The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA). Synovial fluid (SF) from patients with esOA, non-OA knee injury, and inflammatory knee arthritis were analyzed for 35 potential markers using immunoassays. Partial least square discriminant analysis (PLS-DA) was used to derive a biomarker model for cohort classification. The ability of the biomarker model to diagnose esOA was validated by identical wide-spectrum SF analysis of a test cohort of ten patients with esOA.Aims
Methods
This annotation briefly reviews the history of artificial intelligence and machine learning in health care and orthopaedics, and considers the role it will have in the future, particularly with reference to statistical analyses involving large datasets. Cite this article:
Osteoarthritis (OA) is the most prevalent joint disease. However, the specific and definitive genetic mechanisms of OA are still unclear. Tissue-related transcriptome-wide association studies (TWAS) of hip OA and knee OA were performed utilizing the genome-wide association study (GWAS) data of hip OA and knee OA (including 2,396 hospital-diagnosed hip OA patients versus 9,593 controls, and 4,462 hospital-diagnosed knee OA patients versus 17,885 controls) and gene expression reference to skeletal muscle and blood. The OA-associated genes identified by TWAS were further compared with the differentially expressed genes detected by the messenger RNA (mRNA) expression profiles of hip OA and knee OA. Functional enrichment and annotation analysis of identified genes was performed by the DAVID and FUMAGWAS tools.Aims
Methods
Unicompartmental knee arthroplasty (UKA) provides improved early functional outcomes and less postoperative morbidity and pain compared with total knee arthroplasty (TKA). Opioid prescribing has increased in the last two decades, and recently states in the USA have developed online Prescription Drug Monitoring Programs to prevent overprescribing of controlled substances. This study evaluates differences in opioid requirements between patients undergoing TKA and UKA. We retrospectively reviewed 676 consecutive TKAs and 241 UKAs. Opioid prescriptions in morphine milligram equivalents (MMEs), sedatives, benzodiazepines, and stimulants were collected from State Controlled Substance Monitoring websites six months before and nine months after the initial procedures. Bivariate and multivariate analysis were performed for patients who had a second prescription and continued use.Aims
Patients and Methods
The National Hip Fracture Database (NHFD) publishes hospital-level risk-adjusted mortality rates following hip fracture surgery in England, Wales and Northern Ireland. The performance of the risk model used by the NHFD was compared with the widely-used Nottingham Hip Fracture Score. Data from 94 hospitals on patients aged 60 to 110 who had hip fracture surgery between May 2013 and July 2013 were analysed. Data were linked to the Office for National Statistics (ONS) death register to calculate the 30-day mortality rate. Risk of death was predicted for each patient using the NHFD and Nottingham models in a development dataset using logistic regression to define the models’ coefficients. This was followed by testing the performance of these refined models in a second validation dataset.Objectives
Methods
The aim of this study was to evaluate the functional outcome in patients undergoing implant removal (IR) after fracture fixation below the level of the knee. All adult patients (18 to 75 years) undergoing IR after fracture fixation below the level of the knee between November 2014 and September 2016 were included as part of the WIFI (Wound Infections Following Implant Removal Below the Knee) trial, performed in 17 teaching hospitals and two university hospitals in The Netherlands. In this multicentre prospective cohort, the primary outcome was the difference in functional status before and after IR, measured by the Lower Extremity Functional Scale (LEFS), with a minimal clinically important difference of nine points.Aims
Patients and Methods
The purpose of this study was to develop a prognostic model for
predicting survival of patients undergoing surgery owing to metastatic
bone disease (MBD) in the appendicular skeleton. We included a historical cohort of 130 consecutive patients (mean
age 64 years, 30 to 85; 76 females/54 males) who underwent joint
arthroplasty surgery (140 procedures) owing to MBD in the appendicular
skeleton during the period between January 2003 and December 2008.
Primary cancer, pre-operative haemoglobin, fracture Aims
Methods
Electronic forms of data collection have gained interest in recent
years. In orthopaedics, little is known about patient preference
regarding pen-and-paper or electronic questionnaires. We aimed to
determine whether patients undergoing total hip (THR) or total knee
replacement (TKR) prefer pen-and-paper or electronic questionnaires
and to identify variables that predict preference for electronic
questionnaires. We asked patients who participated in a multi-centre cohort study
investigating improvement in health-related quality of life (HRQoL)
after THR and TKR using pen-and-paper questionnaires, which mode
of questionnaire they preferred. Patient age, gender, highest completed
level of schooling, body mass index (BMI), comorbidities, indication
for joint replacement and pre-operative HRQoL were compared between
the groups preferring different modes of questionnaire. We then
performed logistic regression analyses to investigate which variables
independently predicted preference of electronic questionnaires.Objectives
Methods
The influence of identifiable pre-operative factors on the outcome
of eccentric rotational acetabular osteotomy (ERAO) is unknown.
We aimed to determine the factors that might influence the outcome,
in order to develop a scoring system for predicting the prognosis
for patients undergoing this procedure. We reviewed 700 consecutive ERAOs in 54 men and 646 women with
symptomatic acetabular dysplasia or early onset osteoarthritis (OA)
of the hip, which were undertaken between September 1989 and March
2013. The patients’ pre-operative background, clinical and radiological
findings were examined retrospectively. Multivariate Cox regression
analysis was performed using the time from the day of surgery to
a conversion to total hip arthroplasty (THA) as an endpoint. A risk
score was calculated to predict the prognosis for conversion to
THA, and its predictive capacity was investigated.Aims
Patients and Methods
Peri-articular soft-tissue masses or ‘pseudotumours’
can occur after large-diameter metal-on-metal (MoM) resurfacing
of the hip and conventional total hip replacement (THR). Our aim
was to assess the incidence of pseudotumour formation and to identify
risk factors for their formation in a prospective cohort study. A total of 119 patients who underwent 120 MoM THRs with large-diameter
femoral heads between January 2005 and November 2007 were included
in the study. Outcome scores, serum metal ion levels, radiographs
and CT scans were obtained. Patients with symptoms or an identified
pseudotumour were offered MRI and an ultrasound-guided biopsy. There were 108 patients (109 hips) eligible for evaluation by
CT scan at a mean follow-up of 3.6 years (2.5 to 4.5); 42 patients
(39%) were diagnosed with a pseudotumour. The hips of 13 patients
(12%) were revised to a polyethylene acetabular component with small-diameter
metal head. Patients with elevated serum metal ion levels had a
four times increased risk of developing a pseudotumour. This study shows a substantially higher incidence of pseudotumour
formation and subsequent revisions in patients with MoM THRs than
previously reported. Because most revision cases were identified
only after an intensive screening protocol, we recommend close monitoring
of patients with MoM THR.
The April 2012 Children’s orthopaedics Roundup360 looks at osteonecrosis of the femoral head and surgery for dysplasia, femoral head blood flow during surgery, femoroacetabular impingement and sport in adolescence, the Drehmann sign, a predictive algorithm for septic arthritis, ACL reconstruction and arthrofibrosis in children, spinal cord monitoring for those less than four years old, arthroereisis for the flexible flat foot, fixing the displaced lateral humeral fracture, and mobile phones and inclinometer applications
Clinical prediction algorithms are used to differentiate
transient synovitis from septic arthritis. These algorithms typically
include the erythrocyte sedimentation rate (ESR), although in clinical practice
measurement of the C-reactive protein (CRP) has largely replaced
the ESR. We evaluated the use of CRP in a predictive algorithm. The records of 311 children with an effusion of the hip, which
was confirmed on ultrasound, were reviewed (mean age 5.3 years (0.2
to 15.1)). Of these, 269 resolved without intervention and without
long-term sequelae and were considered to have had transient synovitis.
The remaining 42 underwent arthrotomy because of suspicion of septic
arthritis. Infection was confirmed in 29 (18 had micro-organisms
isolated and 11 had a high synovial fluid white cell count). In
the remaining 13 no evidence of infection was found and they were
also considered to have had transient synovitis. In total 29 hips
were categorised as septic arthritis and 282 as transient synovitis.
The temperature, weight-bearing status, peripheral white blood cell
count and CRP was reviewed in each patient. A CRP >
20 mg/l was the strongest independent risk factor for
septic arthritis (odds ratio 81.9, p <
0.001). A multivariable
prediction model revealed that only two determinants (weight-bearing
status and CRP >
20 mg/l) were independent in differentiating septic
arthritis from transient synovitis. Individuals with neither predictor
had a <
1% probability of septic arthritis, but those with both
had a 74% probability of septic arthritis. A two-variable algorithm
can therefore quantify the risk of septic arthritis, and is an excellent
negative predictor.
