scholarly journals Validation of the Donkey Pain Scale (DOPS) for Assessing Postoperative Pain in Donkeys

2021 ◽  
Vol 8 ◽  
Author(s):  
Maria Gláucia Carlos de Oliveira ◽  
Valéria Veras de Paula ◽  
Andressa Nunes Mouta ◽  
Isabelle de Oliveira Lima ◽  
Luã Barbalho de Macêdo ◽  
...  
Keyword(s):  
Internal Consistency ◽  
Acute Pain ◽  
Area Under The Curve ◽  
Principal Component ◽  
Criterion Validity ◽  
Youden Index ◽  
Operating Characteristics ◽  
Total Correlation ◽  
Intervention Point ◽  
Recovery From Anesthesia

This study aimed to validate a scale for assessing acute pain in donkeys. Forty-four adult donkeys underwent castration after sedation with intravenous (IV) xylazine, induction with guaifenesin and thiopental IV, local anesthetic block, and maintenance with isoflurane. The scale was constructed from a pilot study with four animals combined with algetic behaviors described for equines. After content validation, the scale was evaluated in 40 other donkeys by three blinded and one reference evaluator, by means of edited videos referring to the preoperative and postoperative periods: before anesthesia, 3–4 h after recovery from anesthesia, 5–6 h after recovery from anesthesia (2 h after analgesia with flunixin—1.1 mg/kg, dipyrone—10 mg/kg, and morphine—0.2 mg/kg) IV, and 24 h after recovery. Content validity, sensitivity, specificity, and responsiveness of behaviors were investigated to refine the scale. Intra- and inter-evaluator reliabilities were investigated by the weighted kappa coefficient, criterion validity by comparing the scale with the visual analog scale (VAS), internal consistency by Cronbach's α coefficient, item-total correlation by the Spearman coefficient, and intervention point for rescue analgesic by the receiver operating characteristics curve and Youden index. The scale showed very good intra-evaluator reliability (0.88–0.96), good to moderate (0.56–0.66) inter-evaluator reliability, responsiveness for all items, good criterion validity vs. VAS (0.75), acceptable internal consistency (0.64), adequate item-total correlation, except for head position and direction, and according to the principal component analysis, good association among items. The accuracy of the point for rescue analgesic was excellent (area under the curve = 0.91). The rescue analgesic score was ≥ 4 of 11 points. The scale can diagnose and quantify acute pain in donkeys submitted to castration, as the instrument is reliable and valid, with a defined intervention analgesic score.

scholarly journals A critical evaluation for validation of composite and unidimensional postoperative pain scales in horses

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255618
Author(s):  
Paula Barreto da Rocha ◽  
Bernd Driessen ◽  
Sue M. McDonnell ◽  
Klaus Hopster ◽  
Laura Zarucco ◽  
...  
Keyword(s):  
Postoperative Pain ◽  
Internal Consistency ◽  
Video Clip ◽  
Critical Evaluation ◽  
Reliability And Validity ◽  
Principal Component ◽  
Random Order ◽  
Criterion Validity ◽  
Pain Scale ◽  
Rescue Analgesia

Proper pain therapy requires adequate pain assessment. This study evaluated the reliability and validity of the Unesp-Botucatu horse acute pain scale (UHAPS), the Orthopedic Composite Pain Scale (CPS) and unidimensional scales in horses admitted for orthopedic and soft tissue surgery. Forty-two horses were assessed and videotaped before surgery, up to 4 hours postoperatively, up to 3 hours after analgesic treatment, and 24 hours postoperatively (168 video clips). After six evaluators viewing each edited video clip twice in random order at a 20-day interval, they chose whether analgesia would be indicated and applied the Simple Descriptive, Numeric and Visual Analog scales, CPS, and UHAPS. For all evaluators, intra-observer reliability of UHAPS and CPS ranged from 0.70 to 0.97. Reproducibility was variable among the evaluators and ranged from poor to very good for all scales. Principal component analysis showed a weak association among 50% and 62% of the UHAPS and CPS items, respectively. Criterion validity based on Spearman correlation among all scales was above 0.67. Internal consistency was minimally acceptable (0.51–0.64). Item-total correlation was acceptable (0.3–0.7) for 50% and 38% of UHAPS and CPS items, respectively. UHAPS and CPS were specific (90% and 79% respectively), but both were not sensitive (43 and 38%, respectively). Construct validity (responsiveness) was confirmed for all scales because pain scores increased after surgery. The cut-off point for rescue analgesia was ≥ 5 and ≥ 7 for the UHAPS and CPS, respectively. All scales presented adequate repeatability, criterion validity, and partial responsiveness. Both composite scales showed poor association among items, minimally acceptable internal consistency, and weak sensitivity, indicating that they are suboptimal instruments for assessing postoperative pain. Both composite scales require further refinement with the exclusion of redundant or needless items and reduction of their maximum score applied to each item or should be replaced by other tools.

Psychometric Assessment and Precision Remodeling of the Iowa Infant Feeding Attitude Scale to Improve Clinical Use and Efficacy Among Prenatal Women in Canada

2017 ◽  
Vol 34 (1) ◽  
pp. 20-29 ◽  
Author(s):  
Nouf M. AlKusayer ◽  
William K. Midodzi ◽  
Leigh Anne Newhook ◽  
Lorraine Burrage ◽  
Nicole Gill ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Infant Feeding ◽  
Internal Consistency ◽  
Newfoundland And Labrador ◽  
Area Under The Curve ◽  
Principal Component ◽  
Attitude Scale ◽  
Underlying Structure ◽  
Cross Sectional ◽  
Breastfeeding Intention

Background: The 17-item Iowa Infant Feeding Attitude Scale (IIFAS) has been widely used to assess maternal attitudes toward infant feeding and to predict breastfeeding intention. The IIFAS has been validated among prenatal women located in Newfoundland and Labrador in Canada, although its length may prove challenging to complete in a clinical setting. Research aim: The authors aimed to reduce the number of items from the original 17-item IIFAS scale while maintaining reliability and validity. Methods: A nonexperimental cross-sectional design was used among 1,283 women in their third trimester residing in Newfoundland and Labrador. Data were collected from August 2011 to June 2016. An exploratory factor analysis using principal component analysis was performed to explore the underlying structure of the IIFAS. The internal consistency of both the 17-item and reduced version was assessed using Cronbach’s alpha and item-total correlation. The area under the curve and linear regression model were used to assess predictive validity of intention to breastfeed. Results: Our findings revealed that a 13-item IIFAS (Cronbach’s α = .870) had relatively similar internal consistency to the original IIFAS (Cronbach’s α = .868). Three themes were extracted from the factor analysis, resulting in the removal of four items. The reduced scale demonstrated an excellent ability to predict breastfeeding intention (area under the curve = 0.914). Conclusion: The reduced 13-item version of the IIFAS is a psychometrically sound instrument that maintains its accuracy and validity when measuring maternal feeding attitudes during pregnancy and can be more time efficient in clinical settings compared with the 17-item IIFAS.

scholarly journals Thai version of the foot function index: a cross-cultural adaptation with reliability and validity evaluation

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Sunee Bovonsunthonchai ◽  
Suthasinee Thong-On ◽  
Roongtiwa Vachalathiti ◽  
Warinda Intiravoranont ◽  
Sarawut Suwannarat ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Correlation Coefficient ◽  
Internal Consistency ◽  
Reliability And Validity ◽  
Principal Component ◽  
Component Analysis ◽  
Criterion Validity ◽  
Retest Reliability ◽  
Foot Function ◽  
Test Retest Reliability

Abstract Background The study aimed to translate the foot function index (FFI) questionnaire to Thai and to determine psychometric properties of the questionnaire among individuals with plantar foot complaints. Methods The Thai version of the FFI (FFI-Th) was adapted according to a forward and backward translation protocol by two independent translators and analyzed by a linguist and a committee. The FFI-Th was administered among 49 individuals with plantar foot complaints to determine internal consistency, reliability, and validity. Cronbach’s alpha and the Intraclass Correlation Coefficient (ICC3,1) were used to test the internal consistency and test-retest reliability. The Principal Component Analysis with varimax rotation method was used to test the factor structure and construct validity. Furthermore, the criterion validity was tested using Pearson’s correlation coefficient (rp) between the FFI-Th and the visual analogue pain scale (pain-VAS) as well as the EuroQol five-dimensional questionnaire (EQ-5D-5L). Results The FFI-Th showed good to excellent internal consistency and test-retest reliability in the total score, pain, disability, and activity limitation subscales. The Principal Component Analysis produced 4 principal factors from the FFI-Th items. Criterion validity of the FFI-Th total score showed moderate to strong correlations with pain-VAS and EQ-5D-5L, and EQ-VAS scores. Conclusion The FFI-Th was a reliable and valid questionnaire to assess the foot function in a Thai population. Trial registration NCT03161314 (08/05/2017).

scholarly journals Fibrinogen–Albumin-Ratio is an independent predictor of thromboembolic complications in patients undergoing VA-ECMO

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sebastian Roth ◽  
Catrin Jansen ◽  
René M’Pembele ◽  
Alexandra Stroda ◽  
Udo Boeken ◽  
...  
Keyword(s):  
Cardiogenic Shock ◽  
Area Under The Curve ◽  
University Hospital ◽  
Youden Index ◽  
Thromboembolic Complications ◽  
Operating Characteristics ◽  
Albumin Ratio ◽  
Va Ecmo ◽  
The University ◽  
Ecmo Therapy

AbstractVeno-arterial extracorporeal membrane oxygenation (VA-ECMO) supports patients suffering from refractory cardiogenic shock. Thromboembolic complications (TeC) are common in VA-ECMO patients and are associated with increased morbidity and mortality. Valid markers to predict TeC in VA-ECMO patients are lacking. The present study investigated the predictive value of baseline Fibrinogen–Albumin-Ratio (FAR) for in-hospital TeC in patients undergoing VA-ECMO. This retrospective cohort study included patients who underwent VA-ECMO therapy due to cardiogenic shock at the University Hospital Duesseldorf, Germany between 2011 and 2018. Main exposure was baseline FAR measured at initiation of VA-ECMO therapy. The primary endpoint was the in-hospital incidence of TeC. In total, 344 patients were included into analysis (74.7% male, mean age 59 ± 14 years). The in-hospital incidence of TeC was 34%. Receiver operating characteristics (ROC) curve of FAR for in-hospital TeC revealed an area under the curve of 0.67 [95% confidence interval (CI) 0.61–0.74]. Youden index determined a cutoff of 130 for baseline FAR. Multivariate logistic regression revealed an adjusted odds-ratio of 3.72 [95% CI 2.26–6.14] for the association between FAR and TeC. Baseline FAR is independently associated with in-hospital TeC in patients undergoing VA-ECMO. Thus, FAR might contribute to the prediction of TeC in this cohort.

Depressions-Screening bei pädiatrischen Patienten

2012 ◽  
Vol 40 (3) ◽  
pp. 161-169 ◽  
Author(s):  
Barbara Frühe ◽  
Antje-Kathrin Allgaier ◽  
Kathrin Pietsch ◽  
Gerd Schulte-Körne
Keyword(s):  
Kinder Und Jugendliche ◽  
Area Under The Curve ◽  
Receiver Operating Characteristics ◽  
Youden Index ◽  
Operating Characteristics ◽  
Children’S Depression ◽  
Icd 10 ◽  
Receiver Operating

Fragestellung: Für das Screening depressiver Störungen im pädiatrischen Kontext wurde die konkurrente Validität des Depressionsinventars für Kinder und Jugendliche (DIKJ), der Skala Dysphorie aus dem Depressionstest für Kinder (DTK) und des Children’s Depression Screeners (ChilD-S) in Bezug auf ICD-10-Depressionsdiagnosen bei somatisch erkrankten Kindern verglichen. Methodik: Die Daten von 9- bis 12-jährigen pädiatrischen Patienten (N = 228) wurden mittels Receiver Operating Characteristics analysiert. Die daraus ableitbaren Kennwerte wie Area Under the Curve (AUC), Sensitivität (SE) und Spezifität (SP) wurden für jedes Instrument berechnet und miteinander verglichen. Als Goldstandard dienten Depressionsdiagnosen nach ICD-10, erhoben anhand des klinischen Interviews Kinder-DIPS. Ergebnisse: Die konkurrente Validität des 26 Items umfassenden DIKJ war sehr hoch (AUC = 92.6 %), der 25 Items umfassenden Skala Dysphorie zufriedenstellend (AUC = 86.2 %) und des 8 Items umfassenden ChilD-S hervorragend (AUC = 97.5 %); der ChilD-S war dem DIKJ signifikant überlegen. Nach dem Youden-Index sind folgende Cut-Off-Werte zu empfehlen: DIKJ ≥ 12 (SE = 91.7 %, SP = 81.9 %), Skala Dysphorie ≥ 10 (SE = 75.0 %, SP = 89.8 %) und ChilD-S ≥ 10 (SE ≥ 100 %, SP = 86.6 %). Schlussfolgerungen: Sowohl das DIKJ als auch der ChilD-S zeigte eine ausgezeichnete konkurrente Validität für das Screening depressiver Störungen bei pädiatrischen Patienten. Im Vergleich dazu erreichte die Skala Dysphorie etwas niedrigere Validitätsmaße. Für die Implementierung im zeitbegrenzten pädiatrischen Versorgungsalltag ist das ökonomische Verfahren ChilD-S zu favorisieren.

scholarly journals Lithology Discrimination Using Sentinel-1 Dual-Pol Data and SRTM Data

2021 ◽  
Vol 13 (7) ◽  
pp. 1280
Author(s):  
Yi Lu ◽  
Changbao Yang ◽  
Zhiguo Meng
Keyword(s):  
Area Under The Curve ◽  
Remote Sensing Data ◽  
Predictive Ability ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Optical Remote Sensing ◽  
Operating Characteristics ◽  
Auc Value ◽  
Confusion Matrices

Compared to various optical remote sensing data, studies on the performance of dual-pol Synthetic aperture radar (SAR) on lithology discrimination are scarce. This study aimed at using Sentinel-1 data to distinguish dolomite, andesite, limestone, sandstone, and granite rock types. The backscatter coefficients VV and VH, the ratio VV–VH; the decomposition parameters Entropy, Anisotropy, and Alpha were firstly derived and the Kruskal–Wallis rank sum test was then applied to these polarimetric derived matrices to assess the significance of statistical differences among different rocks. Further, the corresponding gray-level co-occurrence matrices (GLCM) features were calculated. To reduce the redundancy and data dimension, the principal component analysis (PCA) was carried out on the GLCM features. Due to the limited rock samples, before the lithology discrimination, the input variables were selected. Several classifiers were then used for lithology discrimination. The discrimination models were evaluated by overall accuracy, confusion matrices, and the area under the curve-receiver operating characteristics (AUC-ROC). Results show that (1) the statistical differences of the polarimetric derived matrices (backscatter coefficients, ratio, and decomposition parameters) among different rocks was insignificant; (2) texture information derived from Sentinel-1 had great potential for lithology discrimination; (3) partial least square discrimination analysis (PLSDA) had the highest overall accuracy (0.444) among the classification models; (4) though the overall accuracy is unsatisfactory, according to the AUC-ROC and confusion matrices, the predictive ability of PLSDA model for limestone is high with an AUC value of 0.8017, followed by dolomite with an AUC value of 0.7204. From the results, we suggest that the dual-pol Sentinel-1 data are able to correctly distinguish specific rocks and has the potential to capture the variation of different rocks.

scholarly journals Validation of perinatal post-traumatic stress disorder questionnaire for Spanish women during the postpartum period

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Antonio Hernández-Martínez ◽  
Sergio Martínez-Vázquez ◽  
Julian Rodríguez-Almagro ◽  
Khalid Saeed Khan ◽  
Miguel Delgado-Rodríguez ◽  
...  
Keyword(s):  
Psychometric Properties ◽  
Internal Consistency ◽  
Post Traumatic Stress Disorder ◽  
Traumatic Stress ◽  
Postnatal Depression ◽  
Stress Disorder ◽  
Criterion Validity ◽  
Post Traumatic Stress ◽  
Spanish Women ◽  
Post Traumatic

AbstractTo determine the psychometric properties of the Perinatal Post-Traumatic Stress Disorder (PTSD) Questionnaire (PPQ) in Spanish. A cross-sectional study of 432 Spanish puerperal women was conducted, following ethical approval. The PPQ was administered online through midwives' associations across Spain. The Edinburgh Postnatal Depression Scale was used to diagnose postnatal depression for examining criterion validity. Data were collected on sociodemographic, obstetric, and neonatal variables. An exploratory factorial analysis (EFA) was performed with convergence and criterion validation. Internal consistency was evaluated using Cronbach's α. The EFA identified three components that explained 63.3% of variance. The PPQ's convergence validation associated the risk of PTSD with variables including birth plan, type of birth, hospital length of stay, hospital readmission, admission of the newborn to care unit, skin-to-skin contact, maternal feeding at discharge, maternal perception of partner support, and respect shown by healthcare professionals during childbirth and puerperium. The area under the ROC curve for the risk of postnatal depression (criterion validity) was 0.86 (95% CI 0.82–0.91). Internal consistency with Cronbach's α value was 0.896. The PPQ used when screening for PTSD in postpartum Spanish women showed adequate psychometric properties.

scholarly journals End-to-end convolutional neural network enables COVID-19 detection from breath and cough audio: a pilot study

2021 ◽  
Vol 7 (2) ◽  
pp. 356-362
Author(s):  
Harry Coppock ◽  
Alex Gaskell ◽  
Panagiotis Tzirakis ◽  
Alice Baird ◽  
Lyn Jones ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Low Cost ◽  
Area Under The Curve ◽  
Alternative Form ◽  
Economic Damage ◽  
Audio Signals ◽  
Operating Characteristics ◽  
Data Set ◽  
Empirical Performance

BackgroundSince the emergence of COVID-19 in December 2019, multidisciplinary research teams have wrestled with how best to control the pandemic in light of its considerable physical, psychological and economic damage. Mass testing has been advocated as a potential remedy; however, mass testing using physical tests is a costly and hard-to-scale solution.MethodsThis study demonstrates the feasibility of an alternative form of COVID-19 detection, harnessing digital technology through the use of audio biomarkers and deep learning. Specifically, we show that a deep neural network based model can be trained to detect symptomatic and asymptomatic COVID-19 cases using breath and cough audio recordings.ResultsOur model, a custom convolutional neural network, demonstrates strong empirical performance on a data set consisting of 355 crowdsourced participants, achieving an area under the curve of the receiver operating characteristics of 0.846 on the task of COVID-19 classification.ConclusionThis study offers a proof of concept for diagnosing COVID-19 using cough and breath audio signals and motivates a comprehensive follow-up research study on a wider data sample, given the evident advantages of a low-cost, highly scalable digital COVID-19 diagnostic tool.

scholarly journals Multi-scale characterizations of colon polyps via computed tomographic colonography

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Weiguo Cao ◽  
Marc J. Pomeroy ◽  
Yongfeng Gao ◽  
Matthew A. Barish ◽  
Almas F. Abbasi ◽  
...  
Keyword(s):  
Area Under The Curve ◽  
Texture Features ◽  
Learning Model ◽  
Colon Polyps ◽  
Texture Descriptor ◽  
Operating Characteristics ◽  
Computed Tomographic ◽  
Multi Scale ◽  
Definition Of ◽  
Occurrence Matrix

AbstractTexture features have played an essential role in the field of medical imaging for computer-aided diagnosis. The gray-level co-occurrence matrix (GLCM)-based texture descriptor has emerged to become one of the most successful feature sets for these applications. This study aims to increase the potential of these features by introducing multi-scale analysis into the construction of GLCM texture descriptor. In this study, we first introduce a new parameter - stride, to explore the definition of GLCM. Then we propose three multi-scaling GLCM models according to its three parameters, (1) learning model by multiple displacements, (2) learning model by multiple strides (LMS), and (3) learning model by multiple angles. These models increase the texture information by introducing more texture patterns and mitigate direction sparsity and dense sampling problems presented in the traditional Haralick model. To further analyze the three parameters, we test the three models by performing classification on a dataset of 63 large polyp masses obtained from computed tomography colonoscopy consisting of 32 adenocarcinomas and 31 benign adenomas. Finally, the proposed methods are compared to several typical GLCM-texture descriptors and one deep learning model. LMS obtains the highest performance and enhances the prediction power to 0.9450 with standard deviation 0.0285 by area under the curve of receiver operating characteristics score which is a significant improvement.

scholarly journals Diagnostic work up of anemic patients: role of iron deficiency

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Daniela Meiser ◽  
Lale Kayikci ◽  
Matthias Orth
Keyword(s):  
Iron Deficiency ◽  
Complete Blood Count ◽  
Iron Status ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Diagnostic Tools ◽  
Operating Characteristics ◽  
Inflammatory Conditions ◽  
Reliable Parameter ◽  
Work Up

AbstractObjectivesDiagnosing disturbances in iron metabolism can be challenging when accompanied by inflammation. New diagnostic tools such as the “Thomas-plot” (TP) (relation of soluble transferrin receptor [sTfR]/log ferritin to reticulocyte hemoglobin content [RET-He]) were established to improve classification of anemias. Aim of this retrospective study was to assess the added diagnostic value of the TP in anemia work up.MethodsPatients from December 2016 to September 2018 with a complete blood count, iron status, RET-He and sTfR were manually classified into the four quadrants of the TP on basis of conventional iron markers. Manual and algorithm-based classifications were compared using cross tabulations, Box–Whisker-Plots as well as Receiver-Operating-Characteristics (ROC) to calculate the diagnostic accuracy using Area under the Curve (AUC) analysis.ResultsA total of 3,745 patients with a conventional iron status, including 1,721 TPs, could be evaluated. In 70% of the cases the manual classification was identical to the TP, in 10% it was deviant. 20% could not clearly be classified, mostly due to inflammatory conditions. In the absence of an inflammatory condition, ferritin was a reliable parameter to define iron deficiency (ID) (AUC 0.958). In the presence of inflammation, the significance of the ferritin index (AUC 0.917) and of the RET-He (AUC 0.957) increased.ConclusionsThe TP can be useful for narrowing down the causes of anemia in complex cases. Further studies with focus on special patient groups, e.g., oncological or rheumatic patients, are desirable.

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