Associations of dexamethasone's effect on morphine consumption after total knee arthroplasty-Subgroup analyses.

The DEXamethasone twice for pain treatment after Total Knee Arthroplasty (DEX-2-TKA) trial showed that adding one and two doses of 24 mg intravenous dexamethasone to paracetamol, ibuprofen and local infiltration analgesia, reduced morphine consumption (primary outcome) within 48 h after TKA. We aimed to explore the differences in the effect of dexamethasone on morphine consumption in different subgroups. Quantile regression adjusted for site was used to test for significant interaction between the predefined dichotomised subgroups and treatment group. The subgroups were defined based on baseline data: sex (male/female), age (≤65 years/>65 years), American Society of Anaesthesiologists (ASA)-score (ASA I + II/III), visual analogue score of preoperative pain at rest (≤30 mm/>30 mm), pain during mobilisation (≤30 mm/>30 mm), type of anaesthesia (spinal anaesthesia/general anaesthesia and spinal converted to general anaesthesia), and prior daily use of analgesics (either paracetamol and/or NSAID/neither). These analyses were supplemented with post hoc multivariate linear regression analyses. Test of interaction comparing sex in the pairwise comparison between DX2 (dexamethasone [24 mg] + dexamethasone [24 mg]) versus placebo (p = .02), showed a larger effect of dexamethasone on morphine consumption in male patients compared to females. Test of interaction comparing age in the pairwise comparison between DX1 (dexamethasone [24 mg] + placebo) versus placebo (p = .04), showed a larger effect of dexamethasone on morphine consumption in younger patients (≤65 years) compared to older. All remaining subgroup analyses showed no evidence of a difference. The supplemental multivariate analyses did not support any significant interaction for sex (p = .256) or age (p = .730) but supported a significant interaction with the type of anaesthesia (p < .001). Our results from the quantile regression analyses indicate that the male sex and younger age (≤65 years) may be associated with a larger analgesic effect of dexamethasone than the effects in other types of patients. However, this is not supported by post-hoc multivariate linear regression analyses. The two types of analyses both supported a possible interaction with the type of anaesthesia.

Prolonged effects of dexamethasone following total knee arthroplasty: A pre-planned sub-study of the DEX-2-TKA trial.

OBJECTIVES: The DEX-2-TKA trial demonstrated that one and two doses of 24 mg intravenous dexamethasone reduced opioid consumption and pain after total knee arthroplasty (TKA). We aimed to investigate the prolonged effects of dexamethasone after the 48-h intervention period. DESIGN: This was a prospective, pre-planned questionnaire follow-up on postoperative days 3-7 of patients in the DEX-2-TKA trial that randomly received: DX1 (dexamethasone 24 mg + placebo), DX2 (dexamethasone 24 mg + dexamethasone 24 mg), and placebo (placebo + placebo) perioperatively and 24 h later. SETTING: A multicenter trial performed at five Danish hospitals. PARTICIPANTS: We analyzed 434 of 485 adult participants enrolled in the DEX-2-TKA trial. OUTCOME MEASURES: Primary outcome was difference between groups in average of all numerical rating scale (NRS) pain scores reported in the morning, at bedtime, and the daily average pain on postoperative days 3-7. Secondary outcomes were sleep quality and patient satisfaction. RESULTS: The median (interquartile range) pain intensity levels for postoperative days 3-7 were: DX2 3.2 (2.1-4.3); DX1 3.3 (2.3-4.1); and placebo 3.3 (2.5-4.7). Hodges-Lehmann median differences between groups were: 0 (95% confidence interval - 0.54 to 0.2), P = 0.38 between DX1 and placebo; 0.1 (-0.47 to 0.33), p = .87 between DX1 and DX2; and 0.1 (-0.6 to 0.13), p = .20 between DX2 and placebo. We found no relevant differences between groups on sleep quality on postoperative days 3-7 nor for patient satisfaction with the analgesic treatment. CONCLUSIONS: We found that neither one nor two doses of 24 mg intravenous dexamethasone demonstrated prolonged effects on overall pain or sleep quality on postoperative days 3-7 after total knee arthroplasty. We also found that dexamethasone had no effect on patient satisfaction. TRIAL REGISTRATION NUMBER: Clinicaltrials.gov NCT03506789 (main result trial).

Breath-Hold Diving Injuries - A Primer for Medical Providers.

ABSTRACT: Breath-hold divers, also known as freedivers, are at risk of specific injuries that are unique from those of surface swimmers and compressed air divers. Using peer-reviewed scientific research and expert opinion, we created a guide for medical providers managing breath-hold diving injuries in the field. Hypoxia induced by prolonged apnea and increased oxygen uptake can result in an impaired mental state that can manifest as involuntary movements or full loss of consciousness. Negative pressure barotrauma secondary to airspace collapse can lead to edema and/or hemorrhage. Positive pressure barotrauma secondary to overexpansion of airspaces can result in gas embolism or air entry into tissues and organs. Inert gas loading into tissues from prolonged deep dives or repetitive shallow dives with short surface intervals can lead to decompression sickness. Inert gas narcosis at depth is commonly described as an altered state similar to that experienced by compressed air divers. Asymptomatic cardiac arrhythmias are common during apnea, normally reversing shortly after normal ventilation resumes. The methods of glossopharyngeal breathing (insufflation and exsufflation) can add to the risk of pulmonary overinflation barotrauma or loss of consciousness from decreased cardiac preload. This guide also includes information for medical providers who are tasked with providing medical support at an organized breath-hold diving event with a list of suggested equipment to facilitate diagnosis and treatment outside of the hospital setting.

Hyperbaric oxygen therapy for long COVID (HOT-LoCO), an interim safety report from a randomised controlled trial.

BACKGROUND: With ~ 50 million individuals suffering from post-COVID condition (PCC), low health related quality of life (HRQoL) is a vast problem. Common symptoms of PCC, that persists 3 months from the onset of COVID-19 are fatigue, shortness of breath and cognitive dysfunction. No effective treatment options have been widely adopted in clinical practice. Hyperbaric oxygen (HBO2) is a candidate drug. METHODS: The objective of this interim analysis is to describe our cohort and evaluate the safety of HBO2 for post covid condition. In an ongoing randomised, placebo-controlled, double blind, clinical trial, 20 previously healthy subjects with PCC were assigned to HBO2 or placebo. Primary endpoints are physical domains in RAND-36; Physical functioning (PF) and Role Physical (RP) at 13 weeks. Secondary endpoints include objective physical tests. Safety endpoints are occurrence, frequency, and seriousness of Adverse Events (AEs). An independent data safety monitoring board (DSMB) reviewed unblinded data. The trial complies with Good Clinical Practice. Safety endpoints are evaluated descriptively. Comparisons against norm data was done using t-test. RESULTS: Twenty subjects were randomised, they had very low HRQoL compared to norm data. Mean (SD) PF 31.75 (19.55) (95% Confidence interval; 22.60-40.90) vs 83.5 (23.9) p < 0.001 in Rand-36 PF and mean 0.00 (0.00) in RP. Very low physical performance compared to norm data. 6MWT 442 (180) (95% CI 358-525) vs 662 (18) meters p < 0.001. 31 AEs occurred in 60% of subjects. In 20 AEs, there were at least a possible relationship with the study drug, most commonly cough and chest pain/discomfort. CONCLUSIONS: An (unexpectedly) high frequency of AEs was observed but the DSMB assessed HBO2 to have a favourable safety profile. Our data may help other researchers in designing trials. Trial Registration ClinicalTrials.gov: NCT04842448. Registered 13 April 2021, https://clinicaltrials.gov/ct2/show/NCT04842448 . EudraCT: 2021-000764-30. Registered 21 May 2021, https://www.clinicaltrialsregister.eu/ctr-search/trial/2021-000764-30/SE.

Pain treatment after total hip arthroplasty: Detailed statistical analysis plan for the RECIPE randomised clinical trial.

BACKGROUND: The RECIPE trial systematically investigates the effects of different combinations of paracetamol, ibuprofen and dexamethasone for pain treatment after total hip arthroplasty. To preserve transparency, minimise risk of bias and to prevent data-driven analysis, we present this detailed statistical analysis plan. METHODS: The RECIPE trial is a randomised, blinded, parallel four-group multicenter clinical trial for patients undergoing planned primary total hip arthroplasty. Interventions are initiated preoperatively and continued for 24 h postoperatively. Primary outcome is total opioid consumption 0-24 h after end of surgery. Primary analysis will be performed in the modified intention to treat population of all patients undergoing total hip arthroplasty, and all analyses will be stratified for site. We will perform pairwise comparisons between each of the four groups. The primary outcome will be analysed using the van Elteren test and we will present Hodges-Lehmann median differences and confidence intervals. Binary outcomes will be analysed using logistic regression. To preserve a family-wise error rate of <0.05, we will use a Bonferroni-adjusted alfa of 0.05/6 = 0.0083 for all six pairwise comparisons between groups when analysing the primary outcome. We will systematically assess the underlying statistical assumptions for each analysis. Data will be analysed by two blinded independent statisticians, and we will write abstracts covering all possible combinations of conclusions, before breaking the blind. DISCUSSION: The RECIPE trial will provide important information on benefit and harm of combinations of the most frequently used non-opioid analgesics for pain after primary hip arthroplasty.

Feasibility of monitoring the resolution of acute pulmonary embolism with non-contrast-enhanced magnetic resonance imaging at one day, one week, one, three, and six months.

BACKGROUND: Pulmonary embolism (PE) is a common cause of death with an incidence of approximately 1-2 cases per 1000 inhabitants in Europe and the United States. Treatment for PE is the administration of anticoagulants for at least three months. PURPOSE: To assess the feasibility of following the resolution rate of PE over time using repeated imaging with a non-contrast-enhanced magnetic resonance imaging (MRI) protocol. MATERIAL AND METHODS: Patients (n = 18) diagnosed with acute PE via computed tomography pulmonary angiography (CTPA) underwent non-contrast-enhanced MRI at two tertiary hospitals. The first MRI was performed within 36 h of CTPA, with follow-up at one week, one, three, and six months. The MRI sequence used was a non-contrast-enhanced standard two-dimensional steady-state free precession under free-breathing and without respiratory or cardiac gating. All MRI scans were then compared to the initial CTPA. The emboli were assessed visually for location and size, and clot burden was calculated using the Qanadli score. RESULTS: MRI revealed complete resolution in seven cases at one week, in five cases at one month, and in three cases at three months. The most significant resolution of emboli occurred within the first few weeks, with only 10% of the diagnosed emboli persisting at the one-month examination. CONCLUSION: The use of MRI imparts the ability to visualize PE without radiation and thus allows multiple examinations to be made, for example in studies investigating the resolution of PE or the evaluation of drug effect in clinical trials.

Wireless point-of-care ultrasound in a multiplace hyperbaric chamber.

Background: Electronic devices remain highly restricted from use during hyperbaric oxygen (HBO2) treatment due to risk of fire in a pressurized, oxygen-rich environment. Over recent decades, point-of- care ultrasound (POCUS) has established utility in most clinical environments except hyperbaric chambers, where only heavily modified POCUS devices have been used. This study evaluated proof of concept, safety, and performance of a wireless off-the-shelf handheld POCUS device in the hyperbaric environment. Materials and Methods: The GE Vscan Air was initially tested in a Class C chamber with 100% nitrogen up to 4.0 ATA and monitored. Second, the Vscan Air was paired with an encased Apple iPad, tested previously for hyperbaric use, and both were pressurized to 2.4 ATA in a Class A chamber (21% oxygen) and evaluated. Similarly, it was then tested at 2.8 ATA and also paired wirelessly with an iPad outside the chamber. Device temperature, image quality, functionality, and wireless connection were tested continuously. Results: The GE Vscan Air automatically shut off due to power button depression during initial compression; thus the power button was punctured with an 18-gauge needle to equalize gas pressure. Thereafter, the system performed well throughout all tests without degradation in function or image quality. The device did not overheat nor reach temperatures concerning for fire hazard. Further, wireless connection to out-of-chamber devices was maintained. Conclusions: Our results suggest that the GE Vscan Air can be used with minor modification in a multi- place hyperbaric chamber. Wireless functionality allows for pairing with a screen and device outside the chamber.

A fully automated algorithm for heart rate detection in post-dive precordial Doppler ultrasound.

Background: Doppler ultrasound is used currently in decompression research for the evaluation of venous gas emboli (VGE). Estimation of heart rate from post-dive Doppler ultrasound recordings can provide a tool for the evaluation of physiological changes from decompression stress, as well as aid in the development of automated VGE detection algorithms that relate VGE presence to cardiac activity. Method: An algorithm based on short-term autocorrelation was developed in MATLAB to estimate the heart rate in post-dive precordial Doppler ultrasound. The algorithm was evaluated on 21 previously acquired and labeled precordial recordings spanning Kisman-Masurel (KM) codes of 111-444 (KM I-IV) with manually derived instantaneous heart rates. Results: A window size of at least two seconds was necessary for robust and accurate instantaneous heart rate estimation with a mean error of 1.56 ± 7.10 bpm. Larger window sizes improved the algorithm performance, at the cost of beat-to-beat heart rate estimates. We also found that our algorithm provides good results for low KM grade Doppler recordings with and without flexion, and high KM grades without flexion. High KM grades observed after movement produced the greatest mean absolute error of 6.12 ± 8.40 bpm. Conclusion: We have developed a fully automated algorithm for the estimation of heart rate in post-dive precordial Doppler ultrasound recordings.

Comparing 'clinical hunch' against clinical decision support systems (PERC rule, wells score, revised Geneva score and YEARS criteria) in the diagnosis of acute pulmonary embolism.

BACKGROUND: Pulmonary embolism (PE) is a common and potentially life-threatening condition. Since it is considered a 'do not miss' diagnosis, PE tends to be over-investigated beyond the evidence-based clinical decision support systems (CDSS), which in turn subjects patients to unnecessary radiation and contrast agent exposure with no apparent benefits in terms of outcome. The purpose of this study was to evaluate the yield of 'clinical hunch' (gestalt) and four CDSS: the PERC Rule, Wells score, revised Geneva score, and Years criteria. METHODS: A review was conducted on the Electronic Medical Records (EMR) of 1566 patients from the Emergency Department at a tertiary teaching hospital who underwent CTPA from the 1st of January 2018 to the 31st of December 2019. The scores for the four CDSS were calculated retrospectively from the EMR data. We considered that a CTPA had been ordered on a clinical hunch when there was no mention of CDSS in the EMR, and no D-dimer test. A bypass of CDSS was confirmed when any step of the diagnostic algorithms was not followed. RESULTS: Of the total 1566 patients who underwent CTPA, 265 (17%) were positive for PE. The diagnosis yield from the five decision groups (clinical hunch and four CDSS) was as follows-clinical hunch, 15%; PERC rule, 18% (6% when bypassed); Wells score, 19% (11% when bypassed); revised Geneva score, 26% (13% when bypassed); and YEARS criteria, 18% (6% when bypassed). CONCLUSION: Clinicians should trust the evidence-based clinical decision support systems in line with the international guidelines to diagnose PE.

Profound hypercapnia but only moderate hypoxia found during underwater rugby play.

Background: Underwater rugby is a team sport where players try to score points with a negatively buoyant ball while submerged in a swimming pool. Reports of syncope incidents at the Swedish Championships led to us to investigate end-tidal oxygen and carbon dioxide levels during simulated match play. Methods: Eight male underwater rugby club players of varying experience participated. Repetitive measurements were made while players were defending during simulated match play. Each time a player surfaced they exhaled through a mouthpiece connected to a flow meter and a gas analyzer to measure tidal volume, PETO2 and PETCO2. Results: Measurements were made over 12 dives, with an average dive duration of 18.5 seconds. The mean maximal PETCO2 across the eight participants was 10.0 kPa (~75 mmHg) (range, 9.1-11.7 [~68-88]). The corresponding mean minimum PETO2 was 7.6 kPa (~57 mmHg) (6.3-10.4 [~47-78)). PETCO2 drifted upward, with the mean upward change from the first to last dive for each participant being +1.8 (~13.5 mmHg) (SD 1.74) kPa. A similar trend for PETO2 was not detected, with a mean change of -0.1 (~0.75 mmHg) (SD 3.79) kPa. Conclusion: Despite high PETCO2 values that were close to narcotic being recorded, these players seemed to regulate their urge to breathe based on hypoxia rather than hypercapnia.

An echo from the past: Building a Doppler repository for big data in diving research.

Decompression sickness (DCS) remains a major operational concern for diving operations, submarine escape and high-altitude jumps. Aside from DCS symptoms, venous gas emboli (VGE) detected with ultrasound post-dive are often used as a marker of decompression stress in humans, with a specificity of 100% even though the sensitivity is poor [1]. Being non-invasive, portable and non-ionizing, ultrasound is particularly suited to regular and repeated monitoring. It could help elucidate inter- and intra-subject variability in VGE and DCS susceptibility, but analyzing these recordings remains a cumbersome task [2].

Point-of-care ultrasound in a multiplace hyperbaric chamber.

Historically, electronic devices have been generally prohibited during hyperbaric oxygen (HBO2) therapy due to risk of fire in a pressurized, oxygen-rich environment. Point-of-care ultrasound (POCUS) however has emerged as a useful imaging modality in diverse clinical settings. Hyperbaric chambers treating critically ill patients would benefit from the application of POCUS at pressure to make real-time patient assessments. Thus far, POCUS during HBO2 therapy has been limited due to required equipment modifications to meet safety standards. Here we demonstrate proof of concept, safety, and successful performance of an off-the-shelf handheld POCUS system (SonoSite iViz) in a clinical hyperbaric environment without need for modification.

Range of Radiologist Performance in a Population-based Screening Cohort of 1 Million Digital Mammography Examinations.

Background There is great interest in developing artificial intelligence (AI)-based computer-aided detection (CAD) systems for use in screening mammography. Comparative performance benchmarks from true screening cohorts are needed. Purpose To determine the range of human first-reader performance measures within a population-based screening cohort of 1 million screening mammograms to gauge the performance of emerging AI CAD systems. Materials and Methods This retrospective study consisted of all screening mammograms in women aged 40-74 years in Stockholm County, Sweden, who underwent screening with full-field digital mammography between 2008 and 2015. There were 110 interpreting radiologists, of whom 24 were defined as high-volume readers (ie, those who interpreted more than 5000 annual screening mammograms). A true-positive finding was defined as the presence of a pathology-confirmed cancer within 12 months. Performance benchmarks included sensitivity and specificity, examined per quartile of radiologists' performance. First-reader sensitivity was determined for each tumor subgroup, overall and by quartile of high-volume reader sensitivity. Screening outcomes were examined based on the first reader's sensitivity quartile with 10 000 screening mammograms per quartile. Linear regression models were fitted to test for a linear trend across quartiles of performance. Results A total of 418 041 women (mean age, 54 years ± 10 [standard deviation]) were included, and 1 186 045 digital mammograms were evaluated, with 972 899 assessed by high-volume readers. Overall sensitivity was 73% (95% confidence interval [CI]: 69%, 77%), and overall specificity was 96% (95% CI: 95%, 97%). The mean values per quartile of high-volume reader performance ranged from 63% to 84% for sensitivity and from 95% to 98% for specificity. The sensitivity difference was very large for basal cancers, with the least sensitive and most sensitive high-volume readers detecting 53% and 89% of cancers, respectively (P < .001). Conclusion Benchmarks showed a wide range of performance differences between high-volume readers. Sensitivity varied by tumor characteristics. © RSNA, 2020 Online supplemental material is available for this article.

Comparison of a Deep Learning Risk Score and Standard Mammographic Density Score for Breast Cancer Risk Prediction.

Background Most risk prediction models for breast cancer are based on questionnaires and mammographic density assessments. By training a deep neural network, further information in the mammographic images can be considered. Purpose To develop a risk score that is associated with future breast cancer and compare it with density-based models. Materials and Methods In this retrospective study, all women aged 40-74 years within the Karolinska University Hospital uptake area in whom breast cancer was diagnosed in 2013-2014 were included along with healthy control subjects. Network development was based on cases diagnosed from 2008 to 2012. The deep learning (DL) risk score, dense area, and percentage density were calculated for the earliest available digital mammographic examination for each woman. Logistic regression models were fitted to determine the association with subsequent breast cancer. False-negative rates were obtained for the DL risk score, age-adjusted dense area, and age-adjusted percentage density. Results A total of 2283 women, 278 of whom were later diagnosed with breast cancer, were evaluated. The age at mammography (mean, 55.7 years vs 54.6 years; P < .001), the dense area (mean, 38.2 cm2 vs 34.2 cm2; P < .001), and the percentage density (mean, 25.6% vs 24.0%; P < .001) were higher among women diagnosed with breast cancer than in those without a breast cancer diagnosis. The odds ratios and areas under the receiver operating characteristic curve (AUCs) were higher for age-adjusted DL risk score than for dense area and percentage density: 1.56 (95% confidence interval [CI]: 1.48, 1.64; AUC, 0.65), 1.31 (95% CI: 1.24, 1.38; AUC, 0.60), and 1.18 (95% CI: 1.11, 1.25; AUC, 0.57), respectively (P < .001 for AUC). The false-negative rate was lower: 31% (95% CI: 29%, 34%), 36% (95% CI: 33%, 39%; P = .006), and 39% (95% CI: 37%, 42%; P < .001); this difference was most pronounced for more aggressive cancers. Conclusion Compared with density-based models, a deep neural network can more accurately predict which women are at risk for future breast cancer, with a lower false-negative rate for more aggressive cancers. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Bahl in this issue.

Identification of Women at High Risk of Breast Cancer Who Need Supplemental Screening.

Background Mammography screening reduces breast cancer mortality, but a proportion of breast cancers are missed and are detected at later stages or develop during between-screening intervals. Purpose To develop a risk model based on negative mammograms that identifies women likely to be diagnosed with breast cancer before or at the next screening examination. Materials and Methods This study was based on the prospective screening cohort Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA), 2011-2017. An image-based risk model was developed by using the Stratus method and computer-aided detection mammographic features (density, masses, microcalcifications), differences in the left and right breasts, and age. The lifestyle extended model included menopausal status, family history of breast cancer, body mass index, hormone replacement therapy, and use of tobacco and alcohol. The genetic extended model included a polygenic risk score with 313 single nucleotide polymorphisms. Age-adjusted relative risks and tumor subtype specific risks were estimated by using logistic regression, and absolute risks were calculated. Results Of 70 877 participants in the KARMA cohort, 974 incident cancers were sampled from 9376 healthy women (mean age, 54 years ± 10 [standard deviation]). The area under the receiver operating characteristic curve (AUC) for the image-based model was 0.73 (95% confidence interval [CI]: 0.71, 0.74). The AUCs for the lifestyle and genetic extended models were 0.74 (95% CI: 0.72, 0.75) and 0.77 (95% CI: 0.75, 0.79), respectively. There was a relative eightfold difference in risk between women at high risk and those at general risk. High-risk women were more likely to be diagnosed with stage II cancers and with tumors 20 mm or larger and were less likely to have stage I and estrogen receptor-positive tumors. The image-based model was validated in three external cohorts. Conclusion By combining three mammographic features, differences in the left and right breasts, and optionally lifestyle factors and family history and a polygenic risk score, the model identified women at high likelihood of being diagnosed with breast cancer within 2 years of a negative screening examination and in possible need of supplemental screening. © RSNA, 2020 Online supplemental material is available for this article.

DEX-2-TKA - DEXamethasone twice for pain treatment after Total Knee Arthroplasty: Detailed statistical analysis plan for a randomized, blinded, three-group multicentre clinical trial.

BACKGROUND: Optimization of post-operative pain treatment is of upmost importance. Multimodal analgesia is the main post-operative pain treatment principle, but the evidence on optimal analgesic combinations is unclear. With the "DEXamethasone twice for pain treatment after TKA" trial, we aim to investigate the role of one or two doses of glucocorticoid for post-operative pain treatment after total knee arthroplasty. To ensure transparency and minimization of bias, we present this article with a detailed statistical analysis plan, to be published before the last participant is enrolled. METHODS: "DEXamethasone twice for pain treatment after TKA" (DEX-2-TKA) is a randomized, blinded, three-group multicentre clinical trial. Participants will be randomized to one of three intervention groups: single dose of iv dexamethasone 24 mg, two consecutive doses of iv dexamethasone 24 mg or matching iv placebo. All three intervention groups will receive paracetamol, NSAID (ibuprofen) and local infiltration analgesia. Participants, treatment providers, outcome assessors, data managers, statisticians and conclusion drawers will be blinded to the allocated intervention. The primary outcome is total opioid consumption (iv morphine milligram equivalents) 0-48 hours post-operatively. Secondary outcomes are (1) visual analogue scale pain levels: (a) during active 45 degrees flexion of the knee at 24 and 48 hours post-operatively, (b) at rest at 24 and 48 hours post-operatively, and (c) during 0-24 hours (highest score) and 24-48 hours post-operatively (highest score); and (2) the proportion of participants with one or more adverse events within 48 hours post-operatively. DISCUSSION: The DEX-2-TKA trial will provide high quality data regarding benefits and harms of adding one or two high-doses of dexamethasone to a multimodal analgesic regimen. TRIAL REGISTRATION: EudraCT: 2018-001099-39 (08/06-18); ClinicalTrials.gov: NCT03506789 (24/04-2019).

DEX-2-TKA-DEXamethasone twice for pain treatment after Total Knee Arthroplasty: A protocol for a randomized, blinded, three-group multicentre clinical trial.

BACKGROUND: Multimodal analgesia is considered the leading principle for post-operative pain treatment, but no gold standard after total knee arthroplasty (TKA) exists. AIM: To investigate the beneficial and harmful effects of one or two doses of 24 mg intravenous dexamethasone (DXM) as part of a multimodal analgesic regimen (paracetamol, NSAID and perioperative local infiltration analgesia) after TKA. We hypothesize that addition of DXM will reduce post-operative opioid consumption. METHODS: DEXamethasone twice for pain treatment after TKA is a randomized, blinded, three-group multicentre clinical trial. Participants will be randomized to one of three groups: placebo, single dose of DXM or two consecutive doses of DXM. Participants, treatment providers and investigators will be blinded to the allocated intervention. The primary outcome is total opioid consumption (units of morphine equivalents) 0-48 hours post-operatively. INCLUSION CRITERIA: unilateral, primary TKA; age ≥18 years; American Society of Anesthesiologists-Score 1-3; Body Mass Index ≥18 and ≤40; for women-not pregnant; and written informed consent. EXCLUSION CRITERIA: allergy or contraindications against trial medication; daily use of high dose opioid and/or use of methadone/transdermal opioids; daily use of systemic glucocorticoids; dysregulated diabetes; and patients suffering from alcohol and/or drug abuse. Four-hundred-and-eighty-six eligible participants are needed to detect or discard a difference of 10 mg morphine equivalents 0-48 hours post-operatively maintaining a familywise error rate of 0.05 and a power of 90% for the three possible pairwise comparisons. DISCUSSION: Recruiting is planned to commence September 2018 and expected to finish March 2020. TRIAL REGISTRATION: EudraCT: 2018-001099-39 (08/06-18); ClinicalTrials.gov: NCT03506789 (24/04-2019). Editorial Comment This is the protocol for the largest randomized clinical trial investigating the effect of one or two doses of dexamethasones on pain treatment after total knee arthroplasty. Due to the pragmatic and rigerous design this study will deliver results of high quality and external validity.

A Multi-million Mammography Image Dataset and Population-Based Screening Cohort for the Training and Evaluation of Deep Neural Networks-the Cohort of Screen-Aged Women (CSAW).

For AI researchers, access to a large and well-curated dataset is crucial. Working in the field of breast radiology, our aim was to develop a high-quality platform that can be used for evaluation of networks aiming to predict breast cancer risk, estimate mammographic sensitivity, and detect tumors. Our dataset, Cohort of Screen-Aged Women (CSAW), is a population-based cohort of all women 40 to 74 years of age invited to screening in the Stockholm region, Sweden, between 2008 and 2015. All women were invited to mammography screening every 18 to 24 months free of charge. Images were collected from the PACS of the three breast centers that completely cover the region. DICOM metadata were collected together with the images. Screening decisions and clinical outcome data were collected by linkage to the regional cancer center registers. Incident cancer cases, from one center, were pixel-level annotated by a radiologist. A separate subset for efficient evaluation of external networks was defined for the uptake area of one center. The collection and use of the dataset for the purpose of AI research has been approved by the Ethical Review Board. CSAW included 499,807 women invited to screening between 2008 and 2015 with a total of 1,182,733 completed screening examinations. Around 2 million mammography images have currently been collected, including all images for women who developed breast cancer. There were 10,582 women diagnosed with breast cancer; for 8463, it was their first breast cancer. Clinical data include biopsy-verified breast cancer diagnoses, histological origin, tumor size, lymph node status, Elston grade, and receptor status. One thousand eight hundred ninety-one images of 898 women had tumors pixel level annotated including any tumor signs in the prior negative screening mammogram. Our dataset has already been used for evaluation by several research groups. We have defined a high-volume platform for training and evaluation of deep neural networks in the domain of mammographic imaging.

Comparison of End-Expiration Versus End-Inspiration Breath-Holds With Respect to Respiratory Motion Artifacts on T1-Weighted Abdominal MRI.

OBJECTIVE. The purpose of this study was to compare respiratory motion artifact and diagnostic image quality between end-inspiration and end-expiration breath-holding techniques on unenhanced and contrast-enhanced axial T1-weighted MRI of the liver. MATERIALS AND METHODS. This retrospective observational study included 50 consecutive subjects undergoing axial T1-weighted liver MRI, with unenhanced images acquired with both end-inspiration and end-expiration breath-holding techniques, and with contrast-enhanced images acquired for 47 of the subjects with either the end-inspiration or the end-expiration breath-holding technique. Three radiologists performed blinded independent evaluations of each unenhanced sequence, contrast-enhanced sequence, and subtraction (contrast-enhanced minus unenhanced) image, using a scale ranging from 1 point (denoting nondiagnostic imaging) to 5 points (denoting no artifacts). Blinded side-by-side assessment of each pair of unenhanced sequences was also performed. Two-tailed Wilcoxon signed rank and Wilcoxon rank sum tests were used to assess statistical significance. RESULTS. A significant improvement in motion scores was noted for sequences acquired in end-expiration, compared with those acquired in end-inspiration, for unenhanced sequences (mean, 3.35 vs 2.80; p < 0.00001), contrast-enhanced sequences (mean, 4.02 vs 3.46; p = 0.0003), and subtraction images (mean, 3.67 vs 2.41; p < 0.00001). Severe degradation of image quality or nondiagnostic image quality was noted for 15% of unenhanced images (23/150), 0% of contrast-enhanced images, and 8% (5/63) of subtraction images acquired on end-expiration, whereas it was noted for 36% (54/150) of unenhanced images, 13% (10/78) of contrast-enhanced images, and 59% (46/78) of subtraction images acquired on end-inspiration. When side-by-side assessment of paired unenhanced sequences was performed, images acquired in end-expiration were significantly favored in 59% of paired sequences (88/150) (p < 0.00001), and no difference between images acquired with both breath-hold techniques was noted for 21% (32/150) of paired sequences. CONCLUSION. The end-expiration breath-holding technique leads to significant decreases in respiratory motion artifacts, compared with the end-inspiration technique, on unenhanced and contrast-enhanced T1-weighted liver MRI.