Nevin Manimala

Anesth Analg. 2022 Apr 13. doi: 10.1213/ANE.0000000000006042. Online ahead of print.

ABSTRACT

BACKGROUND: Two trials reported that a high inspiratory oxygen fraction (Fio2) does not promote myocardial infarction or death. Observational studies can provide larger statistical strength, but associations can be due to unobserved confounding. Therefore, we evaluated the association between intraoperative Fio2 and cardiovascular complications in a large international cohort study to see if spurious associations were observed.

METHODS: We included patients from the Vascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION) study, who were ≥45 years of age, scheduled for overnight hospital admission, and had intraoperative Fio2 recorded. The primary outcome was myocardial injury after noncardiac surgery (MINS), and secondary outcomes included mortality and pneumonia, all within 30 postoperative days. Data were analyzed with logistic regression, adjusted for many baseline cardiovascular risk factors, and illustrated in relation to findings from 2 recent controlled trials.

RESULTS: We included 6588 patients with mean age of 62 years of whom 49% had hypertension. The median intraoperative Fio2 was 0.46 (5%-95% range, 0.32-0.94). There were 808 patients (12%) with MINS. Each 0.10 increase in median Fio2 was associated with a confounder-adjusted increase in odds for MINS: odds ratio (OR), 1.17 (95% confidence interval [CI], 1.12-1.23; P < .0001). MINS occurred in contrast with similar frequencies and no significant difference in controlled trials (2240 patients, 194 events), in which patients were given 80% vs 30% oxygen. Mortality was 2.4% and was not significantly associated with a median Fio2 (OR, 1.07; 95% CI, 0.97-1.19 per 0.10 increase; P = .18), and 2.9% of patients had pneumonia (OR, 1.05; 95% CI, 0.95-1.15 per 0.10 increase; P = .34).

CONCLUSIONS: We observed an association between intraoperative Fio2 and risk of myocardial injury within 30 days after noncardiac surgery, which contrasts with recent controlled clinical trials. Fio2 was not significantly associated with mortality or pneumonia. Unobserved confounding presumably contributed to the observed association between Fio2 and myocardial injury that is not supported by trials.

PMID:35417425 | DOI:10.1213/ANE.0000000000006042

JMIR Res Protoc. 2022 Mar 16. doi: 10.2196/35971. Online ahead of print.

ABSTRACT

BACKGROUND: Social distancing and other non-pharmaceutical interventions to reduce spread of COVID-19 infection in the UK have led to substantial changes in delivering ongoing care for patients with chronic conditions, including type 2 diabetes mellitus (T2DM). Clinical guidelines for management and prevention of complications for people with T2DM delivered in primary care services advise ‘routine annual reviews’ and were developed when face-to-face consultations were the norm. The shift in consultations from face-to-face to remote consultations caused a reduction in direct clinical contact and may impact on the process of care for people with T2DM.

OBJECTIVE: The aim of this study is to explore the impact of the first year of the COVID-19 pandemic on the monitoring of people with T2DM using ‘routine annual reviews’ from a national primary care perspective in England.

METHODS: A retrospective cohort study of adults with T2DM will be performed using routinely collected primary care data from the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC). We will describe the change in the rate of monitoring of glycated haemoglobin (HbA1c) between the first year of the COVID pandemic (2020) and the preceding year (2019). We will also report any change in the eight checks that compose the components of these reviews. The change in glycated haemoglobin (HbA1c) monitoring rates will be determined using a multi-level logistic regression model, adjusting for patient and practice characteristics and similarly, the change in a composite measure of the completeness of all eight checks will be modelled using ordinal regression. The models will be adjusted for the following patient level variables: age, gender, socioeconomic status, ethnicity, COVID-19 shielding status, duration of diabetes, comorbidities; then at practice-level: urban versus rural, practice size, Quality and Outcomes Framework (QOF) achievement, NHS Region and proportion of face-to-face consultations. Ethical approval was provided by the University of Oxford Medical Sciences Interdivisional Research Ethics Committee (2nd September 2021, Reference: R77306/RE001).

RESULTS: The analysis of the data extract will include 3.96 million T2DM patients across 700 practices, which is 6% of the available Oxford-RCGP RSC adult population. The preliminary results will be submitted to a conference under the domain of primary care. The resulting publication will be submitted to a peer-review journal on diabetes and endocrinology.

CONCLUSIONS: The COVID-19 pandemic has impacted on the delivery of care but little is known on the process of care of people with T2DM. This study will report the impact of the COVID-19 pandemic on these processes of care.

INTERNATIONAL REGISTERED REPORT: DERR1-10.2196/35971.

PMID:35417404 | DOI:10.2196/35971

Medicina (B Aires). 2022;82(2):217-222.

ABSTRACT

Uncertainty is present in every medical activity and its inadequate management may have negative consequences. The Physicians’ Reactions to Uncertainty (PRU) scale is used to quantify tolerance to uncertainty in medical doctors. Our objective was to carry out the translation into Spanish, cultural adaptation and validation of the PRU scale. The second objective was to compare the results in the PRU scale according to gender, years since graduation and specialty (surgical vs. clinical). The steps followed were: translation into Spanish, review by the committee, back translation, review of the back translations and conduct of the pilot test. The study population was chosen randomly. The Student’s T test was used to compare the scores in the sub-groups, considering of statistical significance a p value of = 0.05. The a-Cronbach was calculated to establish its reliability. Of 116 physicians, 106 answered the survey (91%). No meaningful difference was found in any of the subscales according to gender. Physicians with less than 10 years since graduation showed significantly greater reluctance to disclose mistakes to physicians (p = 0.0001). Surgical specialty physicians got significantly greater scores in the subscale Reluctance to disclose uncertainty to patients (p = 0.0047). The a-Cronbach average value was 0.78. These findings indicate that younger physicians and surgical specialists have greater reluctance to disclose uncertainty and mistakes. Having this information and a validated tool can be helpful to study uncertainty in medical doctors in Latin America and drive strategies to appropriately deal with it.

PMID:35417385

IEEE Trans Cybern. 2022 Apr 13;PP. doi: 10.1109/TCYB.2022.3162957. Online ahead of print.

ABSTRACT

Various domain adaptation (DA) methods have been proposed to address distribution discrepancy and knowledge transfer between the source and target domains. However, many DA models focus on matching the marginal distributions of two domains and cannot satisfy fault-diagnosed-task requirements. To enhance the ability of DA, a new DA mechanism, called deep joint distribution alignment (DJDA), is proposed to simultaneously reduce the discrepancy in marginal and conditional distributions between two domains. A new statistical metric that can align the means and covariances of two domains is designed to match the marginal distributions of the source and target domains. To align the class conditional distributions, a Gaussian mixture model is used to obtain the distribution of each category in the target domain. Then, the conditional distributions of the source domain are computed via maximum-likelihood estimation, and information entropy and Wasserstein distance are employed to reduce class conditional distribution discrepancy between the two domains. With joint distribution alignment, DJDA can achieve domain confusion to the highest degree. DJDA is applied to the fault transfer diagnosis of a wind turbine gearbox and cross-bearing with unlabeled target-domain samples. Experimental results verify that DJDA outperforms other typical DA models.

PMID:35417368 | DOI:10.1109/TCYB.2022.3162957

IEEE Trans Cybern. 2022 Apr 13;PP. doi: 10.1109/TCYB.2022.3155875. Online ahead of print.

ABSTRACT

One of the important issues associated with real-life high-dimensional data analysis is how to extract significant and relevant features from multiview data. The multiset canonical correlation analysis (MCCA) is a well-known statistical method for multiview data integration. It finds a linear subspace that maximizes the correlations among different views. However, the existing methods to find the multiset canonical variables are computationally very expensive, which restricts the application of the MCCA in real-life big data analysis. The covariance matrix of each high-dimensional view may also suffer from the singularity problem due to the limited number of samples. Moreover, the MCCA-based existing feature extraction algorithms are, in general, unsupervised in nature. In this regard, a new supervised feature extraction algorithm is proposed, which integrates multimodal multidimensional data sets by solving maximal correlation problem of the MCCA. A new block matrix representation is introduced to reduce the computational complexity for computing the canonical variables of the MCCA. The analytical formulation enables efficient computation of the multiset canonical variables under supervised ridge regression optimization technique. It deals with the “curse of dimensionality” problem associated with high-dimensional data and facilitates the sequential generation of relevant features with significantly lower computational cost. The effectiveness of the proposed multiblock data integration algorithm, along with a comparison with other existing methods, is demonstrated on several benchmark and real-life cancer data.

PMID:35417362 | DOI:10.1109/TCYB.2022.3155875

IEEE J Biomed Health Inform. 2022 Apr 13;PP. doi: 10.1109/JBHI.2022.3167252. Online ahead of print.

ABSTRACT

Ultrasonic B-mode imaging offers non-invasive and real-time monitoring of thermal ablation treatment in clinical use, however it faces challenges of moderate lesion-normal contrast and detection accuracy. Quantitative ultrasound imaging techniques have been proposed as promising tools to evaluate the microstructure of ablated tissue. In this study, we introduced Shannon entropy, a non-model based statistical measurement of disorder, to quantitatively detect and monitor microwave-induced ablation in porcine livers. Performance of typical Shannon entropy (TSE), weighted Shannon entropy (WSE), and horizontally normalized Shannon entropy (hNSE) were explored and compared with conventional B-mode imaging. TSE estimated from non-normalized probability distribution histograms was found to have insufficient discernibility of different disorder of data. WSE that improves from TSE by adding signal amplitudes as weights obtained area under receiver operating characteristic (AUROC) curve of 0.895, whereas it underestimated the periphery of lesion region. hNSE provided superior ablated area prediction with the correlation coefficient of 0.90 against ground truth, AUROC of 0.868, and remarkable lesion-normal contrast with contrast-to-noise ratio of 5.86 which was significantly higher than other imaging methods. Data distributions shown in horizontally normalized probability distribution histograms indicated that the disorder of backscattered envelope signal from ablated region increased as treatment went on. These findings suggest that hNSE imaging could be a promising technique to assist ultrasound guided percutaneous thermal ablation.

PMID:35417359 | DOI:10.1109/JBHI.2022.3167252

IEEE Trans Vis Comput Graph. 2022 Apr 13;PP. doi: 10.1109/TVCG.2022.3167151. Online ahead of print.

ABSTRACT

3D point clouds have found a wide variety of applications in multimedia processing, remote sensing, and scientific computing. Although most point cloud processing systems are developed to improve viewer experiences, little work has been dedicated to perceptual quality assessment of 3D point clouds. In this work, we build a new 3D point cloud database, namely the Waterloo Point Cloud (WPC) database. In contrast to existing datasets consisting of small-scale and low-quality source content of constrained viewing angles, the WPC database contains 20 high quality, realistic, and omni-directional source point clouds and 740 diversely distorted point clouds. We carry out a subjective quality assessment experiment over the database in a controlled lab environment. Our statistical analysis suggests that existing objective point cloud quality assessment (PCQA) models only achieve limited success in predicting subjective quality ratings. We propose a novel objective PCQA model based on an attention mechanism and a variant of information content-weighted structural similarity, which significantly outperforms existing PCQA models. The database has been made publicly available at https://github.com/qdushl/Waterloo-Point-Cloud-Database.

PMID:35417349 | DOI:10.1109/TVCG.2022.3167151

Int Orthop. 2022 Apr 13. doi: 10.1007/s00264-022-05370-9. Online ahead of print.

ABSTRACT

PURPOSE: A varus deformity (VD) of the lower limbs results in greater loading of the medial compartment of the knee joint (KJ), leading to its degenerative changes and, eventually, to progressive osteoarthritis (OA) of the joint. The aim of the study was to investigate the mid-term changes in gait biomechanics and clinical symptoms in patients with VD of KJ and OA before and six months after surgical correction.

METHODS: The study enrolled 25 patients with medial OA of grade 2-3 according to Kellgren-Lawrence and a VD of > 3°, who underwent arthroscopic lavage and debridement of the knee joint followed by corrective osteotomy. The control group included 20 healthy adults. Clinical and biomechanical assessments were done twice: immediately prior to and six months after the surgical treatment. Biomechanical parameters of gait were recorded using an inertial sensor system.

RESULTS: According to our findings, there was a statistically significant post-operative increase in the knee extension amplitude by 1.4° in female patients and an insignificant extension increase in male patients. The mean postoperative KOOS score was 66.7 points (46 to 91) in the patient group, 67.1 points (54 to 91) in males, and 59.5 points (46 to 64) in females. As early as six months after a valgus osteotomy, we already observed improved biomechanics of the KJ motions compared to pre-operative data. By that time, the swing flexion amplitude of the affected KJ had increased and became symmetrical, which had not been the case before surgery. We observed a total of three changes in the KJ kinematics after surgery: increased swing flexion amplitudes in both KJs, a decreased extension amplitude in the affected KJ, and increased first flexion amplitudes in both KJs.

CONCLUSION: According to our study, the midterm outcomes after a valgus osteotomy showed clinical improvements based on the VAS and KOOS scores, which were however less pronounced than in similar studies with a longer assessment term after surgery. We also found a significant increase in the amplitude of joint extension, but only in females. As the function of the operated joint is concerned, valgus osteotomy restored the kinematics of walking movements to a nearly normal gait with increased first and second flexion amplitudes. The function of KJ becomes symmetric though the non-operative side. Thus, the healthy and functionally more capable side is copying the movement pattern of the affected side. Hence, the non-operative leg is functioning less efficiently than it is required by the walking pace.

PMID:35416482 | DOI:10.1007/s00264-022-05370-9

Arch Dermatol Res. 2022 Apr 13. doi: 10.1007/s00403-022-02353-z. Online ahead of print.

ABSTRACT

Government-backed medical insurance plans have undergone significant changes in the last decade, but more information is needed to understand reimbursement trends, particularly for specialist medical services. The objective of this study was to identify the ratios of submitted dermatology service charges to allowed Medicare payments over the years. Further variables studied include regional or state variations, gender of provider, hierarchical condition category (HCC) risk scores of patient complexity, and number of services. Data were collected from publicly available Medicare Part B Provider Utilization and Payment Data: Physician and Other Supplier 2012-2017 datasets. All data analysis was performed on SAS 9.4 Statistical Software.Total dermatology related medicare charges-to-payment ratios steadily increased over the years (1.77 [in 2012], 1.82 [2013], 1.87 [2014], 1.95 [2015], 2.02 [2016], and 2.06 [2017]). This suggests that for every $2.06 charged in 2017, dermatology providers could expect $1 of actual payment. When further stratified into medical services vs. drug services, this upward trend remained for medical charges but drug service ratios have remained constant. There was also significant geographic variation in total medicare charges-to-payment ratios as states in the Midwest (mean total ratio: 2.48) had higher charges to payment gaps than states in the Northeast (2.26), West (2.16), and South (1.99; p = 0.01).This study identifies trends and variables associated with dermatology medicare payments. Providers may use this information to better understand changing payment structures in their own practices and hopefully these results can be valuable in future policy discussions.

PMID:35416474 | DOI:10.1007/s00403-022-02353-z

Ir Med J. 2022 Feb 17;115(2):539.

ABSTRACT

Aims The aims of this study are to identify the proportion of ACS patients using an ambulance to transport to hospital and to explore the factors influencing mode of transport. Methods A retrospective, observational cohort design was utilised in this study. Data concerning cases of ACS in a university hospital over a 9-year period was obtained from the Coronary Heart Attack Ireland Register. Descriptive statistics were used to detail demographic and clinical data, as well as to establish the proportion of ambulance usage among ACS patients. Chi-square and t-tests were used to differentiate between groups at baseline. Factors influencing mode of transport were analysed by binary logistic regression. Results 4,229 cases were obtained. Exclusion and inclusion criteria were applied, leaving 1,964 cases for overall analysis. 533 (27%) patients directly used an ambulance, 1,098 (56%) patients presented initially to their GP while 333 (17%) went directly to A&E. Logistic regression showed that age, clinical factors, smoking status and diagnosis each had a statistically significant effect on ambulance usage. Conclusions Ambulance services are underutilised by ACS patients, despite clear benefits of their use. Several factors impacted patients’ mode of transport. Knowledge of these is essential in guiding future awareness campaigns to promote ambulance usage in ACS.

PMID:35416473