Patient "No-Show" Increases the Risk of 90-Day Complications Following Primary Total Knee Arthroplasty: A Retrospective Cohort Study of 6,776 Patients.

BACKGROUND: Patients who "no-show" (NS) clinical appointments are at a high risk of adverse health outcomes. The objective of this study was to evaluate and characterize the relationship between NS visits prior to primary total knee arthroplasty (TKA) and 90-day complications after TKA. METHODS: We retrospectively reviewed 6,776 consecutive patients undergoing primary TKA. Study groups were separated based on whether patients who NS versus always attended their appointment. A NS was defined as an intended appointment that was not canceled or rescheduled ≤2 hours before the appointment in which the patient did not show. Data collected included total number of follow-up appointments prior to surgery, patient demographics, comorbidities, and 90-day postoperative complications. RESULTS: Patients who have ≥3 NS appointments had 1.5 times increased odds of a surgical site infection (odds ratio (OR) 1.54, P = .002) compared to always attended patients. Patients who were ≤65 years old (OR: 1.41, P < .001), smokers (OR: 2.01, P < .001), and had a Charlson comorbidity index ≥3 (OR: 4.48, P < .001) were more likely to miss clinical appointments. CONCLUSION: Patients who have ≥3 NS appointments prior to TKA had an increased risk for surgical site infection. Sociodemographic factors were associated with higher odds of missing a scheduled clinical appointment. These data suggest that orthopaedic surgeons should consider NS data as an important clinical decision-making tool to assess risk for postoperative complications to minimize complications following TKA.

Public reporting of outcomes in radiation oncology: the National Prostate Cancer Audit.

The public reporting of patient outcomes is crucial for quality improvement and informing patient choice. However, outcome reporting in radiotherapy, despite being a major component of cancer control, is extremely sparse globally. Public reporting has many challenges, including difficulties in defining meaningful measures of treatment quality, limitations in data infrastructure, and fragmented health insurance schemes. The National Prostate Cancer Audit (NPCA), done in the England and Wales National Health Service (NHS), shows that it is feasible to develop outcome indicators for radiotherapy treatment, including patient-reported outcomes. The NPCA provides a transparent mechanism for comparing the performance of all NHS providers, with results accessible to patients, providers, and policy makers. Using the NPCA as a case study, we discuss the development of a radiotherapy-outcomes reporting programme, its impact and future potential, and the challenges and opportunities to develop this approach across other tumour types and in different health systems.

Digital contact tracing technologies in epidemics: a rapid review.

BACKGROUND: Reducing the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global priority. Contact tracing identifies people who were recently in contact with an infected individual, in order to isolate them and reduce further transmission. Digital technology could be implemented to augment and accelerate manual contact tracing. Digital tools for contact tracing may be grouped into three areas: 1) outbreak response; 2) proximity tracing; and 3) symptom tracking. We conducted a rapid review on the effectiveness of digital solutions to contact tracing during infectious disease outbreaks. OBJECTIVES: To assess the benefits, harms, and acceptability of personal digital contact tracing solutions for identifying contacts of an identified positive case of an infectious disease. SEARCH METHODS: An information specialist searched the literature from 1 January 2000 to 5 May 2020 in CENTRAL, MEDLINE, and Embase. Additionally, we screened the Cochrane COVID-19 Study Register. SELECTION CRITERIA: We included randomised controlled trials (RCTs), cluster-RCTs, quasi-RCTs, cohort studies, cross-sectional studies and modelling studies, in general populations. We preferentially included studies of contact tracing during infectious disease outbreaks (including COVID-19, Ebola, tuberculosis, severe acute respiratory syndrome virus, and Middle East respiratory syndrome) as direct evidence, but considered comparative studies of contact tracing outside an outbreak as indirect evidence. The digital solutions varied but typically included software (or firmware) for users to install on their devices or to be uploaded to devices provided by governments or third parties. Control measures included traditional or manual contact tracing, self-reported diaries and surveys, interviews, other standard methods for determining close contacts, and other technologies compared to digital solutions (e.g. electronic medical records). DATA COLLECTION AND ANALYSIS: Two review authors independently screened records and all potentially relevant full-text publications. One review author extracted data for 50% of the included studies, another extracted data for the remaining 50%; the second review author checked all the extracted data. One review author assessed quality of included studies and a second checked the assessments. Our outcomes were identification of secondary cases and close contacts, time to complete contact tracing, acceptability and accessibility issues, privacy and safety concerns, and any other ethical issue identified. Though modelling studies will predict estimates of the effects of different contact tracing solutions on outcomes of interest, cohort studies provide empirically measured estimates of the effects of different contact tracing solutions on outcomes of interest. We used GRADE-CERQual to describe certainty of evidence from qualitative data and GRADE for modelling and cohort studies. MAIN RESULTS: We identified six cohort studies reporting quantitative data and six modelling studies reporting simulations of digital solutions for contact tracing. Two cohort studies also provided qualitative data. Three cohort studies looked at contact tracing during an outbreak, whilst three emulated an outbreak in non-outbreak settings (schools). Of the six modelling studies, four evaluated digital solutions for contact tracing in simulated COVID-19 scenarios, while two simulated close contacts in non-specific outbreak settings. Modelling studies Two modelling studies provided low-certainty evidence of a reduction in secondary cases using digital contact tracing (measured as average number of secondary cases per index case - effective reproductive number (R eff)). One study estimated an 18% reduction in R eff with digital contact tracing compared to self-isolation alone, and a 35% reduction with manual contact-tracing. Another found a reduction in R eff for digital contact tracing compared to self-isolation alone (26% reduction) and a reduction in R eff for manual contact tracing compared to self-isolation alone (53% reduction). However, the certainty of evidence was reduced by unclear specifications of their models, and assumptions about the effectiveness of manual contact tracing (assumed 95% to 100% of contacts traced), and the proportion of the population who would have the app (53%). Cohort studies Two cohort studies provided very low-certainty evidence of a benefit of digital over manual contact tracing. During an Ebola outbreak, contact tracers using an app found twice as many close contacts per case on average than those using paper forms. Similarly, after a pertussis outbreak in a US hospital, researchers found that radio-frequency identification identified 45 close contacts but searches of electronic medical records found 13. The certainty of evidence was reduced by concerns about imprecision, and serious risk of bias due to the inability of contact tracing study designs to identify the true number of close contacts. One cohort study provided very low-certainty evidence that an app could reduce the time to complete a set of close contacts. The certainty of evidence for this outcome was affected by imprecision and serious risk of bias. Contact tracing teams reported that digital data entry and management systems were faster to use than paper systems and possibly less prone to data loss. Two studies from lower- or middle-income countries, reported that contact tracing teams found digital systems simpler to use and generally preferred them over paper systems; they saved personnel time, reportedly improved accuracy with large data sets, and were easier to transport compared with paper forms. However, personnel faced increased costs and internet access problems with digital compared to paper systems. Devices in the cohort studies appeared to have privacy from contacts regarding the exposed or diagnosed users. However, there were risks of privacy breaches from snoopers if linkage attacks occurred, particularly for wearable devices. AUTHORS' CONCLUSIONS: The effectiveness of digital solutions is largely unproven as there are very few published data in real-world outbreak settings. Modelling studies provide low-certainty evidence of a reduction in secondary cases if digital contact tracing is used together with other public health measures such as self-isolation. Cohort studies provide very low-certainty evidence that digital contact tracing may produce more reliable counts of contacts and reduce time to complete contact tracing. Digital solutions may have equity implications for at-risk populations with poor internet access and poor access to digital technology. Stronger primary research on the effectiveness of contact tracing technologies is needed, including research into use of digital solutions in conjunction with manual systems, as digital solutions are unlikely to be used alone in real-world settings. Future studies should consider access to and acceptability of digital solutions, and the resultant impact on equity. Studies should also make acceptability and uptake a primary research question, as privacy concerns can prevent uptake and effectiveness of these technologies.

Comparative assessment of DNA methylation patterns between reduced representation bisulfite sequencing and Sequenom EpiTyper methylation analysis.

AIM: Validation of sequencing-based DNA methylation data is an important step for meaningful translation of findings. However, there has been limited assessment of different platforms to validate methylation data from next generation sequencing. METHODS: We performed a comparative methylation analysis between the genome-wide platform of reduced representation bisulfite sequencing with a targeted, Sequenom EpiTyper platform (four genes were analyzed in 15 cell lines covering 52 CpG sites). RESULTS: We show that the accuracy of validation substantially improves if results from multiple and adjacent CpG sites are combined rather than at single CpG sites. We demonstrate increased read number improves accuracy of reduced representation bisulfite sequencing results. Further, by using series of replicates, we document variation in samples analyzed by Sequenom EpiTyper, indicating the importance of including replicates to increase precision. CONCLUSION: The results reveal potential sources of bias and provide a guideline for refining study design for DNA methylation analysis.

Quantifying severe urinary complications after radical prostatectomy: the development and validation of a surgical performance indicator using hospital administrative data.

OBJECTIVES: To develop and validate a surgical performance indicator based on severe urinary complications that require an intervention within 2 years of radical prostatectomy (RP), identified in hospital administrative data. PATIENTS AND METHODS: Men who underwent RP between 2008 and 2012 in England were identified using hospital administrative data. A transparent coding framework based on procedure codes was developed to identify severe urinary complications which were grouped into 'stricture', 'incontinence' and 'other'. Their validity as a performance indicator was assessed by evaluating the consistency with diagnosis codes and association with patient and surgical characteristics. Kaplan-Meier methods were used to assess time to first occurrence and multivariable logistic regression was used to estimate adjusted odds ratios (ORs) for patient and surgical characteristics. RESULTS: A total of 17 299 men were included, of whom 2695 (15.6%) experienced at least one severe urinary complication within 2 years. High proportions of men with a complication had relevant diagnosis codes: 86% for strictures and 93% for incontinence. Urinary complications were more common in men from poorer socio-economic backgrounds (OR comparing lowest with highest quintile: 1.45; 95% confidence interval [CI] 1.26-1.67) and in those with prolonged length of hospital stay (OR 1.54, 95% CI 1.40-1.69), and were less common in men who underwent robot-assisted surgery (OR 0.65, 95% CI 0.58-0.74). CONCLUSION: These results show that severe urinary complications identified in administrative data provide a medium-term performance indicator after RP. They can be used for research assessing outcomes of treatment methods and for service evaluation comparing performance of prostate cancer surgery providers.

Efficient Recycled Algorithms for Quantitative Trait Models on Phylogenies.

We present an efficient and flexible method for computing likelihoods for phenotypic traits on a phylogeny. The method does not resort to Monte Carlo computation but instead blends Felsenstein's discrete character pruning algorithm with methods for numerical quadrature. It is not limited to Gaussian models and adapts readily to model uncertainty in the observed trait values. We demonstrate the framework by developing efficient algorithms for likelihood calculation and ancestral state reconstruction under Wright's threshold model, applying our methods to a data set of trait data for extrafloral nectaries across a phylogeny of 839 Fabales species.