scholarly journals Correlation of Ultrasonographic Estimation of Fetal Weight with Actual Birth Weight as Seen in a Private Specialist Hospital in South East Nigeria

2019 ◽  
Vol 2019 ◽  
pp. 1-4
Author(s):  
Chisolum Ogechukwu Okafor ◽  
Charles Ikechukwu Okafor ◽  
Ikechukwu Innocent Mbachu ◽  
Izuchukwu Christian Obionwu ◽  
Michael Echeta Aronu
Keyword(s):  
Birth Weight ◽  
Mean Absolute Error ◽  
Pearson Correlation ◽  
Absolute Error ◽  
Fetal Weight ◽  
Percentage Error ◽  
Mean Error ◽  
The Mean ◽  
Route Of Delivery ◽  
Private Specialist

Background. Ultrasound estimation of fetal weight at term provides vital information for the skilled birth attendants to make decisions on the possible best route of delivery of the fetus. This is more pertinent in a setting where women book late for antenatal care. Aim and Objectives. The study evaluated the accuracy of estimation of fetal weight with ultrasound machine at term. Methods. This was a cross sectional study conducted at a private specialist hospital in Nigeria. A coded questionnaire was used to retrieve relevant information which included the last menstrual period, gestational age, parity, and birth weight. Other information obtained includes Ultrasound-delivery interval, maternal weight, and route of delivery. The ultrasound was used to estimate the fetal weight. The actual birth weight was determined using a digital baby weighing scale. The data were inputted into Microsoft excel and analyzed using STATA version 14. Statistical significance was considered at p-values less than 0.05. Measures of accuracy evaluated in the statistical analysis included mean error, mean absolute error, mean percentage error, and mean absolute percentage error. Pearson correlation was done between the estimated ultrasound fetal weight and the actual birth weight. The proportion of estimates within ±10% of actual birth weight was also determined. Result.A total of 170 pregnant women participated in the study. The mean maternal age was 30.77 years ± 5.54. The mean birth weight was 3.47 kg ± 0.47, while the mean estimated ultrasound weight was 3.43 kg ± 0.8. There was positive correlation between the ultrasound estimated weight and the actual birth weight. The mean ultrasound scan to delivery interval was 0.8 days (with range of 0–2 days). The study recorded a mean error of estimation of 41.17 grams and mean absolute error of 258.22 grams. The mean percentage error was 0.65%, while the mean absolute error of estimation was 7.56%. About 72.54% of the estimated weights were within 10% of the actual birth weight. Conclusion. The ultrasound estimated fetal weight correlated with the actual birth weight. Ultrasound estimation of fetal weight should be done when indicated to aid the clinician in making decisions concerning routes of delivery.

Estimation of fetal weight by ultrasonography after preterm premature rupture of membranes: comparison of different formulas

2017 ◽  
Vol 45 (2) ◽  
Author(s):  
Sertac Esin ◽  
Mutlu Hayran ◽  
Yusuf Aytac Tohma ◽  
Mahmut Guden ◽  
Ismail Alay ◽  
...  
Keyword(s):  
Birth Weight ◽  
Gestational Age ◽  
Fetal Weight ◽  
Percentage Error ◽  
Weight Estimation ◽  
Premature Rupture ◽  
Preterm Premature Rupture ◽  
Absolute Percentage Error ◽  
The Mean ◽  
Weight Groups

AbstractObjective:To compare different ultrasonographic fetal weight estimation formulas in predicting the fetal birth weight of preterm premature rupture of membrane (PPROM) fetuses.Methods:Based on the ultrasonographic measurements, the estimated fetal weight (EFW) was calculated according to the published formulas. The comparisons used estimated birth weight (EBW) and observed birth weight (OBW) to calculate the mean absolute percentage error [(EBW–OBW)/OBW×100], mean percentage error [(EBW–OBW)/OBW×100)] and their 95% confidence intervals.Results:There were 234 PPROM patients in the study period. The mean gestational age at which PPROM occured was 31.2±3.7 weeks and the mean gestational age of delivery was 32.4±3.2 weeks. The mean birth weight was 1892±610 g. The median absolute percentage error for 33 formulas was 11.7%. 87.9% and 21.2% of the formulas yielded inaccurate results when the cut-off values for median absolute percentage error were 10% and 15%, respectively. The Vintzileos’ formula was the only method which had less than or equal to 10% absolute percentage error in all age and weight groups.Conclusions:For PPROM patients, most of the formulas designed for sonographic fetal weight estimation had acceptable performance. The Vintzileos’ method was the only formula having less than 10% absolute percentage error in all gestational age and weight groups; therefore, it may be the preferred method in this cohort. Amniotic fluid index (AFI) before delivery had no impact on the performance of the formulas in terms of mean percentage errors.

Comparison between clinical estimated fetal weights (CEFW) Versus Ultrasonographic estimated fetal weight (UEFW) for co-relation with actual birth weight (ABW) in 3rd Trimester of Pregnancy

2020 ◽  
Vol 3 (1) ◽  
pp. e1-e4
Author(s):  
Rabia Razaq
Keyword(s):  
Birth Weight ◽  
Pearson Correlation ◽  
Tertiary Care ◽  
Fetal Weight ◽  
P Value ◽  
Cross Sectional ◽  
Positive Correlation ◽  
Study Results ◽  
The Mean ◽  
Estimated Fetal Weight

Background: Accurate prenatal estimation of birth weight is useful in the management of labour and delivery. Objective: To determine the correlation between clinical estimated fetal weight with actual birth weight in 3rd trimester of pregnancy and to determine the correlation between Ultrasonographic fetal weight assessment with actual birth weight in 3rd trimester of pregnancy. Material & Methods: This cross sectional study with non-probability purposive sampling technique was conducted in three tertiary care hospitals of Punjab, Department of Obstetrics & Gynaecology, Allied Hospital, Faisalabad, Lady Aitcheson Hospital Lahore and Lady Willington Hospital Lahore. Informed consent was obtained from each female to use their data for research purpose. Demographic details were also noted. Then females undergo CEFW was done by using Johnson’s formula. Then ultrasonography was done on every female by experienced radiologists to get UEFW. FW measurement was done by using Shepard formula. Then females were followed-up till delivery of fetus. Actual birth weight (ABW) was noted on birth. Pearson correlation was used to measure the correlation coefficient for CEFW and UEFW with ABW. P-value≤0.05 was taken as significant. Results: In our study the mean age of the patients was 29.60±6.23 years and the mean gestational age of 33.30±2.31 weeks. The mean BMI value of the patients was 23.08±1.26 Kg/m2, the mean CEFW value 2219.60±556.41 grams while the mean UEFW value of the patients was 2227.77±521.94 grams and the mean value of ABW of the patients was 2284.00±515.29 grams. In our study the positive correlation was found between the CEFW, UEFW with ABW of the baby. Conclusion: Our study results concluded that both the clinical estimation ultrasonography estimation showed the feasible and reliable results. Both showed positive correlation with actual birth weight.

scholarly journals Accuracy and reliability of ultrasound estimation of fetal weight in women with a singleton term pregnancy

2019 ◽  
Vol 9 (1) ◽  
pp. 323
Author(s):  
Reena Sharma ◽  
Rohit Bhoil ◽  
Poojan Dogra ◽  
Sushruti Kaushal ◽  
Ajay Sharma
Keyword(s):  
Birth Weight ◽  
Mode Of Delivery ◽  
Absolute Error ◽  
Mean Absolute Percentage Error ◽  
Fetal Weight ◽  
Percentage Error ◽  
Strong Positive Correlation ◽  
Positive Correlation ◽  
Absolute Percentage Error ◽  
Estimated Fetal Weight

Background: Prenatal estimation of birth-weight is of utmost importance to predict the mode of delivery. This is also an important parameter of antenatal care. This study was conducted to evaluate the accuracy of estimated fetal weight by ultrasound, compared with actual birth weight.Methods: This was a prospective and comparative study comprising 110 pregnant women at term. Patients who had their sonography done within 7 days from date of delivery were included. Fetal weight was estimated by Hadlock 2 formula, the software of which was preinstalled in ultrasound-machine. The estimated fetal weight was compared to the post-delivery birth-weight. The Pearson's correlation coefficient was used and the accuracy of sonographic fetal weight estimation was evaluated using mean error, mean absolute error, mean percentage error, mean absolute percentage error and proportion of estimates within 10% of actual birth weight.Results: Mean estimated and actual birth weights were 3120.8±349.4 gm and 3088.2±404.5 g respectively. There was strong positive correlation between estimated fetal weight and actual birth weight (r = 0.58, p<0.001). The mean percentage error and mean absolute percentage error of ultrasound fetal weight estimations were 1.96±11.8% and 8.7±8.2% respectively. The percentage of estimates within ±10% of the actual birth weight was found to be 67.3%. In 23% of the cases, ultrasound overestimated the birth weight. In 13% of the cases, ultrasound underestimated the birth weight.Conclusions: There was strong positive correlation between actual and sonographically estimated fetal weight. So, ultrasonography can be considered as useful tool for estimating the fetal weight for improving the perinatal outcome.

scholarly journals A new hybrid of Fuzzy C-Means Method and Fuzzy Linear Regression Model in Predicting Manufacturing Income

2018 ◽  
Vol 7 (4.30) ◽  
pp. 473
Author(s):  
Nurfarawahida Ramly ◽  
Mohd Saifullah Rusiman ◽  
Norziha Che Him ◽  
Maria Elena Nor ◽  
Supar Man ◽  
...  
Keyword(s):  
Linear Regression ◽  
Mean Absolute Error ◽  
Human Perception ◽  
Absolute Error ◽  
Percentage Error ◽  
Fuzzy Linear Regression ◽  
Fuzzy C Means ◽  
Fuzzy Linear Regression Model ◽  
The Mean ◽  
Ambiguous Data

Analysis by human perception could not be solved using traditional method since uncertainty within the data have to be dealt with first. Thus, fuzzy structure system is considered. The objectives of this study are to determine suitable cluster by using fuzzy c-means (FCM) method, to apply existing methods such as multiple linear regression (MLR) and fuzzy linear regression (FLR) as proposed by Tanaka and Ni and to improve the FCM method and FLR model proposed by Zolfaghari to predict manufacturing income. This study focused on FLR which is suitable for ambiguous data in modelling. Clustering is used to cluster or group the data according to its similarity where FCM is the best method. The performance of models will measure by using the mean square error (MSE), the mean absolute error (MAE) and the mean absolute percentage error (MAPE). Results shows that the improvisation of FCM method and FLR model obtained the lowest value of error measurement with MSE=1.825 , MAE=115932.702 and MAPE=95.0366. Therefore, as the conclusion, a new hybrid of FCM method and FLR model are the best model for predicting manufacturing income compared to the other models.

scholarly journals Feasibility of Sonography in estimating Fetal Weight of Low Birth Weight Babies

2016 ◽  
Vol 7 (2) ◽  
pp. 42-48
Author(s):  
Lavanya Rai ◽  
Sanghamithra Reddy ◽  
Shripad Hebbar
Keyword(s):  
Birth Weight ◽  
Absolute Error ◽  
Fetal Weight ◽  
Percentage Error ◽  
Weight Estimation ◽  
Validation Group ◽  
Absolute Percentage Error ◽  
Low Birth Weight Babies ◽  
Formula Derivation ◽  
New Formula

ABSTRACT Background Currently available ultrasound-based fetal birth weight estimation methods have been designed for a group of neonates with wide birth weight range and hence are faced with increased error of margin. Whenever there is a need for delivering pregnant woman with small fetus, prior knowledge of approximate fetal weight is of utmost importance for neonatal survival, and an error in this process can result in significant morbidity/mortality to the newborn baby. This necessitates need for the establishment of new birth weight formula exclusively for this subset of fetuses. Objectives To test the accuracy of established formulae in fetuses ≤ 2000 gm at birth in singleton pregnancies. To develop new formula for this group of small fetuses delivering in our institution with maximal accuracy and reliability and to prospectively validate this formula in subsequent set of pregnant cohort. Materials and methods The current study was done in two phases: The first phase was a formula derivation phase wherein the four major parameters [biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL)] were evaluated from a set of 128 postpartum women who delivered a neonate weighing ≤2 kg within 1 week of ultrasound examination. Stepwise regression analysis using birth weight as dependent parameter and fetal biometric parameters as independent parameters was used to develop the best formula for estimating fetal weight at birth. In the second phase (formula validation phase), the newly derived formula was tested for its accuracy in 31 pregnant women who gave birth to neonates weighing ≤2 kg. Results The new formula (log10 [BW] = 1.0131 + 0.0216 × HC + 0.0448 × AC + 0.2183 × FL + 0.0001 × BPD × AC – 0.0059 × AC × FL) was superior to established birth weight formulae. In the formula derivation group, the lowest mean ± standard deviation (SD) absolute error was 130 ± 91 gm and the lowest mean absolute percentage error was 9.8 ± 7% SD for the new formula and 61.7% of weight estimates fell within ± 10% of the actual weight at birth and this percentage further increased to 83.6 and 91.4% for error of margin of ±15 and ±20% respectively. When this formula was applied in the validation group, the absolute error in grams was 102 ± 115 and absolute percentage error was 7.4 ± 7; hence 77.4% fell within 10%, 80.6% fell within 15%, 90.3% fell within 20%. Further, in the validation group, mean ± SD of estimated birth weight was 1337 ± 406 gm, which was closest to actual birth weight (1328 ± 433 gm). Conclusion Our new formula is likely to estimate birth weight in small fetuses (≤2 kg) with reasonable accuracy and reliability. When compared to available methods of ultrasound birth weight estimation, absolute error and absolute percentage error is least with our formula indicating a good fit. How to cite this article Reddy S, Hebbar S, Rai L. Feasibility of Sonography in estimating Fetal Weight of Low Birth Weight Babies. Int J Infertil Fetal Med 2016;7(2):42-48.

scholarly journals Accuracy of Fetal Weight Estimation by Ultrasonographic Evaluation in a Northeastern Region of India

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Ranjumoni Konwar ◽  
Bharati Basumatary ◽  
Malamoni Dutta ◽  
Putul Mahanta
Keyword(s):  
Birth Weight ◽  
Pregnant Women ◽  
Absolute Error ◽  
Cross Sectional Study ◽  
Fetal Weight ◽  
Percentage Error ◽  
Cross Sectional ◽  
Weight Category ◽  
Obstetric Management ◽  
The Difference

Background and Objectives. Fetal weight evaluation in utero is a significant component in obstetric practices. The present study aims to estimate the fetal weight (EFW) by evaluating two available formulas using ultrasound parameters and comparing them with actual birth weight (ABW) after delivery. The accuracy and efficacy of both EFW formulas in detecting intrauterine growth retardation (IUGR) and macrosomia were also compared in our local sample of the population. Methods. The cross-sectional study included 100 pregnant women aged 20–45 years from the Kamrup district admitted to Guwahati Medical College and Hospital, Guwahati, Assam. The data were analyzed using Microsoft Excel and SPSS version 16. The EFW at term was calculated using Shepard’s formula and Hadlock’s formula. Differences in means are compared using the one-way ANOVA or Kruskal–Wallis test and paired t-test. The accuracy of the two procedures was evaluated using mean absolute error (MAE) and mean absolute percentage error (MAPE). A p value<0.05 was considered significant. Results. The present study included 100 pregnant women aged 21–38 years with term or postterm pregnancies subjected to ultrasonographic evaluation within 72 hours of delivery. The mean (±s.d.) EFW by Shepard’s formula was 2716.05 (±332.38) g and Hadlock’s formula was 2740.44 (±353.23) g, respectively. For Hadlock’s formula, MAE ± s.d. was found to be higher (overall 84.59 ± 76.54) specifically in the weight category less than 2500 (106.42 ± 88.11) as compared to Shepard’s (overall MAE ± s.d = 79.86 ± 64.78, and among ABW < 2500 g, MAE ± s.d = 65.04 ± 61.02). The overall MAPE of Hadlock’s formula was 3.14% and that for Shepard’s formula was 2.91%, and the difference was not statistically significant. Both Shepard’s formula and Hadlock’s formula had a sensitivity of 92.85% in detecting IUGR, but Hadlock’s method had higher specificity (66%), higher PPV (86.67%), and higher NPV (80%). Conclusion. The ultrasonographic evaluation of fetal weight helps predict fetal birth weight precisely and can influence obstetric management decisions concerning timing and route of delivery, thus reducing perinatal morbidity and mortality.

Modeling and Predicting Tensile Strength of Tungsten Alloy by Using PSO-SVR

2012 ◽  
Vol 455-456 ◽  
pp. 1497-1503
Author(s):  
J.L. Tang ◽  
C.Z. Cai ◽  
X.J. Zhu ◽  
G.L. Wang ◽  
D.F. Cao
Keyword(s):  
Tensile Strength ◽  
Mean Absolute Error ◽  
Back Propagation ◽  
Absolute Error ◽  
Back Propagation Neural Network ◽  
Influential Factors ◽  
Tungsten Alloy ◽  
Percentage Error ◽  
The Mean ◽  
Bpnn Model

In this paper, the support vecstor regression (SVR) approach combined with particle swarm optimization (PSO) is proposed to establish a model for predicting tungsten tensile strength base on the tension experimental data of tungsten alloy under two influential factors, including tungsten content and deformation magnitude. Comparing the prediction result of PSO-SVR model with that of back propagation neural network (BPNN) model, it is shown that the prediction precision of SVR model is higher evaluated by identical training and test samples. The mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE) of SVR model, all are smaller than those of BPNN. This study suggests that SVR is an effective and powerful tool for predicting the tensile strength of tungsten alloy.

Establish a new equation for ultrasonographic estimated fetal weight in Chongqing: a prospective study

2020 ◽  
Author(s):  
Chenhuizi Wu ◽  
Jianfeng Sun ◽  
Liuyun Cai ◽  
Xinru Deng ◽  
Fenglan Zhang ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Mean Absolute Error ◽  
Estimation Error ◽  
Local Population ◽  
Absolute Error ◽  
Population Characteristics ◽  
Fetal Weight ◽  
The Mean ◽  
New Equation ◽  
Weight Compensation

Abstract Background: Variation in fetal growth between populations should not be ignored, and a single universal standard is not appropriate for everyone. Therefore, according to regional population characteristics, it is necessary to find a more accurate equation for ultrasound estimation of fetal weight. The purpose of this study was to create a new equation for ultrasound estimation of fetal weight according to the local population in Chongqing and compare it with representative equations. Methods: This prospective study included data on pregnant women who gave birth to a single child at full term in our hospital from December 2016 to November 2019. The fetal weight compensation model was established by using the second-order linear regression model, then the equation of fetal weight was established by utilizing the multiple reverse elimination regression technique. The accuracy of the equation established in this study was respectively compared with the Hadlock equation, Combs equation and Stirnemann equation by estimation error.Results: Through the fetal weight compensation equation, the predicted fetal weight equation suitable for Chongqing fetuses was successfully established with the variables of biparietal diameter, head circumference, abdominal circumference and femur length. In the sets established by 1925 data, the mean absolute error and standard deviation of the estimation error of the equation established in this study were 178.9g and 140.3g respectively. In the 300 validation sets, the mean absolute error and Standard deviation of Chongqing equation were 173.08g and 128.59g respectively. Compared with representative equations, the mean absolute error and the standard deviation of the new equation were the lowest.Conclusions: According to the local population characteristics of Chongqing, this study created the equation for estimated fetal weight, which is more accurate and suitable. This equation has high clinical guidance and reference value for monitoring and management of fetal weight and maternal delivery process.

scholarly journals An Algorithm for Density Enrichment of Sparse Collaborative Filtering Datasets Using Robust Predictions as Derived Ratings

Algorithms ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 174
Author(s):  
Dionisis Margaris ◽  
Dimitris Spiliotopoulos ◽  
Gregory Karagiorgos ◽  
Costas Vassilakis
Keyword(s):  
Collaborative Filtering ◽  
Mean Absolute Error ◽  
Pearson Correlation ◽  
Absolute Error ◽  
Mean Square ◽  
Error Metrics ◽  
Target User ◽  
The Mean ◽  
Rating Prediction ◽  
Sparsity Problem

Collaborative filtering algorithms formulate personalized recommendations for a user, first by analysing already entered ratings to identify other users with similar tastes to the user (termed as near neighbours), and then using the opinions of the near neighbours to predict which items the target user would like. However, in sparse datasets, too few near neighbours can be identified, resulting in low accuracy predictions and even a total inability to formulate personalized predictions. This paper addresses the sparsity problem by presenting an algorithm that uses robust predictions, that is predictions deemed as highly probable to be accurate, as derived ratings. Thus, the density of sparse datasets increases, and improved rating prediction coverage and accuracy are achieved. The proposed algorithm, termed as CFDR, is extensively evaluated using (1) seven widely-used collaborative filtering datasets, (2) the two most widely-used correlation metrics in collaborative filtering research, namely the Pearson correlation coefficient and the cosine similarity, and (3) the two most widely-used error metrics in collaborative filtering, namely the mean absolute error and the root mean square error. The evaluation results show that, by successfully increasing the density of the datasets, the capacity of collaborative filtering systems to formulate personalized and accurate recommendations is considerably improved.

Explanation Plus Prediction—The Logical Focus of Project Management Research

2021 ◽  
pp. 875697282199994
Author(s):  
Joseph F. Hair ◽  
Marko Sarstedt
Keyword(s):  
Project Management ◽  
Statistical Models ◽  
Predictive Power ◽  
Mean Absolute Error ◽  
Explanatory Power ◽  
Absolute Error ◽  
Model Parameters ◽  
Mean Square ◽  
Management Research ◽  
The Mean

Most project management research focuses almost exclusively on explanatory analyses. Evaluation of the explanatory power of statistical models is generally based on F-type statistics and the R 2 metric, followed by an assessment of the model parameters (e.g., beta coefficients) in terms of their significance, size, and direction. However, these measures are not indicative of a model’s predictive power, which is central for deriving managerial recommendations. We recommend that project management researchers routinely use additional metrics, such as the mean absolute error or the root mean square error, to accurately quantify their statistical models’ predictive power.

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