Category: Nevin Manimala

J Med Internet Res. 2023 Apr 4;25:e39259. doi: 10.2196/39259.

ABSTRACT

BACKGROUND: The majority of Germans see a deficit in information availability for choosing a physician. An increasing number of people use physician rating websites and decide upon the information provided. In Germany, the most popular physician rating website is Jameda.de, which offers monthly paid membership plans. The platform operator states that paid memberships have no influence on the rating indicators or list placement.

OBJECTIVE: The goal of this study was to investigate whether a physician’s membership status might be related to his or her quantitative evaluation factors and to possibly quantify these effects.

METHODS: Physician profiles were retrieved through the search mask on Jameda.de website. Physicians from 8 disciplines in Germany’s 12 most populous cities were specified as search criteria. Data Analysis and visualization were done with Matlab. Significance testing was conducted using a single factor ANOVA test followed by a multiple comparison test (Tukey Test). For analysis, the profiles were grouped according to member status (nonpaying, Gold, and Platinum) and analyzed according to the target variables-physician rating score, individual patient’s ratings, number of evaluations, recommendation quota, number of colleague recommendations, and profile views.

RESULTS: A total of 21,837 nonpaying profiles, 2904 Gold, and 808 Platinum member profiles were acquired. Statistically significant differences were found between paying (Gold and Platinum) and nonpaying profiles in all parameters we examined. The distribution of patient reviews differed also by membership status. Paying profiles had more ratings, a better overall physician rating, a higher recommendation quota, and more colleague recommendations, and they were visited more frequently than nonpaying physicians’ profiles. Statistically significant differences were found in most evaluation parameters within the paid membership packages in the sample analyzed.

CONCLUSIONS: Paid physician profiles could be interpreted to be optimized for decision-making criteria of potential patients. With our data, it is not possible to draw any conclusions of mechanisms that alter physicians’ ratings. Further research is needed to investigate the causes for the observed effects.

PMID:37014690 | DOI:10.2196/39259

J Med Internet Res. 2023 Apr 4;25:e40337. doi: 10.2196/40337.

ABSTRACT

BACKGROUND: This paper reviews nationally representative public opinion surveys on artificial intelligence (AI) in the United States, with a focus on areas related to health care. The potential health applications of AI continue to gain attention owing to their promise as well as challenges. For AI to fulfill its potential, it must not only be adopted by physicians and health providers but also by patients and other members of the public.

OBJECTIVE: This study reviews the existing survey research on the United States’ public attitudes toward AI in health care and reveals the challenges and opportunities for more effective and inclusive engagement on the use of AI in health settings.

METHODS: We conducted a systematic review of public opinion surveys, reports, and peer-reviewed journal articles published on Web of Science, PubMed, and Roper iPoll between January 2010 and January 2022. We include studies that are nationally representative US public opinion surveys and include at least one or more questions about attitudes toward AI in health care contexts. Two members of the research team independently screened the included studies. The reviewers screened study titles, abstracts, and methods for Web of Science and PubMed search results. For the Roper iPoll search results, individual survey items were assessed for relevance to the AI health focus, and survey details were screened to determine a nationally representative US sample. We reported the descriptive statistics available for the relevant survey questions. In addition, we performed secondary analyses on 4 data sets to further explore the findings on attitudes across different demographic groups.

RESULTS: This review includes 11 nationally representative surveys. The search identified 175 records, 39 of which were assessed for inclusion. Surveys include questions related to familiarity and experience with AI; applications, benefits, and risks of AI in health care settings; the use of AI in disease diagnosis, treatment, and robotic caregiving; and related issues of data privacy and surveillance. Although most Americans have heard of AI, they are less aware of its specific health applications. Americans anticipate that medicine is likely to benefit from advances in AI; however, the anticipated benefits vary depending on the type of application. Specific application goals, such as disease prediction, diagnosis, and treatment, matter for the attitudes toward AI in health care among Americans. Most Americans reported wanting control over their personal health data. The willingness to share personal health information largely depends on the institutional actor collecting the data and the intended use.

CONCLUSIONS: Americans in general report seeing health care as an area in which AI applications could be particularly beneficial. However, they have substantial levels of concern regarding specific applications, especially those in which AI is involved in decision-making and regarding the privacy of health information.

PMID:37014676 | DOI:10.2196/40337

JMIR Res Protoc. 2023 Apr 4;12:e45178. doi: 10.2196/45178.

ABSTRACT

BACKGROUND: Women often experience many unique health issues and conditions throughout their working lives. The Internet of Things (IoT) is a system of interrelated digital devices that can enable data exchanges over a network without human-to-human or human-to-computer interaction. The usage of applications and IoT in improving women’s health has recently increased worldwide. However, there has been no consensus on the effectiveness of IoT in improving women’s health outcomes.

OBJECTIVE: This systematic review and network meta-analysis (NMA) aims to assess and synthesize the role of apps and the IoT in improving women’s health and to identify the ranking of interventions for ensuring better results for each stated outcome.

METHODS: Our systematic review and NMA will be conducted in accordance with the guidelines of the Cochrane Handbook. We will comprehensively search the following electronic databases: PubMed (including MEDLINE), Cochrane Central Register of Controlled Trials, Embase, Cumulative Index to Nursing and Allied Health Literature (ie, CINAHL), PsycINFO, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry, along with other resources to identify relevant randomized controlled trials that have assessed the effects of various apps and the IoT with regard to improving working-aged women’s health in high-income countries. We will segment and analyze the results of the included studies based on age categories (women undergoing a preconception period, those undergoing gestational and postpartum periods, and menopausal and pre- and postmenopausal women) and the medical history (women who have a specific medical condition-eg, cancer or diabetes-and women who do not have them) separately. Two independent reviewers will perform the study selection, data extraction, and quality assessment. Our primary outcomes include health status, well-being, and quality of life. We will perform pairwise meta-analysis and NMA to estimate the direct, indirect, and relative effects of apps and the IoT on women’s health outcomes. We will also assess the hierarchy of interventions, statistical inconsistencies, and certainties of evidence for each outcome.

RESULTS: We plan to conduct the search in January 2023 and are currently discussing search strategies with the literature search specialists. The final report is planned for submission to a peer-reviewed journal in September 2023.

CONCLUSIONS: To the best of our knowledge, this review will be the first to identify the ranking of IoT intervention for ensuring working-aged women’s health outcomes. These findings may be of great use to researchers, policy makers, and others with an interest in the field.

TRIAL REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO) CRD42022384620; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=384620.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/45178.

PMID:37014674 | DOI:10.2196/45178

Transl Vis Sci Technol. 2023 Apr 3;12(4):2. doi: 10.1167/tvst.12.4.2.

ABSTRACT

PURPOSE: To design and validate a high-sensitivity semiautomated algorithm, based on adaptive contrast image, able to identify and quantify tear meniscus height (TMH) from optical coherence tomography (OCT) images by using digital image processing (DIP) techniques.

METHODS: OCT images of the lacrimal meniscus of healthy patients and with dry eye are analyzed by our algorithm, which is composed of two stages: (1) the region of interest and (2) TMH detection and measurement. The algorithm performs an adaptive contrast sequence based on morphologic operations and derivative image intensities. Trueness, repeatability, and reproducibility for TMH measurements are computed and the algorithm performance is statistically compared against the corresponding negative obtained manually by using a commercial software.

RESULTS: The algorithm showed excellent repeatability supported by an intraclass correlation coefficient equal to 0.993, a within-subject standard deviation equal to 9.88, and a coefficient of variation equal to 2.96%, and for the reproducibility test, the results did not show a significant difference as the mean value was 244.4 ± 114.9 µm for an expert observer versus 242.4 ± 111.2 µm for the inexperienced observer (P = 0.999). The method strongly suggests the algorithm can predict measurements that are manually performed with commercial software.

CONCLUSIONS: The presented algorithm possess high potential to identify and measure TMH from OCT images in a reproducible and repeatable way with minimal dependency on user.

TRANSLATIONAL RELEVANCE: The presented work shows a methodology on how, by using DIP, it is possible to process OCT images to calculate TMH and aid ophthalmologists in the diagnosis of dry eye disease.

PMID:37014649 | DOI:10.1167/tvst.12.4.2

JAMA Netw Open. 2023 Apr 3;6(4):e236530. doi: 10.1001/jamanetworkopen.2023.6530.

ABSTRACT

IMPORTANCE: The prevalence of antiphospholipid antibodies (aPL) and their association with future atherosclerotic cardiovascular disease (ASCVD) risk has yet to be thoroughly investigated.

OBJECTIVE: To determine the association between measurements of aPL at a single time point and ASCVD risk in a diverse population.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study measured 8 aPL (anticardiolipin [aCL] IgG/IgM/IgA, anti-beta-2 glycoprotein I [aβ2GPI] IgG/IgM/IgA, and antiphosphatidylserine/prothrombin [aPS/PT] IgG/IgM) by solid-phase assays in plasma from participants of the Dallas Heart Study (DHS) phase 2, a multiethnic, population-based cohort study. Blood samples were collected between 2007 and 2009. The median follow-up was 8 years. Statistical analysis was performed from April 2022 to January 2023.

MAIN OUTCOMES AND MEASURES: Associations of aPL with future ASCVD events (defined as first nonfatal myocardial infarction, first nonfatal stroke, coronary revascularization, or death from cardiovascular cause) were assessed by Cox proportional hazards models, adjusting for known risk factors, medications, and multiple comparisons.

RESULTS: Among the 2427 participants (mean [SD] age, 50.6 [10.3] years; 1399 [57.6%] female; 1244 [51.3%] Black, 339 [14.0%] Hispanic, and 796 [32.8%] White), the prevalence of any positive aPL tested at a single time point was 14.5% (353 of 2427), with approximately one-third of those detected at a moderate or high titer; aCL IgM had the highest prevalence (156 individuals [6.4%]), followed by aPS/PT IgM (88 [3.4%]), aβ2GPI IgM (63 [2.6%]), and aβ2GPI IgA (62 [2.5%]). The IgA of aCL (adjusted hazard ratio [HR], 4.92; 95% CI, 1.52-15.98) and aβ2GPI (HR, 2.91; 95% CI, 1.32-6.41) were independently associated with future ASCVD events. The risk further increased when applying a positivity threshold of at least 40 units (aCL IgA: HR, 9.01 [95% CI, 2.73-29.72]; aβ2GPI IgA: HR, 4.09 [95% CI, 1.45-11.54]). Levels of aβ2GPI IgA negatively correlated with cholesterol efflux capacity (r = -0.055; P = .009) and positively correlated with circulating oxidized LDL (r = 0.055; P = .007). aβ2GPI IgA-positive plasma was associated with an activated endothelial cell phenotype as evidenced by increased surface expression of surface E-selectin, intercellular adhesion molecule-1, and vascular cell adhesion molecule-1.

CONCLUSIONS AND RELEVANCE: In this population-based cohort study, aPL detectable by solid-phase assays were present in a substantial proportion of adults; positive aCL IgA and aβ2GPI IgA at a single time point were independently associated with future ASCVD events. Longitudinal studies with serial aPL measurements are needed to further explore these findings.

PMID:37014642 | DOI:10.1001/jamanetworkopen.2023.6530

JAMA Netw Open. 2023 Apr 3;6(4):e236805. doi: 10.1001/jamanetworkopen.2023.6805.

ABSTRACT

IMPORTANCE: Adequate prehospital triage is pivotal to enable optimal care in inclusive trauma systems and reduce avoidable mortality, lifelong disabilities, and costs. A model has been developed to improve the prehospital allocation of patients with traumatic injuries and was incorporated in an application (app) to be implemented in prehospital practice.

OBJECTIVE: To evaluate the association between the implementation of a trauma triage (TT) intervention with an app and prehospital mistriage among adult trauma patients.

DESIGN, SETTING, AND PARTICIPANTS: This population-based, prospective quality improvement study was conducted in 3 of the 11 Dutch trauma regions (27.3%), with full coverage of the corresponding emergency medical services (EMS) regions participating in this study. Participants included adult patients (age ≥16 years) with traumatic injuries who were transported by ambulance between February 1, 2015, and October 31, 2019, from the scene of injury to any emergency department in the participating trauma regions. Data were analyzed between July 2020 and June 2021.

EXPOSURES: Implementation of the TT app and the awareness of need for adequate triage created by its implementation (ie, the TT intervention).

MAIN OUTCOMES AND MEASURES: The primary outcome was prehospital mistriage, evaluated in terms of undertriage and overtriage. Undertriage was defined as the proportion of patients with an Injury Severity Score (ISS) of 16 or greater who were initially transported to a lower-level trauma center (designated to treat patients who are mildly and moderately injured) and overtriage as the proportion of patients with an ISS of less than 16 who were initially transported to a higher-level trauma center (designated to treat patients who are severely injured).

RESULTS: A total of 80 738 patients were included (40 427 [50.1%] before and 40 311 [49.9%] after implementation of the intervention), with a median (IQR) age of 63.2 (40.0-79.7) years and 40 132 (49.7%) male patients. Undertriage decreased from 370 of 1163 patients (31.8%) to 267 of 995 patients (26.8%), while overtriage rates did not increase (8202 of 39 264 patients [20.9%] vs 8039 of 39 316 patients [20.4%]). The implementation of the intervention was associated with a statistically significantly reduced risk for undertriage (crude risk ratio [RR], 0.95; 95% CI, 0.92 to 0.99, P = .01; adjusted RR, 0.85; 95% CI, 0.76-0.95; P = .004), but the risk for overtriage was unchanged (crude RR, 1.00; 95% CI, 0.99-1.00; P = .13; adjusted RR, 1.01; 95% CI, 0.98-1.03; P = .49).

CONCLUSIONS AND RELEVANCE: In this quality improvement study, implementation of the TT intervention was associated with improvements in rates of undertriage. Further research is needed to assess whether these findings are generalizable to other trauma systems.

PMID:37014639 | DOI:10.1001/jamanetworkopen.2023.6805

Aging Clin Exp Res. 2023 Apr 4. doi: 10.1007/s40520-023-02390-2. Online ahead of print.

ABSTRACT

BACKGROUND: Postoperative delirium (POD) is a major complication following a surgical procedure. There is evidence that improving knowledge about POD could enhance POD care and patient outcomes.

AIM: The study aimed to evaluate whether the amount of delirium education among registered nurses working in post-anaesthetics care units (PACU) impacts on their self-reported confidence and competence in recognising and managing delirium as well as prior knowledge on factors that influence the risk of delirium onset for older people.

METHOD: The current study utilised an online survey on delirium care practice among registered nurses in PACUs. The survey consisted of 27 items. There were questions about confidence and competence in delirium care, knowledge about delirium risk factors, and ranked responses to two case scenario questions to evaluate the application of POD care. There were also demographic questions, including previous experience with delirium care education.

RESULTS: A total of 336 responses were generated from registered nurses working in PACU. Our findings found substantial variability among the respondents about their delirium care education. The amount of delirium education did not influence the PACU registered nurses’ confidence or competence in delirium care. In addition, previous education did not have an impact on their knowledge about delirium risk factors.

DISCUSSION AND CONCLUSION: These findings suggested that the quantity of prior education about delirium did not improve the confidence, competence, knowledge, or case scenario questions of PACU registered nurses. Thus, delirium care education needs to be transformed to ensure it has a positive effect on delirium care clinical practice by registered nurses in PACU.

PMID:37014618 | DOI:10.1007/s40520-023-02390-2

Aging Clin Exp Res. 2023 Apr 4. doi: 10.1007/s40520-023-02398-8. Online ahead of print.

ABSTRACT

BACKGROUND: Handgrip strength (HGS) is a well-established clinical biomarker that assesses functional capacity in older populations. In addition, HGS is a diagnostic tool that forecasts aging health conditions, such as sarcopenia.

AIMS: This paper provides HGS statistical tolerance regions and presents the need to establish HGS reference values according to patients’ characteristics.

METHODS: For this purpose, we used a conditional tolerance algorithm for HGS, and we observed the tolerances regions in different age strata and sex of non-sarcopenic individuals from the National Health and Nutrition Examination Survey (NHANES, wave 2011-2012).

RESULTS AND DISCUSSION: Our results have critical implications for sarcopenia, since conventional and available HGS cut-offs do not consider age range.

CONCLUSIONS: This paper offers new perspectives on the evolution of traditional definitions of sarcopenia according to the principles of precision medicine.

PMID:37014617 | DOI:10.1007/s40520-023-02398-8

Atten Percept Psychophys. 2023 Apr 4. doi: 10.3758/s13414-023-02703-7. Online ahead of print.

ABSTRACT

The current study aims to explore one factor that likely contributes to these statistical regularities, familiarity. Are highly familiar stimuli perceived more readily? Previous work showing effects of familiarity on perception have used recognition tasks, which arguably tap into post-perceptual processes. Here we use a perceptual task that does not depend on explicit recognition; participants were asked to discriminate whether a rapidly presented image was intact or scrambled. The familiarity level of stimuli was manipulated. Results show that famous or upright orientated logos (Experiments 1 and 2) or faces (Experiment 3) were better discriminated than novel or inverted logos and faces. To further dissociate our task from recognition, we implemented a simple detection task (Experiment 4) and directly compared the intact/scrambled task to a recognition task (Experiment 5) on the same set of faces used in Experiment 3. The fame and orientation familiarity effect were still present in the simple detection task, and the duration needed on the intact/scrambled task was significantly less than the recognition task. We conclude that familiarity effect demonstrated here is not driven by explicit recognition and instead reflects a true perceptual effect.

PMID:37014611 | DOI:10.3758/s13414-023-02703-7

Environ Sci Pollut Res Int. 2023 Apr 4. doi: 10.1007/s11356-023-26578-1. Online ahead of print.

ABSTRACT

PM_2.5 is an important air pollution index, which has been widely concerned. An excellent PM_2.5 prediction system can effectively help people protect their respiratory tract from injury. However, due to the strong uncertainty of PM_2.5 data, the accuracy of traditional point prediction and interval prediction method is not satisfactory, especially for interval prediction, which is usually difficult to achieve the expected interval coverage (PINC). In order to solve the above problems, a new hybrid PM_2.5 prediction system is proposed, which can quantify the certainty and uncertainty of future PM_2.5 at the same time. For point prediction, a multi-strategy improved multi-objective crystal algorithm (IMOCRY) is proposed; the chaotic mapping and screening operator are added to make the algorithm more suitable for practical application. At the same time, the combined neural network based on unconstrained weighting method further improves the point prediction accuracy. For interval prediction, a new strategy is proposed, which uses the combination of fuzzy information granulation and variational mode decomposition to process the data. The high-frequency components are extracted by the VMD method, and then quantified by FIG method. By this way, the fuzzy interval prediction results with high coverage and low interval width are obtained. Through 4 groups of experiments and 2 groups of discussions, the advanced nature, accuracy, generalization, and fuzzy prediction ability of the prediction system are all satisfactory, which verified the effect of the system in practical application.

PMID:37014598 | DOI:10.1007/s11356-023-26578-1