Arthroscopic evaluation of the ACL double bundle structure

In order to describe the arthroscopic presence of the double bundle structure and to evaluate the value of different portals in knee arthroscopy, we assessed the AM and PL bundle anatomy. We prospectively examined the knees of 60 patients undergoing arthroscopic surgery for pathology unrelated to the ACL. Arthroscopy was performed in a two portal technique using an anterolateral (ALP) and an anteromedial (AMP) portal. With the arthroscope in the ALP, we could distinguish an AM and PL bundle in 28%. Switching the arthroscope to the AMP, differentiation of the bundles was possible in 67%. In all remaining cases visualization of the PL bundle was possible after retraction of the AM bundle. Use of AMP increased visualization of the PL bundle. It seems reasonable to perform arthroscopy for ACL reconstruction with the arthroscope in the AMP and to establish an additional medial working portal to increase the visualization of the femoral ACL insertion sites for optimal femoral tunnel placement

Accuracy of biplane x-ray imaging combined with model-based tracking for measuring in-vivo patellofemoral joint motion

<p>Abstract</p> <p>Background</p> <p>Accurately measuring <it>in-vivo</it> motion of the knee's patellofemoral (PF) joint is challenging. Conventional measurement techniques have largely been unable to accurately measure three-dimensional, <it>in-vivo</it> motion of the patella during dynamic activities. The purpose of this study was to assess the accuracy of a new model-based technique for measuring PF joint motion.</p> <p>Methods</p> <p>To assess the accuracy of this technique, we implanted tantalum beads into the femur and patella of three cadaveric knee specimens and then recorded dynamic biplane radiographic images while manually flexing and extending the specimen. The position of the femur and patella were measured from the biplane images using both the model-based tracking system and a validated dynamic radiostereometric analysis (RSA) technique. Model-based tracking was compared to dynamic RSA by computing measures of bias, precision, and overall dynamic accuracy of four clinically-relevant kinematic parameters (patellar shift, flexion, tilt, and rotation).</p> <p>Results</p> <p>The model-based tracking technique results were in excellent agreement with the RSA technique. Overall dynamic accuracy indicated errors of less than 0.395 mm for patellar shift, 0.875° for flexion, 0.863° for tilt, and 0.877° for rotation.</p> <p>Conclusion</p> <p>This model-based tracking technique is a non-invasive method for accurately measuring dynamic PF joint motion under <it>in-vivo</it> conditions. The technique is sufficiently accurate in measuring clinically relevant changes in PF joint motion following conservative or surgical treatment.</p

Extrapolation for Time-Series and Cross-Sectional Data

Extrapolation methods are reliable, objective, inexpensive, quick, and easily automated. As a result, they are widely used, especially for inventory and production forecasts, for operational planning for up to two years ahead, and for long-term forecasts in some situations, such as population forecasting. This paper provides principles for selecting and preparing data, making seasonal adjustments, extrapolating, assessing uncertainty, and identifying when to use extrapolation. The principles are based on received wisdom (i.e., experts’ commonly held opinions) and on empirical studies. Some of the more important principles are:• In selecting and preparing data, use all relevant data and adjust the data for important events that occurred in the past.• Make seasonal adjustments only when seasonal effects are expected and only if there is good evidence by which to measure them.• In extrapolating, use simple functional forms. Weight the most recent data heavily if there are small measurement errors, stable series, and short forecast horizons. Domain knowledge and forecasting expertise can help to select effective extrapolation procedures. When there is uncertainty, be conservative in forecasting trends. Update extrapolation models as new data are received.• To assess uncertainty, make empirical estimates to establish prediction intervals.• Use pure extrapolation when many forecasts are required, little is known about the situation, the situation is stable, and expert forecasts might be biased

Factors that influence the intra-articular rupture pattern of the ACL graft following single-bundle reconstruction

The number of revision anterior cruciate ligament (ACL) surgeries performed annually continues to rise. The purpose of this study was to determine the most common rupture pattern in ACL revision cases after previous single-bundle reconstruction. The second aim was to determine the relationship between rupture pattern and patient-specific factors (age, gender, time between the initial ACL reconstruction and re-injury, and etiology/mechanism of failure) and surgical factors (graft type, tunnel angle). This was a cohort study of 60 patients that underwent revision ACL surgery after previous single-bundle ACL reconstruction. Three sports medicine-trained orthopedic surgeons reviewed the arthroscopic videos and determined the rupture pattern of the grafts. The rupture pattern was then correlated to the above-mentioned factors. The inter-observer agreement had a kappa of 0.7. The most common rupture pattern after previous single-bundle ACL reconstruction is elongation of the graft. This is different from the native ACL, which displays more proximal ruptures. With the use of autograft tissue and after a longer period of time, the rupture pattern in revision surgery is more similar to that of the native ACL. The most common rupture pattern after previous single-bundle reconstruction was elongation of the graft. Factors that influenced the rupture pattern were months between ACL reconstruction and re-injury and graft type. Cohort study, Level I

Rule-Based Forecasting: Using Judgment in Time-Series Extrapolation

Rule-Based Forecasting (RBF) is an expert system that uses judgment to develop and apply rules for combining extrapolations. The judgment comes from two sources, forecasting expertise and domain knowledge. Forecasting expertise is based on more than a half century of research. Domain knowledge is obtained in a structured way; one example of domain knowledge is managers= expectations about trends, which we call “causal forces.” Time series are described in terms of 28 conditions, which are used to assign weights to extrapolations. Empirical results on multiple sets of time series show that RBF produces more accurate forecasts than those from traditional extrapolation methods or equal-weights combined extrapolations. RBF is most useful when it is based on good domain knowledge, the domain knowledge is important, the series is well behaved (such that patterns can be identified), there is a strong trend in the data, and the forecast horizon is long. Under ideal conditions, the error for RBF’s forecasts were one-third less than those for equal-weights combining. When these conditions are absent, RBF neither improves nor harms forecast accuracy. Some of RBF’s rules can be used with traditional extrapolation procedures. In a series of studies, rules based on causal forces improved the selection of forecasting methods, the structuring of time series, and the assessment of prediction intervals

Dynamic loading of human engineered heart tissue enhances contractile function and drives a desmosome-linked disease phenotype

The role that mechanical forces play in shaping the structure and function of the heart is critical to understanding heart formation and the etiology of disease but is challenging to study in patients. Engineered heart tissues (EHTs) incorporating human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes have the potential to provide insight into these adaptive and maladaptive changes. However, most EHT systems cannot model both preload (stretch during chamber filling) and afterload (pressure the heart must work against to eject blood). Here, we have developed a new dynamic EHT (dyn-EHT) model that enables us to tune preload and have unconstrained contractile shortening of >10%. To do this, three-dimensional (3D) EHTs were integrated with an elastic polydimethylsiloxane strip providing mechanical preload and afterload in addition to enabling contractile force measurements based on strip bending. Our results demonstrated that dynamic loading improves the function of wild-type EHTs on the basis of the magnitude of the applied force, leading to improved alignment, conduction velocity, and contractility. For disease modeling, we used hiPSC-derived cardiomyocytes from a patient with arrhythmogenic cardiomyopathy due to mutations in the desmoplakin gene. We demonstrated that manifestation of this desmosome-linked disease state required dyn-EHT conditioning and that it could not be induced using 2D or standard 3D EHT approaches. Thus, a dynamic loading strategy is necessary to provoke the disease phenotype of diastolic lengthening, reduction of desmosome counts, and reduced contractility, which are related to primary end points of clinical disease, such as chamber thinning and reduced cardiac output

ACL graft re-rupture after double-bundle reconstruction: factors that influence the intra-articular pattern of injury

To determine the most common rupture patterns of previously reconstructed DB-ACL cases, seen at the time of revision surgery, and to determine the influence of age, gender, time between the initial ACL reconstruction and re-injury, tunnel angle and etiology of failure. Forty patients who presented for revision surgery after previous double-bundle ACL reconstruction were enrolled. Three orthopedic surgeons independently reviewed the arthroscopic videos and determined the rupture pattern of both the anteromedial and posterolateral grafts. The graft rupture pattern was then correlated with the previously mentioned factors. The most common injury pattern seen at the time of revision ACL surgery was mid-substance AM and PL bundle rupture. Factors that influenced the rupture pattern (proximal vs. mid-substance and distal rupture vs. elongated, but in continuity) were months between ACL reconstruction and re-injury (P = 0.002), the etiology of failure (traumatic vs. atraumatic) (P = 0.025) and the measured graft tunnel angle (P = 0.048). The most common pattern of graft re-rupture was mid-substance AM and mid-substance PL. As the length of time from the initial DB-ACL reconstruction to revision surgery increased, the pattern of injury more closely resembled that of the native ACL. Evaluation of patients who have undergone double-bundle ACL reconstruction, with a particular focus on graft maturity, mechanism of injury and femoral tunnel angles, and graft rupture pattern assists in preoperative planning for revision surger

Rotational knee laxity: Reliability of a simple measurement device in vivo

<p>Abstract</p> <p>Background</p> <p>Double bundle ACL reconstruction has been demonstrated to decrease rotational knee laxity. However, there is no simple, commercially-available device to measure knee rotation. The investigators developed a simple, non-invasive device to measure knee rotation. In conjunction with a rigid boot to rotate the tibia and a force/moment sensor to allow precise determination of torque about the knee, a magnetic tracking system measures the axial rotation of the tibia with respect to the femur. This device has been shown to have acceptable levels of test re-test reliability to measure knee rotation in cadaveric knees.</p> <p>Methods</p> <p>The objective of this study was to determine reliability of the device in measuring knee rotation of human subjects. Specifically, the intra-tester reliability within a single testing session, test-retest reliability between two testing sessions, and inter-tester reliability were assessed for 11 male subjects with normal knees.</p> <p>Results</p> <p>The 95% confidence interval for rotation was less than 5° for intra-tester, test-retest, and inter-tester reliability, and the standard error of measurement for the differences between left and right knees was found to be less than 3°.</p> <p>Conclusion</p> <p>It was found that the knee rotation measurements obtained with this device have acceptable limits of reliability for clinical use and interpretation.</p

Multi-step time series prediction intervals using neuroevolution

Multi-step time series forecasting (TSF) is a crucial element to support tactical decisions (e.g., designing production or marketing plans several months in advance). While most TSF research addresses only single-point prediction, prediction intervals (PIs) are useful to reduce uncertainty related to important decision making variables. In this paper, we explore a large set of neural network methods for multi-step TSF and that directly optimize PIs. This includes multi-step adaptations of recently proposed PI methods, such as lower--upper bound estimation (LUBET), its ensemble extension (LUBEXT), a multi-objective evolutionary algorithm LUBE (MLUBET) and a two-phase learning multi-objective evolutionary algorithm (M2LUBET). We also explore two new ensemble variants for the evolutionary approaches based on two PI coverage--width split methods (radial slices and clustering), leading to the MLUBEXT, M2LUBEXT, MLUBEXT2 and M2LUBEXT2 methods. A robust comparison was held by considering the rolling window procedure, nine time series from several real-world domains and with different characteristics, two PI quality measures (coverage error and width) and the Wilcoxon statistic. Overall, the best results were achieved by the M2LUBET neuroevolution method, which requires a reasonable computational effort for time series with a few hundreds of observations.This article is a result of the project NORTE-01- 0247-FEDER-017497, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). We would also like to thank the anonymous reviewers for their helpful suggestionsinfo:eu-repo/semantics/publishedVersio