predictive equations
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2022 ◽  
pp. 026010602110701
Author(s):  
Carmen de Cáceres ◽  
Teresa Rico ◽  
Cristina Abreu ◽  
Ana Isabel Velasco ◽  
Rafael Lozano ◽  
...  

Background: The adaptation of Parenteral Nutrition (PN) to actual energy requirements of hospitalised patients is essential, since excessive and insufficient nutritional intake have been associated with poor clinical outcomes. Aim: To evaluate the adaptation of prescribed PN to the estimated nutritional requirements using three predictive equations and the influence of excessive/insufficient nutrient intake on patient clinical outcomes (nutritional parameters, metabolic and infectious complications). Methods: Prospective, observational study in hospitalised patients nutritionally assessed. Data was collected the first and fifth/sixth day of PN with clinical (infection, length of hospital stay), biochemical (visceral proteins, cholesterol, glucose, triglycerides, lymphocytes, CRP) and anthropometric parameters (skin folds, height, weight). Theoretical requirements were calculated using Harris-Benedict (HB), Mifflin-St Jeor (MF) and 25 Kcal/Kg/day formulas. The HB formula was used to compare estimated and provided requirements. Results: A total of 94 patients (mean: 72 ± 13.7 years old) were included with initial mean weight and height of 69.2 Kg and 162.8 cm, respectively (mean BMI: 26.1 Kg/m2). No statistically significant differences were found between the actual (1620 Kcal/day) and estimated caloric mean calculated with HB (1643 Kcal/day) and MF (1628 Kcal/day). When comparing with the caloric estimation, 31.9% of patients were underfed, while 14.9% were overfed. Intergroup analysis demonstrated significant variations in albumin, prealbumin, glucose, cholesterol, triglycerides and MUAC, with a significant increase of hyperglycaemia (+37.86; p < 0.05) and hypertriglyceridemia (+63.10; p < 0.05), being higher in overfed patients. Conclusion: In our study, inadequate nutrient intake was associated with a higher degree of hyperglycaemia and hypertriglyceridemia, without positive impact on anthropometric parameters.


Author(s):  
Sang-Hyun Kim ◽  
Sung Yong Park ◽  
Sung Tae Kim ◽  
Se-Jin Jeon

AbstractThe proper estimation of prestressing force (PF) distribution is critical to ensure the safety and serviceability of prestressed concrete (PSC) structures. Although the PF distribution can be theoretically calculated based on certain predictive equations, the resulting accuracy of the theoretical PF needs to be further validated by comparison with reliable test data. Therefore, a Smart Strand with fiber optic sensors embedded in a core wire was developed and applied to a full-scale specimen and two long-span PSC girder bridges in this study. The variation in PF distribution during tensioning and anchoring was measured using the Smart Strand and was analyzed by comparison with the theoretical distribution calculated using the predictive equations for short-term prestress losses. In particular, the provisions for anchorage seating loss and elastic shortening loss were reviewed and possible improvements were proposed. A new method to estimate the amount of anchorage slip based on real PF distributions revealed that the general assumption of 3–6-mm slip falls within a reasonable range. Finally, the sensitivity of the PF distribution to a few of the variables included in the equation of the elastic shortening loss was examined. The study results confirmed that the developed Smart Strand can be used to improve the design parameters or equations in PSC structures by overcoming the drawbacks of conventional sensing technologies.


2021 ◽  
Vol 9 ◽  
Author(s):  
Jimena Fuentes-Servín ◽  
Azalia Avila-Nava ◽  
Luis E. González-Salazar ◽  
Oscar A. Pérez-González ◽  
María Del Carmen Servín-Rodas ◽  
...  

Background and Aims: The determination of energy requirements is necessary to promote adequate growth and nutritional status in pediatric populations. Currently, several predictive equations have been designed and modified to estimate energy expenditure at rest. Our objectives were (1) to identify the equations designed for energy expenditure prediction and (2) to identify the anthropometric and demographic variables used in the design of the equations for pediatric patients who are healthy and have illness.Methods: A systematic search in the Medline/PubMed, EMBASE and LILACS databases for observational studies published up to January 2021 that reported the design of predictive equations to estimate basal or resting energy expenditure in pediatric populations was carried out. Studies were excluded if the study population included athletes, adult patients, or any patients taking medications that altered energy expenditure. Risk of bias was assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies.Results: Of the 769 studies identified in the search, 39 met the inclusion criteria and were analyzed. Predictive equations were established for three pediatric populations: those who were healthy (n = 8), those who had overweight or obesity (n = 17), and those with a specific clinical situation (n = 14). In the healthy pediatric population, the FAO/WHO and Schofield equations had the highest R2 values, while in the population with obesity, the Molnár and Dietz equations had the highest R2 values for both boys and girls.Conclusions: Many different predictive equations for energy expenditure in pediatric patients have been published. This review is a compendium of most of these equations; this information will enable clinicians to critically evaluate their use in clinical practice.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=226270, PROSPERO [CRD42021226270].


2021 ◽  
pp. 204589402110590
Author(s):  
Lucy Robertson ◽  
Katrina Oates ◽  
Andrew Fletcher ◽  
Karl Sylvester

In pulmonary vascular disease (PVD) exercise abnormalities can include reduced exercise capacity, reduced oxygen pulse (O2 pulse) and elevated VE/VCO2. The association of clinical measures such as 6 minute walk work (6MWW), haemodynamics, lung function and echocardiogram to peak VO2, O2 pulse and VE/VCO2 has not been fully investigated in PVD Aims: To determine the relationship of 6MWW and other clinical measures to peak VO2, peak O2 pulse and VE/VCO2. Additionally, to investigate the ability to predict peak VO2 from 6MWW and other clinical parameters. Methods: Clinical data was retrospectively analysed from 63 chronic thromboembolic pulmonary hypertension (CTEPH) and 54 chronic thromboembolic disease (CTED) patients. 6 minute walk test measures, haemodynamics, lung function and echocardiographic measures were correlated with peak VO2, peak O2 pulse and VE/VCO2. Predictive equations were developed to predict peak V̇O2 in both CTEPH and CTED cohorts and subsequently validated. Results: A number of clinical parameters correlated to peak VO2, peak O2 pulse and VE/VCO2. 6MWW and TLCO demonstrated the strongest correlation to peak VO2 and peak O2 pulse. The validation of the predictive equations showed a variable level of agreement between measured peak VO2 and calculated peak VO2 from the predictive equations. Conclusion: 6MWW and additionally a number of clinical test parameters were associated to peak VO2, peak O2 pulse and VE/VCO2. 6MWW and TLCO were particularly highly correlated to peak VO2 and similarly to peak O2 pulse. The validation of the predictive equations showed a variable level of agreement and therefore may have limited clinical applicability.


Author(s):  
Maurizio Marra ◽  
Olivia Di Vincenzo ◽  
Iolanda Cioffi ◽  
Rosa Sammarco ◽  
Delia Morlino ◽  
...  

Abstract Background An accurate estimation of athletes’ energy needs is crucial in diet planning to improve sport performance and to maintain an appropriate body composition. This study aimed to develop and validate in elite athletes new equations for estimating resting energy expenditure (REE) based on anthropometric parameters as well as bioimpedance analysis (BIA)-derived raw variables and to validate the accuracy of selected predictive equations. Methods Adult elite athletes aged 18–40 yrs were studied. Anthropometry, indirect calorimetry and BIA were performed in all subjects. The new predictive equations were generated using different regression models. The accuracy of the new equations was assessed at the group level (bias) and at the individual level (precision accuracy), and then compared with the one of five equations used in the general population or three athletes-specific formulas. Results One-hundred and twenty-six male athletes (age 26.9 ± 9.1 yrs; weight 71.3 ± 10.9 kg; BMI 22.8 ± 2.7 kg/m2) from different sport specialties were randomly assigned to the calibration (n = 75) or validation group (n = 51). REE was directly correlated with individual characteristics, except for age, and raw BIA variables. Most of the equations from the literature were reasonably accurate at the population level (bias within ±5%). The new equations showed a mean bias −0.3% (Eq. A based on anthropometric parameters) and −0.6% (Eq. B based on BIA-derived raw variables). Precision accuracy (individual predicted-measured differences within ±5%) was ~75% in six out of eight of the selected equations and even higher for Eq. A (82.4%) and Eq. B (92.2%). Conclusion In elite athletes, BIA-derived phase angle is a significant predictor of REE. The new equations have a very good prediction accuracy at both group and individual levels. The use of phase angle as predictor of REE requires further research with respect to different sport specialties, training programs and training level.


2021 ◽  
Vol 12 ◽  
Author(s):  
Maximilian Rembe ◽  
Jochen Christoph Reif ◽  
Erhard Ebmeyer ◽  
Patrick Thorwarth ◽  
Viktor Korzun ◽  
...  

Reciprocal recurrent genomic selection is a breeding strategy aimed at improving the hybrid performance of two base populations. It promises to significantly advance hybrid breeding in wheat. Against this backdrop, the main objective of this study was to empirically investigate the potential and limitations of reciprocal recurrent genomic selection. Genome-wide predictive equations were developed using genomic and phenotypic data from a comprehensive population of 1,604 single crosses between 120 female and 15 male wheat lines. Twenty superior female lines were selected for initiation of the reciprocal recurrent genomic selection program. Focusing on the female pool, one cycle was performed with genomic selection steps at the F2 (60 out of 629 plants) and the F5 stage (49 out of 382 plants). Selection gain for grain yield was evaluated at six locations. Analyses of the phenotypic data showed pronounced genotype-by-environment interactions with two environments that formed an outgroup compared to the environments used for the genome-wide prediction equations. Removing these two environments for further analysis resulted in a selection gain of 1.0 dt ha−1 compared to the hybrids of the original 20 parental lines. This underscores the potential of reciprocal recurrent genomic selection to promote hybrid wheat breeding, but also highlights the need to develop robust genome-wide predictive equations.


2021 ◽  
Author(s):  
Puneet Khanna ◽  
Heena Garg ◽  
Bikash Ranjan Ray ◽  
Ajay Singh ◽  
Riddhi Kundu ◽  
...  

2021 ◽  
pp. 1-8
Author(s):  
Huijuan Ruan ◽  
Qingya Tang ◽  
Qi Yang ◽  
Fangwen Hu ◽  
Wei Cai

<b><i>Objective:</i></b> Several predictive equations have been used to estimate patients’ energy expenditure. The study aimed to describe the characteristics of resting energy expenditure (REE) in patients undergoing mechanical ventilation during early postoperative stage after cardiac surgery and evaluate the validity of 9 REE predictive equations. <b><i>Methods:</i></b> This was a prospective observational study. Patients aged 18–80 years old, undergone open-heart surgery, were enrolled between January 2017 and 2018. The measured REE (mREE) was evaluated via indirect calorimetry (IC). The predictive resting energy expenditure (pREE) was suggested by 9 predictive equations, including Harris-Benedict (HB), HB coefficient method, Ireton-Jones, Owen, Mifflin, Liu, 25 × body weight (BW), 30 × BW, and 35 × BW. The association between mREE and pREE was assessed by Pearson’s correlation, paired <i>t</i> test, Bland-Altman method, and the limits of agreement (LOA). <b><i>Results:</i></b> mREE was related to gender, BMI, age, and body temperature. mREE was significantly correlated with pREE, as calculated by 9 equations (all <i>p</i> &#x3c; 0.05). There was no significant difference between pREE and mREE, as calculated by 30 × BW kcal/kg/day (<i>t</i> = 0.782, <i>p</i> = 0.435), while significant differences were noted between mREE and pREE calculated by other equations (all <i>p</i> &#x3c; 0.05). Taking the 30 × BW equation as a suitable candidate, most of the data points were within LOA, and the percentage was 95.6% (129/135). Considering the rationality of clinical use, accurate predictions (%) were calculated, and only 40.74% was acceptable. <b><i>Conclusions:</i></b> The 30 × BW equation is relatively acceptable for estimating REE in 9 predictive equations in the early stage after heart surgery. However, the IC method should be the first choice if it is feasible.


Author(s):  
Xiaomin Chen ◽  
George H. Bryan

AbstractHorizontal homogeneity is typically assumed in the design of planetary boundary layer (PBL) parameterizations in weather prediction models. Consistent with this assumption, PBL schemes with predictive equations for subgrid turbulence kinetic energy (TKE) typically neglect advection of TKE. However, tropical cyclone (TC) boundary layers are inhomogeneous, particularly in the eyewall. To gain further insight, this study examines the effect of advection of TKE using the Mellor-Yamada-Nakanishi-Niino (MYNN) PBL scheme in idealized TC simulations. The analysis focuses on two simulations, one that includes TKE advection (CTL) and one that does not (NoADV). Results show that relatively large TKE in the eyewall above 2 km is predominantly attributable to vertical advection of TKE in CTL. Interestingly, buoyancy production of TKE is negative in this region in both simulations; thus, buoyancy effects cannot explain observed columns of TKE in TC eyewalls. Both horizontal and vertical advection of TKE tends to reduce TKE and vertical viscosity (Km) in the near-surface inflow layer, particularly in the eyewall of TCs. Results also show that the simulated TC in CTL has slightly stronger maximum winds, slightly smaller radius of maximum wind (RMW), and ~5% smaller radius of gale-force wind than in NoADV. These differences are consistent with absolute angular momentum being advected to smaller radii in CTL. Sensitivity simulations further reveal that the differences between CTL and NoADV are more attributable to vertical advection (rather than horizontal advection) of TKE. Recommendations for improvements of PBL schemes that use predictive equations for TKE are also discussed.


2021 ◽  
Vol 11 (18) ◽  
pp. 8503
Author(s):  
Flávio A. Damasceno ◽  
Joseph L. Taraba ◽  
George B. Day ◽  
Randi A. Black ◽  
Jeffrey M. Bewley ◽  
...  

Among animal facilities, compost-bedded pack (CBP) barns have attracted a lot of attention from milk producers and the scientific community. Systematic investigation of the main thermal properties utilizing sawdust in CBP barns is of environmental and economic relevance. In this paper, the aim was to (a) develop predictive equations for the thermal conductivity (k) of compost bedding as a function of moisture content (MC), the degree of compaction (DCo), and particle size (PS); and (b) investigate the links between k and depth within bedding material. Samples of compost bedding materials were collected from 42 commercial CBP barns distributed throughout Kentucky (USA). From these predictive equations, it was possible to understand how the MC, DCo, and PS of the bedding materials may influence the behavior of k. These results are very useful for solving obstacles to simulate and predict the variable outcomes of the compost bedding materials process in CBP barns, allowing for its optimization, consequently reducing the time and energy spent on their optimization and allowing for simulation and assessment of compost bedding process modifications. The results of the current study may have important implications in the design and management of bedded pack barns.


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