Knee instruments and rating scales designed to measure outcomes

In this article, the knee instruments and rating scales that are designed to measure outcomes are revised. Although the International Knee Documentation Committee Subjective Knee Form can be used as a general knee measure, no instrument is currently universally applicable across the spectrum of knee disorders and patient groups. Clinicians and researchers looking to use a patient-based score for measurement of outcomes must consider the specific patient population in which it has been evaluated. The Western Ontario and McMaster Universities Osteoarthritis Index is recommended for the evaluation of treatment effect in persons with osteoarthritis (OA). This is a generic health status questionnaire that contains 36 items, is widely used, and easy to complete. The Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaire evaluates the functional status and quality of life (QoL) of patients with any type of knee injury who are at increased risk of developing OA; i.e., patients with anterior cruciate ligament (ACL) injury, meniscus injury, or chondral injury. So far, the KOOS questionnaire has been validated for several orthopedic procedures such as total knee arthroplasty, ACL reconstruction, and meniscectomy. The utilization of QoL questionnaires is crucial to the adequate assessment of a number of orthopedic procedures of the knee. The questionnaires are generally well accepted by the patients and open up new perspectives in the analysis of prognostic factors for optimal QoL of patients undergoing knee surgery

Analytical model for the calculation of lateral velocity distributions in potential cross-sections

[EN] The hydraulic modeling of water depth and flow velocities in open channel flows that were fitted by power-law cross-section stand out for their versatility, allowing their use in numerous practical applications, both in natural and artificial channels. The determination of the hydraulic variables of depth and average velocity has been widely studied in potential cross-sections; however, the variation seen in these variables along the cross-section was not found in the literature. Knowledge of this variation allows the development of studies (e.g. to know the approximate damage in different areas of the cross-section, to analyse sediment transport, or other applications in river hydraulics). This paper presents a methodology which allows calculation of the hydraulic variables in any area of a power-law cross-section. The methodology is applied to symmetrical cross-sections, comparing its generated results with the obtained values by different computational hydraulic codes, which are thoroughly accepted by scientific community, such as CES, HEC-RAS and IBER. The obtained predictions of hydraulic parameters (using the explicit formulation described in this research) present very low errors when compared with results of other models, with great computational cost. These errors reach a root mean square error (RMSE) of 0.13 and 0.05 in the determination of velocities' lateral distribution and the ratio between velocity and average velocity. These values indicate a very successful validation for the analysed symmetrical sections.[ES] La modelización hidráulica de calados y velocidades de flujo, en cauces con secciones que admiten una representación de tipo potencial, se destaca por su versatilidad, permitiendo su utilización en numerosas aplicaciones prácticas tanto en canales naturales como artificiales. El cálculo de las variables hidráulicas (calado y velocidad media) ha sido ampliamente estudiado para este tipo de secciones. Sin embargo, en la literatura técnica no se han encontrado estudios que muestren la variación de estas magnitudes a lo largo de la sección transversal. El conocimiento de esta variación permite desarrollar estudios (ejemplo: conocer de manera aproximada los daños en diferentes zonas de la sección, analizar el transporte de sedimentos, estudiar los procesos de erosión u otras aplicaciones en hidráulica fluvial). Presentamos una metodología que permite el cálculo de las variables hidráulicas en cualquier zona de una sección tipo potencial. La metodología es aplicada a secciones simétricas, comparando los resultados generados con los obtenidos por diferentes códigos hidráulicos computacionales ampliamente aceptados por la comunidad científica (p-e- CES, HECRAS e IBER). Las predicciones de los parámetros hidráulicos obtenidas (usando la formulación explícita descrita en este artículo) presentan errores muy bajos, en comparación con otros modelos con mayor costo computacional. Estos errores alcanzan un valor promedio para la raíz del error cuadrático medio (RMSE) en el cálculo de la distribución lateral de velocidades de 0.13 y de 0.05, en el cálculo de la relación de velocidades respecto a la velocidad media. Estos valores indican una validación muy satisfactoria para las secciones simétricas analizadas.Sánchez-Romero, F.; Pérez-Sánchez, M.; López Jiménez, PA. (2018). Modelo analítico para el cálculo de distribuciones de velocidad laterales en secciones tipo potencial-ley. RIBAGUA - Revista Iberoamericana del Agua. 5(1):29-47. doi:10.1080/23863781.2018.1442189S29475

Assessing stability and change of four performance measures: a longitudinal study evaluating outcome following total hip and knee arthroplasty

BACKGROUND: Physical performance measures play an important role in the measurement of outcome in patients undergoing hip and knee arthroplasty. However, many of the commonly used measures lack information on their psychometric properties in this population. The purposes of this study were to examine the reliability and sensitivity to change of the six minute walk test (6MWT), timed up and go test (TUG), stair measure (ST), and a fast self-paced walk test (SPWT) in patients with hip or knee osteoarthritis (OA) who subsequently underwent total joint arthroplasty. METHODS: A sample of convenience of 150 eligible patients, part of an ongoing, larger observational study, was selected. This included 69 subjects who had a diagnosis of hip OA and 81 diagnosed with knee OA with an overall mean age of 63.7 ± 10.7 years. Test-retest reliability, using Shrout and Fleiss Type 2,1 intraclass correlations (ICCs), was assessed preoperatively in a sub-sample of 21 patients at 3 time points during the waiting period prior to surgery. Error associated with the measures' scores and the minimal detectable change at the 90% confidence level was determined. A construct validation process was applied to evaluate the measures' abilities to detect deterioration and improvement at two different time points post-operatively. The standardized response mean (SRM) was used to quantify change for all measures for the two change intervals. Bootstrapping was used to estimate the 95% confidence intervals (CI) for the SRMs. RESULTS: The ICCs (95% CI) were as follows: 6MWT 0.94 (0.88,0.98), TUG 0.75 (0.51, 0.89), ST 0.90 (0.79, 0.96), and the SPWT 0.91 (0.81, 0.97). Standardized response means varied from .79 to 1.98, being greatest for the ST and 6MWT over the studied time intervals. CONCLUSIONS: The test-retest estimates of the 6MWT, ST, and the SPWT met the requisite standards for making decisions at the individual patient level. All measures were responsive to detecting deterioration and improvement in the early postoperative period

Small Increase of Actual Physical Activity 6 Months After Total Hip or Knee Arthroplasty

Limitation in daily physical activity is one of the reasons for total hip arthroplasty (THA) or total knee arthroplasty (TKA). However, studies of the effects of THA or TKA generally do not determine actual daily activity as part of physical functioning. We determined the effect of THA or TKA on patients’ actual physical activity and body function (pain, stiffness), capacity to perform tasks, and self-reported physical functioning. We also assessed whether there are differences in the effect of the surgery between patients undergoing THA or TKA and whether the improvements vary between these different outcome measures. We recruited patients with long-standing end-stage osteoarthritis of the hip or knee awaiting THA or TKA. Measurements were performed before surgery and 3 and 6 months after surgery. Actual physical activity improved by 0.7%. Patients’ body function, capacity, and self-reported physical functioning also improved. The effects of the surgery on these aspects of physical functioning were similar for THA and TKA. The effect on actual physical activity (8%) was smaller than on body function (80%–167%), capacity (19%–36%), and self-reported physical functioning (87%–112%). Therefore, in contrast to the large effect on pain and stiffness, patients’ capacity, and their self-reported physical functioning, the improvement in actual physical activity of our patients was less than expected 6 months after surgery

Modeling early recovery of physical function following hip and knee arthroplasty

BACKGROUND: Information on early recovery after arthroplasty is needed to help benchmark progress and make appropriate decisions concerning patient rehabilitation needs. The purpose of this study was to model early recovery of physical function in patients undergoing total hip (THA) and knee (TKA) arthroplasty, using physical performance and self-report measures. METHODS: A sample of convenience of 152 subjects completed testing, of which 69 (mean age: 66.77 ± 8.23 years) underwent THA and 83 (mean age: 60.25 ± 11.19 years) TKA. Postoperatively, patients were treated using standardized care pathways and rehabilitation protocols. Using a repeated measures design, patients were assessed at multiple time points over the first four postoperative months. Outcome measures included the Lower Extremity Function Scale (LEFS), the physical function subscale of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC PF), the 6 minute walk test (6 MWT), timed up and go test (TUG) and a timed stair test (ST). Average recovery curves for each of the measures were characterized using hierarchical linear modeling. Predictors of recovery were sequentially modeled after validation of the basic developmental models. RESULTS: Slopes of recovery were greater in the first 6 to 9 weeks with a second-degree polynomial growth term (weeks squared) providing a reasonable fit for the data over the study interval. Different patterns of recovery were observed between the self-report measures of physical function and the performance measures. In contrast to the models for the WOMAC PF and the LEFS, site of arthroplasty was a significant predictor (p = 0.001) in all of the physical performance measure models with the patients post TKA initially demonstrating higher function. Site of arthroplasty (p = 0.025) also predicted the rate of change for patients post THA and between 9 to 11 weeks after surgery, the THA group surpassed the function of the patients post TKA. CONCLUSION: Knowledge about the predicted growth curves will assist clinicians in referencing patient progress, and determining the critical time points for measuring change. The study has contributed further evidence to highlight the benefit of using physical performance measures to learn about the patients' actual level of disability

Corticotropin Releasing Factor-Induced CREB Activation in Striatal Neurons Occurs via a Novel Gβγ Signaling Pathway

The peptide corticotropin-releasing factor (CRF) was initially identified as a critical component of the stress response. CRF exerts its cellular effects by binding to one of two cognate G-protein coupled receptors (GPCRs), CRF receptor 1 (CRFR1) or 2 (CRFR2). While these GPCRs were originally characterized as being coupled to Gαs, leading to downstream activation of adenylyl cyclase (AC) and subsequent increases in cAMP, it has since become clear that CRFRs couple to and activate numerous other downstream signaling cascades. In addition, CRF signaling influences the activity of many diverse brain regions, affecting a variety of behaviors. One of these regions is the striatum, including the nucleus accumbens (NAc). CRF exerts profound effects on striatal-dependent behaviors such as drug addiction, pair-bonding, and natural reward. Recent data indicate that at least some of these behaviors regulated by CRF are mediated through CRF activation of the transcription factor CREB. Thus, we aimed to elucidate the signaling pathway by which CRF activates CREB in striatal neurons. Here we describe a novel neuronal signaling pathway whereby CRF leads to a rapid Gβγ- and MEK-dependent increase in CREB phosphorylation. These data are the first descriptions of CRF leading to activation of a Gβγ-dependent signaling pathway in neurons, as well as the first description of Gβγ activation leading to downstream CREB phosphorylation in any cellular system. Additionally, these data provide additional insight into the mechanisms by which CRF can regulate neuronal function