Category: Nevin Manimala

J Cataract Refract Surg. 2023 Feb 15. doi: 10.1097/j.jcrs.0000000000001169. Online ahead of print.

ABSTRACT

PURPOSE: To develop a novel virtual surgery simulation platform to predict postoperative corneal stiffness (Kcmean) after laser vision correction (LVC) surgery.

SETTING: Narayana Nethralaya eye hospital and Sankara Nethralaya, India; Humanitas Clinical and Research Center, Italy.

DESIGN: Retrospective, observational case series.

METHODS: 529 eyes from 529 patients from three eye centres and 10 post-SMILE ectasia eyes were included. The software (called AcuSimX™) derived the anisotropic, fibril and extra-cellular matrix biomechanical properties (using finite element calculation) of the cornea using the preoperative Corvis-ST, Pentacam (OCULUS Optikgerate Gmbh, Germany) measurement and inverse finite element method assuming published healthy collagen fibril orientations. Then, the software computed postoperative Kcmean was adjusted with an artificial intelligence (AI) model (Orange AI, Slovenia) for measurement uncertainties. A decision tree was developed to classify ectasia from normal eyes using the software computed and preoperative parameters.

RESULTS: In the training cohort (n = 371), the mean absolute error (MAE) and intraclass correlation coefficient (ICC) were 6.24 N/m and 0.84 [95% CI: 0.80-0.87], respectively. Similarly in the test cohort (n = 158), these were 6.47 N/m and 0.84 [0.78-0.89], respectively. In the 10 ectasia eyes, the measured in vivo (74.01 [70.01, 78.01]) and software computed (74.1 [69.03, 79.17]) Kcmean weren’t statistically different (p=0.96). While no statistically significant differences in these values were observed between the stable and ectasia groups (p≥0.14), the decision tree classification had an AUROC of 1.0.

CONCLUSION: The novel software provided an easy to use virtual surgery simulation platform for post-LVC corneal stiffness prediction by clinicians and was assessed in post-SMILE ectasia eyes. Further assessments with ectasia after surgeries are required.

PMID:36791274 | DOI:10.1097/j.jcrs.0000000000001169

Health Rep. 2023 Feb 15;34(2):29-39. doi: 10.25318/82-003-x202300200003-eng.

ABSTRACT

BACKGROUND: Utility scores are an important tool for evaluating health-related quality of life. Utility score norms have been published for Canadian adults, but no nationally representative utility score norms are available for children and youth.

DATA AND METHODS: Health Utilities Index Mark 3 (HUI3) data from two recent cycles of the Canadian Health Measures Survey (i.e., 2016 and 2017, and 2018 and 2019) were used to provide utility score norms for children aged 6 to 11 years and adolescents aged 12 to 17 years. Children younger than 14 years answered the HUI3 under the supervision of an adult, while older children answered without supervision. Utility scores were reported as a weighted average (95% confidence intervals [CIs]) and median values (interquartile range). Utility scores were stratified by sociodemographic and medical characteristics of the child or adolescent. Regression analyses were used to identify predictors of utility scores. All results were weighted using sampling weights provided by Statistics Canada.

RESULTS: Among the 2,297,136 children aged 6 to 11 years and the 2,329,185 adolescents aged 12 to 17 years in the weighted sample, the average utility scores were 0.95 (95% CI: 0.94 to 0.95) and 0.89 (95% CI: 0.87 to 0.90), respectively. Approximately 60% of the children and 34% of the adolescents had a utility score of 1.00. Analyses identified several factors associated with utility scores (e.g., age, chronic condition and income levels), although differences were observed between children and adolescents.

INTERPRETATION: This study provides utility score estimates based on a nationally representative sample of Canadian children and youth. Further research examining the determinants of utility scores of children and adolescents is warranted.

PMID:36791271 | DOI:10.25318/82-003-x202300200003-eng

Health Rep. 2023 Feb 15;34(2):17-28. doi: 10.25318/82-003-x202300200002-eng.

ABSTRACT

BACKGROUND: Online digital media are a central part of adolescents’ lives, providing opportunities for social connection. However, some research has suggested that online digital media use may be negatively associated with mental health. Little population-based research has examined associations between various types of online digital media use and adolescent mental health.

DATA AND METHODS: Data from 13,600 adolescents aged 12 to 17 were drawn from the 2019 Canadian Health Survey on Children and Youth. Adolescents reported on how frequently they used social media, video or instant messaging, and online gaming, as well as their general mental health, eating disorder symptoms and, for those aged 15 to 17, suicidal ideation and attempt. Logistic regression was used to estimate the odds of each outcome from the frequency of each type of digital media use, stratified by sex.

RESULTS: Associations were noted between the frequency of social media and video and instant messaging use, and general mental health, eating disorder symptoms, and suicidal ideation and attempt. After cybervictimization and sleep adequacy were accounted for, associations with eating disorder symptoms remained significant for girls and boys. Never participating in online gaming was associated with lower odds of lower general mental health and suicidal ideation among girls, but not boys.

INTERPRETATION: Different types of online digital media use are differentially associated with mental health outcomes, and associations differ between sexes. The associations between social media and video or instant messaging, and mental ill health may be partially explained by the experience of cybervictimization and sleep adequacy. More research on online gaming, particularly among girls, is needed to clarify associations with mental health.

PMID:36791270 | DOI:10.25318/82-003-x202300200002-eng

Health Rep. 2023 Feb 15;34(2):3-16. doi: 10.25318/82-003-x202300200001-eng.

ABSTRACT

BACKGROUND: Mortality rates in Canada have been shown to vary by population group (e.g., Indigenous peoples, immigrants) and social economic status (e.g., income levels). Mortality patterns for some groups, including Black individuals, are not as well known. The objective of this study was to assess cause-specific mortality for Black adults living in Canada.

METHODS: Mortality inequalities between Black and White cohort members were estimated by sex using Cox proportional hazard models, based on data from the 2001, 2006 and 2011 Canadian Census Health and Environment Cohorts (CanCHECs). The CanCHEC cycles were combined and followed for mortality between Census Day and December 31, 2016 or 2019, resulting in a follow-up period of 15.6, 13.6 or 8.6 years, depending on the CanCHEC cycle.

RESULTS: Ischemic heart disease mortality was the leading cause of death among adult Black males (12.9%) and females (9.8%), as it is for adult White males (16.4%) and females (12.4%). Despite reduced risk of all-cause mortality among Black males and females, compared with White cohort members, there was notable increased risk for some cause-specific mortality. For instance, in the age-adjusted model, among the 25 causes of death examined, Black males had an increased risk of dying from four causes (HIV/AIDS, prostate cancer, diabetes mellitus and cerebrovascular disease), compared with White males. Similarly, Black females were at an increased risk for 6 causes of death (HIV/AIDS, stomach cancer, corpus uteri cancer, lymphomas and multiple myeloma, diabetes mellitus, and endocrine disorders) out of the 27 causes of death examined. These relative increased risks persisted for most causes of death after adjustment for differences in important social determinants of health.

INTERPRETATION: Results showed substantial variability in the risk of dying by cause of death between Black and White cohort members. An important step in reducing health inequities is the routine identification and surveillance of different health outcomes by population groups. This study helps fill that information gap.

PMID:36791269 | DOI:10.25318/82-003-x202300200001-eng

Environ Sci Technol. 2023 Feb 15. doi: 10.1021/acs.est.2c06117. Online ahead of print.

ABSTRACT

In the marine environment, discarded cigarette filters (CFs) deteriorate and leach filter-associated chemicals. The study aim was to assess the effects of smoked CFs (SCFs) and non-smoked CFs (NCFs) particles on individual life-history traits in the deposit-feeding polychaete Capitella teleta and extrapolate these to possible population-level effects. C. teleta was exposed to sediment-spiked particles of NCFs and SCFs at an environmentally realistic concentration (0.1 mg particles g^-1 dw sed) and a 100-fold higher (10 mg particles g^-1 dw sed) concentration. Experimental setup incorporated 11 individual endpoints and lasted approximately 6 months. There were significant effects on all endpoints, except from adult body volume and egestion rate, in worms exposed to 10 mg SCF particles g^-1 dw sed. Although not statistically significant, there was ≥50% impact on time between reproductive events and number of eggs per female at 0.1 mg SCF particles g^-1 dw sed. None of the endpoints was significantly affected by NCFs. Results suggest that SCFs are likely to affect individual life-history traits of C. teleta, whereas the population model suggests that these effects might not transform into population-level effects. The results further indicate that chemicals associated with CFs are the main driver causing the effects rather than the CF particles.

PMID:36791268 | DOI:10.1021/acs.est.2c06117

Sci Adv. 2023 Feb 15;9(7):eabn3999. doi: 10.1126/sciadv.abn3999. Epub 2023 Feb 15.

ABSTRACT

Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (i) in the translation of real-world goals to goals on a particular set of training data, (ii) in the translation of abstract goals on the training data to a concrete mathematical problem, (iii) in the use of an algorithm to solve the stated mathematical problem, and (iv) in the use of a particular code implementation of the chosen algorithm. We detail how trust can fail at each step and illustrate our taxonomy with two case studies. Finally, we describe a wide variety of methods that can be used to increase trust at each step of our taxonomy. The use of our taxonomy highlights not only steps where existing research work on trust tends to concentrate and but also steps where building trust is particularly challenging.

PMID:36791188 | DOI:10.1126/sciadv.abn3999

J Med Internet Res. 2023 Feb 15;25:e42985. doi: 10.2196/42985.

ABSTRACT

BACKGROUND: By the end of 2022, more than 100 million people were infected with COVID-19 in the United States, and the cumulative death rate in rural areas (383.5/100,000) was much higher than in urban areas (280.1/100,000). As the pandemic spread, people used social media platforms to express their opinions and concerns about COVID-19-related topics.

OBJECTIVE: This study aimed to (1) identify the primary COVID-19-related topics in the contiguous United States communicated over Twitter and (2) compare the sentiments urban and rural users expressed about these topics.

METHODS: We collected tweets containing geolocation data from May 2020 to January 2022 in the contiguous United States. We relied on the tweets’ geolocations to determine if their authors were in an urban or rural setting. We trained multiple word2vec models with several corpora of tweets based on geospatial and timing information. Using a word2vec model built on all tweets, we identified hashtags relevant to COVID-19 and performed hashtag clustering to obtain related topics. We then ran an inference analysis for urban and rural sentiments with respect to the topics based on the similarity between topic hashtags and opinion adjectives in the corresponding urban and rural word2vec models. Finally, we analyzed the temporal trend in sentiments using monthly word2vec models.

RESULTS: We created a corpus of 407 million tweets, 350 million (86%) of which were posted by users in urban areas, while 18 million (4.4%) were posted by users in rural areas. There were 2666 hashtags related to COVID-19, which clustered into 20 topics. Rural users expressed stronger negative sentiments than urban users about COVID-19 prevention strategies and vaccination (P<.001). Moreover, there was a clear political divide in the perception of politicians by urban and rural users; these users communicated stronger negative sentiments about Republican and Democratic politicians, respectively (P<.001). Regarding misinformation and conspiracy theories, urban users exhibited stronger negative sentiments about the “covidiots” and “China virus” topics, while rural users exhibited stronger negative sentiments about the “Dr. Fauci” and “plandemic” topics. Finally, we observed that urban users’ sentiments about the economy appeared to transition from negative to positive in late 2021, which was in line with the US economic recovery.

CONCLUSIONS: This study demonstrates there is a statistically significant difference in the sentiments of urban and rural Twitter users regarding a wide range of COVID-19-related topics. This suggests that social media can be relied upon to monitor public sentiment during pandemics in disparate types of regions. This may assist in the geographically targeted deployment of epidemic prevention and management efforts.

PMID:36790847 | DOI:10.2196/42985

JMIR Res Protoc. 2023 Feb 15;12:e44456. doi: 10.2196/44456.

ABSTRACT

BACKGROUND: The World Federation of Obesity warns that the main health problem of the next decade will be childhood obesity. It is known that factors such as gestational obesity produce profound effects on fetal programming and are strong predictors of overweight and obesity in children. Therefore, establishing healthy eating behaviors during pregnancy is the key to the primary prevention of the intergenerational transmission of obesity. Mobile health (mHealth) programs are potentially more effective than face-to-face interventions, especially during a public health emergency such as the COVID-19 outbreak.

OBJECTIVE: This study aims to evaluate the effectiveness of an mHealth intervention to reduce excessive weight gain in pregnant women who attend family health care centers.

METHODS: The design of the intervention corresponds to a classic randomized clinical trial. The participants are pregnant women in the first trimester of pregnancy who live in urban and semiurban areas. Before starting the intervention, a survey will be applied to identify the barriers and facilitators perceived by pregnant women to adopt healthy eating behaviors. The dietary intake will be estimated in the same way. The intervention will last for 12 weeks and consists of sending messages through a multimedia messaging service with food education, addressing the 3 domains of learning (cognitive, affective, and psychomotor). Descriptive statistics will be used to analyze the demographic, socioeconomic, and obstetric characteristics of the respondents. The analysis strategy follows the intention-to-treat principle. Logistic regression analysis will be used to compare the intervention with routine care on maternal pregnancy outcome and perinatal outcome.

RESULTS: The recruitment of study participants began in May 2022 and will end in May 2023. Results include the effectiveness of the intervention in reducing the incidence of excessive gestational weight gain. We also will examine the maternal-fetal outcome as well as the barriers and facilitators that influence the weight gain of pregnant women.

CONCLUSIONS: Data from this effectiveness trial will determine whether mami-educ successfully reduces rates of excessive weight gain during pregnancy. If successful, the findings of this study will generate knowledge to design and implement personalized prevention strategies for gestational obesity that can be included in routine primary care.

TRIAL REGISTRATION: ClinicalTrials.gov NCT05114174; https://clinicaltrials.gov/ct2/show/NCT05114174.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44456.

PMID:36790846 | DOI:10.2196/44456

JMIR Med Educ. 2023 Feb 15;9:e40040. doi: 10.2196/40040.

ABSTRACT

BACKGROUND: Remote and virtual simulations have gained prevalence during the COVID-19 pandemic as institutions maintain social distancing measures. Because of the challenges of cost, flexibility, and feasibility in traditional mannequin simulation, many health care educators have used videos as a remote simulation modality; however, videos provide minimal interactivity.

OBJECTIVE: In this study, we aimed to evaluate the role of interactivity in students’ simulation experiences. We analyzed students’ perceptions of technology acceptance and authenticity in interactive and noninteractive simulations.

METHODS: Undergraduate nursing students participated in interactive and noninteractive simulations. The interactive simulation was conducted using interactive video simulation software that we developed, and the noninteractive simulation consisted of passively playing a video of the simulation. After each simulation, the students completed a 10-item technology acceptance questionnaire and 6-item authenticity questionnaire. The data were analyzed using the Wilcoxon signed-rank test. In addition, we performed an exploratory analysis to compare technology acceptance and authenticity in interactive local and remote simulations using the Mann-Whitney U test.

RESULTS: Data from 29 students were included in this study. Statistically significant differences were found between interactive and noninteractive simulations for overall technology acceptance (P<.001) and authenticity (P<.001). Analysis of the individual questionnaire items showed statistical significance for 3 out of the 10 technology acceptance items (P=.002, P=.002, and P=.004) and 5 out of the 6 authenticity items (P<.001, P<.001, P=.001, P=.003, and P=.005). The interactive simulation scored higher than the noninteractive simulation in all the statistically significant comparisons. Our exploratory analysis revealed that local simulation may promote greater perceptions of technology acceptance (P=.007) and authenticity (P=.027) than remote simulation.

CONCLUSIONS: Students’ perceptions of technology acceptance and authenticity were greater in interactive simulation than in noninteractive simulation. These results support the importance of interactivity in students’ simulation experiences, especially in remote or virtual simulations in which students’ involvement may be less active.

PMID:36790842 | DOI:10.2196/40040

J Infect Dis. 2023 Feb 15:jiad043. doi: 10.1093/infdis/jiad043. Online ahead of print.

ABSTRACT

INTRODUCTION: We assessed the incidence and risk factors for first detection and redetection with the same human papillomavirus (HPV) genotype, and prevalence of cytological lesions during HPV redetections.

METHODS: The Ludwig-McGill cohort study followed women aged 18-60 years from São Paulo, Brazil in 1993-1997 for up to 10 years. Women provided cervical samples for cytology testing and HPV DNA testing at each visit. A redetection was defined as a recurring genotype-specific HPV positive result after one or more intervening negative visits. Predictors of genotype-specific redetection were assessed using adjusted hazard ratios (aHR) with Cox regression modeling.

RESULTS: 2184 women contributed 2368 incident HPV genotype-specific first detections and 308 genotype-specific redetections over a median follow-up of 6.5 years. The cumulative incidence of redetection with the same genotype was 6.6% at 1 year and 14.8% at 5 years after the loss of positivity of the first detection. Neither age (aHR 0.90, 95%CI 0.54-1.47 for ≥45y vs. <25y) nor new sexual partner acquisition (aHR 0.98, 95%CI 0.70-1.35) were statistically associated with genotype-specific redetection. High-grade squamous intraepithelial lesion prevalence was similar during first HPV detections (2.9%) and redetection (3.2%).

CONCLUSIONS: Our findings suggest many HPV redetections were likely reactivations of latent recurring infections.

PMID:36790831 | DOI:10.1093/infdis/jiad043