Classification of Soccer and Basketball Players’ Jumping Performance Characteristics: A Logistic Regression Approach

This study aimed to examine countermovement jump (CMJ) kinetic data using logistic regression, in order to distinguish sports-related mechanical profiles. Eighty-one professional basketball and soccer athletes participated, each performing three CMJs on a force platform. Inferential parametric and nonparametric statistics were performed to explore group differences. Binary logistic regression was used to model the response variable (soccer or not soccer). Statistical significance (p < 0.05) was reached for differences between groups in maximum braking rate of force development (RFDDmax, U79 = 1035), mean braking rate of force development (RFDDavg, U79 = 1038), propulsive impulse (IMPU, t79 = 2.375), minimum value of vertical displacement for center of mass (SBCMmin, t79 = 3.135), and time difference (% of impulse time; ΔΤ) between the peak value of maximum force value (FUmax) and SBCMmin (U79 = 1188). Logistic regression showed that RFDDavg, impulse during the downward phase (IMPD), IMPU, and ΔΤ were all significant predictors. The model showed that soccer group membership could be strongly related to IMPU, with the odds ratio being 6.48 times higher from the basketball group, whereas RFDDavg, IMPD, and ΔΤ were related to basketball group. The results imply that soccer players execute CMJ differently compared to basketball players, exhibiting increased countermovement depth and impulse generation during the propulsive phase.

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Role of Ambulatory Blood Pressure Monitoring in Predicting Adverse Maternofetal Events in Pregnancy

Indian Journal of Cardiovascular Disease in Women WINCARS ◽

10.1055/s-0040-1708576 ◽

2021 ◽

Author(s):

Satish Kumar Rao Vavilala ◽

Indrani Garre ◽

Sumalatha Beeram

Keyword(s):

Blood Pressure ◽

Logistic Regression ◽

Standard Deviation ◽

Ambulatory Blood Pressure ◽

Blood Pressure Monitoring ◽

Statistical Significance ◽

Binary Logistic Regression ◽

Pressure Monitoring ◽

In Pregnancy

Abstract Aims To correlate the relationship between the ambulatory blood pressure parameters and the occurrence of the antenatal and postnatal adverse maternofetal events in pregnancy. Methods Observational study designed for 50 pregnant patients who had an appointment to the obstetrics with abnormal blood pressure (BP) measurements and for whom ambulatory blood pressure monitoring (ABPM) was studied between January 2019 and June 2019. Data about age, personal history, obstetrics, family, body mass index (BMI), weight gain in pregnancy, values of blood pressure in the appointment, values recorded in ABPM, delivery and newborn, pregnancy and postpartum events, and follow-up of woman and child. Data were analyzed using descriptive and inferential statistics with Minitab 17.0 for Windows. Results Patients demographic data, clinical history, and laboratory results, including the ABPM parameters, were compiled. Antenatal complications occurred in 22 patients (44%), and postpartum complications were found in 41 patients (82%) whose ABPM values were deranged. Antenatal complications were studied using the binary logistic regression analysis for calculating the role each factor played in the development of hypertension. In the sample studied, mean age was 24.980 with a standard deviation of 4.876 (p = 0.003; minimum age of 19 years and maximum age of 38 years), mean weight of patient was 63.71 with a standard deviation of 63.71 (p = 0.001), mean gravida was 1.780 with a standard deviation of 0.910 (p = 0.034), mean gestation weeks at presentation was 33.000 weeks with a standard deviation of 4.086 (p = 0.041), mean birth weight was 2.226 with a standard deviation of 0.797 (p = 0.000), mean maximum diastole was 109.22 with a standard deviation of 16.53 (p = 0.002), mean day maximum systole was 187.2 with a standard deviation of 203.5 (p = 0.009), mean day minimum diastole was 63.50 with a standard deviation of 12.99 (p = 0.013), all of which had statistical significance. It is found that the nighttime diastolic blood pressure (DBP) and daytime maximum systolic blood pressure (SBP) were the best predictors of adverse events. Among antenatal complications (ANC), the most common complication is intrauterine growth restriction (IUGR), noted in (n = 19, 86.36%) preterm delivery (n = 17, 77.27%) among the 17 babies who were delivered preterm; 12 (70.5%) needed neonatal intensive care unit (NICU) care of which 4 (25%) babies died because of prematurity; intrauterine death (IUD) was noted in 7 (31.81%) patients and eclampsia was seen in 5 (22.72%). Nondippers proðle had a worse survival rate at follow-up until delivery compared with those with a dipper proðle. Postnatal complications were seen in 41 patients; among them, 13 patients (31.7%) had abnormal fundus examination, 15 patients (36.58%) required usage of antihypertensive beyond first postpartum, 9 patients (21.95%) required blood transfusion for severe bleeding in the form of postpartum hemorrhage. Binary logistic regression for systolic dippers versus nondippers shows statistical significance in age (p = 0.023), weight (p = 0.038), and para (p = 0.045) (Table 3). Binary logistic regression for diastolic dippers versus nondippers shows statistical significance in age (p = 0.039), weight (p = 0.020), birth weight (p = 0.010), maximum heart rate (p = 0.043), and ANC (p = 0.007) Adverse events occurred most commonly in nondippers. Systole nondippers is noted in (n = 41, 82%). Dippers is noted in (n = 9, 18%), Diastole nondippers is noted in (n = 39, 78%) Dippers is noted in (n = 11, 22%). Conclusion ABPM recorded blood pressure is very precise. ABPM is the advised method for both diagnostic and therapeutic monitoring of hypertensive pregnancy diseases, mainly in situations like whitecoat hypertension, masked hypertension, nocturnal hypertension, and nondipping profile. In patients with high-risk pregnancy, elderly primigravida, and precious pregnancy, who have a high-risk of developing pregnancy-induced hypertension (PIH) and related complications, early use of ABPM predicts adverse maternofetal events, which when intervened at an earlier date can prevent antenatal and postnatal complications.

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Variability in the Application of Force During the Vertical Jump in Children and Adults

Journal of Applied Biomechanics ◽

10.1123/jab.2014-0043 ◽

2014 ◽

Vol 30 (6) ◽

pp. 679-684 ◽

Cited By ~ 3

Author(s):

Pablo Floria ◽

Luis A. Gómez-Landero ◽

Andrew J. Harrison

Keyword(s):

Coefficient Of Variation ◽

Development Time ◽

Task Complexity ◽

Vertical Jump ◽

Center Of Mass ◽

Mass Movement ◽

Rate Of Force Development ◽

Force Development ◽

Velocity Relationship ◽

Force Velocity

The purpose of this study was to determine if children exhibit greater variability in center of mass movement and kinetics compared with adults in vertical jumping. Countermovement jumps with arms (CMJA) and without arms (CMJ) performed by 20 female children and 20 female adults were examined using force platform. The data were analyzed using continuous methods to determine differences in variability between groups and between types of jump. Jumping variability was measured by using the average coefficient of variation of the force-, velocity-, displacement-, and rate of force development-time curves across the jump. The analysis indicated that children and adults had similar levels of variability in the CMJ but different levels in the CMJA. In the CMJA, the children had a greater coefficient of variation than adults in force- (20 ± 7% and 12 ± 6%), velocity- (41 ± 14% and 22 ± 9%), displacement- (8 ± 16% and 23 ± 11%) and rate of force development-time (103 ± 46% and 75 ± 42%) curves, as well as in force-velocity relationship (6 ± 2% and 4 ± 2%). The results of analysis suggest that the variability depends on both the level of maturation of the participants as well as the task complexity.

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INTERPRETATION OF PROPULSIVE FORCE IN TETHERED SWIMMING THROUGH PRINCIPAL COMPONENT ANALYSIS

Revista Brasileira de Medicina do Esporte ◽

10.1590/1517-869220182403175155 ◽

2018 ◽

Vol 24 (3) ◽

pp. 178-181 ◽

Cited By ~ 2

Author(s):

Rodrigo Maciel Andrade ◽

Aylton José Figueira Júnior ◽

Vanessa Metz ◽

Alberto Carlos Amadio ◽

Júlio Cerca Serrão

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

Peak Force ◽

Rate Of Force Development ◽

Impulse Generation ◽

Force Development ◽

Time To Peak ◽

Force Time ◽

Minimum Force

ABSTRACT Introduction: Propulsive force in swimming, represented through impulse, is related to performance. However, since the as different biomechanical parameters contribute to impulse generation, coaches have a difficult task when seeking for performance improvement. Objective: Identify the main components involved in impulse generation in the front crawl stroke. Methods: Fourteen swimmers underwent a 10-second all-out fully tethered swimming test. The following parameters were obtained from the force-time curve: minimum force, peak force, mean force, time to peak force, rate of force development and stroke duration. This stage was followed by a principal component analysis. Results: The principal component analysis showed that component 1, predominantly kinetic, was composed of peak force, mean force and rate of force development, and accounted for 49.25% of total impulse variation, while component 2, predominantly temporal, composed of minimum force, stroke duration, and time to peak force, represented 26.43%. Conclusion: Kinetic parameters (peak force, mean force, and rate of force development) are more closely associated with impulse augmentation and, hypothetically, with non-tethered swimming performance. Level of Evidence II; Diagnostic studies - Investigating a diagnostic test.

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Unilateral hamstring foam rolling does not impair strength but the rate of force development of the contralateral muscle

PeerJ ◽

10.7717/peerj.7028 ◽

2019 ◽

Vol 7 ◽

pp. e7028 ◽

Cited By ~ 2

Author(s):

Xin Ye ◽

Benjamin S. Killen ◽

Krista L. Zelizney ◽

William M. Miller ◽

Sunggun Jeon

Keyword(s):

Repeated Measures ◽

Statistical Significance ◽

Rate Of Force Development ◽

Isometric Strength ◽

Contralateral Limb ◽

Strength Performance ◽

Foam Rolling ◽

Force Development ◽

Emg Amplitude ◽

Hip Flexion

Background Self-administered foam rolling (SAFR) is an effective massage technique often used in sport and rehabilitation settings to improve range of motion (ROM) without impairing the strength performance. However, the effects of unilateral SAFR on contralateral non-intervened muscle’s rate of force development (RFD) are unknown. Therefore, the purpose of this investigation was to examine the acute effects of unilateral hamstrings SAFR on the contralateral limb flexibility, the isometric strength, and the RFD parameters. Methods Thirty-four subjects (21 women) completed two separate randomly sequenced experimental visits, during which the control (rested for 10 min) or ten, 30-second SAFR were performed with the dominant hamstring muscle group. Before (Pre) and after (Post) the interventions, the contralateral hip flexion passive ROM, the maximal explosive isometric strength of the contralateral knee flexors with the corresponding prime mover muscles’ surface electromyographic (EMG) amplitude were measured. Separate two-way (time ×intervention) repeated measures analyses of variance (ANOVAs) were used to examine the potential changes of the dependent variables. Results The SAFR significantly improved the contralateral limb ROM (Pre vs. Post: 68.3 ± 21.0 vs. 73.2 ± 23.2 degrees, p < 0.001; d = 0.22). No change was found for the contralateral isometric strength or the maximal EMG amplitude. For the RFD parameters, the percent changes of the RFDs for the first 50, 100, and 200 ms of the maximal explosive isometric contraction were −31.2%, −16.8%, and −10.1%, respectively, following the unilateral SAFR, relative to the control condition. In addition, the decrement of the first 50-ms RFD reached statistical significance (p = 0.007; Cohen’s d = 0.44). Conclusion Ten sets of 30-second unilateral hamstring SAFR improved the ROM of the non-intervened contralateral limb, but decreased its ability to generate force, especially during the early phase (e.g., 50 ms) of the maximal explosive contraction.

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Comparison of Predictive Models in Classification of Nutritional Status among Arsenic Affected People in Rural Areas in Bangladesh: An Artificial Neural Network (ANN) and Logistic Regression Approach

Journal of Shaheed Suhrawardy Medical College ◽

10.3329/jssmc.v6i2.31773 ◽

2017 ◽

Vol 6 (2) ◽

pp. 71-75

Author(s):

Azizur Rahman ◽

Mariam Akter ◽

Ajit Kumar Majumder ◽

Md Atiqul Islam ◽

AFM Arshedi Sattar

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Logistic Regression ◽

Clinical Data ◽

Predictive Models ◽

Rural Areas ◽

Binary Logistic Regression ◽

Binary Outcome ◽

Artificial Neural

Background: Clinical data play an important role in medical sector for binary outcome variables. Various methods can be applied to build predictive models for the clinical data with binary outcome variables.Objective: This research was aimed to explore and compare the process of constructing common predictive models.Methodology: Models based on an artificial neural network (the connectionist approach) and binary logistic regressions were compared in their ability to classifying malnourished subjects and those with over-weighted participants in rural areas of Bangladesh. Subjects were classified according to the indicator of nutritional status measured by body mass index (BMI). This study also investigated the effects of different factors on the BMI level of adults of six Villages in Bangladesh. Demographic, anthropometric and clinical data were collected based on aged over 30 years from six Villages in Bangladesh that were identified as mainly dependent on wells contaminated with arsenic.Result: A total of 460 participants were recruited for this study. Out of 460(140 male and 320 females) participants 186(40.44%) were identified as malnourished (BMK18.5 gm), and the remainder 274(59.56%) were found as over-weighted (BMI>18.5 gm). Among other factors, arsenic exposures were found as significant risk factors for low body mass index (BMI) with a higher value of odds ratio. This study shows that, binary logistic regression correctly classified 72.85% of cases with malnourished in the training datasets, 76.08% in the testing datasets and 75.26% of all subjects. The sensitivities of the neural network architecture for the training and testing datasets and for all subjects were 84.28%, 84.78% and 81 .72% respectively, indicate better performance than binary logistic regression model.Conclusion: This study demonstrates a significant performance of artificial neural network than the binary logistic regression models in classification of malnourished participants from over-weighted ones.J Shaheed Suhrawardy Med Coll, 2014; 6(2):71-75

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On the Comparison of Deep Learning Neural Network and Binary Logistic Regression for Classifying the Acceptance Status of Bidikmisi Scholarship Applicants in East Java

MATEMATIKA ◽

10.11113/matematika.v34.n3.1141 ◽

2018 ◽

Vol 34 (3) ◽

pp. 83-90

Author(s):

Nita Cahyani ◽

Kartika Fithriasari ◽

Irhamah Irhamah ◽

Nur Iriawan

Keyword(s):

Neural Network ◽

Logistic Regression ◽

Deep Learning ◽

Binary Logistic Regression ◽

Training Data ◽

Regression Methods ◽

Logistic Regression Method ◽

Validation Procedure ◽

Deep Learning Neural Network

Neural Network and Binary Logistic Regression are modern and classical data mining analysis tools that can be used to classify data on Bidikmisi scholarship acceptance in East Java Province, Indonesia. One form of Neural Network model available for various applications is the Resilient Backpropagation Neural Network (Resilient BPNN). This study aims to compare the performance of the Resilient BPNN method as a Deep Learning Neural Network and Binary Logistic Regression method in determining the classification of Bidikmisi scholarship acceptance in East Java Province. After preprocessing data and dividing them into two parts, i.e. sets of testing and training data, with 10-foldcross-validation procedure, the Resilient BPNN and Binary Logistic Regression methods are implemented. The result shows that Resilient BPNN with two hidden layers is the best platformnetwork model. The classificationG-mean resulted by these both methods is that Resilient BPNN with two hidden layers is more representative with better performance than Binary Logistic Regression. The Resilient BPNN is recommended to be used topredict acceptance of Bidikmisi applicants yearly.

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816 The Effect Of COVID-19 And Service Delivery Changes On 30-Day Mortality in Fractured Neck of Femur Patients: A Case-Control Study

British Journal of Surgery ◽

10.1093/bjs/znab134.089 ◽

2021 ◽

Vol 108 (Supplement_2) ◽

Author(s):

A Winarski ◽

L Williams ◽

H Ingoe

Keyword(s):

Logistic Regression ◽

Service Delivery ◽

Case Control Study ◽

Statistical Significance ◽

Binary Logistic Regression ◽

Case Control ◽

Median Length ◽

Fractured Neck Of Femur ◽

Neck Of Femur ◽

Control Study

Abstract Introduction The majority of neck of femur (NOF) fractures occur within the home, therefore admissions were not expected to change during the COVID-19 pandemic(1) . This study investigates the effect of coronavirus and our department’s response on 30-day mortality for patients admitted with NOF fractures. Method Data from 65 fractured NOF admissions (22nd March - 24th May 2020) was compared with 62 patients from the same period in 2019. Binary logistic regression was used to explore 30-day mortality; accounting for differences in ASA, anaesthetic type, anticoagulation status, surgery type, age, time to surgery and year of admission. Results The odds of 30-day mortality was statistically significantly higher in patients who were suspected/confirmed COVID-19 positive (n = 10),(OR 2.39, 95%CI (1.60-74.13)). In COVID-19 negative patients (n = 55), the odds of 30-day mortality was lower in 2020, and approached statistical significance (0.232, 95%CI (0.053-1.02)), compared to the same period in 2019. Median length of stay (LOS) in patients who survived was 11 days in 2020 and 15.5 days in 2019 (p = 0.003). Conclusions The results suggest that a COVID-19 diagnosis significantly increases the 30-day mortality in patients with a fractured NOF. The changes implemented in service delivery have shortened LOS and appeared to improve 30-day mortality for those without COVID-19.

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Outer Nuclear Layer as the Main Predictor to Anatomic Response to Half Dose Photodynamic Therapy in Chronic Central Serous Retinopathy

Journal of Ophthalmology ◽

10.1155/2019/5859063 ◽

2019 ◽

Vol 2019 ◽

pp. 1-6 ◽

Cited By ~ 1

Author(s):

Keissy Sousa ◽

Ana Rita Viana ◽

Joana Pires ◽

Carla Ferreira ◽

Lara Queirós ◽

...

Keyword(s):

Logistic Regression ◽

Photodynamic Therapy ◽

Regression Model ◽

Outer Nuclear Layer ◽

Statistical Significance ◽

Subretinal Fluid ◽

Binary Logistic Regression ◽

Central Serous Retinopathy ◽

Half Dose ◽

Interdigitation Zone

Purpose. To evaluate the predictors for subretinal fluid resorption in patients with chronic central serous retinopathy (cCSR) submitted to half-dose photodynamic therapy (HD-PDT). Methods. Observational, longitudinal, and retrospective study of patients with cCSR submitted to HD-PDT in a tertiary ophthalmology department in Portugal between January 2015 and February 2018. Best-corrected visual acuity (BCVA) and SD-OCT at baseline and 12 ± 3 months after treatment were performed. The central macular thickness (CMT), outer nuclear layer (ONL) thickness, integrity of the external limiting membrane (ELM), ellipsoid (EZ) and interdigitation zone (IZ), subretinal fluid (SFR) height, and choroidal thickness (CT) were evaluated. Patients were classified into responders and nonresponders based on SRF resorption. Results. Sixty-one eyes of 42 patients were included; 75.4% were classified as responders. Final BCVA was significantly better in responders (p=0.002). The baseline ONL was thicker (p<0.01) and intact ELM (67.2% vs. 16.4%), EZ (49.2% vs. 8.2%), and IZ (31.2% vs. 1.6%) were more prevalent in responders than in nonresponders. Anatomic response was correlated with a thicker ONL (rs (59) = 0.416, p=0.001∗), intact ELM (rs (59) = 0.261, p=0.04∗), EZ (rs (59) = 0.278, p=0.03∗), and IZ (rs (59) = 0.318, p=0.01∗). Binary logistic regression showed that a thicker ONL thickness increased the chance of an anatomic response to HD-PDT. The other evaluated retinal layers did not have statistical significance in the binary regression model. Conclusions. cCSR responders to HD-PDT have a better final BCVA, a thicker baseline ONL, and an intact baseline ELM, EZ, and IZ. However, ONL was the only predictor in a logistic regression model for SRF resorption.

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Does the Presence of a Physical Disability Affect Classification of Sexual Assault?

Journal of Interpersonal Violence ◽

10.1177/0886260521997951 ◽

2021 ◽

pp. 088626052199795

Author(s):

Alec Dalton ◽

Dayna Henry ◽

Sarah Blackstone ◽

Julia Passuth ◽

Haley Birchfield ◽

...

Keyword(s):

Sexual Assault ◽

Physical Disability ◽

Online Survey ◽

Statistical Significance ◽

Binary Logistic Regression ◽

Binary Logistic Regression Model ◽

Clear Trend ◽

Disability Status ◽

The Impact

The occurrence of sexual assault is common and problematic, especially among those with disabilities. While many other characteristics of the victim, perpetrator, and situation involving a sexual assault have been shown to affect perceptions, only one study has examined the impact of a hypothetical victim with a physical disability. Therefore, the purpose of this study was to explore the effect that a victim and/or perpetrator’s physical disability status has on individuals’ classification of encounters as sexual assault. University students over the age of 18 ( n = 207) completed an anonymous online survey which included reading an ambiguous scenario involving a sexual assault in which either the victim, perpetrator or neither was in a wheelchair. Participants classified the scenario as either representing a sexual assault or not and completed the Illinois Rape Myth Acceptance scale and demographic information. A binary logistic regression model was conducted to examine the effects of conditions, participant gender and RMA score on sexual assault classification. In the scenario with the victim in a wheelchair, 71.6% of participants agreed sexual assault occurred; when the perpetrator was in a wheelchair 58.6% classified the scenario as sexual assault. In the control condition 61.4% agreed sexual assault occurred. Condition was not associated with classification at a statistically significant level; however, the effect sizes indicate participants were more likely to classify sexual assault when the victim was in a wheelchair (OR = 1.41), but less likely to blame a perpetrator in a wheelchair (OR = 0.69) compared to the control condition. Despite a lack of statistical significance, the data show a clear trend away from blaming individuals with disabilities in sexual assault scenarios. These findings can have implications within the legal system where incorrect decisions may be made due to bias based on disability status.

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Effect of COVID-19 Vaccination on Seizures in Patients With Epilepsy: a Multicenter, Retrospective Study

10.21203/rs.3.rs-965045/v1 ◽

2021 ◽

Author(s):

Xiqin Fang ◽

Shan Qiao ◽

Ranran Zhang ◽

Tingting Yang ◽

Zhihao Wang ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Statistical Significance ◽

Univariate Analysis ◽

Binary Logistic Regression ◽

P Value ◽

Binary Logistic Regression Analysis ◽

Patients With Epilepsy ◽

Vaccination Period

Abstract Background: Previous study have shown that seizures may occur as a result of vaccination. This study aimed to evaluate the risk and correlative factors of seizures in patients with epilepsy (PWE) after being vaccinated with COVID-19 and to provide reference opinions for PWE to receive COVID-19 vaccine.Methods: We retrospectively enrolled PWE patients who were vaccinated against COVID-19 in the epilepsy centers of nine hospitals in China. The binary logistic regression analysis included variables with a P-value less than 0.1 in the univariate analysis.Results: The study included 290 patients, of which 40 (13.8%) developed seizures within 14 days after vaccination, whereas 250 (86.2%) remained seizure-free. The binary logistic regression analysis revealed statistical significance in seizures within three months before vaccination (P<0.001, OR=10.121, 95% CI: 4.301-23.816) and withdrawal or reduction of anti-seizures medications (ASM) during the peri-vaccination period (P=0.027, OR=4.452, 95% CI: 1.182-16.768). In addition, 32 of 33 patients (97.0%) who were seizure-free within three months before vaccination and had normal EEG results before vaccination did not have any seizures within 14 days following vaccination.Conclusions: SARS-CoV-2 may induce epilepsy through an inflammatory cascade. It is recommended to provide the COVID-19 vaccine to seizure-free patients for at least three months before vaccination, and the vaccination is safer if EEG result is normal. During peri-vaccination period, all PWE should be prohibited from reducing ASM dosage. PWE with well-controlled seizures who have discontinued ASM might consider resuming ASM during the peri-vaccination period if their EEG results are aberrant.

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