scholarly journals Multifactorial assessment of measurement errors affecting intraoral quantitative sensory testing reliability

2017 ◽  
Vol 16 (1) ◽  
pp. 93-98 ◽  
Author(s):  
Estephan J. Moana-Filho ◽  
Aurelio A. Alonso ◽  
Flavia P. Kapos ◽  
Vladimir Leon-Salazar ◽  
Scott H. Durand ◽  
...  
Keyword(s):  
Measurement Error ◽  
Measurement Errors ◽  
Quantitative Sensory Testing ◽  
Linear Models ◽  
Intraclass Correlation ◽  
Sensory Testing ◽  
Multiple Sources ◽  
Cold Pain ◽  
Sources Of Error ◽  
Wide Range

AbstractBackground and purpose (aims)Measurement error of intraoral quantitative sensory testing (QST) has been assessed using traditional methods for reliability, such as intraclass correlation coefficients (ICCs). Most studies reporting QST reliability focused on assessingone source of measurement error at a time, e.g., inter- or intra-examiner (test–retest) reliabilities and employed two examiners to test inter-examiner reliability. The present study used a complex design with multiple examiners with the aim of assessing the reliability of intraoral QST taking account of multiple sources of error simultaneously.MethodsFour examiners of varied experience assessed 12 healthy participants in two visits separated by 48 h. Seven QST procedures to determine sensory thresholds were used: cold detection (CDT), warmth detection (WDT), cold pain (CPT), heat pain (HPT), mechanical detection (MDT), mechanical pain (MPT) and pressure pain (PPT). Mixed linear models were used to estimate variance components for reliability assessment; dependability coefficients were used to simulate alternative test scenarios.ResultsMost intraoral QST variability arose from differences between participants (8.8–30.5%), differences between visits within participant (4.6–52.8%), and error (13.3–28.3%). For QST procedures other than CDT and MDT, increasing the number of visits with a single examiner performing the procedures would lead to improved dependability (dependability coefficient ranges: single visit, four examiners = 0.12–0.54; four visits, single examiner = 0.27–0.68). A wide range of reliabilities for QST procedures, as measured by ICCs, was noted for inter- (0.39–0.80) and intra-examiner (0.10–0.62) variation.ConclusionReliability of sensory testing can be better assessed by measuring multiple sources of error simultaneously instead of focusing on one source at a time. In experimental settings, large numbers of participants are needed to obtain accurate estimates of treatment effects based on QST measurements. This is different from clinical use, where variation between persons (the person main effect) is not a concern because clinical measurements are done on a single person.ImplicationsFuture studies assessing sensorytestingreliabilityinboth clinicaland experimental settings would benefit from routinely measuring multiple sources of error. The methods and results of this study can be used by clinical researchers to improve assessment of measurement error related to intraoral sensorytesting. This should lead to improved resource allocation when designing studies that use intraoral quantitative sensory testing in clinical and experimental settings.© 2017 Scandinavian Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

scholarly journals Estimating Measurement Errors and Score Dependability of NECO 2019 Mathematics Examination

2021 ◽  
Vol 2 (3) ◽  
pp. 50-55
Author(s):  
James Uzomba Okeaba ◽  
Nkechi Patricia-Mary Esomonu
Keyword(s):  
Measurement Error ◽  
Measurement Errors ◽  
Rank Order ◽  
Generalizability Theory ◽  
Simple Random Sampling ◽  
Error Variance ◽  
Multiple Sources ◽  
Sources Of Error ◽  
Mathematics Examination ◽  
Research Questions

This study estimated measurement error and score dependability in examinations using the Generalizability Theory. Scores obtained by the students (object of measurements) in examinations are affected by multiple sources of error (facets), and these scores are used in taking relative and absolute decisions about the students. There is, therefore, needed to estimate measurement error and score dependability to find the extent of the contributions of the facets to error in examination scores. Three research questions and one hypothesis were used to guide the study. The study population comprised 5,085 SS3 students of the 34 Government-owned senior secondary schools in Yenagoa LGA of Bayelsa State 2019/2020 academic session. 10 schools were selected using simple random sampling technic and the 1,525 SS3 students of the selected schools formed the sample. section A of the 2018 NECO Mathematics main paper and 2018 NECO Mathematics Marking Scheme were used to collect the data. EduG version 6.0-e based on ANOVA and Generalizability theory was used to answer the three research questions. A 95% confidence interval was computed using the standard error variance components to test the hypothesis. The findings of the study revealed that some hidden sources of error were at play in the study. the students’ facets (σ2S) made the highest contribution to measurement error in examination scores followed by the residual (σ2SIM). Also, the Students’ facet was significantly different (p< 0.05) in its contributions to measurement error, while the other facets and their interactions were not significantly different in their contribution to measurement error. Hence, Ho1 was not accepted for the students’ facet but accepted for other facets. An increase in the level of markers from 1 to 4 with level of items 5 yielded an outcome of 0.84 to 0.91 respectively, a generalizability coefficient of 0.94 high enough to rank order students according to their relative abilities in examinations was obtained when the level of markers was at 2 with an increment in level of items to 10. An index of dependability of 0.93 that is high enough to maximize reliability was obtained when we have level of markers at 2 and the items at 10.

scholarly journals Comparison and evaluation of statistical error models for scRNA-seq

2021 ◽  
Author(s):  
Saket Choudhary ◽  
Rahul Satija
Keyword(s):  
Linear Models ◽  
Negative Binomial ◽  
Statistical Error ◽  
Rna Seq ◽  
Multiple Sources ◽  
Error Models ◽  
Wide Range ◽  
Data Driven Approach ◽  
Downstream Analysis ◽  
Experimental Processing

Heterogeneity in single-cell RNA-seq (scRNA-seq) data is driven by multiple sources, including biological variation in cellular state as well as technical variation introduced during experimental processing. Deconvolving these effects is a key challenge for preprocessing workflows. Recent work has demonstrated the importance and utility of count models for scRNA-seq analysis, but there is a lack of consensus on which statistical distributions and parameter settings are appropriate. Here, we analyze 58 scRNA-seq datasets that span a wide range of technologies, systems, and sequencing depths in order to evaluate the performance of different error models. We find that while a Poisson error model appears appropriate for sparse datasets, we observe clear evidence of overdispersion for genes with sufficient sequencing depth in all biological systems, necessitating the use of a negative binomial model. Moreover, we find that the degree of overdispersion varies widely across datasets, systems, and gene abundances, and argues for a data-driven approach for parameter estimation. Based on these analyses, we provide a set of recommendations for modeling variation in scRNA-seq data, particularly when using generalized linear models or likelihood-based approaches for preprocessing and downstream analysis.

Electromagnetic and thermal parameter identification method for best prediction of temperature distribution on transformer tank covers

2015 ◽  
Vol 34 (2) ◽  
pp. 485-495 ◽  
Author(s):  
Patricia Penabad Durán ◽  
Paolo Di Barba ◽  
Xose Lopez-Fernandez ◽  
Janusz Turowski
Keyword(s):  
Temperature Distribution ◽  
Measurement Error ◽  
Parameter Identification ◽  
Objective Function ◽  
Measurement Errors ◽  
Optimization Algorithms ◽  
Identification Problem ◽  
Content Type ◽  
Identification Method ◽  
Wide Range

Purpose – The purpose of this paper is to describe a parameter identification method based on multiobjective (MO) deterministic and non-deterministic optimization algorithms to compute the temperature distribution on transformer tank covers. Design/methodology/approach – The strategy for implementing the parameter identification process consists of three main steps. The first step is to define the most appropriate objective function and the identification problem is solved for the chosen parameters using single-objective (SO) optimization algorithms. Then sensitivity to measurement error of the computational model is assessed and finally it is included as an additional objective function, making the identification problem a MO one. Findings – Computations with identified/optimal parameters yield accurate results for a wide range of current values and different conductor arrangements. From the numerical solution of the temperature field, decisions on dimensions and materials can be taken to avoid overheating on transformer covers. Research limitations/implications – The accuracy of the model depends on its parameters, such as heat exchange coefficients and material properties, which are difficult to determine from formulae or from the literature. Thus the goal of the presented technique is to achieve the best possible agreement between measured and numerically calculated temperature values. Originality/value – Differing from previous works found in the literature, sensitivity to measurement error is considered in the parameter identification technique as an additional objective function. Thus, solutions less sensitive to measurement errors at the expenses of a degradation in accuracy are identified by means of MO optimization algorithms.

scholarly journals Quantitative sensory testing predicts histological small fiber neuropathy in postural tachycardia syndrome

2019 ◽  
Vol 10 (5) ◽  
pp. 428-434
Author(s):  
Sophia C.I. Billig ◽  
Joana C. Schauermann ◽  
Roman Rolke ◽  
Istvan Katona ◽  
Jörg B. Schulz ◽  
...  
Keyword(s):  
Skin Biopsy ◽  
Quantitative Sensory Testing ◽  
Pain Threshold ◽  
Detection Threshold ◽  
Small Fiber Neuropathy ◽  
Sensory Testing ◽  
Cold Pain ◽  
Noninvasive Test ◽  
Small Fiber ◽  
Heat Pain Threshold

BackgroundRetrospective investigation of the somatosensory profile and prediction of histologic small fiber neuropathy (SFN) in postural orthostatic tachycardia syndrome (POTS) was performed using quantitative sensory testing (QST) as a standardized noninvasive test.MethodsIn this investigation, full data sets from 30 patients (age: 34.03 ± 10.82 years, n = 6 males), including results of autonomic function testing, norepinephrine values, skin biopsy, and QST, were retrospectively analyzed. The QST data were compared with healthy controls (HCs) (age: 34.20 ± 10.5 years, n = 6 males, t test: 0.95).ResultsThe evaluation of all QST parameters in POTS compared with HCs yielded differences in all thermal parameters (cold detection threshold: p < 0.05, warm detection threshold: p < 0.001, thermal sensory limen: p < 0.001, cold pain threshold: p < 0.05, and heat pain threshold: p < 0.001) and in paradoxical heat sensations (p < 0.05). Differences in nonpainful stimuli (mechanical detection threshold: p < 0.05 and vibration detection threshold: p < 0.001) were also detected. All patients who had clinical signs of SFN in combination with impairment of small fibers in QST also had SFN on skin biopsy.ConclusionThese results suggest that a non–region-specific SFN in POTS compared with controls can be detected by noninvasive QST that predicts histologic small fiber pathology.

Quantitation of measurement error with Optimal Segments: basis for adaptive time course smoothing

1993 ◽  
Vol 264 (6) ◽  
pp. E902-E911 ◽  
Author(s):  
D. C. Bradley ◽  
G. M. Steil ◽  
R. N. Bergman
Keyword(s):  
Measurement Error ◽  
Measurement Errors ◽  
Time Course ◽  
Smooth Curve ◽  
Random Group ◽  
Smooth Curves ◽  
Original Curve ◽  
Wide Range ◽  
Data Points ◽  
Time Courses

We introduce a novel technique for estimating measurement error in time courses and other continuous curves. This error estimate is used to reconstruct the original (error-free) curve. The measurement error of the data is initially assumed, and the data are smoothed with "Optimal Segments" such that the smooth curve misses the data points by an average amount consistent with the assumed measurement error. Thus the differences between the smooth curve and the data points (the residuals) are tentatively assumed to represent the measurement error. This assumption is checked by testing the residuals for randomness. If the residuals are nonrandom, it is concluded that they do not resemble measurement error, and a new measurement error is assumed. This process continues reiteratively until a satisfactory (i.e., random) group of residuals is obtained. In this case the corresponding smooth curve is taken to represent the original curve. Monte Carlo simulations of selected typical situations demonstrated that this new method ("OOPSEG") estimates measurement error accurately and consistently in 30- and 15-point time courses (r = 0.91 and 0.78, respectively). Moreover, smooth curves calculated by OOPSEG were shown to accurately recreate (predict) original, error-free curves for a wide range of measurement errors (2-20%). We suggest that the ability to calculate measurement error and reconstruct the error-free shape of data curves has wide applicability in data analysis and experimental design.

scholarly journals Thermal Quantitative Sensory Testing in Fibromyalgia Patients / Termāla Kvantitatīva Sensora Testēšana Fibromialģijas Pacientiem

2015 ◽  
Vol 69 (5) ◽  
pp. 215-222
Author(s):  
Marija Mihailova ◽  
Ināra Logina ◽  
Santa Rasa ◽  
Svetlana Čapenko ◽  
Modra Murovska ◽  
...  
Keyword(s):  
Quantitative Sensory Testing ◽  
Pain Threshold ◽  
Fibromyalgia Impact Questionnaire ◽  
Sensory System ◽  
Thermal Stimulus ◽  
Thermal Perception ◽  
Sensory Testing ◽  
Inhibitory System ◽  
Cold Pain ◽  
Heat Pain Threshold

AbstractFibromyalgia (FM) is a chronic disorder manifested by diffuse musculoskeletal pain, fatigue, sleep, and emotional disturbance. The disorder is probably associated with dysfunction of C and A delta peripheral nerve fibres. Thermal quantitative sensory testing (QST) was used to analyse thinly myelinated A delta fibres and nonmylinated C fibres, which function in the nociceptive sensory system, and the spinothalamic pathway. The observation that FM pain has neuropathic nature increased the value of QST as an additional diagnostic tool. The research group included 51 patients. Somatic symptoms were assessed using the Fatigue Severity Score (FSS), Fibromyalgia Impact Questionnaire (FIQ) and American College of Rheumatology (ACR) 2010 year diagnostic criteria. QST was performed by using thermal stimulus at wrist and feet. QST results were compared with 20 non-FM controls matched for age and sex. FM patients showed significant alteration of thermal perception and pain threshold compared with that in healthy controls, which demonstrated possible neuropathic pain nature in FM patients. Changes were more expressed in warm perception and heat pain threshold, which probably indicates that in FM patients C fibres are more damaged and warm perception and warm pain threshold are more sensitive, which may be used as FM diagnostics. We also found statistically significant negative correlations between warm and cold perception thresholds and between heat and cold pain thresholds, reflecting central sensitization or a defective pain inhibitory system.

Early thermal quantitative sensory testing to measure acute oxaliplatin neurotoxicity and predict chronic neuropathy in gastrointestinal malignancies.

2012 ◽  
Vol 30 (4_suppl) ◽  
pp. 425-425
Author(s):  
Sangeetha Reddy ◽  
Nancy Kwon ◽  
Halla Sayed Nimeiri ◽  
Mary Frances Mulcahy ◽  
Robert Norm Harden ◽  
...  
Keyword(s):  
High Risk ◽  
Quantitative Sensory Testing ◽  
Low Risk ◽  
Cold Sensitivity ◽  
Sensory Testing ◽  
Cold Pain ◽  
Gastrointestinal Malignancies ◽  
Time Points ◽  
Significant Difference ◽  
Chronic Neuropathy

425 Background: Acute oxaliplatin neurotoxicity has been shown to be predictive of chronic oxaliplatin neuropathy. A recent study by Attal et al showed that tQST (thermal quantitative sensory testing) at cycle 4 provides a noninvasive method for predicting chronic neuropathy. A high risk population defined as those experiencing pain with a ≥ 20 degree cold stimulus had an OR of 39 for developing a severe chronic neuropathy at 1 year. Our study was designed to test the utility of tQST at earlier time points for predicting chronic neuropathy. Methods: Gastrointestinal cancer patients receiving FOLFOX were evaluated over a 1 year period for the development of acute and chronic oxaliplatin neurotoxicity: before starting FOLFOX, 1 hour into oxaliplatin infusion, before cycles 2, 4 and 12, and 1 year after start of treatment. Patients underwent a series of QSTs to measure thermal and mechanical sensitivities, fine motor skills, vibration detection, validated questionnaires, and presence of hyperalgesia. Results: Preliminary analysis of 13 patients using cycle 4 data as a surrogate for chronic neuropathy shows that cold pain (the temperature at which subjects report pain) prior to starting FOLFOX and at cycle 2 is predictive of cold pain at cycle 4, rs = 0.67 (p=.01) and 0.49 (p=0.09), respectively. There is a significant difference in cold pain across all time points between high and low risk populations(p=0.02 at baseline, p=0.04 during cycle 1, p=0.08 at cycle 2, and p=0.03 at cycle 4). Correlation between cycles 1 and 4 is seen for changes in cold sensitivity from baseline, rs = 0.52 (p=0.07). Conclusions: Baseline tQST correlates to cycle 4 measurements and may be an early predictor of patients at the highest risk for chronic neuropathy. These preliminary data indicate an inherent, pre-existing sensitivity to oxaliplatin induced chronic neuropathy for high risk patients which can be detected with tQST. Early identification of these patients can allow for preventive measures to decrease the incidence of this debilitating chronic adverse effect of oxaliplatin. A larger biomarker validation study is planned using tQST to stratify patients into high and low risk.

Reliability of orofacial quantitative sensory testing for pleasantness and unpleasantness

Cephalalgia ◽  
2020 ◽  
Vol 40 (11) ◽  
pp. 1191-1201
Author(s):  
Pankaj Taneja ◽  
Camilla Krause-Hirsch ◽  
Stine Laursen ◽  
Caroline Juul Sørensen ◽  
Håkan Olausson ◽  
...  
Keyword(s):  
Quantitative Sensory Testing ◽  
Intraclass Correlation ◽  
Research Network ◽  
Sensory Testing ◽  
German Research ◽  
Orofacial Region ◽  
The Right ◽  
Testing Protocols ◽  
Healthy Participants ◽  
Somatosensory Function

Background Quantitative sensory testing protocols for perceptions of pleasantness and unpleasantness based on the German Research Network on Neuropathic Pain protocol were recently introduced. However, there are no reliability studies yet published. Aim To evaluate the intra-examiner (test-retest) and inter-examiner reliability for orofacial pleasantness and unpleasantness quantitative sensory testing protocols. Methods Sixteen healthy participants from Aarhus University (11 women and five men, mean age 24, range 21–26 years) contributed. Two examiners were trained in performing the entire quantitative sensory testing protocols for pleasantness and unpleasantness, which included the additional dynamic tactile stimulation test using a goat-hair brush. Each participant underwent examination of both protocols by each examiner (inter-examiner reliability) on day 1. They returned at least 8 days following the testing to be re-examined by one examiner (intra-examiner reliability). All testing was performed on the skin of the right mandibular mental region. The intraclass correlation (ICC) was used to determine reliability. Results For the protocol investigating pleasantness, the majority of parameters had good to excellent intra-examiner (11/14: Intraclass correlation 0.67–0.87) and inter-examiner (13/14: Intraclass correlation 0.62–0.96) reliabilities. Similarly, the protocol investigating unpleasantness had good to excellent intra-examiner (intraclass correlation 0.63–0.99) and inter-examiner (intraclass correlation 0.65–0.98) reliabilities for most (13/15) of the parameters. Conclusion Intra and inter-examiner reliabilities in the majority of quantitative sensory testing parameters (apart from the summation ratio) investigating pleasantness and unpleasantness are acceptable when assessing somatosensory function of the orofacial region. Trial registration: NA

scholarly journals Mechanical punctate pain threshold is associated with headache frequency and phase in patients with migraine

Cephalalgia ◽  
2020 ◽  
Vol 40 (9) ◽  
pp. 990-997
Author(s):  
Li-Ling Hope Pan ◽  
Yen-Feng Wang ◽  
Kuan-Lin Lai ◽  
Wei-Ta Chen ◽  
Shih-Pin Chen ◽  
...  
Keyword(s):  
Chronic Migraine ◽  
Quantitative Sensory Testing ◽  
Pain Threshold ◽  
Episodic Migraine ◽  
Headache Frequency ◽  
Healthy Controls ◽  
Sensory Testing ◽  
Dynamic Changes ◽  
Cold Pain ◽  
Pain Thresholds

Objective Previous studies regarding the quantitative sensory testing are inconsistent in migraine. We hypothesized that the quantitative sensory testing results were influenced by headache frequency or migraine phase. Methods This study recruited chronic and episodic migraine patients as well as healthy controls. Participants underwent quantitative sensory testing, including heat, cold, and mechanical punctate pain thresholds at the supraorbital area (V1 dermatome) and the forearm (T1 dermatome). Prospective headache diaries were used for headache frequency and migraine phase when quantitative sensory testing was performed. Results Twenty-eight chronic migraine, 64 episodic migraine and 32 healthy controls completed the study. Significant higher mechanical punctate pain thresholds were found in episodic migraine but not chronic migraine when compared with healthy controls. The mechanical punctate pain thresholds decreased as headache frequency increased then nadired. In episodic migraine, mechanical punctate pain thresholds were highest ( p < 0.05) in those in the interictal phase and declined when approaching the ictal phase in both V1 and T1 dermatomes. Linear regression analyses showed that in those with episodic migraine, headache frequency and phase were independently associated with mechanical punctate pain thresholds and accounted for 29.7% and 38.9% of the variance in V1 ( p = 0.003) and T1 ( p < 0.001) respectively. Of note, unlike mechanical punctate pain thresholds, our study did not demonstrate similar findings for heat pain thresholds and cold pain thresholds in migraine. Conclusion Our study provides new insights into the dynamic changes of quantitative sensory testing, especially mechanical punctate pain thresholds in patients with migraine. Mechanical punctate pain thresholds vary depending on headache frequency and migraine phase, providing an explanation for the inconsistency across studies.

scholarly journals Thermal Pain in Complex Regional Pain Syndrome Type I

2014 ◽  
Vol 17;1 (1;17) ◽  
pp. 71-79
Author(s):  
John R. Grothusen
Keyword(s):  
Complex Regional Pain Syndrome ◽  
Quantitative Sensory Testing ◽  
Thermal Hyperalgesia ◽  
Pain Syndrome ◽  
Heat Pain ◽  
Syndrome Type ◽  
Sensory Testing ◽  
Cold Pain ◽  
Thermal Pain ◽  
Heat Hyperalgesia

Background: Quantitative sensory testing (QST), with thermal threshold determinations, is a routine part of the comprehensive clinical workup of patients suffering from chronic pain, especially those with Complex Regional Pain Syndrome seen at our outpatient pain clinic. This is done to quantitatively assess each patient’s small fiber and sensory function in a controlled manner. Most patients have normal sensory detection thresholds, but there are large differences in thermal pain thresholds. Some patients display no thermal hyperalgesia, while other patients display severe thermal hyperalgesia when tested in all 4 limbs. Objectives: To ascertain the prevalence of thermal hyperalgesia in patients with complex regional pain syndrome type 1 (CRPS-I). Study Design: This was a retrospective review of the results of QST performed on 105 patients as part of their clinical workup. Setting: The outpatient clinic of the Department of Neurology at Drexel University College of Medicine. Methods: All patients had a diagnosis of CRPS-I. Thermal quantitative sensory testing, including cool detection, warm detection, cold pain, and heat pain, was performed on 8 distal sites on each patient as part of a comprehensive clinical examination. Results: With regards to thermal hyperalgesia, patients with CPRS-I appear to fall into distinct groups. One subgroup displays evidence of generalized cold and heat hyperalgesia, one subgroup displays evidence of generalized cold hyperalgesia only, one displays evidence of heat hyperalgesia only, and one subgroup does not display evidence of cold or heat hyperalgesia. Limitations: This study is based on retrospective information on a relatively small (105 patient records) number of patients. Since only patients with CRPS-I were included, the results are only applicable to this group. Conclusions: Thermal QST provides useful information about the sensory phenotype of individual patients. Subgrouping based on thermal hyperalgesia may be useful for future studies regarding prognosis, treatment selection, and efficacy. Key words: Complex regional pain syndrome, CRPS, quantitative sensory testing, QST, cold pain, heat pain, thermal hyperalgesia

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