L. Peterson, and J. Luedicke. "Weight-Based Victimization: Bullying Experiences of Weight Loss Treatment-Seeking Youth." PEDIATRICS 131, no. 1 (December 24, 2012): e1-e9. http://dx.doi.org/10.1542/peds.2012-1106.

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27

Jian, Gaopeng, Zhouchen Lin, and Rongquan Feng. "Two-weight and three-weight linear codes based on Weil sums." Finite Fields and Their Applications 57 (May 2019): 92–107. http://dx.doi.org/10.1016/j.ffa.2019.02.001.

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28

S, Toshniwal, Toshniwal P, Bhabhor N, Bhabhor A, and Chaudhary R. "A community based cross sectional study on the prevalence of low birth weight neonates and maternal factor responsible for the low birth weight." Asian Pacific Journal of Health Sciences 4, no. 3 (September 30, 2017): 239–44. http://dx.doi.org/10.21276/apjhs.2017.4.3.36.

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29

Yang, Yunjun. "Evidence based exercise to control weight." Journal of Korean Medical Association 60, no. 10 (2017): 806. http://dx.doi.org/10.5124/jkma.2017.60.10.806.

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30

KATSURA, Toshiki, and Akiko HOSHINO. "Weight Cycling in Population-based Studies." JOURNAL OF THE JAPANESE ASSOCIATION OF RURAL MEDICINE 52, no. 6 (2004): 979–91. http://dx.doi.org/10.2185/jjrm.52.979.

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31

TUCKER, MIRIAM E. "Weight-Based Correction Improves Insulin Dosing." Hospitalist News 2, no. 10 (October 2009): 2. http://dx.doi.org/10.1016/s1875-9122(09)70218-4.

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32

Johnson, Eleanor K., Dave J. Adams, and Petra J. Cameron. "Peptide based low molecular weight gelators." J. Mater. Chem. 21, no. 7 (2011): 2024–27. http://dx.doi.org/10.1039/c0jm03099f.

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33

LECHNER, DEBRA L. "A Standardized Weight-Based Heparin Protocol." Nursing Management (Springhouse) 28, no. 4 (April 1997): 32F. http://dx.doi.org/10.1097/00006247-199704010-00007.

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34

Paschalis, Antonis, Ioannis Voyiatzis, and Dimitris Gizopoulos. "Accumulator Based 3-Weight Pattern Generation." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 20, no. 2 (February 2012): 357–61. http://dx.doi.org/10.1109/tvlsi.2010.2102373.

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35

Hubbard, Betsy. "Meal Replacement-Based Weight-Loss Programs." Obesity Management 3, no. 6 (December 2007): 292–95. http://dx.doi.org/10.1089/obe.2007.0122.

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36

Emes, Claudia, Beth Velde, Mary Moreau, Douglas D. Murdoch, and Rebecca Trussell. "An Activity Based Weight Control Program." Adapted Physical Activity Quarterly 7, no. 4 (October 1990): 314–24. http://dx.doi.org/10.1123/apaq.7.4.314.

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Two methods of introducing obese adolescents to aerobic exercise were compared. A fast-start group began with five aerobic sessions per week and gradually reduced these to three over a period of 12 weeks. A slow-start group began with one per week and gradually increased to three. A control group had an equivalent amount of time in interactive group sessions and nonaerobic activity. The program was assessed by physical fitness, anthropometry, and attendance. Results were analyzed by multivariate analysis. The method of introducing exercise to the subjects produced no significant differences on measures of fitness or anthropometry. Significant effects for time were shown for strength, push-ups, body mass index, the sum of five skinfolds, gluteal and abdominal circumferences, weight, and percent overweight. Significant differences in the absenteeism rates were shown among groups. However, no relationship was found between absenteeism and changes in weight or overall fitness levels.

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37

Yee, William P., Linda L. Norton, and William J. Spruill. "Clarification of weight-based heparin protocol." American Journal of Health-System Pharmacy 59, no. 18 (September 15, 2002): 1788. http://dx.doi.org/10.1093/ajhp/59.18.1788.

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38

Spruill, William J. "Clarification of weight-based heparin protocol." American Journal of Health-System Pharmacy 59, no. 18 (September 15, 2002): 1788. http://dx.doi.org/10.1093/ajhp/59.18.1788-a.

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39

Spruill, William J. "Clarification of weight-based heparin protocol." American Journal of Health-System Pharmacy 59, no. 18 (September 15, 2002): 1788. http://dx.doi.org/10.1093/ajhp/59.18.1788a.

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40

Rivey, Michael P., and John P. Peterson. "Pharmacy-managed, Weight-based Heparin Protocol." American Journal of Health-System Pharmacy 50, no. 2 (February 1, 1993): 279–84. http://dx.doi.org/10.1093/ajhp/50.2.279.

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41

Yu, Liangjun, Shengfeng Gan, Yu Chen, and Meizhang He. "Correlation-Based Weight Adjusted Naive Bayes." IEEE Access 8 (2020): 51377–87. http://dx.doi.org/10.1109/access.2020.2973331.

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42

Eggleton, Alison. "Paracetamol doses based on patient weight." Nurse Prescribing 12, no. 9 (September 2, 2014): 429. http://dx.doi.org/10.12968/npre.2014.12.9.429.

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43

Celaya, Enric, and Alejandro Agostini. "Online EM with Weight-Based Forgetting." Neural Computation 27, no. 5 (May 2015): 1142–57. http://dx.doi.org/10.1162/neco_a_00723.

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In the online version of the EM algorithm introduced by Sato and Ishii ( 2000 ), a time-dependent discount factor is introduced for forgetting the effect of the old estimated values obtained with an earlier, inaccurate estimator. In their approach, forgetting is uniformly applied to the estimators of each mixture component depending exclusively on time, irrespective of the weight attributed to each unit for the observed sample. This causes an excessive forgetting in the less frequently sampled regions. To address this problem, we propose a modification of the algorithm that involves a weight-dependent forgetting, different for each mixture component, in which old observations are forgotten according to the actual weight of the new samples used to replace older values. A comparison of the time-dependent versus the weight-dependent approach shows that the latter improves the accuracy of the approximation and exhibits much greater stability.

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44

Sikorski, C., J. Spahlholz, M. Hartlev, and S. G. Riedel-Heller. "Weight-based discrimination: an ubiquitary phenomenon?" International Journal of Obesity 40, no. 2 (August 27, 2015): 333–37. http://dx.doi.org/10.1038/ijo.2015.165.

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45

Yin, Xuesong, Jie Yu, and Rongrong Jiang. "Neighbor-based Data Weight Collaborative Filtering." IOSR Journal of Computer Engineering 16, no. 4 (2014): 06–10. http://dx.doi.org/10.9790/0661-16410610.

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46

Macdonald, Erin M., John J. Koval, Renato Natale, Timothy Regnault, and M. Karen Campbell. "Population-Based Placental Weight Ratio Distributions." International Journal of Pediatrics 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/291846.

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The placental weight ratio (PWR) is a health indicator that reflects the balance between fetal and placental growth. The PWR is defined as the placental weight divided by the birth weight, and it changes across gestation. Its ranges are not well established. We aimed to establish PWR distributions by gestational age and to investigate whether the PWR distributions vary by fetal growth adequacy, small, average, and large for gestational age (SGA, AGA, and LGA). The data came from a hospital based retrospective cohort, using all births at two London, Ontario hospitals in the past 10 years. All women who delivered a live singleton infant between 22 and 42 weeks of gestation were included(n=41441). Nonparametric quantile regression was used to fit the curves. The results demonstrate decreasing PWR and dispersion, with increasing gestational age. A higher proportion of SGA infants have extreme PWRs than AGA and LGA, especially at lower gestational ages. On average, SGA infants had higher PWRs than AGA and LGA infants. The overall curves offer population standards for use in research studies. The curves stratified by fetal growth adequacy are the first of their kind, and they demonstrate that PWR differs for SGA and LGA infants.Corrigendum to “Population-Based Placental Weight Ratio Distributions”

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47

Ghilardi, Silvio, Silvio Ranise, and Thomas Valsecchi. "Light-Weight SMT-based Model Checking." Electronic Notes in Theoretical Computer Science 250, no. 2 (September 2009): 85–102. http://dx.doi.org/10.1016/j.entcs.2009.08.019.

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48

Rajak, Deepak, Roopam Gupta, and Sanjeev Sharma. "Racs based Weight Optimization and Layered Clustering-based ECOC." International Journal of Computer Applications 129, no. 9 (November 17, 2015): 14–16. http://dx.doi.org/10.5120/ijca2015906889.

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49

Visentin, S., A. Londero, E. Mercanzin, M. Di Giovanni, M. Andolfatto, V. Bernardini, and E. Cosmi. "EP18.14: Estimated fetal weight: comparison between weight estimate based on the symphysis‐fundus height measurement and weight estimate based on ultrasound measurements." Ultrasound in Obstetrics & Gynecology 54, S1 (September 30, 2019): 347. http://dx.doi.org/10.1002/uog.21492.

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50

Kumar, Manoj, and Vinay Kumar Deolia. "RSWECNN: Refined Semantic Weight based Convolutional Neural Network (WECNN) Segmentation for Fruit Flower Detection." Journal of Advanced Research in Dynamical and Control Systems 11, no. 11-SPECIAL ISSUE (November 29, 2019): 189–98. http://dx.doi.org/10.5373/jardcs/v11sp11/20192947.

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