scholarly journals Effect of Speed and Surface Type on Individual Rein and Combined Left–Right Circle Movement Asymmetry in Horses on the Lunge

2021 ◽  
Vol 8 ◽  
Author(s):  
Thilo Pfau ◽  
Emma Persson-Sjodin ◽  
Harriet Gardner ◽  
Olivia Orssten ◽  
Elin Hernlund ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Clinical Decision Making ◽  
Linear Models ◽  
Clinical Decision ◽  
Diagnostic Process ◽  
Limits Of Agreement ◽  
Random Factor ◽  
Speed Increase ◽  
Straight Line ◽  
Movement Asymmetry

Differences in movement asymmetry between surfaces and with increasing speed increase the complexity of incorporating gait analysis measurements from lunging into clinical decision making. This observational study sets out to quantify by means of quantitative gait analysis the influence of surface and speed on individual-rein movement asymmetry measurements and their averages across reins (average-rein measurements). Head, withers, and pelvic movement asymmetry was quantified in 27 horses, identified previously as presenting with considerable movement asymmetries on the straight, during trot in hand and on the lunge on two surfaces at two speeds. Mixed linear models (p < 0.05) with horse as the random factor and surface and speed category (and direction) as fixed factors analyzed the effects on 11 individual-rein and average-rein asymmetry measures. Limits of agreement quantified differences between individual-rein and average-rein measurements. A higher number of individual-rein asymmetry variables—particularly when the limb that contributed to movement asymmetry on the straight was on the inside of the circle—were affected by speed (nine variables, all p ≤ 0.047) and surface (three variables, all p ≤ 0.037) compared with average-rein asymmetry variables (two for speed, all p ≤ 0.003; two for surface, all p ≤ 0.046). Six variables were significantly different between straight-line and average-rein assessments (all p ≤ 0.031), and asymmetry values were smaller for average-rein assessments. Limits of agreement bias varied between +0.4 and +4.0 mm with standard deviations between 3.2 and 12.9 mm. Fewer average-rein variables were affected by speed highlighting the benefit of comparing left and right rein measurements. Only one asymmetry variable showed a surface difference for individual-rein and average-rein data, emphasizing the benefit of assessing surface differences on each rein individually. Variability in straight-line vs. average-rein measurements across horses and exercise conditions highlight the potential for average-rein measurements during the diagnostic process; further studies after diagnostic analgesia are needed.

Clinical decision making in spastic bilateral CP – Planning interventions using clinical gait analysis: A case study

2015 ◽  
Vol 42 ◽  
pp. S37
Author(s):  
M. Alvela ◽  
M. Bergmann ◽  
M.-L. Ööpik ◽  
Ü. Kruus ◽  
K. Englas ◽  
...  
Keyword(s):  
Decision Making ◽  
Gait Analysis ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Clinical Gait Analysis

Neural Network Subtyping of Depression

1998 ◽  
Vol 32 (5) ◽  
pp. 687-694 ◽  
Author(s):  
Tony M. Florio ◽  
Gordon Parker ◽  
Marie-Paule Austin ◽  
Ian Hickie ◽  
Philip Mitchell ◽  
...  
Keyword(s):  
Neural Network ◽  
Clinical Decision Making ◽  
Linear Models ◽  
Function Analysis ◽  
Clinical Decision ◽  
Linear Analysis ◽  
Linear Discriminant ◽  
Non Linear ◽  
Depressive Subtypes ◽  
Definition Of

Objective: To examine the applicability of a neural network classification strategy to examine the independent contribution of psychomotor disturbance (PMD) and endogeneity symptoms to the DSM-III-R definition of melancholia. Method: We studied 407 depressed patients with the clinical dataset comprising 17 endogeneity symptoms and the 18-item CORE measure of behaviourally rated PMD. A multilayer perceptron neural network was used to fit non-linear models of varying complexity. A linear discriminant function analysis was also used to generate a model for comparison with the non-linear models. Results: Models (linear and non-linear) using PMD items only and endogeneity symptoms only had similar rates of successful classification, while non-linear models combining both PMD and symptom scores achieved the best classifications. Conclusions: Our current non-linear model was superior to a linear analysis, a finding which may have wider application to psychiatric classification. Our non-linear analysis of depressive subtypes supports the binary view that melancholic and non-melancholic depression are separate clinical disorders rather than different forms of the same entity. This study illustrates how non-linear modelling with neural networks is a potentially fruitful approach to the study of the diagnostic taxonomy of psychiatric disorders and to clinical decision-making.

scholarly journals Operationalization of the learned non-use phenomenon - A Delphi study

2020 ◽  
Author(s):  
Theresa Hirsch ◽  
Maria Barthel ◽  
Pauline Aarts ◽  
Yi-An Chen ◽  
Susanna Freivogel ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Delphi Study ◽  
Clinical Decision Making ◽  
Negative Reinforcement ◽  
Brain Lesion ◽  
Clinical Decision ◽  
Diagnostic Process ◽  
Sources Of Information ◽  
Wide Range

AbstractThe discrepancy between residual functional capacity and reduced use of the contralesional hand, frequently observed after a brain lesion, has been termed Learned Non-Use (LNU) and is thought to depend on the interaction of neuronal mechanisms during recovery and learning-dependent mechanisms such as negative reinforcement. Despite the generally accepted existence of the LNU phenomenon among clinicians and researchers, no unequivocal and transdisciplinary definition exists to date. Furthermore, although therapeutic approaches are implemented in clinical practice to explicitly target LNU, no standardized diagnostic routine is described in the current literature.Based on a structured group communication following the Delphi method among clinical and scientific experts in the field of LNU, knowledge from both, the work with patient populations and with animal models, was synthesized and integrated to reach consensus regarding a transdisciplinary definition of the LNU phenomenon. Furthermore, the mode and strategy of the diagnostic process, as well as the sources of information and outcome parameters relevant for the clinical decision making, were described with a wide range showing the current lack of a consistent universal diagnostic approach. Building on these results, the need for the development of a structured diagnostic procedure and its implementation into clinical practice is emphasized. Moreover, it exists a striking gap between the prevailing hypotheses regarding the mechanisms underlying the LNU phenomenon and the actual evidence. Therefore, basic research is needed to bridge between bedside and bench and eventually improve clinical decision making and further development of interventional strategies beyond the field of stroke rehabilitation.

scholarly journals Improving the Estimation of Subgroup Effects for Clinical Trial Participants with Multimorbidity by Incorporating Drug Class-Level Information in Bayesian Hierarchical Models: A Simulation Study

2021 ◽  
pp. 0272989X2110295
Author(s):  
Laurie J. Hannigan ◽  
David M. Phillippo ◽  
Peter Hanlon ◽  
Laura Moss ◽  
Elaine W. Butterly ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Hierarchical Models ◽  
Clinical Decision Making ◽  
Linear Models ◽  
Clinical Decision ◽  
Bayesian Hierarchical Models ◽  
World Health ◽  
Bayesian Hierarchical ◽  
Meta Analyses ◽  
Subgroup Effects

Background There is limited guidance for using common drug therapies in the context of multimorbidity. In part, this is because their effectiveness for patients with specific comorbidities cannot easily be established using subgroup analyses in clinical trials. Here, we use simulations to explore the feasibility and implications of concurrently estimating effects of related drug treatments in patients with multimorbidity by partially pooling subgroup efficacy estimates across trials. Methods We performed simulations based on the characteristics of 161 real clinical trials of noninsulin glucose-lowering drugs for diabetes, estimating subgroup effects for patients with a hypothetical comorbidity across related trials in different scenarios using Bayesian hierarchical generalized linear models. We structured models according to an established ontology—the World Health Organization Anatomic Chemical Therapeutic Classifications—allowing us to nest all trials within drugs and all drugs within anatomic chemical therapeutic classes, with effects partially pooled at each level of the hierarchy. In a range of scenarios, we compared the performance of this model to random effects meta-analyses of all drugs individually. Results Hierarchical, ontology-based Bayesian models were unbiased and accurately recovered simulated comorbidity-drug interactions. Compared with single-drug meta-analyses, they offered a relative increase in precision of up to 250% in some scenarios because of information sharing across the hierarchy. Because of the relative precision of the approaches, a large proportion of small subgroup effects was detectable only using the hierarchical model. Conclusions By assuming that similar drugs may have similar subgroup effects, Bayesian hierarchical models based on structures defined by existing ontologies can be used to improve the precision of treatment efficacy estimates in patients with multimorbidity, with potential implications for clinical decision making.

scholarly journals Towards a Mobile Gait Analysis for Patients with a Spinal Cord Injury: A Robust Algorithm Validated for Slow Walking Speeds

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7381
Author(s):  
Charlotte Werner ◽  
Chris Awai Awai Easthope ◽  
Armin Curt ◽  
László Demkó
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Gait Analysis ◽  
Clinical Decision Making ◽  
Inertial Sensors ◽  
Clinical Decision ◽  
Cord Injury ◽  
Spatio Temporal ◽  
The Individual ◽  
Walking Speeds

Spinal cord injury (SCI) patients suffer from diverse gait deficits depending on the severity of their injury. Gait assessments can objectively track the progress during rehabilitation and support clinical decision making, but a comprehensive gait analysis requires far more complex setups and time-consuming protocols that are not feasible in the daily clinical routine. As using inertial sensors for mobile gait analysis has started to gain ground, this work aimed to develop a sensor-based gait analysis for the specific population of SCI patients that measures the spatio-temporal parameters of typical gait laboratories for day-to-day clinical applications. The proposed algorithm uses shank-mounted inertial sensors and personalized thresholds to detect steps and gait events according to the individual gait profiles. The method was validated in nine SCI patients and 17 healthy controls walking on an instrumented treadmill while wearing reflective markers for motion capture used as a gold standard. The sensor-based algorithm (i) performed similarly well for the two cohorts and (ii) is robust enough to cover the diverse gait deficits of SCI patients, from slow (0.3 m/s) to preferred walking speeds.

scholarly journals A Cognitive Autopsy Approach towards Understanding Diagnostic Failure

2020 ◽  
Author(s):  
Pat Croskerry ◽  
Samuel Campbell
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Performance ◽  
Critical Role ◽  
Clinical Decision ◽  
Diagnostic Error ◽  
Diagnostic Process ◽  
Base Line ◽  
Root Cause ◽  
Knowledge Based

Diagnostic failure has emerged as one of the most significant threats to patient safety, and it is important to understand the antecedents of such failures. A consensus has developed in the literature that the majority are due to individual or system factors or some combination of the two. A major source of variance in individual clinical performance is due to cognitive and affective biases, however, their role in clinical decision making has been difficult to assess partly because they are difficult to investigate experimentally. A significant drawback has been that experimental manipulations appear to confound assessment of the context surrounding the diagnostic process itself. The present qualitative study uses a detailed narrative account of selected actual cases of diagnostic error to explore the effect of biases in the ‘real world’ emergency medicine (EM) context. Thirty anonymized EM cases were analysed in depth through a process of root cause analysis that included an assessment of error producing conditions, knowledge-based errors, and how clinicians were thinking and deciding during each case. A prominent feature of the study was the identification of specific cognitive and affective biases – through a process called cognitive autopsy. The cases covered a broad range of diagnoses across a wide variety of disciplines. A total of 24 discrete cognitive and affective biases that contributed to misdiagnosis were identified and their incidence recorded. 5-6 biases were detected per case, and observed on 168 occasions across the 30 cases. Thirteen error-producing conditions (EPCs) were identified. Knowledge-based errors were rare, occurring in only 5 definite instances. The ordinal position in which biases appeared in the diagnostic process was recorded. This study provides a base-line for understanding the critical role that biases play in clinical decision making and sheds light on important aspects of the diagnostic process.

scholarly journals Improved interpretation of studies comparing methods of dietary assessment: combining equivalence testing with the limits of agreement

2016 ◽  
Vol 115 (7) ◽  
pp. 1273-1280 ◽  
Author(s):  
Marijka J. Batterham ◽  
Christel Van Loo ◽  
Karen E. Charlton ◽  
Dylan P. Cliff ◽  
Anthony D. Okely
Keyword(s):  
Clinical Decision Making ◽  
Dietary Assessment ◽  
A Priori ◽  
Clinical Decision ◽  
Equivalence Testing ◽  
Limits Of Agreement ◽  
Data Set ◽  
Sample Data ◽  
The Mean ◽  
Acceptable Agreement

AbstractThe aim of this study was to demonstrate the use of testing for equivalence in combination with the Bland and Altman method when assessing agreement between two dietary methods. A sample data set, with eighty subjects simulated from previously published studies, was used to compare a FFQ with three 24 h recalls (24HR) for assessing dietary I intake. The mean I intake using the FFQ was 126·51 (sd 54·06) µg and using the three 24HR was 124·23 (sd 48·62) µg. The bias was −2·28 (sd 43·93) µg with a 90 % CI 10·46, 5·89 µg. The limits of agreement (LOA) were −88·38, 83·82 µg. Four equivalence regions were compared. Using the conventional 10 % equivalence range, the methods are shown to be equivalent both by using the CI (−12·4, 12·4 µg) and the two one-sided tests approach (lower t=−2·99 (79 df), P=0·002; upper t=2·06 (79 df), P=0·021). However, we make a case that clinical decision making should be used to set the equivalence limits, and for nutrients where there are potential issues with deficiency or toxicity stricter criteria may be needed. If the equivalence region is lowered to ±5 µg, or ±10 µg, these methods are no longer equivalent, and if a wider limit of ±15 µg is accepted they are again equivalent. Using equivalence testing, acceptable agreement must be assessed a priori and justified; this makes the process of defining agreement more transparent and results easier to interpret than relying on the LOA alone.

scholarly journals Smartphone-Based Pelvic Movement Asymmetry Measures for Clinical Decision Making in Equine Lameness Assessment

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1665
Author(s):  
Eva Marunova ◽  
Leea Dod ◽  
Stefan Witte ◽  
Thilo Pfau
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Upward Movement ◽  
Discriminative Power ◽  
Visual Evaluation ◽  
Significant Difference ◽  
Pelvic Movement ◽  
Movement Asymmetry ◽  
Asymmetry Measures

Visual evaluation of hindlimb lameness in the horse is challenging. Objective measurements, simultaneous to visual assessment, are used increasingly to aid clinical decision making. The aim of this study was to investigate the association of pelvic movement asymmetry with lameness scores (UK scale 0–10) of one experienced veterinarian. Absolute values of pelvic asymmetry measures, quantifying differences between vertical minima (AbPDMin), maxima (AbPDMax) and upward movement amplitudes (AbPDUp), were recorded during straight-line trot with a smartphone attached to the sacrum (n = 301 horses). Overall, there was a significant difference between lameness grades for all three asymmetry measures (p < 0.001). Five pair-wise differences (out of 10) were significant for AbPDMin (p ≤ 0.02) and seven for AbPDMax (p ≤ 0.03) and AbPDUp (p ≤ 0.02). Receiver operating curves assessed sensitivity and specificity of asymmetry measures against lameness scores. AbPDUp had the highest discriminative power (area under curve (AUC) = 0.801–0.852) followed by AbPDMax (AUC = 0.728–0.813) and AbPDMin (AUC = 0.688–0.785). Cut-off points between non-lame (grade 0) and lame horses (grades 1–4) with a minimum sensitivity of 75% were identified as AbPDUp ≥ 7.5 mm (67.6% specificity), AbPDMax ≥ 4.5 mm (51.9% specificity) and AbPDMin ≥ 2.5 mm (33.3% specificity). In conclusion, pelvic upward movement amplitude difference (AbPDUp) was the asymmetry parameter with the highest discriminative power in this study.

scholarly journals Orientation-Invariant Spatio-Temporal Gait Analysis Using Foot-Worn Inertial Sensors

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3940
Author(s):  
Vânia Guimarães ◽  
Inês Sousa ◽  
Miguel Velhote Correia
Keyword(s):  
Gait Analysis ◽  
Relative Error ◽  
Clinical Decision Making ◽  
Inertial Sensors ◽  
Clinical Decision ◽  
The Body ◽  
Sensor Data ◽  
Sensor Orientation ◽  
Optical Motion ◽  
Spatio Temporal

Inertial sensors can potentially assist clinical decision making in gait-related disorders. Methods for objective spatio-temporal gait analysis usually assume the careful alignment of the sensors on the body, so that sensor data can be evaluated using the body coordinate system. Some studies infer sensor orientation by exploring the cyclic characteristics of walking. In addition to being unrealistic to assume that the sensor can be aligned perfectly with the body, the robustness of gait analysis with respect to differences in sensor orientation has not yet been investigated—potentially hindering use in clinical settings. To address this gap in the literature, we introduce an orientation-invariant gait analysis approach and propose a method to quantitatively assess robustness to changes in sensor orientation. We validate our results in a group of young adults, using an optical motion capture system as reference. Overall, good agreement between systems is achieved considering an extensive set of gait metrics. Gait speed is evaluated with a relative error of −3.1±9.2 cm/s, but precision improves when turning strides are excluded from the analysis, resulting in a relative error of −3.4±6.9 cm/s. We demonstrate the invariance of our approach by simulating rotations of the sensor on the foot.

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