Weight Estimation Methods Research Articles

Comparison of paediatric weight estimation methods at a tertiary hospital in Ghana.

IntroductionWeight estimation in children is critical in paediatric emergencies. The Broselow Tape (BT) and most age-based formulae for weight estimation were derived in high-income countries and are thought to overestimate the weight of children in low-income countries. This study sought to validate the 2017 BT, and eight age-based weight estimation formulae among Ghanaian children and to derive a weight estimation formula using this data.MethodsA cross-sectional study was conducted in the Tamale Teaching Hospital (TTH) in Ghana. Children aged between 2 months and 13 years had their weights estimated by the 2017 BT and eight age-based formulae. These estimated weights were compared to the weight of the children measured by a calibrated Seca scale using mean percentage error (MPE) and the percentage of weight estimates within 10% and 20% of actual weight. Bland-Altman method was used to assess agreement between estimated and actual weight of the children. A new formula was derived by linear regression.ResultsSeven hundred and seventy-five children took part in the study. The 2017 BT, Original APLS (APLS1) and Nelson's formulae performed best with proportion of weight estimates within 10% of actual weight being 47.5%, 51.1% and 47.5% respectively. The formula developed in this study was: WE = 3Am / 10 + 5 (for infants <12 months), WE = 2A + 7 (1 to 4 years) and WE = 2A + 9 (5 to 13 years), where WE is estimated weight, Am is age in completed months and A is age in completed years. The new formula had similar accuracy as the three best performing methods in this study.ConclusionThe Broselow Tape, APLS1 and the Nelson's formula were the most accurate in this study. APLS1 and the Broselow Tape can be used for weight estimation in Ghanaian children when no other better method is available.

Comparison of Some Methods for Estimating Parameters of General Linear Model in Presence of Heteroscedastic Problem and High Leverage Points

Linear regression is one of the most important statistical tools through which it is possible to know the relationship between the response variable and one variable (or more) of the independent variable(s), which is often used in various fields of science. Heteroscedastic is one of the linear regression problems, the effect of which leads to inaccurate conclusions. The problem of heteroscedastic may be accompanied by the presence of extreme outliers in the independent variables (High leverage points) (HLPs), the presence of (HLPs) in the data set result unrealistic estimates and misleading inferences. In this paper, we review some of the robust weighted estimation methods that accommodate both Robust and classical methods in the detection of extreme outliers (High leverage points) (HLPs) and the determination of weights. The methods include both Diagnostic Robust Generalized Potential Based on Minimum Volume Ellipsoid (DRGP (MVE)), Diagnostic Robust Generalized Potential Based on Minimum Covariance Determinant (DRGP (MCD)), and Diagnostic Robust Generalized Potential Based on Index Set Equality (DRGP (ISE)). The comparison was made according to the standard error criterion of the estimated parameters SE ( ) and SE ( ) of general linear regression model, for sample sizes (n=60, n=100, n=160), with different degree (severity) of heterogeneity, and contamination percentage (HLPs) are (τ =10%, τ=30%). it was found through comparison that weighted least squares estimation based on the weights of the DRGP (ISE) method are considered the best in estimating the parameters of the multiple linear regression model because they have the lowest standard error values of the estimators ( ) and ( ) as compared to other methods.&#x0D; Paper type: A case study

A Total Variation With Joint Norms For Infrared and Visible Image Fusion

A single infrared image or visible image for the same scene is usually insufficient to simultaneously reveal the infrared objects and the scene details. Thus, image fusion techniques play an important role in producing a single image from the images captured by infrared and visible sensors. In this paper, we propose a novel total variation (TV)-based fusion for infrared and visible images. In our model, a weighted fidelity term is employed to fuse both the infrared objects in the infrared image and the salient scenes in the visible image. To this end, a weight estimation method is developed based on the global luminance contrast-based saliency. Also, to overcome the over-fitting, two constraints are further introduced to merge more details from the visible image and prevent the luminance degradation for the fused result, respectively. Moreover, joint norms are exploited to produce a better result. <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${{\boldsymbol{l}}_{2,1,{\boldsymbol{rc}}}}$</tex-math></inline-formula> provides the structural group sparseness for the fidelity term, whereas <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${{\boldsymbol{l}}_{1/2}}$</tex-math></inline-formula> presents the better gradient sparse for the detail preserving term and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${{\boldsymbol{l}}_2}$</tex-math></inline-formula> is utilized for the luminance degradation preventing term. Experimental results indicate that the proposed method can give state-of-the-art performances both in visual perception and quantitative scores than other methods.

Do Clothing Labels Play a Role for Weight Estimation in Pediatric Emergencies? A Prospective, Cross-Sectional Study.

The aim of this study was to investigate the usability of the age value listed on the labels on children's clothes in the age-based weight estimation method recommended by the Pediatric Advanced Life Support (PALS) guidelines. This prospective, cross-sectional study was organized in Antalya Training and Research Hospital Emergency Department. Children aged between 1-12 years were included in the study. The weight measurements of the children were obtained based on the age-related criteria on the labels of their clothes. The estimated values were compared with the real values of the cases measured on the scale. One-thousand ninety-four cases were included, the mean age of cases in age-based measurements was 6.25 years, which was 6.5 years in label-based measurements. Average weights measured 25.75kg according to age-based measurements, 26.5kg according to label-based measurements, and 26.0kg on the scales, and showed no statistical difference (P <.0001). It was estimated that 741 (67.7%) of age-based measurements and 775 (70.8%) of label-based measurements were within (±)10% values within the normal measurement limits and no significant difference was measured. In the emergency department and prehospital setting, children with an unknown age and that need resuscitation and interventional procedures for stabilization, and have no time for weight estimation, checking the age on clothing label (ACL) instead of the actual age (AA) can be safely used for the age-dependent weight calculation formula recommended by the PALS guide.

Are adults just big kids? Can the newer paediatric weight estimation systems be used in adults?

The weight of a patient is an important variable that impacts on their medical care. Although some drugs are prescribed on a so-called 'adult dose' basis, we know that adults come in all shapes and sizes - a 'one-dose-fits-all' approach is not necessarily appropriate. As a measured weight may not always be available, an alternative method of accurately estimating weight is required. To assess and compare the accuracy of weight estimations in adults by patient self-estimation, the Mercy method, Buckley method, Broca index and PAWPER XL-MAC (paediatric advanced weight prediction in the emergency room eXtra length/eXtra large mid-arm circumference) method. This was a prospective, cross-sectional study conducted at a tertiary academic hospital in a metropolitan area of Johannesburg, South Africa. Anthropometric variables of height, abdominal circumference, thigh circumference, mid-arm circumference and humeral length were measured. These variables were then applied to the various weight estimation methods and compared with the patient's actual weight. There were 188 adult patients included in the study. None of the methodologies evaluated in this study achieved the recommended &gt;70% of weight estimations within 10% of the patient's actual weight (PW10). The Mercy method was the closest to achieving greater than the recommended 95% for weight estimation falling within 20% of the patient's actual weight (PW20). The PW20 for the Mercy method was 91.5%. The PAWPER XL-MAC and patient self-estimate methods achieved a PW20 of 85.1% and 86.1%, respectively. The Broca and Buckley methods performed poorly overall. None of the evaluated weight estimation methodologies was accurate enough for use in adult weight estimation. The Mercy and PAWPER XL-MAC methodologies both showed significant promise for use in adult weight estimation, but need further refinement. Although patient self-estimates were similarly accurate to those found in previous studies, they were not an accurate option; self-estimations would remain the first choice if the patient was able to provide such an estimation. The Broca index and Buckley method cannot be recommended owing to their poor performance.

Body weight estimation of yak based on cloud edge computing

In stock farming, the body size parameters and weight of yaks can reasonably reflect the growth and development characteristics, production performance and genetic characteristics of yaks. However, it is difficult for herders to measure the body size and weight of yaks by traditional manual methods. Fortunately, with the development of edge computing, herders can use mobile devices to estimate the yak’s body size and weight. The purpose of this paper is to provide a machine vision-based yak weight estimation method for the edge equipment and establish a yak estimation comprehensive display system based on the user’s use of the edge equipment in order to maximize the convenience of herdsmen’s work. In our method, a set of yak image foreground extraction and measurement point recognition algorithm suitable for edge equipment were developed to obtain yak’s measurement point recognition image, and the ratio between body sizes was transmitted to the cloud server. Then, the body size and weight of yaks were estimated using the data mining method, and the body size estimation data were constantly displayed in the yak estimation comprehensive display system. Twenty-five yaks in different age groups were randomly selected from the herd to perform experiments. The experimental results show that the foreground extraction method can obtain segmentation image with good boundary, and the yak measurement point recognition algorithm has good accuracy and stability. The average error between the estimated values and the actual measured values of body height, oblique length, chest depth, cross height and body weight is 1.95%, 3.11%, 4.91%, 3.35% and 7.79%, respectively. Compared with the traditional manual measurement method, the use of mobile end to estimate the body size and weight of yaks can improve the measurement efficiency, facilitate the herdsmen to breed yaks, reduce the stimulation of manual measurement on yaks and lay a solid foundation for the fine breeding of yaks in Sanjiangyuan region.

Estimating the marginal hazard ratio by simultaneously using a set of propensity score models: A multiply robust approach.

The inverse probability weighted Cox model is frequently used to estimate the marginal hazard ratio. Its validity requires a crucial condition that the propensity score model be correctly specified. To provide protection against misspecification of the propensity score model, we propose a weighted estimation method rooted in the empirical likelihood theory. The proposed estimator is multiply robust in that it is guaranteed to be consistent when a set of postulated propensity score models contains a correctly specified model. Our simulation studies demonstrate satisfactory finite sample performance of the proposed method in terms of consistency and efficiency. We apply the proposed method to compare the risk of postoperative hospitalization between sleeve gastrectomy and Roux-en-Y gastric bypass using data from a large medical claims and billing database. We further extend the development to multisite studies to enable each site to postulate multiple site-specific propensity score models.

Body Weight Estimation using 2D Body Image

Two dimensional images of a person implicitly contain several useful biometric information such as gender, iris colour, weight, etc. Among them, body weight is a useful metric for a number of usecases such as forensics, fitness and health analysis, airport dynamic luggage allowance, etc. Most current solutions for body weight estimation from images make use of additional apparatus like depth sensors and thermal cameras along with predefined features such as gender and height which generally make them more computationally intensive. Motivated by the need to provide a time and cost efficient solution, a novel computer-vision based method for body weight estimation using only 2D images of people is proposed. Considering the anthropometric features from the two most common types of images, facial and full body, facial landmark measurements and body joint measurements are used in deep learning and XG boost regression models to estimate the person’s body weight. The results obtained, though comparable to previous approaches, perform much faster due to the reduced complexities of the proposed models, with facial models performing better than full body models.

Pediatric weight estimation: validation of the PAWPER XL tape and the PAWPER XL tape mid-arm circumference method in a South African hospital.

ObjectiveThe primary aim of this study was to prospectively compare the performance of the Broselow tape, Mercy method, pediatric advanced weight prediction in the emergency room extra-long (PAWPER XL) tape, and PAWPER XL mid-arm circumference (MAC) method in estimating the weight of children from a low-income setting. The secondary aim was to analyze the time taken to perform each method.MethodsThis analyzed a convenience study sample of 300 children aged 0 to 18 years at the Baragwanath Hospital in South Africa. Weight estimations were obtained using each of the weight estimation systems on each child. These weight estimations were then compared against the actual weight to determine bias, precision, and accuracy of the estimation methods.ResultsThe PAWPER XL tape and PAWPER XL-MAC methods performed the best and provided estimated weights within 10% of the actual weight in 62.7% and 67.3% of cases, respectively, followed by the Mercy method (56.5%) and Broselow tape (43.9%). The use of MAC improved the accuracy of estimation, especially in heavier and taller children. The median times taken to perform measurements using the Broselow tape, Mercy method, PAWPER XL tape, and PAWPER XL-MAC method were 11.3 seconds, 34.7 seconds, 9.3 seconds, and 33.9 seconds respectively.ConclusionThe PAWPER XL tape and PAWPER XL-MAC methods were the most accurate methods of estimating weight in this group of children. These methods may be considered in preference to the Broselow tape or the Mercy method for emergency weight estimation in low socioeconomic status populations.

Clinical Estimation of Fetal Weight with Reference to Johnson’s Formula: An Alternative Solution Adjacent to Sonographic Estimation of Fetal Weight

Background Fetal weight estimation plays a significant role in the antenatal management of high risk pregnancies. It is also an important parameter for predicting the neonatal outcome and informs decision for the mode of intra-partum management of the pregnant women. Among the various methods of prenatal fetal weight estimation, the most commonly used are clinical estimation and sonography. Objective The objective of this study was to compare the accuracy of clinical estimation of fetal weight using Johnson's formula and sonographic estimation with actual birth weight. Method This prospective study was conducted at Dhulikhel Hospital, Kathmandu University Hospital, from January 2017 to August 2018. The study included 335 pregnant women at term gestation. Result The estimation of fetal weight at term pregnancy using Johnson's formula is as effective as sonological method. For clinical method, the fetal weight falls between 95 gm and 183 gm at 95% confidence interval. With respect to ultrasound method, the fetal weight is found to be 45 gm and 132 gm at 95% confidence interval at p value < 0.001. Conclusion Clinical estimation of fetal weight can be utilized as an alternative to sonological estimation in the management of labor and delivery. Johnson's formula is a simple, easy, cost-effective, and universally applicable method to predict fetal birth weight and can be used anywhere by doctors, nurses, midwives and paramedics in centers where ultrasound is not available.

Evaluation of the Accuracy of Horse Body Weight Estimation Methods.

Simple SummaryHorse body weight estimation and monitoring of the weight variations are necessary to determine the amount of feed and feed additives for the proper functioning of the animal. Due to the cost and practical challenge of weighing horses on a large scale, several alternative methods for estimating the body weight of horses have been developed. One of them is to determine a horse’s body weight using a formula. The aim of the study was to evaluate established formulae for estimating horse body weight from data gathered using measurement tape. The investigation was conducted on a group of 299 adult horses of five breeds: ponies, Polish Noble Half Breed, Silesian Breed, Wielkopolski Breed and Thoroughbred. For each horse, body measurements were performed and the actual body weight of the horses was measured with an electronic scales. The horse’s body weight measurements were compared with the result of seven different formulae. It was found that the use of formulae for body weight estimation can be useful in determining feed dosages and additives, medicines, or deworming agents.Methods of estimating horse body weight using mathematical formulae have better accuracy than methods of reading body weight from measuring tape. The aim of the study was to evaluate established formulae for estimating horse body weight from data gathered using measurement tape. The research was conducted in a group of 299 adult horses and ponies of selected breeds: ponies (n = 58), Polish Noble Half Breed (n = 150), Silesian Breed (n = 23), Wielkopolski Breed (n = 52), and Thoroughbred (n = 16). Body measurements were performed on each horse using a measuring stick and tape. The actual body weight of the horses was measured with electronic scale. Statistical analysis was carried out separately for individual breeds of horses. In each of the research groups formulae were selected, the results of which were closest to the actual horse body weight readings. The use of formulae for body weight estimation can be useful in determining feed dosages and additives, medicines or deworming agents. Regular weight measurement is important for maintaining a healthy horse.

Accurate Indoor Positioning Using Temporal–Spatial Constraints Based on Wi-Fi Fine Time Measurements

The IEEE 802.11mc-2016 protocol enables certified devices to obtain precise ranging information using time-of-flight-based techniques. The ranging error increases in indoor environments due to the multipath effect. Traditional methods utilize only the ranging measurements of the current location, thus limiting the abilities to reduce the influence of multipath problems. This article introduces a robust positioning method that leverages the constraints of multiple positioning nodes at different positions. We transfer a sequence of temporal ranging measurements into multiple virtual positioning clients (VPCs) in the spatial domain by considering their spatial constraints. Defining an objective function and the spatial constraints of the VPCs as Karush–Kuhn–Tucker conditions, we solve the positioning estimation with nonconvex optimization. We propose an iterative weight estimation method for the time of flight ranging and the VPC to optimize the positioning model. An extensive experimental campaign demonstrates that our proposal can remarkably improve the positioning accuracy in complex indoor environments.

Methods for Estimating Endotracheal Tube Insertion Depth in Neonates: A Systematic Review and Meta-Analysis.

To systematically review the methods for estimating endotracheal tube (ETT) insertion depth in neonates. Medline, Embase, Cochrane Central, and Cumulative Index to Nursing and Allied Health Literature databases searched for randomized clinical trials (RCTs). RCTs comparing two or more different methods to estimate ETT insertion depth were included. Two co-authors independently extracted the data and assessed the risk of bias. The primary outcome includes the proportion of optimally placed ETT tips identified on chest X-ray. Eight RCTs evaluating seven different estimation methods were included. Trials varied defining the optimal position of the ETT tip. Overall, the percentage of optimal position ranged from 8.8 to 93%. The weight, gestation nomogram, and vocal cord estimation methods resulted in malpositioning of ETT tips in more than half of infants ≤30 weeks' gestational age. The rates of optimal ETT tip placement with the digital palpation method differ between moderately (83-93%; two RCTs) and extremely (47%; one RCT) preterm infants. Meta-analysis showed no difference between weight-based and digital palpation methods (relative risk = 0.88; 95% confidence interval = 0.75-1.04; three RCTs; participants = 205; I 2 = 0%; quality of evidence, low). Commonly used estimation methods for ETT tip placement are inaccurate and unreliable. Further research is required to improve the accuracy of estimation methods and also to identify the usefulness of the digital palpation method in large clinical trials.

Validation and human factor analysis study of an infant weight estimation device

BackgroundWeight is critical for the medical management of infants; however, scales can be unavailable or inaccessible in some practice settings. We recently developed and validated a robust infant weight estimation method based on chest circumference (CC) and head circumference (HC). This study was designed to determine the human factors (HF) experience with, and predictive performance of, an infant weight estimation device that implements this method.MethodsProspective, multi-center, observational, masked study of 486 preterm and term infants (0–90 days) assessed by 15 raters. Raters measured the infant using calibrated scales/measures and masked versions of the device. Raters also evaluated critical tasks associated with device use. Mean error (ME) and mean percentage error (MPE) were used to assess predictive performance.ResultAmong 486 infants enrolled (36.8 ± 4.0 weeks gestational age, 31.5 ± 28.6 days postnatal age), predicted weight correlated highly with actual weight (r = 0.97, ME: − 69 ± 257 g, MPE: − 1.3 ± 6.9%). Predicted weight was within 10 and 15% of actual weight in 86 and 99%, of infants. HF errors were low, 0.1–0.8% depending on task. In all cases raters were confident or very confident in their measurements.ConclusionThe device was statistically equivalent to the method on which it was based and approximated weight with acceptable variance from the true weight. HF data suggest the device is easy to use. This device can be used to estimate weight in infants when calibrated scales are impractical or unavailable.

Comparison of weight estimation methods in hospitalized Brazilian children and adolescents.

Introduction: in emergencies or in situations involving critically ill patients, an accurate calculation of body weight is essential to ensure adequate medical care. Generally, simple techniques are used to determine weight. Aim: to evaluate the weight estimation methods Advanced Paediatric Life Support (APLS) Update, Luscombe and Owens, Best Guess, and the Broselow tape, comparing measured weight with the weight estimated by each method in hospitalized Brazilian children and adolescents. Methods: an observational study in which anthropometric data were collected from patients of 0-14 years of age between August 2016 and January 2017. The paired t-test was used to compare the patients' measured weight with their estimated weight. The accuracy of each method was analyzed using Bland-Altman plots and Lin's concordance correlation coefficient. Results: the sample consisted of 446 patients. Most of the patients were male (58.1%), of 1-5 years of age (43%) and well nourished (85%). For those under 12 months of age, the APLS Update and Best Guess methods performed best, with the difference in means of measured weight and estimated weight being 0.4 kg (p = 0.183) and -0.2 kg (p = 0.140), respectively. In the 1-5 years of age group only the APLS Update yielded satisfactory results (0.2 kg; p = 0.200). The best agreement with measured weight, according to the Bland-Altman plots and Lin's coefficient, was found for the Broselow tape (CC = 0.96). Conclusion: of the estimation methods evaluated the Broselow tape was the most accurate one. Further studies are required to adapt this method for use in the Brazilian population, thus ensuring its appropriate application in this country.

Comparison of age-based weight estimation with actual measured weight in children aged one to twelve years in Enugu.

This study was carried out to evaluate the degree of accuracy of age-based weight estimation methods in assessing the weight of the Nigerian child. The weights of one thousand, four hundred and fifty-six (1,456) children were measured and compared with the updated Advanced Paediatric Life Support (APLS), Best guess, Nelson and Luscombe & Owen methods. The updated APLS, Nelson and Luscombe & Owen methods underestimated the weights in younger children while overestimating in older ones. Best guess overestimated the weights across all ages. The Nelson formula had the best agreement within 10% and 20% of the measured weights among all methods. A linear regression analysis produced an equation for weight estimation: weight (W) = 2.058 Y + 9.925, where W is weight in kilogram and Y is the age in years. None of the weight estimation formulae assessed was entirely accurate in our study, though the Nelson method showed superior agreement.

How well does the Best Guess method predict children's weight in an emergency department in 2018-2019?

For seriously ill children, weight is often required to direct critical interventions. As it is not always feasible to measure weight in emergencies, age-based weight prediction formulae may be used as an alternative. The Best Guess formulae, derived in Australia, have been shown to be among the most accurate age-based methods in Australian children. They were validated in 2010. The present study aims to re-validate the Best Guess formulae and compare their performance to the previous validation cohort. A prospective observational study was conducted in the paediatric ED of a community teaching hospital. It included a convenience sample of children aged 1 month to 10 years who presented between July 2018 and April 2019. Seriously ill children were excluded. Data collected included measured weight, height, gender, age and ethnic group. The outcomes of interest were predictive performance of Best Guess formulae and comparison of predictive accuracy with a 2005 cohort from the same ED. A total of 961 patients were included; 42% girls, median age 3 years. The sample was ethnically diverse. Mean percent difference in weight was -3.3% with the formulae usually over-estimating weight. Overall, agreement within 10% was 41.8%; agreement within 20% was 72.6%. Predictive accuracy was not significantly different between the cohorts. The Best Guess method has not reduced in accuracy as a weight estimation method in emergent situations in this Australian cohort, despite a tendency to slightly over-estimate children's weight. Further study is needed to test the Best Guess method's accuracy in ethnic subgroups.

Causal inference with noisy data: Bias analysis and estimation approaches to simultaneously addressing missingness and misclassification in binary outcomes.

Causal inference has been widely conducted in various fields and many methods have been proposed for different settings. However, for noisy data with both mismeasurements and missing observations, those methods often break down. In this paper, we consider a problem that binary outcomes are subject to both missingness and misclassification, when the interest is in estimation of the average treatment effects (ATE). We examine the asymptotic biases caused by ignoring missingness and/or misclassification and establish the intrinsic connections between missingness effects and misclassification effects on the estimation of ATE. We develop valid weighted estimation methods to simultaneously correct for missingness and misclassification effects. To provide protection against model misspecification, we further propose a doubly robust correction method which yields consistent estimators when either the treatment model or the outcome model is misspecified. Simulation studies are conducted to assess the performance of the proposed methods. An application to smoking cessation data is reported to illustrate the use of the proposed methods.

English

Uganda&rsquo;s beef industry has been growing slowly and requires sustained monitoring of actors at post-harvest handling points in order to decrease public health risks and losses. This study documented causes of losses and estimated economic values at post-harvest handling points along the beef value chain. It was carried out at slaughter houses, transporters and butcher shops in the districts of Western, Central and Eastern Uganda. A cross sectional study was conducted among meat handlers who were interviewed to find out the losses incurred in the value chain. Microbial load from carcass swabs were collected and evaluated using standard microbiological methods to determine microbial contamination of beef. The causes of losses varied at different handling points. The actors at slaughter houses indicated the major losses were due to low beef demand (15.3%), insecurity (13.4%) and poor weight estimation methods (11.03%). Losses at the butchery included, beef waste (22.4%), drip loss (19.7%) and beef spoilage (18.4%). Microbial analysis showed the highest microbial prevalence at the butchery (70-100%) followed by slaughter (50-80%) and lastly transport (30-50%). Microbial contamination on carcass leads to spoilage and hence market loss because exportation does not admit contaminated foods. Actors reported beef waste and drip loss as the major causes of losses at the butchery. To reduce losses, public health care education for meat handlers and adherence to strict standard operating procedures (SOPs) are a key. Key words: Losses, post-harvest, beef value chain, handling points, Uganda. &nbsp;

Discrepancy Analysis between Clinical Versus Ultrasound Estimated Fetal Weight and Actual Birth Weight at 3rd Trimester

Background: In obstetric management fetal weight estimation is an important consideration when planning the mode of delivery in our day to day practice. In Bangladesh low birth weight is a major public health problem &amp; incidence is 38% - 58%. Neonatal mortality and morbidity also yet high. So accurate antenatal estimation of fetal weight is a good way to detect macrosomia or small for date baby. Thus to improve the pregnancy outcome and neonatal outcome decreasing various chance of neonatal mortality and morbidity antenatal fetal weight prediction is an invaluable parameter in some situation where to identify the at risk pregnancy for low birth weight become necessary. Reliable method for prenatal estimation of fetal weight two modalities have got popularity - Clinical estimation and another one is ultrasonic estimation. This study was designed to determine the accuracy of clinical versus ultrasound estimated fetal weight detecting the discrepancy with actual birth weight at third trimester. So that we can verify more reliable and accurate method.&#x0D; Objectives: To find out more accurate and reliable modality of fetal weight estimation in antenatal period during obstetric management planning. To compare clinical versus ultrasound estimated fetal weight &amp; to determine discrepancy of both variable with actual birth weight.&#x0D; Method: This prospective, cross sectional analytical study was carried out in Dhaka Medical College Hospital from January 2006 to December 2006. By purposive sampling 100 pregnant women fulfilling inclusion criteria were included in my study in third trimester (29wks-40wks). In clinical weight estimation procedure SFH (Symphysio Fundal Height) was measured in centimeter. On pervaginal finding whether vertex below or above the ischial spine was determined. By Johnson’s formula fetal weight in grams was estimated. Then by ultrasound scan different biometric measurements were taken and finally by Hadlock’s formula fetal weight was estimated. Eventually actual birth weight was taken after birth by Globe Brand weighing machine. Accuracy of both modalities were compared and which one was more reliable predictor was determined by statistical analysis.&#x0D; Results: After data collection were analyzed by computer based software (SPSS). There was gradual and positive relationship between symphysiofundal height and estimated birth weight. Discrepancy between clinical and actual birth weight at third trimester was statistically significant – Paired Student’s ‘t’ test was done where p value was &lt;0.001. Whereas discrepancy between sonographically estimated fetal weight with actual birth weight was not statistically significant (by paired ‘t’ test where p value was &gt;0.05). That implies discrepancy between ultrasound estimated fetal weight and actual birth weight was significantly less than that of clinically estimated fetal weight. 14% clinically and 46% sonographically estimated fetal weight were observed within £ 5% of actual birth weight. 31% clinical and 42% sonographically estimates observed within 6% to 10% of actual birth weight and 55% clinical and 12% sonographically estimate were &gt;10% of actual birth weight. That is about 88% sonographical versus 45% clinical estimates were within 10% of actual birth weight.&#x0D; Conclusion: There is no doubt about importance of fetal weight in many obstetric situations. Clinical decisions at times depends on fetal weight. Whether to use oxytocin, to use forceps or vacuum for delivery or extend of trial or ended by Caesarian section immediately or no scope of trial to be largely depend on fetal size and weight. So more accurate modality for antenatal fetal weight estimation has paramount importance. In my study sonographically estimated weight have more accuracy than that of clinical estimate in predicting actual birth weight. Sonographically estimated fetal weight is more reliable, accurate and reproducible rather than other modality.&#x0D; J Shaheed Suhrawardy Med Coll, June 2019, Vol.11(1); 32-38