Methods

3D-printed titanium implants were inserted into an oversized drill-hole in the tibiae of C57Bl/6 mice (n = 54). After implantation, the mice were randomly divided into three treatment groups (phosphate buffered saline (PBS)-control, iPTH, and delayed iPTH). Radiological analysis, micro-CT (µCT), and biomechanical pull-out testing were performed to assess implant loosening, bone formation, and osseointegration. Peri-implant tissue formation and cellular composition were evaluated by histology.

Methods

Patient peri-implant fibrotic tissue was analyzed for NETs biomarkers. To enhance osseointegration in loose implant conditions, an innate immune system pathway (NETs) was either inhibited (Pad4^-/- mice) or resolved with a pharmacological agent (DNase 1) in a murine model of osseointegration failure.

Methods

We retrospectively reviewed 19,428 patients undergoing a primary THA or TKA between 1 February 2016 and 31 December 2019. Two reductions in the number of opioid tablets prescribed at discharge were implemented over this time; as such, we analyzed three periods (P1, P2, and P3) with different routine discharge MME (750, 520, and 320 MMEs, respectively). We investigated 90-day refill rates, refill MMEs, and whether discharge MMEs were associated with represcribing in a multivariate model.

Methods

Peri-implant membrane was retrieved from five patients during total hip revision surgery and analyzed for the presence of NETs (citH3+ with extracellular DNA) via immunofluorescence. A Ti-6Al-4V implant was inserted in an oversized drill-hole in the right proximal tibia of 8-week-old C57BL/6J and PAD4 knockout mice (n=3 per group). Fourteen days later, all mice were euthanized, and implanted tibias were dissected. Fibrosis and osseointegration at the bone-implant interface were assessed by micro-computed tomography (microCT) and hematoxylin and eosin (H&E) staining. H&E samples were scored blindly by the investigator and another observer for signs of poor (score=0) to excellent osseointegration (score=3) using a rubric established in our lab.

Methods

In-vitro: Xen 36 S. aureus biofilm was grown on Ti-6Al-4V mouse tibial implants for 1 day or 5 days and subsequently exposed to growth media, 1000× minimal inhibitory concentration (MIC) Vancomycin, or 5× MIC PlySs2. Implants were sonicated and analyzed for Colony Forming Units (CFU).

In-vivo: A Ti-6Al-4V implant was inserted into the proximal tibia of C57BL/6J mice (n=21). All mice received 10⁴ CFU inoculation of Xen 36 S. aureus to the knee joint capsule and the infection was permitted 5 days to progress. On day 5 the mice were separated into three groups (n=7/group): (1) no further surgical intervention (control group), (2) irrigation and debridement (I&D) with saline, (3) I&D with 2mg/mL PlySs2. No implant-exchange was performed to mimic a debridement, antibiotic, and implant retention (DAIR) therapeutic strategy. All mice were sacrificed at day 10.

Materials and Methods

An implant was inserted into the right tibia of 16-week-old female C57BL/6 mice (n = 38). Mice received anti-VEGF receptor-1 (VEGFR-1) antibody (25 mg/kg) and VEGF receptor-2 (VEGFR-2) antibody (25 mg/kg; n = 19) or an isotype control antibody (n = 19). Flow cytometric (n = 4/group) and immunofluorescent (n = 3/group) analyses were performed at two weeks post-implantation to detect the distribution and density of CD31^hiEMCN^hi endothelium. RNA sequencing analysis was performed using sorted CD31^hiEMCN^hi endothelial cells (n = 2/group). Osteoblast lineage cells expressing osterix (OSX) and osteopontin (OPN) were also detected with immunofluorescence. Mechanical pull-out testing (n = 12/group) was used at four weeks post-implantation to determine the strength of the bone-implant interface. After pull-out testing, the tissue attached to the implant surface was harvested. Whole mount immunofluorescent staining of OSX and OPN was performed to determine the amount of osteoblast lineage cells.

Patients and Methods

A retrospective review of 91 patients who underwent revision THA using 96 CFACs was undertaken, comparing features between radiologically failed and successful cases. Patient characteristics (demographic, clinical, and radiological) and implant features (design characteristics and intraoperative features) were collected. There were 74 women and 22 men; their mean age was 62 years (31 to 85). The mean follow-up was 24.9 months (sd 27.6; 0 to 116). Two sets of statistical analyses were performed: 1) univariate analyses (Pearson’s chi-squared and independent-samples Student’s t-tests) for each feature; and 2) bivariable logistic regressions using features identified from a random forest analysis.

Patients and Methods

A total of 28 OxZr femoral heads were retrieved during revision total hip arthroplasty (THA) and matched to 28 retrieved CoCr heads according to patient demographics. The mean age at index was 56 years (46 to 83) in the OxZr group and 70 years (46 to 92) in the CoCr group. Fretting and corrosion scores of the female taper of the heads were measured according to the modified Goldberg scoring method.

Methods

We reviewed 96 CFAC cases performed in 91 patients between 2004 and 2017, from which 36 variables were collected spanning patient demographics, pre-operative clinical and radiographic features, intraoperative information, and implant design characteristics. Patient demographics and relevant clinical features were collected from individual medical records. Radiographic review included analysis of pre-operative radiographs, computer tomographic (CT) scans, and serial post-operative radiographs. Radiographic failure was defined as loosening or gross migration as determined by a board-certified orthopedic surgeon. CFAC implant design characteristics and intra-operative features were collected from the design record, surgical record and post-operative radiograph for each case respectively.

Two sets of statistical analyses were performed with this dataset. First, univariate analyses were performed for each variable, comprising of a Pearson chi-square test for categorical variables and an independent t-test for continuous variables. Second, a random forest supervised machine learning method was applied to identify the most influential variables within the dataset, which were then used to perform a bivariable logistic regression to generate odds ratios. Statistical significance for this study was set at p < 0.05.