Revisiting patient satisfaction following total knee arthroplasty: a longitudinal observational study.

BACKGROUND: Total knee arthroplasty (TKA) is the most common joint replacement surgery in Canada. Earlier Canadian work reported 1 in 5 TKA patients expressing dissatisfaction following surgery. A better understanding of satisfaction could guide program improvement. We investigated patient satisfaction post-TKA in British Columbia (BC). METHODS: A cohort of 515 adult TKA patients was recruited from across BC. Survey data were collected preoperatively and at 6 and 12 months, supplemented by administrative health data. The primary outcome measure was patient satisfaction with outcomes. Potential satisfaction drivers included demographics, patient-reported health, quality of life, social support, comorbidities, and insurance status. Multivariable growth modeling was used to predict satisfaction at 6 months and change in satisfaction (6 to 12 months). RESULTS: We found dissatisfaction rates ("very dissatisfied", "dissatisfied" or "neutral") of 15% (6 months) and 16% (12 months). Across all health measures, improvements were seen post-surgery. The multivariable model suggests satisfaction at 6 months is predicted by: pre-operative pain, mental health and physical health (odds ratios (ORs) 2.65, 3.25 and 3.16), and change in pain level, baseline to 6 months (OR 2.31). Also, improvements in pain, mental health and physical health from 6 to 12 months predicted improvements in satisfaction (ORs 1.24, 1.30 and 1.55). CONCLUSIONS: TKA is an effective intervention for many patients and most report high levels of satisfaction. However, if the TKA does not deliver improvements in pain and physical health, we see a less satisfied patient. In addition, dissatisfied TKA patients typically see limited improvements in mental health.

Combining deep residual neural network features with supervised machine learning algorithms to classify diverse food image datasets.

Obesity is increasing worldwide and can cause many chronic conditions such as type-2 diabetes, heart disease, sleep apnea, and some cancers. Monitoring dietary intake through food logging is a key method to maintain a healthy lifestyle to prevent and manage obesity. Computer vision methods have been applied to food logging to automate image classification for monitoring dietary intake. In this work we applied pretrained ResNet-152 and GoogleNet convolutional neural networks (CNNs), initially trained using ImageNet Large Scale Visual Recognition Challenge (ILSVRC) dataset with MatConvNet package, to extract features from food image datasets; Food 5K, Food-11, RawFooT-DB, and Food-101. Deep features were extracted from CNNs and used to train machine learning classifiers including artificial neural network (ANN), support vector machine (SVM), Random Forest, and Naive Bayes. Results show that using ResNet-152 deep features with SVM with RBF kernel can accurately detect food items with 99.4% accuracy using Food-5K validation food image dataset and 98.8% with Food-5K evaluation dataset using ANN, SVM-RBF, and Random Forest classifiers. Trained with ResNet-152 features, ANN can achieve 91.34%, 99.28% when applied to Food-11 and RawFooT-DB food image datasets respectively and SVM with RBF kernel can achieve 64.98% with Food-101 image dataset. From this research it is clear that using deep CNN features can be used efficiently for diverse food item image classification. The work presented in this research shows that pretrained ResNet-152 features provide sufficient generalisation power when applied to a range of food image classification tasks.

The importance of informational, clinical and personal support in patient experience with total knee replacement: a qualitative investigation.

BACKGROUND: Total knee arthroplasty (TKA) is the most frequently performed joint replacement surgery in North America. Patient perspectives on TKA have been investigated in various ways, including finding as many as 20% of TKA patients are dissatisfied with their surgical outcomes. Understanding the patient experience with TKA broadly and in relation to patient satisfaction is a key gap in existing literature. METHODS: We report on the qualitative component of a mixed methods prospective cohort study examining patient experience and satisfaction post-TKA for adults in British Columbia, Canada. Data collection consisted of 45 in-depth interviews about individuals' knee surgery experiences conducted eight months after surgery. Analysis consisted of thematic coding by multiple coders. RESULTS: Participants' descriptions of their TKA experiences were primarily concerned with support, or the provision of aid and assistance. Support was insufficient when their expectations of support were not met; unmet support expectations led to an overall negative TKA experience. Support operated in three key domains: (1) informational support, (2) clinical support, and (3) personal support. Key sources of informational and clinical support included pre-optimisation clinics, surgeons, and physiotherapists. Key topics for informational support included pain, pain management, and recovery trajectories. Personal support was provided by family, friends, other TKA patients, employers, and themselves. CONCLUSIONS: Patient needs and expectations for support are shaped both before and after TKA surgery. Patients with an overall positive TKA experience had improvement in their knee pain, stiffness or functioning post-TKA, had their major expectations and needs for support met during their TKA recovery, and believed that any significant future expectations or needs for ongoing support would be adequately met. In contrast, patients with an overall negative TKA experience had at least one major expectation or need for support not met during their TKA recovery, even in cases where they had good TKA outcomes. Suggested interventions to improve the experience of persons receiving TKA include an expanded patient navigator model, revised pre-surgery educational materials, particularly around pain expectations and management, and comprehensive sharing of other patients' TKA experience.

Clinically Relevant Concentrations of Ketamine Inhibit Osteoclast Formation In Vitro in Mouse Bone Marrow Cultures.

Ketamine has been used safely in clinics for decades for analgesia and anesthesia. It is increasingly popular in clinical practice due to its new uses and importance for emergency procedures. It is known that ketamine is sequestered in the bone marrow and the major receptors for ketamine, noncompetitive N-methyl-d-aspartate receptors (NMDARs), are expressed in osteoclasts (OCs) and osteoblasts. However, the impact of ketamine on OCs or osteoblasts is unknown. In this study, we investigated the effects of ketamine on osteoclastogenesis and regulation of NMDARs expression in vitro. Bone marrows (BMs) or bone marrow macrophages (BMMs) were cultured in the presence of macrophage colony-stimulating factor (M-CSF) and receptor activator of nuclear factor kappa-B ligand (RANKL) with or without ketamine for up to 6 days. OC formation peaked at day 5. On day 5 of culture, ketamine inhibited OC formation from both BM and BMM cultures at clinically relevant concentrations (3-200 µM). Ketamine inhibited RANKL-induced expression of nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 1 (NFATc1) in BMM cultures. Inhibition of ketamine on RANKL-induced osteoclastogenesis is associated with down-regulation of NMDARs. In addition, ketamine significantly inhibited the M-CSF induced migration of BMMs, inhibited cell fusion and significantly increased mature OC apoptosis. We conclude that clinically relevant concentrations of ketamine inhibit OC formation in both BM and BMM cultures in vitro through inhibiting migration and fusion process and enhancing mature OC apoptosis. It is likely that ketamine regulates osteoclastogenesis, at least in part, via its effects on NMDAR expression. J. Cell. Biochem. 118: 914-923, 2017. © 2016 Wiley Periodicals, Inc.

Sperm contamination in archived and contemporary herring samples.

Studies using archived scales and otoliths to examine ancient fish populations have become increasingly common, despite many methodological challenges in ancient DNA research. Here, we describe a case of DNA contamination in both modern and historical samples of Pacific herring (Clupea pallasii), where the source of the contamination is likely from milt spillage during collection. We describe a series of experiments to remove contamination using pre-extraction wash treatments. Though contamination was easily removed from contemporary fin clippings, no method was successful at removing contamination from historical scales. We discuss the implications of our findings to the genetic analysis of archived samples.