A new tool to screen patients with severe obstructive sleep apnea in the primary care setting: a prospective multicenter study

Background The coordination between different levels of care is essential for the management of obstructive sleep apnea (OSA). The objective of this multicenter project was to develop a screening model for OSA in the primary care setting. Methods Anthropometric data, clinical history, and symptoms of OSA were recorded in randomly selected primary care patients, who also underwent a home sleep apnea test (HSAT). Respiratory polygraphy or polysomnography were performed at the sleep unit to establish definite indication for continuous positive airway pressure (CPAP). By means of cross-validation, a logistic regression model (CPAP yes/no) was designed, and with the clinical variables included in the model, a scoring system was established using the β coefficients (PASHOS Test). In a second stage, results of HSAT were added, and the final accuracy of the model was assessed. Results 194 patients completed the study. The clinical test included the body mass index, neck circumference and observed apneas during sleep (AUC 0.824, 95% CI 0.763–0.886, P < 0.001). In a second stage, the oxygen desaturation index (ODI) of 3% (ODI3% ≥ 15%) from the HSAT was added (AUC 0.911, 95% CI 0.863–0.960, P < 0.001), with a sensitivity of 85.5% (95% CI 74.7–92.1) and specificity of 67.8% (95% CI 55.1–78.3). Conclusions The use of this model would prevent referral to the sleep unit for 55.1% of the patients. The two-stage PASHOS model is a useful and practical screening tool for OSA in primary care for detecting candidates for CPAP treatment. Clinical Trial Registration Registry: ClinicalTrials.gov; Name: PASHOS Project: Advanced Platform for Sleep Apnea Syndrome Assessment; URL: https://clinicaltrials.gov/ct2/show/NCT02591979; Identifier: NCT02591979. Date of registration: October 30, 2015.

Functional signaling test identifies HER2 negative breast cancer patients who may benefit from c-Met and pan-HER combination therapy

Background Research is revealing the complex coordination between cell signaling systems as they adapt to genetic and epigenetic changes. Tools to uncover these highly complex functional linkages will play an important role in advancing more efficacious disease treatments. Current tumor cell signal transduction research is identifying coordination between receptor types, receptor families, and transduction pathways to maintain tumor cell viability despite challenging tumor microenvironment conditions. Methods In this report, coactivated abnormal levels of signaling activity for c-Met and HER family receptors in live tumor cells were measured by a new clinical test to identify a subpopulation of breast cancer patients that could be responsive to combined targeted therapies. The CELsignia Multi-Pathway Signaling Function (CELsignia) Test uses an impedance biosensor to quantify an individual patient’s ex vivo live tumor cell signaling response in real-time to specific HER family and c-Met co-stimulation and targeted therapies. Results The test identified breast tumors with hyperactive HER1, HER2, HER3/4, and c-Met coordinated signaling that express otherwise normal amounts of these receptors. The supporting data of the pre-clinical verification of this test included analyses of 79 breast cancer patients’ cell response to HER and c-Met agonists. The signaling results were confirmed using clinically approved matching targeted drugs, and combinations of targeted drugs in addition to correlative mouse xenograft tumor response to HER and c-Met targeted therapies. Conclusions The results of this study demonstrated the potential benefit of a functional test for identifying a subpopulation of breast cancer patients with coordinated abnormal HER and c-Met signaling for a clinical trial testing combination targeted therapy.

The quality of artificial intelligence algorithms for identifying manifestations of multiple sclerosis on magnetic resonance imaging (systematic review)

A systematic review was undertaken to summarize the data regarding accuracy and effectiveness of artificial intelligence algorithms for identifying MRI manifestations of multiple sclerosis. The review included 39 papers, whose authors put forth a multitude of corresponding algorithms and mathematical models. However, quality assessment of these developments was limited by retrospective testing on repeat data sets. Clinical test results were almost entirely absent, and there were no prospective independent studies of accuracy and applicability. The relatively high values obtained for the main measures (similarity, sensitivity and specificity coefficients, which were 7585%) were offset by the methodological errors when creating the baseline data sets, and lack of validation using independent data. Due to small sample sizes and methodological errors when measuring the result accuracy, most of the studies did not meet the criteria for evidence-based research. Studies with the highest methodological quality had algorithms that achieved a sensitivity of 51.677.0%, with a SrensenDice coefficient of 53.556.0%. These numbers are not high, but they indicate that automatic identification of multiple sclerosis manifestations on magnetic resonance imaging may be achievable. Further development of computer-aided analysis requires the creation of clinical use scenarios and testing methodology, and prospective clinical testing.

The Temporal Pattern of Arterial Stiffness during Aging: A Large-Scale Cross-Sectional Study

Brachial-ankle pulse wave velocity (baPWV) is a noninvasive clinical test that provides quantification for the stiffness of both the aorta and peripheral arteries by measuring the brachial and tibial arterial wave velocities. The temporal pattern of baPWV values during aging was investigated in this paper. A gradual increase in baPWV with respect to age was observed, suggesting an increase in the stiffness of arterial vessels as age increases. The ΔbaPWV value, defined as the absolute value of the difference between bilateral baPWV, also showed a positive correlation with aging. Many underlying physiological conditions such as hyperlipidemia, hypertension, diabetes, and hyperglycemia have previously been shown to elevate baPWV and contribute to the decline of arterial function. The effect of factors including biological sex, blood pressure, and blood glucose levels on the baPWV temporal pattern were also investigated. Between the ages of 18 and 50, men in the study had significantly higher baPWV readings than females of comparable age on average. However, after the age of 50, mean baPWV values increased at a greater rate in females than in males. In addition, blood pressure and blood glucose were shown to be associated with baPWV values. The results will improve existing prediction models for future cardiovascular episodes induced by arterial hardening in different age groups.

SARS-CoV-2 Distribution in Residential Housing Suggests Contact Deposition and Correlates with Rothia sp

Monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces is emerging as an important tool for identifying past exposure to individuals shedding viral RNA. Our past work has demonstrated that SARS-CoV-2 reverse transcription-quantitative PCR (RT-qPCR) signals from surfaces can identify when infected individuals have touched surfaces such as Halloween candy, and when they have been present in hospital rooms or schools. However, the sensitivity and specificity of surface sampling as a method for detecting the presence of a SARS-CoV-2 positive individual, as well as guidance about where to sample, has not been established. To address these questions, and to test whether our past observations linking SARS-CoV-2 abundance to Rothia spp. in hospitals also hold in a residential setting, we performed detailed spatial sampling of three isolation housing units, assessing each sample for SARS-CoV-2 abundance by RT-qPCR, linking the results to 16S rRNA gene amplicon sequences to assess the bacterial community at each location and to the Cq value of the contemporaneous clinical test. Our results show that the highest SARS-CoV-2 load in this setting is on touched surfaces such as light switches and faucets, but detectable signal is present in many non-touched surfaces that may be more relevant in settings such as schools where mask wearing is enforced. As in past studies, the bacterial community predicts which samples are positive for SARS-CoV-2, with Rothia sp. showing a positive association.ImportanceSurface sampling for detecting SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is increasingly being used to locate infected individuals. We tested which indoor surfaces had high versus low viral loads by collecting 381 samples from three residential units where infected individuals resided, and interpreted the results in terms of whether SARS-CoV-2 was likely transmitted directly (e.g. touching a light switch) or indirectly (e.g. by droplets or aerosols settling). We found highest loads where the subject touched the surface directly, although enough virus was detected on indirectly contacted surfaces to make such locations useful for sampling (e.g. in schools, where students do not touch the light switches and also wear masks so they have no opportunity to touch their face and then the object). We also documented links between the bacteria present in a sample and the SARS-CoV-2 virus, consistent with earlier studies.

A Data Analytics Approach for Revealing Influencing Factors of HPV-Related Cancers From Population-Level Statistics Data

Human papillomavirus (HPV) is considered as one of the major causes of multiple cancers, including cervical, anal, and vaginal cancers. Some studies analyzed the infection patterns of cancers caused by HPV using individual clinical test data, which is resource and time expensive. In order to facilitate the understanding of cancers caused by HPV, we propose to use data analytics methods to reveal the influencing factors from the population-level statistics data, which is available more easily. Particularly, we demonstrate the effectiveness of data analytics approach by introducing a predictive analytics method in studying the risk factors of cervix cancer in the United States. Besides accurate prediction of the number of infections, the predictive analytics method discovers the population statistic factors that most affect the cervical cancer infection pattern. Furthermore, we discuss the potential directions in developing more advanced data analytics approaches in studying cancers caused by HPV.

Improving postal survey response using behavioural science: a nested randomised control trial

Background Systematic reviews have identified effective strategies for increasing postal response rates to questionnaires; however, most studies have isolated single techniques, testing the effect of each one individually. Despite providing insight into explanatory mechanisms, this approach lacks ecological validity, given that multiple techniques are often combined in routine practice. Methods We used a two-armed parallel randomised controlled trial (n = 2702), nested within a cross-sectional health survey study, to evaluate whether using a pragmatic combination of behavioural science and evidenced-based techniques (e.g., personalisation, social norms messaging) in a study invitation letter increased response to the survey, when compared with a standard invitation letter. Participants and outcome assessors were blinded to group assignment. We tested this in a sample of women testing positive for human papillomavirus (HPV) at cervical cancer screening in England. Results Overall, 646 participants responded to the survey (response rate [RR] = 23.9%). Logistic regression revealed higher odds of response in the intervention arm (n = 357/1353, RR = 26.4%) compared with the control arm (n = 289/1349, RR = 21.4%), while adjusting for age, deprivation, clinical site, and clinical test result (aOR = 1.30, 95% CI: 1.09–1.55). Conclusion Applying easy-to-implement behavioural science and evidence-based methods to routine invitation letters improved postal response to a health-related survey, whilst adjusting for demographic characteristics. Our findings provide support for the pragmatic adoption of combined techniques in routine research to increase response to postal surveys. Trial registration ISRCTN, ISRCTN15113095. Registered 7 May 2019 – retrospectively registered.