Femoral and tibial phenotypes of varus alignment in a Southeast Asian arthritic population: a descriptive study.

INTRODUCTION: Knowledge of femoral and tibial morphology is important for patient-specific surgery in both joint reconstruction and preservation procedures. Studies evaluating morphological variance in femoral and tibial alignments in Asian populations are scarce. This is the first descriptive study evaluating the femoral and tibial phenotypes of varus alignment in a Southeast Asian population. METHODS: Long-leg coronal standing radiographs of 2021 limbs were obtained, and the hip-knee-ankle angle, mechanical lateral distal femoral angle, medial proximal tibial angle and joint line convergence angle were measured. Joint line obliquity was calculated, and the knees were classified according to the Coronal Plane Alignment of Knee (CPAK) classification. Descriptive analyses on alignment parameters and demographic data (age, gender, ethnicity and body mass index [BMI]) were performed and entered into a linear regression model. RESULTS: The highest frequency of limb alignment in the population was found to be CPAK type I (52.71%, n = 1003). Tibial varus was the largest contributor of varus malignment. Of the varus knees (n = 1247), varus deformity was found solely in the tibia (68.60%), solely in the femur (2.07%) and was contributed by both the femur and the tibia (4.97%). In the linear regression model, BMI was found to be a strong determinant for femoral varus (P = 0.004) and joint line incongruence (P < 0.001). CONCLUSION: The findings of this study will be important to surgeons during planning for joint preservation procedures (such as corrective osteotomies) and joint arthroplasties to restore alignment.

Simultaneous bilateral revision total knee arthroplasty following Abiotrophia defectiva infection.

A 65-year old man presented with 6-week history of bilateral knee pain and swelling, with difficulty mobilising. He had bilateral total knee arthroplasties in situ performed 5 years prior complicated by postoperative wound infection. Bilateral synovial fluid cultures were positive for Abiotrophia defectiva, and extensive investigations had not identified an extra-articular source of infection. Failing debridement antibiotic and implant retention procedure, the patient underwent a simultaneous bilateral 2-stage revision with articulated cement spacers impregnated with vancomycin and gentamycin. The patient received 6 weeks of intravenous antibiotics after each stage. A. defectiva is a nutritiously fastidious organism, posing a challenge for clinical laboratories to isolate and perform antimicrobial susceptibility testing, yet prosthetic joint infections caused by A. defectiva are scarce in literature and present atypically with subacute signs of chronic infection. This poses a diagnostic and therapeutic challenge, and two-stage revision is the only documented treatment that successfully eradicates the infection.

Prognostic DNA methylation biomarkers in ovarian cancer.

PURPOSE: Aberrant DNA methylation, now recognized as a contributing factor to neoplasia, often shows definitive gene/sequence preferences unique to specific cancer types. Correspondingly, distinct combinations of methylated loci can function as biomarkers for numerous clinical correlates of ovarian and other cancers. EXPERIMENTAL DESIGN: We used a microarray approach to identify methylated loci prognostic for reduced progression-free survival (PFS) in advanced ovarian cancer patients. Two data set classification algorithms, Significance Analysis of Microarray and Prediction Analysis of Microarray, successfully identified 220 candidate PFS-discriminatory methylated loci. Of those, 112 were found capable of predicting PFS with 95% accuracy, by Prediction Analysis of Microarray, using an independent set of 40 advanced ovarian tumors (from 20 short-PFS and 20 long-PFS patients, respectively). Additionally, we showed the use of these predictive loci using two bioinformatics machine-learning algorithms, Support Vector Machine and Multilayer Perceptron. CONCLUSION: In this report, we show that highly prognostic DNA methylation biomarkers can be successfully identified and characterized, using previously unused, rigorous classifying algorithms. Such ovarian cancer biomarkers represent a promising approach for the assessment and management of this devastating disease.