scholarly journals Invalidity of light sensor data in field studies and a proposal of an algorithmic approach for detection and filtering of non-wear time

2021 ◽  
Author(s):  
Larissa C Hunt ◽  
Josef Fritz ◽  
Michael Herf ◽  
Céline Vetter
Keyword(s):  
Light Exposure ◽  
Area Under The Curve ◽  
Field Studies ◽  
Population Based ◽  
Light Signal ◽  
Sensor Data ◽  
Youden Index ◽  
Wear Time ◽  
Light Sensor ◽  
Environmental Light

Wearable light sensors are increasingly used in intervention and population-based studies investigating the consequences of environmental light exposure on human physiology. An important step in such analyses is the reliable detection of non-wear time. We observed in light data that days with less wear-time also have lower variability in the light signal, and we sought to test if the standard deviation of the change between subsequent samples can detect this condition. In this study, we propose and validate an easy-to-implement algorithm designed to discriminate between days with a non-wear time >4h ('invalid days') vs. ≤4h ('valid days') and investigate to which extent values of commonly used physiologically meaningful light variables differ between invalid days, valid days, and algorithm-selected non-wear days. We used 83 days of light data from a field study with high participant compliance, complemented by 47 days of light data where free-living individuals were instructed not to wear the sensor for varying amounts of time. Light data were recorded every two minutes using the pendant-worn f.luxometer light sensor; validity was derived from daily logs where participants recorded all non wear time. The algorithm-derived score discriminated well between valid and invalid days (area under the curve (AUC): 0.77, 95% CI: 0.67-0.87). The best cut-off value (i.e., highest Youden index) correctly recognized valid days with a probability of 87% ('sensitivity'), and invalid days with a probability of 63% ('specificity'). Values of various light variables derived from algorithm selected days only (median: 264.3 (Q1: 153.6, Q3: 420.0) for 24h light intensity (in lux); 496.0 (404.0, 582.0) for time spent above 50-lux) gave values close to those derived from self reported valid days only. However, these values did not significantly differ when derived across all days compared to self-reported valid days. Our results suggest that our proposed algorithm discriminates well between valid and invalid days. However, in high compliance cohorts, distortions in aggregated light measures of individual-level environmental light recordings across days appear to be small, making the application of our algorithm optional, but not necessary.

scholarly journals Measuring Facial Illuminance with Smartphones and Mobile Devices

2021 ◽  
Vol 11 (16) ◽  
pp. 7566
Author(s):  
Rosa María Salmerón-Campillo ◽  
Arthur Bradley ◽  
Mateusz Jaskulski ◽  
Norberto López-Gil
Keyword(s):  
Light Exposure ◽  
Light Sources ◽  
Ambient Light ◽  
Myopia Progression ◽  
Full Field ◽  
High Linearity ◽  
Light Sensor ◽  
Environmental Light ◽  
The Face ◽  
Office Lighting

Introduction: To uncover a relationship between light exposure and myopia is complicated because of the challenging nature of measuring visually relevant illumination experienced by children. Objective: To find a methodology to measure face illuminance using a mobile device. Methods: Accuracy and precision of the mobile device’s built-in ambient light sensor were tested under three different lighting conditions: full-field, a single small light, and one mimicking typical office illumination. Face illuminance was computed in six faces with different skin reflectances using pixel values in face images captured by the device camera placed at 30 cm in front of the face. The results were compared with those obtained with a commercial light meter situated at the face. Results: The illuminance measured by the device’s ambient light sensor showed high linearity (R2 > 0.99) slightly under-estimating or conversely over-estimating face illuminance with full-field or single light sources but accurate for office lighting. Face illuminance measured by the devices’ camera under indoor conditions using the new methodology showed a mean relative error of 27% and a high linearity (R2 > 0.94). Conclusions: Introduction of an app can be used to assess the association between visually relevant environmental light levels and myopia progression.

scholarly journals Comparing the characteristics and predicting the survival of patients with head and neck melanoma versus body melanoma: a population-based study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuxin Ding ◽  
Runyi Jiang ◽  
Yuhong Chen ◽  
Jing Jing ◽  
Xiaoshuang Yang ◽  
...  
Keyword(s):  
Head And Neck ◽  
Health Management ◽  
External Validation ◽  
Area Under The Curve ◽  
Population Based ◽  
Survival Prediction ◽  
Cancer Specific Survival ◽  
Cox Models ◽  
Lentigo Maligna Melanoma ◽  
Clinical Tools

Abstract Background Previous studies reported cutaneous melanoma in head and neck (HNM) differed from those in other regions (body melanoma, BM). Individualized tools to predict the survival of patients with HNM or BM remain insufficient. We aimed at comparing the characteristics of HNM and BM, developing and validating nomograms for predicting the survival of patients with HNM or BM. Methods The information of patients with HNM or BM from 2004 to 2015 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The HNM group and BM group were randomly divided into training and validation cohorts. We used the Kaplan-Meier method and multivariate Cox models to identify independent prognostic factors. Nomograms were developed via the rms and dynnom packages, and were measured by the concordance index (C-index), the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and calibration plots. Results Of 70,605 patients acquired, 21% had HNM and 79% had BM. The HNM group contained more older patients, male sex and lentigo maligna melanoma, and more frequently had thicker tumors and metastases than the BM group. The 5-year cancer-specific survival (CSS) and overall survival (OS) rates were 88.1 ± 0.3% and 74.4 ± 0.4% in the HNM group and 92.5 ± 0.1% and 85.8 ± 0.2% in the BM group, respectively. Eight variables (age, sex, histology, thickness, ulceration, stage, metastases, and surgery) were identified to construct nomograms of CSS and OS for patients with HNM or BM. Additionally, four dynamic nomograms were available on web. The internal and external validation of each nomogram showed high C-index values (0.785–0.896) and AUC values (0.81–0.925), and the calibration plots showed great consistency. Conclusions The characteristics of HNM and BM are heterogeneous. We constructed and validated four nomograms for predicting the 3-, 5- and 10-year CSS and OS probabilities of patients with HNM or BM. These nomograms can serve as practical clinical tools for survival prediction and individual health management.

scholarly journals PvMSP8 as a Novel Plasmodium vivax Malaria Sero-Marker for the Peruvian Amazon

Pathogens ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 282
Author(s):  
Elizabeth Villasis ◽  
Katherine Garro ◽  
Angel Rosas-Aguirre ◽  
Pamela Rodriguez ◽  
Jason Rosado ◽  
...  
Keyword(s):  
Plasmodium Vivax ◽  
Area Under The Curve ◽  
Surface Protein ◽  
Merozoite Surface Protein ◽  
Population Based ◽  
Peruvian Amazon ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Malaria Exposure ◽  
Plasmodium Vivax Malaria

The measurement of recent malaria exposure can support malaria control efforts. This study evaluated serological responses to an in-house Plasmodium vivax Merozoite Surface Protein 8 (PvMSP8) expressed in a Baculovirus system as sero-marker of recent exposure to P. vivax (Pv) in the Peruvian Amazon. In a first evaluation, IgGs against PvMSP8 and PvMSP10 proteins were measured by Luminex in a cohort of 422 Amazonian individuals with known history of Pv exposure (monthly data of infection status by qPCR and/or microscopy over five months). Both serological responses were able to discriminate between exposed and non-exposed individuals in a good manner, with slightly higher performance of anti-PvMSP10 IgGs (area under the curve AUC = 0.78 [95% CI = 0.72–0.83]) than anti-PvMSP8 IgGs (AUC = 0.72 [95% CI = 0.67–0.78]) (p = 0.01). In a second evaluation, the analysis by ELISA of 1251 plasma samples, collected during a population-based cross-sectional survey, confirmed the good performance of anti-PvMSP8 IgGs for discriminating between individuals with Pv infection at the time of survey and/or with antecedent of Pv in the past month (AUC = 0.79 [95% CI = 0.74–0.83]). Anti-PvMSP8 IgG antibodies can be considered as a good biomarker of recent Pv exposure in low-moderate transmission settings of the Peruvian Amazon.

Muscle strength cut-points for metabolic syndrome detection among adults and the elderly from Brazil

2021 ◽  
Vol 46 (4) ◽  
pp. 379-388
Author(s):  
Tiago Rodrigues de Lima ◽  
David Alejandro González-Chica ◽  
Eleonora D’Orsi ◽  
Xuemei Sui ◽  
Diego Augusto Santos Silva
Keyword(s):  
Metabolic Syndrome ◽  
Muscle Strength ◽  
Lifestyle Modification ◽  
Handgrip Strength ◽  
Area Under The Curve ◽  
Roc Curves ◽  
The Elderly ◽  
Youden Index ◽  
Cross Sectional ◽  
Cut Points

We aimed to determine cut-points for muscle strength based on metabolic syndrome diagnosis. This cross-sectional analysis comprised data from 2 cohorts in Brazil (EpiFloripa Adult, n = 626, 44.0 ± 11.1 years; EpiFloripa Aging, n = 365, 71.6 ± 6.1 years). Metabolic syndrome was assessed by relative handgrip strength (kgf/kg). Metabolic syndrome was defined as including ≥3 of the 5 metabolic abnormalities according to the Joint Interim Statement. Optimal cut-points from Receiver Operating Characteristic (ROC) curves were determined. Adjusted logistic regression was used to test the association between metabolic syndrome and the cut-points created. The cut-point identified for muscle strength was 1.07 kgf/kg (Youden index = 0.310; area under the curve (AUC)) = 0.693, 95% CI 0.614–0.764) for men and 0.73 kgf/kg (Youden index = 0.481; AUC = 0.768, 95% confidence interval (CI) = 0.709–0.821) for women (age group 25 to < 50 years). The best cut-points for men and women aged 50+ years were 0.99 kgf/kg (Youden index = 0.312; AUC = 0.651; 95% CI = 0.583–0.714) and 0.58 kgf/kg (Youden index = 0.378; AUC = 0.743; 95% CI = 0.696–0.786), respectively. Cut-points derived from ROC analysis have good discriminatory power for metabolic syndrome among adults aged 25 to <50 years but not for adults aged 50+ years. Novelty: First-line management recommendation for metabolic syndrome is lifestyle modification, including improvement of muscle strength. Cut-points for muscle strength levels according to sex and age range based on metabolic syndrome were created. Cut-points for muscle strength can assist in the identification of adults at risk for cardiometabolic disease.

scholarly journals Value and Diagnostic Efficacy of Fetal Morphology Assessment Using Ultrasound in A Poor-Resource Setting

Diagnostics ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 109 ◽  
Author(s):  
Ukweh ◽  
Ugbem ◽  
Okeke ◽  
Ekpo
Keyword(s):  
Predictive Value ◽  
Performance Metrics ◽  
Area Under The Curve ◽  
Youden Index ◽  
Likelihood Ratios ◽  
Diagnostic Efficacy ◽  
Predictive Values ◽  
Resource Setting ◽  
Post Test ◽  
Sensitivity Specificity

Background: Ultrasound is operator-dependent, and its value and efficacy in fetal morphology assessment in a low-resource setting is poorly understood. We assessed the value and efficacy of fetal morphology ultrasound assessment in a Nigerian setting. Materials and Methods: We surveyed fetal morphology ultrasound performed across five facilities and followed-up each fetus to ascertain the outcome. Fetuses were surveyed in the second trimester (18th–22nd weeks) using the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) guideline. Clinical and surgical reports were used as references to assess the diagnostic efficacy of ultrasound in livebirths, and autopsy reports to confirm anomalies in terminated pregnancies, spontaneous abortions, intrauterine fetal deaths, and still births. We calculated sensitivity, specificity, positive and negative predictive values, Area under the curve (AUC), Youden index, likelihood ratios, and post-test probabilities. Results: In total, 6520 fetuses of women aged 15–46 years (mean = 31.7 years) were surveyed. The overall sensitivity, specificity, and AUC were 77.1 (95% CI: 68–84.6), 99.5 (95% CI: 99.3–99.7), and 88.3 (95% CI: 83.7–92.2), respectively. Other performance metrics were: positive predictive value, 72.4 (95% CI: 64.7–79.0), negative predictive value, 99.6 (95% CI: 99.5–99.7), and Youden index (77.1%). Abnormality prevalence was 1.67% (95% CI: 1.37–2.01), and the positive and negative likelihood ratios were 254 (95% CI: 107.7–221.4) and 0.23 (95% CI: 0.16–0.33), respectively. The post-test probability for positive test was 72% (95% CI: 65–79). Conclusion: Fetal morphology assessment is valuable in a poor economics setting, however, the variation in the diagnostic efficacy across facilities and the limitations associated with the detection of circulatory system anomalies need to be addressed.

scholarly journals The Environmental Light Influences the Circulatory Levels of Retinoic Acid and Associates with Hepatic Lipid Metabolism

Endocrinology ◽  
2008 ◽  
Vol 149 (12) ◽  
pp. 6336-6342 ◽  
Author(s):  
Wenqiang Pang ◽  
Chunying Li ◽  
Yue Zhao ◽  
Shiming Wang ◽  
Wei Dong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Retinoic Acid ◽  
Adenosine Receptors ◽  
Light Exposure ◽  
Retinoic Acid Receptor ◽  
Hepatic Lipase ◽  
Mouse Retina ◽  
Acid Receptor ◽  
Hepatic Lipid ◽  
Environmental Light

Environmental light is involved in the regulation of photochemical reaction in mouse retina. It remains unclear whether light-mediated increase in all-trans retinoic acid (ATRA) synthesis in retina will result in altering the circulatory levels of ATRA and regulating downstream gene expression and physiological function. Here we showed circulatory levels of ATRA decreased in mice under constant darkness and elevated by light exposure. Fat gene pancreatic lipase-related protein 2 (mPlrp2) and its partner procolipase (mClps), but not hepatic lipase (mHl), activated in livers for responding to lack of light illuminating. Light-triggered alterations in circulatory ATRA levels regulated ecto-5′-nucleotidase gene expression by retinoic acid receptor retinoic acid receptor-α and modulated 5′-AMP levels in blood and were associated with mPlrp2 and mClps expression in the livers. Mice deficient in adenosine receptors displayed mPlrp2 and mClps expression in livers under 12-h light, 12-h dark cycles. Caffeine blocked adenosine receptors and induced hepatic mPlrp2 and mClps expression in wild-type mice. Mice activated in hepatic mPlrp2 and mClps expression lowered hepatic and serum lipid levels and markedly elevated circulatory levels of all-trans retinol. Our results suggest environmental light influence hepatic lipid homeostasis by light-modulated retinoic acid signaling associated with mPlrp2 and mClps gene expression in livers.

scholarly journals A Novel Nomogram for Predicting Cancer-Specific Survival in Patients With Spinal Chordoma: A Population-Based Analysis

2021 ◽  
Vol 20 ◽  
pp. 153303382110365
Author(s):  
Zhangheng Huang ◽  
Zhiyi Fan ◽  
Chengliang Zhao ◽  
He Sun
Keyword(s):  
Prognostic Factors ◽  
Area Under The Curve ◽  
Risk Groups ◽  
Population Based ◽  
Disease Stage ◽  
Survival Prediction ◽  
Cancer Specific Survival ◽  
Spinal Chordoma ◽  
Prediction Of Prognosis ◽  
High Degree

Background: Chordoma is a rare malignant bone tumor, and the survival prediction for patients with chordoma is difficult. The objective of this study was to construct and validate a nomogram for predicting cancer-specific survival (CSS) in patients with spinal chordoma. Methods: A total of 316 patients with spinal chordoma were identified from the SEER database between 1998 and 2015. The independent prognostic factors for patients with spinal chordoma were determined by univariate and multivariate Cox analyses. The prognostic nomogram was established for patients with spinal chordoma based on independent prognostic factors. Furthermore, we performed internal and external validations for this nomogram. Results: Primary site, disease stage, histological type, surgery, and age were identified as independent prognostic factors for patients with spinal chordoma. A nomogram for predicting CSS in patients with spinal chordoma was constructed based on the above 5 variables. In the training cohort, the area under the curve for predicting 1-, 3-, and 5-year CSS were 0.821, 0.856, and 0.920, respectively. The corresponding area under the curve in the validation cohort were 0.728, 0.804, and 0.839, respectively. The calibration curves of the nomogram showed a high degree of agreement between the predicted and the actual results, and the decision curve analysis further demonstrated the satisfactory clinical utility of the nomogram. Conclusions: The prognostic nomogram provides a considerably more accurate prediction of prognosis for patients with spinal chordoma. Clinicians can use it to categorize patients into different risk groups and make personalized treatment methods.

scholarly journals Galectin-3 in Critically Ill Patients with Sepsis and/or Trauma: A Good Predictor of Outcome or Not?

2018 ◽  
Vol 0 (0) ◽  
Author(s):  
Jasna Jevdjic ◽  
Maja Surbatovic ◽  
Snezana Milosavljevic ◽  
Goran Rondovic ◽  
Ivan Stanojevic ◽  
...  
Keyword(s):  
Severe Sepsis ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Good Predictor ◽  
Injury Severity ◽  
Area Under The Curve ◽  
University Hospital ◽  
Youden Index ◽  
Lethal Outcome ◽  
Galectin 3

Abstract Severe sepsis and/or trauma complicated with multiple organ dysfunction syndrome are leading causes of death in critically ill patients. The aim of this prospective, observational, single centre study was to assess the prognostic value of galectin-3 regarding outcome in critically ill patients with severe trauma and/or severe sepsis. The outcome measure was hospital mortality. In total, 75 critically ill patients who were admitted to the intensive care unit of the tertiary university hospital were enrolled in a prospective observational study. Blood samples were collected upon fulfilling Sepsis-3 criteria and for a traumatized Injury Severity Score > 25 points. Levels of galectin-3 were significantly higher in nonsurvivors on the day of enrolment - Day 1 (p<0.05). On Day 1, the area under the curve (AUC) for the galectin-3 for lethal outcome was 0.602. At a cut-off level of 262.82 ng/mL, the sensitivity was 53%, and the specificity was 69.7%, which was objectively determined by a Youden index of 0.20. The discriminative power of galectin-3 in predicting outcome was statistically significant. Galectin-3 on Day 1 is a fairly good predictor of lethal outcome.

Imaging-based prediction of histological clot composition from admission CT imaging

2021 ◽  
pp. neurintsurg-2020-016774
Author(s):  
Uta Hanning ◽  
Peter B Sporns ◽  
Marios N Psychogios ◽  
Astrid Jeibmann ◽  
Jens Minnerup ◽  
...  
Keyword(s):  
Machine Learning ◽  
Vascular Tissue ◽  
Large Diameter ◽  
Small Diameter ◽  
Area Under The Curve ◽  
Quantitative Information ◽  
Youden Index ◽  
Quantitative Image ◽  
Characteristic Area ◽  
Contrast Ct

BackgroundThrombus composition has been shown to be a major determinant of recanalization success and occurrence of complications in mechanical thrombectomy. The most important parameters of thrombus behavior during interventional procedures are relative fractions of fibrin and red blood cells (RBCs). We hypothesized that quantitative information from admission non-contrast CT (NCCT) and CT angiography (CTA) can be used for machine learning based prediction of thrombus composition.MethodsThe analysis included 112 patients with occlusion of the carotid-T or middle cerebral artery who underwent thrombectomy. Thrombi samples were histologically analyzed and fractions of fibrin and RBCs were determined. Thrombi were semi-automatically delineated in CTA scans and NCCT scans were registered to the same space. Two regions of interest (ROIs) were defined for each thrombus: small-diameter ROIs capture vessel walls and thrombi, large-diameter ROIs reflect peri-vascular tissue responses. 4844 quantitative image markers were extracted and evaluated for their ability to predict thrombus composition using random forest algorithms in a nested fivefold cross validation.ResultsTest set receiver operating characteristic area under the curve was 0.83 (95% CI 0.80 to 0.87) for differentiating RBC-rich thrombi and 0.84 (95% CI 0.80 to 0.87) for differentiating fibrin-rich thrombi. At maximum Youden-Index, RBC-rich thrombi were identified at 77% sensitivity and 74% specificity; for fibrin-rich thrombi the classifier reached 81% sensitivity at 73% specificity.ConclusionsMachine learning based analysis of admission imaging allows for prediction of clot composition. Perspectively, such an approach could allow selection of clot-specific devices and retrieval procedures for personalized thrombectomy strategies.

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