Portable, handheld, and affordable blood perfusion imager for screening of subsurface cancer in resource-limited settings.

Precise information on localized variations in blood circulation holds the key for noninvasive diagnostics and therapeutic assessment of various forms of cancer. While thermal imaging by itself may provide significant insights on the combined implications of the relevant physiological parameters, viz. local blood perfusion and metabolic balance due to active tumors as well as the ambient conditions, knowledge of the tissue surface temperature alone may be somewhat inadequate in distinguishing between some ambiguous manifestations of precancer and cancerous lesions, resulting in compromise of the selectivity in detection. This, along with the lack of availability of a user-friendly and inexpensive portable device for thermal-image acquisition, blood perfusion mapping, and data integration acts as a deterrent against the emergence of an inexpensive, contact-free, and accurate in situ screening and diagnostic approach for cancer detection and management. Circumventing these constraints, here we report a portable noninvasive blood perfusion imager augmented with machine learning-based quantitative analytics for screening precancerous and cancerous traits in oral lesions, by probing the localized alterations in microcirculation. With a proven overall sensitivity >96.66% and specificity of 100% as compared to gold-standard biopsy-based tests, the method successfully classified oral cancer and precancer in a resource-limited clinical setting in a double-blinded patient trial and exhibited favorable predictive capabilities considering other complementary modes of medical image analysis as well. The method holds further potential to achieve contrast-free, accurate, and low-cost diagnosis of abnormal microvascular physiology and other clinically vulnerable conditions, when interpreted along with complementary clinically evidenced decision-making perspectives.

Supermarket/hypermarket opportunistic screening for atrial fibrillation (SHOPS-AF) using sensors embedded in the handles of supermarket trolleys: A feasibility study.

BACKGROUND: Atrial fibrillation (AF) increases the risk of death, stroke, heart failure, cognitive decline, and healthcare costs but is often asymptomatic and undiagnosed. There is currently no national screening program for AF. The advent of validated hand-held devices allows AF to be detected in non-healthcare settings, enabling screening to be undertaken within the community. METHOD AND RESULTS: In this novel observational study, we embedded a MyDiagnostick single lead ECG sensor into the handles of shopping trolleys in four supermarkets in the Northwest of England: 2155 participants were recruited. Of these, 231 participants either activated the sensor or had an irregular pulse, suggesting AF. Some participants agreed to use the sensor but refused to provide their contact details, or consent to pulse assessment. In addition, some data were missing, resulting in 203 participants being included in the final analyses. Fifty-nine participants (mean age 73.6 years, 43% female) were confirmed or suspected of having AF; 20 were known to have AF and 39 were previously undiagnosed. There was no evidence of AF in 115 participants and the remaining 46 recordings were non-diagnostic, mainly due to artefact. Men and older participants were significantly more likely to have newly diagnosed AF. Due to the number of non-diagnostic ECGs (n = 46), we completed three levels of analyses, excluding all non-diagnostic ECGs, assuming all non-diagnostic ECGs were masking AF, and assuming all non-diagnostic ECGs were not AF. Based on the results of the three analyses, the sensor's sensitivity (95% CI) ranged from 0.70 to 0.93; specificity from 0.15 to 0.97; positive predictive values (PPV) and negative predictive values (NPV) ranged from 0.24 to 0.56 and 0.55 to 1.00, respectively. These values should be interpreted with caution, as the ideal reference standard on 1934 participants was imperfect. CONCLUSION: The study demonstrates that the public will engage with AF screening undertaken as part of their daily routines using hand-held devices. Sensors can play a key role in identifying asymptomatic patients in this way, but the technology must be further developed to reduce the quantity of non-diagnostic ECGs.

Promoting smartphone-based keratitis screening using meta-learning: A multicenter study.

OBJECTIVE: Keratitis is the primary cause of corneal blindness worldwide. Prompt identification and referral of patients with keratitis are fundamental measures to improve patient prognosis. Although deep learning can assist ophthalmologists in automatically detecting keratitis through a slit lamp camera, remote and underserved areas often lack this professional equipment. Smartphones, a widely available device, have recently been found to have potential in keratitis screening. However, given the limited data available from smartphones, employing traditional deep learning algorithms to construct a robust intelligent system presents a significant challenge. This study aimed to propose a meta-learning framework, cosine nearest centroid-based metric learning (CNCML), for developing a smartphone-based keratitis screening model in the case of insufficient smartphone data by leveraging the prior knowledge acquired from slit-lamp photographs. METHODS: We developed and assessed CNCML based on 13,009 slit-lamp photographs and 4,075 smartphone photographs that were obtained from 3 independent clinical centers. To mimic real-world scenarios with various degrees of sample scarcity, we used training sets of different sizes (0 to 20 photographs per class) from the HUAWEI smartphone to train CNCML. We evaluated the performance of CNCML not only on an internal test dataset but also on two external datasets that were collected by two different brands of smartphones (VIVO and XIAOMI) in another clinical center. Furthermore, we compared the performance of CNCML with that of traditional deep learning models on these smartphone datasets. The accuracy and macro-average area under the curve (macro-AUC) were utilized to evaluate the performance of models. RESULTS: With merely 15 smartphone photographs per class used for training, CNCML reached accuracies of 84.59%, 83.15%, and 89.99% on three smartphone datasets, with corresponding macro-AUCs of 0.96, 0.95, and 0.98, respectively. The accuracies of CNCML on these datasets were 0.56% to 9.65% higher than those of the most competitive traditional deep learning models. CONCLUSIONS: CNCML exhibited fast learning capabilities, attaining remarkable performance with a small number of training samples. This approach presents a potential solution for transitioning intelligent keratitis detection from professional devices (e.g., slit-lamp cameras) to more ubiquitous devices (e.g., smartphones), making keratitis screening more convenient and effective.

Using Wearable Digital Devices to Screen Children for Mental Health Conditions: Ethical Promises and Challenges.

In response to a burgeoning pediatric mental health epidemic, recent guidelines have instructed pediatricians to regularly screen their patients for mental health disorders with consistency and standardization. Yet, gold-standard screening surveys to evaluate mental health problems in children typically rely solely on reports given by caregivers, who tend to unintentionally under-report, and in some cases over-report, child symptomology. Digital phenotype screening tools (DPSTs), currently being developed in research settings, may help overcome reporting bias by providing objective measures of physiology and behavior to supplement child mental health screening. Prior to their implementation in pediatric practice, however, the ethical dimensions of DPSTs should be explored. Herein, we consider some promises and challenges of DPSTs under three broad categories: accuracy and bias, privacy, and accessibility and implementation. We find that DPSTs have demonstrated accuracy, may eliminate concerns regarding under- and over-reporting, and may be more accessible than gold-standard surveys. However, we also find that if DPSTs are not responsibly developed and deployed, they may be biased, raise privacy concerns, and be cost-prohibitive. To counteract these potential shortcomings, we identify ways to support the responsible and ethical development of DPSTs for clinical practice to improve mental health screening in children.

Emotional health screening of mothers, preliminary validation of a 3-item instrument: A research brief.

A number of countries now recommend population-wide depression screening for perinatal women, using validated tools. A stepped-approach to screening - involving universal screening with a brief measure, followed by targeted screening using a longer measure for those women identified as at greater risk - is used in some settings. This brief report describes the test performance characteristics of a 3-item mood screening instrument, developed for use within a digital parenting program. Participants (n = 404) in this cross-sectional study were mothers of children aged up to 3 years. The majority (65.5 %) were first-time mothers, and their mean age was 32.8 years. Data were collected using an online survey. The test performance of the brief 3-item mood screening instrument (possible score range = 0-300) was examined using Receiver Operating Characteristic (ROC) analysis, with a score of 13 or more on the Edinburgh Postnatal Depression Scale (EPDS) used as the reference standard. The mood screening instrument demonstrated excellent range when compared to the reference standard. Optimal balance between sensitivity (0.77) and specificity (0.78), was achieved at a cut-point of 160 or less. Analysis was limited by using only the EPDS as the reference standard. This preliminary data supports the use of this 3-item mood screening instrument to screen for postnatal depression symptoms and may be integrated into a mobile Health or online tool. Future research should examine the test performance of the 3-item mood screening instrument against a diagnostic tool.

The Use of the RETeval Portable Electroretinography Device for Low-Cost Screening: A Mini-Review.

Electroretinography (ERG) provides crucial insights into retinal function and the integrity of the visual pathways. However, ERG assessments classically require a complicated technical background with costly equipment. In addition, the placement of corneal or conjunctival electrodes is not always tolerated by the patients, which restricts the measurement for pediatric evaluations. In this short review, we give an overview of the use of the RETeval portable ERG device (LKC Technologies, Inc., Gaithersburg, MD, USA), a modern portable ERG device that can facilitate screening for diseases involving the retina and the optic nerve. We also review its potential to provide ocular biomarkers in systemic pathologies, such as Alzheimer's disease and central nervous system alterations, within the framework of oculomics.

Application of a portable instrument for rapid and reliable detection of SARS-CoV-2 infection in any environment.

The ongoing outbreak of the novel coronavirus (SARS-CoV-2) infection is creating serious challenges for health laboratories that seek to identify viral infections as early as possible, optimally at the earliest appearance of symptom. Indeed, there is urgent need to develop and deploy robust diagnostic methodologies not only to use in health laboratory environments but also directly in places where humans circulate and spread the virus such as airports, trains, boats, and any public aggregation places. The success of a reliable and sensitive asymptomatic diagnosis relies on the identification and measurement of informative biomarkers from human host and virus in a rapid, sensitive, and inexpensive manner. The objective of this article is to describe an innovative multidisciplinary approach to develop an efficient, inexpensive, and easy-to-use portable instrument (bCUBE® by Hyris Ltd) that can be employed as a surveillance system for the emergency caused by SARS-CoV-2. A solution for Coronavirus testing, compliant with CDC guidelines, is scheduled to be released in the next weeks. In addition, we will describe a workflow and path of an integrated multi-omic approach that will lead to host and pathogen biomarker discovery in order to train the instrument to provide reliable results based on a specific biomarker's fingerprint of SARS-CoV-2 infection.

Artificial intelligence in diabetic retinopathy screening: from idea to a medical device in clinical practice.

With the growing significance of artificial intelligence in healthcare, new perspectives are emerging in primary care. Diabetic retinopathy, a microvascular complication of diabetes mellitus, often remains unnoticed until patient is facing complications. Artificial intelligence presents a promising solution that can enhance the accessibility of diabetic retinopathy screening for a broader range of patients. The key challenge lies in successfully integrating the solution into clinical practice, a demanding process with multiple phases to ensure the resulting medical device is effective and safe for patient use. Aireen software uses artificial intelligence to perform diabetic retinopathy screening on retinal images captured by optical fundus cameras. The medical device complies with European Medical Device Regulation 2017/745 and was introduced to the market in 2023. Collaboration between physicians and the development team played a crucial role throughout the entire lifecycle of the medical device. Physicians were engaged in defining the intended use of the medical device, risk analysis, data annotation for training and software validation, as well as throughout a clinical trial. A clinical trial was conducted on 1,274 patients with type 1 and type 2 diabetes mellitus, where Aireen medical device achieved a sensitivity of 94.0% and a specificity of 90.7% compared to the reference evaluation. This clinical trial confirmed the potential of Aireen to enhance the availability of diabetic retinopathy screening and early disease detection.

Discriminative Accuracy of the CAPTURE Tool for Identifying Chronic Obstructive Pulmonary Disease in US Primary Care Settings.

Importance: Chronic obstructive pulmonary disease (COPD) is underdiagnosed in primary care. Objective: To evaluate the operating characteristics of the CAPTURE (COPD Assessment in Primary Care To Identify Undiagnosed Respiratory Disease and Exacerbation Risk) screening tool for identifying US primary care patients with undiagnosed, clinically significant COPD. Design, Setting, and Participants: In this cross-sectional study, 4679 primary care patients aged 45 years to 80 years without a prior COPD diagnosis were enrolled by 7 primary care practice-based research networks across the US between October 12, 2018, and April 1, 2022. The CAPTURE questionnaire responses, peak expiratory flow rate, COPD Assessment Test scores, history of acute respiratory illnesses, demographics, and spirometry results were collected. Exposure: Undiagnosed COPD. Main Outcomes and Measures: The primary outcome was the CAPTURE tool's sensitivity and specificity for identifying patients with undiagnosed, clinically significant COPD. The secondary outcomes included the analyses of varying thresholds for defining a positive screening result for clinically significant COPD. A positive screening result was defined as (1) a CAPTURE questionnaire score of 5 or 6 or (2) a questionnaire score of 2, 3, or 4 together with a peak expiratory flow rate of less than 250 L/min for females or less than 350 L/min for males. Clinically significant COPD was defined as spirometry-defined COPD (postbronchodilator ratio of forced expiratory volume in the first second of expiration [FEV1] to forced vital capacity [FEV1:FVC] <0.70 or prebronchodilator FEV1:FVC <0.65 if postbronchodilator spirometry was not completed) combined with either an FEV1 less than 60% of the predicted value or a self-reported history of an acute respiratory illness within the past 12 months. Results: Of the 4325 patients who had adequate data for analysis (63.0% were women; the mean age was 61.6 years [SD, 9.1 years]), 44.6% had ever smoked cigarettes, 18.3% reported a prior asthma diagnosis or use of inhaled respiratory medications, 13.2% currently smoked cigarettes, and 10.0% reported at least 1 cardiovascular comorbidity. Among the 110 patients (2.5% of 4325) with undiagnosed, clinically significant COPD, 53 had a positive screening result with a sensitivity of 48.2% (95% CI, 38.6%-57.9%) and a specificity of 88.6% (95% CI, 87.6%-89.6%). The area under the receiver operating curve for varying positive screening thresholds was 0.81 (95% CI, 0.77-0.85). Conclusions and Relevance: Within this US primary care population, the CAPTURE screening tool had a low sensitivity but a high specificity for identifying clinically significant COPD defined by presence of airflow obstruction that is of moderate severity or accompanied by a history of acute respiratory illness. Further research is needed to optimize performance of the screening tool and to understand whether its use affects clinical outcomes.

Toxic effects of nanomaterials for health applications: How automation can support a systematic review of the literature?

Systematic reviews of the scientific literature can be an important source of information supporting the daily work of the regulators in their decision making, particularly in areas of innovative technologies where the regulatory experience is still limited. Significant research activities in the field of nanotechnology resulted in a huge number of publications in the last decades. However, even if the published data can provide relevant information, scientific articles are often of diverse quality, and it is nearly impossible to manually process and evaluate such amount of data in a systematic manner. In this feasibility study, we investigated to what extent open-access automation tools can support a systematic review of toxic effects of nanomaterials for health applications reported in the scientific literature. In this study, we used a battery of available tools to perform the initial steps of a systematic review such as targeted searches, data curation and abstract screening. This work was complemented with an in-house developed tool that allowed us to extract specific sections of the articles such as the materials and methods part or the results section where we could perform subsequent text analysis. We ranked the articles according to quality criteria based on the reported nanomaterial characterisation and extracted most frequently described toxic effects induced by different types of nanomaterials. Even if further demonstration of the reliability and applicability of automation tools is necessary, this study demonstrated the potential to leverage information from the scientific literature by using automation systems in a tiered strategy.

Clinical Validation of a Multitarget Fecal Immunochemical Test for Colorectal Cancer Screening : A Diagnostic Test Accuracy Study.

BACKGROUND: The fecal immunochemical test (FIT) is used in colorectal cancer (CRC) screening, yet it leaves room for improvement. OBJECTIVE: To develop a multitarget FIT (mtFIT) with better diagnostic performance than FIT. DESIGN: Diagnostic test accuracy study. SETTING: Colonoscopy-controlled series. PARTICIPANTS: Persons (n = 1284) from a screening (n = 1038) and referral (n = 246) population were classified by their most advanced lesion (CRC [n = 47], advanced adenoma [n = 135], advanced serrated polyp [n = 30], nonadvanced adenoma [n = 250], and nonadvanced serrated polyp [n = 53]), along with control participants (n = 769). MEASUREMENTS: Antibody-based assays were developed and applied to leftover FIT material. Classification and regression tree (CART) analysis was applied to biomarker concentrations to identify the optimal combination for detecting advanced neoplasia. Performance of this combination, the mtFIT, was cross-validated using a leave-one-out approach and compared with FIT at equal specificity. RESULTS: The CART analysis showed a combination of hemoglobin, calprotectin, and serpin family F member 2-the mtFIT-to have a cross-validated sensitivity for advanced neoplasia of 42.9% (95% CI, 36.2% to 49.9%) versus 37.3% (CI, 30.7% to 44.2%) for FIT (P = 0.025), with equal specificity of 96.6%. In particular, cross-validated sensitivity for advanced adenomas increased from 28.1% (CI, 20.8% to 36.5%) to 37.8% (CI, 29.6% to 46.5%) (P = 0.006). On the basis of these results, early health technology assessment indicated that mtFIT-based screening could be cost-effective compared with FIT. LIMITATION: Study population is enriched with persons from a referral population. CONCLUSION: Compared with FIT, the mtFIT showed better diagnostic accuracy in detecting advanced neoplasia because of an increased detection of advanced adenomas. Moreover, early health technology assessment indicated that these results provide a sound basis to pursue further development of mtFIT as a future test for population-based CRC screening. A prospective screening trial is in preparation. PRIMARY FUNDING SOURCE: Stand Up to Cancer/Dutch Cancer Society, Dutch Digestive Foundation, and HealthHolland.

Comprehensive Evaluation of Rhythm Monitoring Strategies in Screening for Atrial Fibrillation: Insights From Patients at Risk Monitored Long Term With an Implantable Loop Recorder.

BACKGROUND: Stroke is an increasing health problem worldwide. Atrial fibrillation (AF) is a major risk factor for stroke, and the attention given to AF screening is rising, as new monitoring technologies emerge. We aimed to evaluate the performance of a large panel of screening strategies and to assess population characteristics associated with diagnostic yield. METHODS: Individuals with stroke risk factors but without AF were recruited from the general population to undergo screening with an implantable loop recorder. New-onset AF lasting ≥6 minutes was adjudicated by senior cardiologists. After continuous monitoring for >3 years, complete day-to-day heart rhythm data sets were reconstructed for every participant, including exact time of onset and termination of all AF episodes. Random sampling was applied to assess the sensitivity and negative predictive value of screening with various simulated screening strategies compared with the implantable loop recorder. The diagnostic yield across strategies and population subgroups was compared by use of nonparametric tests. RESULTS: The rhythm data sets comprised 590 participants enduring a total of 659 758 days of continuous monitoring and 20 110 AF episodes. In these data, a single 10-second ECG yielded a sensitivity (and negative predictive value) of 1.5% (66%) for AF detection, increasing to 8.3% (67%) for twice-daily 30-second ECGs during 14 days and to 11% (68%), 13% (68%), 15% (69%), 21% (70%), and 34% (74%) for a single 24-hour, 48-hour, 72-hour, 7-day, or 30-day continuous monitoring, respectively. AF detection further improved when subsequent screenings were performed or when the same monitoring duration was spread over several periods compared with a single period (eg, three 24-hour monitorings versus one 72-hour monitoring; P<0.0001 for all comparisons). The sensitivity was consistently higher among participants with age ≥75 years, male sex, CHADS2 score >2, or NT-proBNP (N-terminal pro-B-type natriuretic peptide) ≥40 pmol/L and among participants with underlying ≥24-hour AF episodes compared with shorter AF (P<0.0001 for all screening strategies). CONCLUSIONS: In screening for AF among participants with stroke risk factors, the diagnostic yield increased with duration, dispersion, and number of screenings, although all strategies had low yield compared with the implantable loop recorder. The sensitivity was higher among participants who were older, were male, or had higher NT-proBNP. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02036450.

Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial.

BACKGROUND & AIMS: One-fourth of colorectal neoplasias are missed during screening colonoscopies; these can develop into colorectal cancer (CRC). Deep learning systems allow for real-time computer-aided detection (CADe) of polyps with high accuracy. We performed a multicenter, randomized trial to assess the safety and efficacy of a CADe system in detection of colorectal neoplasias during real-time colonoscopy. METHODS: We analyzed data from 685 subjects (61.32 ± 10.2 years old; 337 men) undergoing screening colonoscopies for CRC, post-polypectomy surveillance, or workup due to positive results from a fecal immunochemical test or signs or symptoms of CRC, at 3 centers in Italy from September through November 2019. Patients were randomly assigned (1:1) to groups who underwent high-definition colonoscopies with the CADe system or without (controls). The CADe system included an artificial intelligence-based medical device (GI-Genius, Medtronic) trained to process colonoscopy images and superimpose them, in real time, on the endoscopy display a green box over suspected lesions. A minimum withdrawal time of 6 minutes was required. Lesions were collected and histopathology findings were used as the reference standard. The primary outcome was adenoma detection rate (ADR, the percentage of patients with at least 1 histologically proven adenoma or carcinoma). Secondary outcomes were adenomas detected per colonoscopy, non-neoplastic resection rate, and withdrawal time. RESULTS: The ADR was significantly higher in the CADe group (54.8%) than in the control group (40.4%) (relative risk [RR], 1.30; 95% confidence interval [CI], 1.14-1.45). Adenomas detected per colonoscopy were significantly higher in the CADe group (mean, 1.07 ±1.54) than in the control group (mean 0.71 ± 1.20) (incidence rate ratio, 1.46; 95% CI, 1.15-1.86). Adenomas 5 mm or smaller were detected in a significantly higher proportion of subjects in the CADe group (33.7%) than in the control group (26.5%; RR, 1.26; 95% CI, 1.01-1.52), as were adenomas of 6 to 9 mm (detected in 10.6% of subjects in the CADe group vs 5.8% in the control group; RR, 1.78; 95% CI, 1.09-2.86), regardless of morphology or location. There was no significant difference between groups in withdrawal time (417 ± 101 seconds for the CADe group vs 435 ± 149 for controls; P = .1) or proportion of subjects with resection of non-neoplastic lesions (26.0% in the CADe group vs 28.7% of controls; RR, 1.00; 95% CI, 0.90-1.12). CONCLUSIONS: In a multicenter, randomized trial, we found that including CADe in real-time colonoscopy significantly increases ADR and adenomas detected per colonoscopy without increasing withdrawal time. ClinicalTrials.gov no: 04079478.

Development of a patient-reported outcome measure for patients who have recovered from a subarachnoid hemorrhage: the "questionnaire for the screening of symptoms in aneurysmal subarachnoid hemorrhage" (SOS-SAH).

BACKGROUND: Patients who have been successfully treated for an aneurysmal subarachnoid hemorrhage (aSAH) often retain multiple health complaints, including mood disorders, cognitive complaints, fatigue, and problems with social participation. These problems are not always fully addressed during hospital visits or in current outcome measures, such as the modified Rankin score and the Glasgow Outcome Scale. Here, we present the development of the "Questionnaire for the Screening of Symptoms in aneurysmal Subarachnoid Hemorrhage" (SOS-SAH), which screens for the self-reported symptoms of patients with mild disabilities. METHODS: During the development of the SOS-SAH we adhered to the PROM-cycle framework for the selection and implementation of patient-reported outcome measures (PROMs). The SOS-SAH was developed in an iterative process informed by a literature study. Patients and healthcare professionals were involved in the development process through participating in a working group, interviews, and a cognitive validation study. RESULTS AND CONCLUSIONS: Relevant patient-reported outcomes (PROs) were identified for patients with aSAH. The SOS-SAH was developed primarily using domains and items from existing PROMs and, if necessary, by developing new items. The SOS-SAH consists of 40 items and covers 14 domains: cognitive abilities, hypersensitivity to stimuli, anxiety, depression, fatigue, social roles, personality change, language, vision, taste, smell, hearing, headache, and sexual function. It also includes a proxy measurement for use by family members to assess cognitive functioning and personality change.

Does the Fast Alcohol Screening Test Accurately Distinguish Between Harmful and Severely Dependent Tiers of Alcohol Misuse?

AIMS: Primary aim: to determine the efficacy of FAST (the Fast Alcohol Screening Test) for detecting harmful and dependent levels of alcohol use. Secondary aim: to compare the performance of the FAST to two short forms of the Alcohol Use Disorder Identification Test (AUDIT): the AUDIT-C and AUDIT-3. METHODS: Data from 3336 individuals in South Wales, compiled from full AUDIT datasets, were examined. AUROC analysis, alongside measures of sensitivity and specificity of the FAST, AUDIT-C and AUDIT-3 were utilized for the identification of harmful and dependent alcohol use. RESULTS: The FAST demonstrated efficacy in the identification of harmful and dependent levels of alcohol use, with superior performance to both the AUDIT-C and AUDIT-3. CONCLUSION: The present paper demonstrates the potential of the FAST as a cost- and time-effective method for appropriate screening and signposting in the stepped care model utilized by many health care and treatment services. Further studies are needed to ensure validity, both within the general population and for specific services and populations.

Are the International Classification of Functioning, Disability and Health (ICF) domains considered in the obstructive sleep apnea instruments? An integrative review.

PURPOSE: Obstructive Sleep Apnea (OSA) is related to cardiovascular, metabolic, and neurocognitive diseases. Furthermore, OSA symptoms, such as excessive sleepiness, fatigue, and mood disorders, may interfere in functioning. The assessment of this aspect in patients with OSA is not frequent and no specific instrument is available in the literature. Our aim is to identify if the International Classification of Functioning, Disability and Health (ICF) domains are considered in the validated instruments used to assess patients with OSA. METHODS: In this integrative literature review, three databases were searched: Pubmed, Embase, and LILACS. Bibliographic survey was carried out in 2020, between March and July. Articles published in English, Portuguese, and Spanish with validated tools to assess OSA in adults were included. RESULTS: Thirty instruments have undergone a process of concept extraction and coding according to the ICF, generating a total of 769 significant concepts. It was observed that the function domain was the most prevalent, making 42% (n = 323) of the concepts, followed by domains of activity (16%), participation (10%), environmental factors (5%), personal factor (5%), and structure (1%). Only one instrument, the "Sleep Apnea Quality of Life Index (SAQLI)," encompasses all domains of the ICF in its constructs. CONCLUSION: In the analyzed instruments, the function domain prevails, with most concepts related to sleep functions. Only one validated instrument included in this research covered all the ICF domains. This instrument closely matched the recommended way of assessing functioning, though it approached the domains in an unbalanced way.

Prediction of obstructive sleep apnea: comparative performance of three screening instruments on the apnea-hypopnea index and the oxygen desaturation index.

PURPOSE: To evaluate the performance of the NoSAS (neck, obesity, snoring, age, sex) score, the STOP-Bang (snoring, tiredness, observed apneas, blood pressure, body mass index, age, neck circumference, gender) questionnaire, and the Epworth sleepiness score (ESS) as a screening tool for obstructive sleep apnea (OSA) severity based on the apnea-hypopnea index (AHI) and the oxygen desaturation index (ODI). METHODS: Data from 235 patients who were monitored by ambulant polysomnography (PSG) were retrospectively analyzed. OSA severity was classified based on the AHI; similar classification categories were made based on the ODI. Discrimination was assessed by the area under the curve (AUC), while predictive parameters were calculated by four-grid contingency tables. RESULTS: The NoSAS score and the STOP-Bang questionnaire were both equally adequate screening tools for the AHI and the ODI with AUC ranging from 0.695 to 0.767 and 0.684 to 0.767, respectively. Both questionnaires perform better when used as a continuous variable. The ESS did not show adequate discrimination for screening for OSA (AUC ranging from 0.450 to 0.525). Male gender, age, and BMI proved to be the strongest individual predictors in this cohort. CONCLUSION: This is the first study to evaluate the predictive performance of three different screening instruments with respect to both the AHI and the ODI. This is important, due to increasing evidence that the ODI may have a higher reproducibility in the clinical setting. The NoSAS score and the STOP-Bang questionnaire proved to be equally adequate to predict OSA severity based on both the AHI and the ODI.

Screening performance of the chest X-ray in adult blunt trauma evaluation: Is it effective and what does it miss?

BACKGROUND: Although chest x-ray (CXR) is often used as a screening tool for thoracic injury in adult blunt trauma assessment, its screening performance is unclear. Using chest CT as the referent standard, we sought to determine the screening performance of CXR for injury. METHODS: We analyzed data from the NEXUS Chest CT study, in which we prospectively enrolled blunt trauma patients older than 14 years who received chest imaging as part of their evaluation at nine level I trauma centers. For this analysis, we included patients who had both CXR and chest CT. We used CT as the referent standard and categorized injuries as clinically major or minor according to an a priori expert panel classification. RESULTS: Of 11,477 patients enrolled, 4501 had both CXR and chest CT; 1496 (33.2%) were found to have injury, of which 256 (17%) were classified as major injury. CXR missed injuries in 818 patients (54.7%), of which 63 (7.7%) were classified as major injuries. For injuries of major clinical significance, CXR had a sensitivity of 75.4% (95% confidence interval [CI] 69.6-80.4%), specificity of 86.2% (95% CI 85.1-87.2%), negative predictive value of 98.3 (95%CI 97.9-98.6%), and positive predictive value of 24.7 (95%CI 22.9-26.7%). For any injury CXR had a sensitivity of 45.3% (95% CI 42.8-47.9%), specificity of 96.6% (95% CI 95.9-97.2%), negative predictive value of 78% (95% CI 77.2-78.8%), and positive predictive value of 86.9% (95% CI 84.5-89.0%). The most common missed major injuries were pneumothorax (30/185; 16.2%), spinal fractures (19/39; 48.7%), and hemothorax (8/70; 11.4%). The most common missed minor injuries were rib fractures (381/836; 45.6%), pulmonary contusion (203/462; 43.9%), and sternal fractures (153/229; 66.8%). CONCLUSIONS: When used alone, without other trauma screening criteria, CXR has poor screening performance for blunt thoracic injury.

Evaluation of a novel approach to recognising community-acquired paediatric sepsis at ED triage by combining an electronic screening algorithm with clinician assessment.

OBJECTIVE: We report the utilisation and impact of a novel triage-based electronic screening tool (eST) combined with clinical assessment to recognise sepsis in paediatric ED. METHODS: An electronic sepsis screening tool was implemented in the paediatric EDs of two large UK secondary care hospitals between June 2018 and January 2019. Patients eligible for screening were children < 16 years of ages excluding those with minor injuries or who were brought directly to resuscitation. Subsequently, a retrospective evaluation was performed to determine the performance of the tool alone and in combination with clinical assessment after triage, to identify septic patients, using sensitivity, specificity, positive, negative predictive values (PPV and NPV) and likelihood ratios. RESULTS: 19 912 children were triaged during the study period, of whom 90 (0.45%) were classified as having sepsis. 99% of all eligible patients were screened. The eST alerted for 2651 (13.3%) patients. After immediate physician assessment, 151 were treated for sepsis in the ED, of whom 70 had a final diagnosis of sepsis. Eight patients who were not thought to be septic returned with sepsis within 24 hours. The eST showed a sensitivity of 86.7% (95% CI 77.5% to 92.6%), specificity 87.0% (95% CI 86.5% to 87.5%), PPV 2.94% (95% CI 2.35% to 3.68%), NPV 99.9% (95% CI 99.8% to 99.9%) which improved with combined clinical assessment to a sensitivity of 90.0% (95% CI 81.4% to 95.0%), specificity 99.4 (95% CI 99.3% to 99.5%), PPV 42.0 (95% CI 35.0% to 49.3%) and NPV 99.9% (95% CI 99.9% to 99.9%). CONCLUSION: Utilisation of a novel triage-based eST allowed sepsis screening in over 99% of eligible patients. The screening tool showed good accuracy to recognise sepsis at triage in the ED, which was augmented further by combining it with clinician assessment. The screening tool requires further refinement through multicentre evaluation to avoid missing sepsis cases.