Nevin Manimala

IEEE J Biomed Health Inform. 2024 Mar 5;PP. doi: 10.1109/JBHI.2024.3372968. Online ahead of print.

ABSTRACT

OBJECTIVE: To develop a cuffless method for estimating blood pressure (BP) from fingertip strain plethysmography (SPG) recordings.

METHODS: A custom-built micro-electromechanical systems (MEMS) strain sensor is employed to record heartbeat-induced vibrations at the fingertip. An XGboost regressor is then trained to relate SPG recordings to beat-to-beat systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) values. For this purpose, each SPG segment in this setup is represented by a feature vector consisting of cardiac time interval, amplitude features, statistical properties, and demographic information of the subjects. In addition, a novel concept, coined geometric features, are introduced and incorporated into the feature space to further encode the dynamics in SPG recordings. The performance of the regressor is assessed on 32 healthy subjects through 5-fold cross-validation (5-CV) and leave-subject-out cross validation (LSOCV).

RESULTS: Mean absolute errors (MAEs) of 3.88 mmHg and 5.45 mmHg were achieved for DBP and SBP estimations, respectively, in the 5-CV setting. LSOCV yielded MAEs of 8.16 mmHg for DBP and 16.81 mmHg for SBP. Through feature importance analysis, 3 geometric and 26 integral-related features introduced in this work were identified as primary contributors to BP estimation. The method exhibited robustness against variations in blood pressure level (normal to critical) and body mass index (underweight to obese), with MAE ranges of [1.28, 4.28] mmHg and [2.64, 7.52] mmHg, respectively.

CONCLUSION: The findings suggest high potential for SPG-based BP estimation at the fingertip.

SIGNIFICANCE: This study presents a fundamental step towards the augmentation of optical sensors that are susceptible to dark skin tones.

PMID:38442050 | DOI:10.1109/JBHI.2024.3372968

JMIR Form Res. 2024 Mar 5;8:e49411. doi: 10.2196/49411.

ABSTRACT

BACKGROUND: Research gaps refer to unanswered questions in the existing body of knowledge, either due to a lack of studies or inconclusive results. Research gaps are essential starting points and motivation in scientific research. Traditional methods for identifying research gaps, such as literature reviews and expert opinions, can be time consuming, labor intensive, and prone to bias. They may also fall short when dealing with rapidly evolving or time-sensitive subjects. Thus, innovative scalable approaches are needed to identify research gaps, systematically assess the literature, and prioritize areas for further study in the topic of interest.

OBJECTIVE: In this paper, we propose a machine learning-based approach for identifying research gaps through the analysis of scientific literature. We used the COVID-19 pandemic as a case study.

METHODS: We conducted an analysis to identify research gaps in COVID-19 literature using the COVID-19 Open Research (CORD-19) data set, which comprises 1,121,433 papers related to the COVID-19 pandemic. Our approach is based on the BERTopic topic modeling technique, which leverages transformers and class-based term frequency-inverse document frequency to create dense clusters allowing for easily interpretable topics. Our BERTopic-based approach involves 3 stages: embedding documents, clustering documents (dimension reduction and clustering), and representing topics (generating candidates and maximizing candidate relevance).

RESULTS: After applying the study selection criteria, we included 33,206 abstracts in the analysis of this study. The final list of research gaps identified 21 different areas, which were grouped into 6 principal topics. These topics were: “virus of COVID-19,” “risk factors of COVID-19,” “prevention of COVID-19,” “treatment of COVID-19,” “health care delivery during COVID-19,” “and impact of COVID-19.” The most prominent topic, observed in over half of the analyzed studies, was “the impact of COVID-19.”

CONCLUSIONS: The proposed machine learning-based approach has the potential to identify research gaps in scientific literature. This study is not intended to replace individual literature research within a selected topic. Instead, it can serve as a guide to formulate precise literature search queries in specific areas associated with research questions that previous publications have earmarked for future exploration. Future research should leverage an up-to-date list of studies that are retrieved from the most common databases in the target area. When feasible, full texts or, at minimum, discussion sections should be analyzed rather than limiting their analysis to abstracts. Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction.

PMID:38441952 | DOI:10.2196/49411

JMIR Form Res. 2024 Mar 5;8:e51141. doi: 10.2196/51141.

ABSTRACT

BACKGROUND: Restorative dentistry plays a crucial role in dental practice, necessitating professionals to stay abreast with the latest advancements in the field. The advancement of technology has made web-based learning a widely used method of education delivery in dentistry, providing learners with extensive information and flexibility.

OBJECTIVE: This study aims to evaluate how effective an online educational course in restorative dentistry is for dental graduates in Syria.

METHODS: This study used a pre-experimental study design, with pretest and posttest assessments to measure changes in participants’ knowledge and skills. A total of 21 dental graduates completed the online course in restorative dentistry, which was hosted on Moodle, using the learning management system of the Syrian Virtual University. Participants were provided with a suggested learning sequence and had the flexibility to navigate the course on their own and at their own pace. The course was developed based on the principles of web course design and web-based course development using the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) general instructional design model. The pretest and posttest assessments consisted of 50 multiple-choice questions with a single correct answer, aligning with the course content. Furthermore, participants were asked to complete a course acceptance survey upon finishing the course.

RESULTS: The results showed a significant improvement in the participants’ knowledge of restorative dentistry, supported by a statistically significant P value of less than .05. The effect size of the difference between the pre and posttest indicated that the effect size, as indicated by ω², demonstrated a significant 62.1% difference between the pre and posttest, indicating a high and statistically significant effect. Furthermore, the value derived from the Haridy obtained work ratio formula indicated that the educational program was effective, with an effectiveness amount of 3.36%. Additionally, 93% (n=19) of respondents expressed confidence in having gained the expected benefits from the educational course upon its completion.

CONCLUSIONS: The findings indicated a notable enhancement in the participants’ understanding of restorative dentistry. The participants’ high satisfaction rate and positive feedback from the course acceptance survey further emphasize the favorable reception of the web-based learning approach. This study highlights the potential of web-based learning in dental education, opening the door for future research in this area. The findings of this study carry important implications for the design and implementation of web-based educational programs in dentistry, suggesting that such programs can serve as an effective tool for continuous professional development in the field.

PMID:38441921 | DOI:10.2196/51141

Phytochem Anal. 2024 Mar 4. doi: 10.1002/pca.3345. Online ahead of print.

ABSTRACT

INTRODUCTION: Plants of the Rosa genus are renowned for their pronounced and pleasant aroma and colors.

OBJECTIVE: The aim of this work was to develop a novel liquid chromatographic triple quadrupole time-of-flight tandem mass spectrometric (LC-QTOF-MS/MS) method for the investigation of the bioactive fingerprint of petals of different genotypes belonging to Rosa damascena and Rosa centifolia species.

METHODOLOGY: Central composite design (CCD) of response surface methodology (RSM) was used for the optimization of the LC-QTOF-MS/MS method. The method was validated and target, suspect, and non-target screening workflows were applied. Statistical analysis and chemometric tools were utilized to explore the metabolic fingerprint of the Rosa species.

RESULTS: RSM revealed that the optimal extraction parameters involved mixing 11 mg of sample with 1 mL of MeOH:H₂ O (70:30, v/v). Target analysis confirmed the presence of 11 analytes, all of which demonstrated low limits of quantification (LOQs; as low as 0.048 ng mg^-1 ) and sufficient recoveries (RE: 85%-107%). In total, 28 compounds were tentatively identified through suspect analysis. Non-target analysis enabled the generation of robust OPLS-DA and HCA models that classified the samples according to their species with 100% accuracy.

CONCLUSIONS: A novel LC-QTOF-MS/MS method was developed and applied in the analysis of 47 R. centifolia and R. damascena flowers belonging to different genotypes.

PMID:38439140 | DOI:10.1002/pca.3345

Pharm Stat. 2024 Mar 4. doi: 10.1002/pst.2376. Online ahead of print.

ABSTRACT

Recent years have seen an increasing interest in incorporating external control data for designing and evaluating randomized clinical trials (RCT). This may decrease costs and shorten inclusion times by reducing sample sizes. For small populations, with limited recruitment, this can be especially important. Bayesian dynamic borrowing (BDB) has been a popular choice as it claims to protect against potential prior data conflict. Digital twins (DT) has recently been proposed as another method to utilize historical data. DT, also known as PROCOVA™, is based on constructing a prognostic score from historical control data, typically using machine learning. This score is included in a pre-specified ANCOVA as the primary analysis of the RCT. The promise of this idea is power increase while guaranteeing strong type 1 error control. In this paper, we apply analytic derivations and simulations to analyze and discuss examples of these two approaches. We conclude that BDB and DT, although similar in scope, have fundamental differences which need be considered in the specific application. The inflation of the type 1 error is a serious issue for BDB, while more evidence is needed of a tangible value of DT for real RCTs.

PMID:38439136 | DOI:10.1002/pst.2376

J Sleep Res. 2024 Mar 4:e14183. doi: 10.1111/jsr.14183. Online ahead of print.

ABSTRACT

We assessed the relation between air pollution, weather, and adherence to positive airway pressure (PAP) therapy in a retrospective community-based repeated-measures study of adults with obstructive sleep apnea who purchased PAP devices from a registered provider between 2013 and 2017 (Ottawa, Ontario, Canada) and had at least one day of data. Daily PAP-derived data, air pollution, and weather databases were linked using postal code. The exposures were mean nocturnal (8:00 p.m. to 8:00 a.m.) (i) residential concentrations of nitrogen dioxide (NO₂ ), fine particulate matter <=2.5 μm (PM_2.5 ), ozone (O₃ ), and Air Quality Health Index (AQHI), and (ii) temperature, relative humidity, and barometric pressure. Covariates in the main model were demographics, season, exposure year, and PAP therapy mode. We analysed 8148 adults (median age of 54 years and 61% men) and 2,071,588 days of data. Based on daily data, the median (interquartile range) daily PAP usage was 416 (323-487) min. Using mixed-effect regression analyses to incorporate daily data and clustering by individuals, we found a statistically significant decrease in adherence for increased levels of NO₂ , PM_2.5 , and AQHI. The largest effect was for NO₂ : a decrease in daily PAP use while comparing the highest versus lowest quartiles (Qs) was 3.4 (95% confidence interval [CI] 2.8-3.9) min. Decreased PAP adherence was also associated with increased temperature (Q4 versus Q1: 2.6 [95% CI: 1.5-3.7] min) and decreased barometric pressure (Q1 versus Q4: 2.0 [95% CI 1.5-2.5] min). We observed modest but statistically significant acute effects of air pollution and weather on daily PAP adherence.

PMID:38439127 | DOI:10.1111/jsr.14183

Indian J Med Res. 2024 Jan 1;159(1):26-34. doi: 10.4103/ijmr.ijmr_3266_21. Epub 2024 Mar 4.

ABSTRACT

BACKGROUND OBJECTIVES: The tribal populations are vulnerable to mental health issues owing to various reasons. However, limited research has been conducted to assess depression and related determinants among tribal adults aged ≥45 yr (45 years and older). The present study aimed to assess the prevalence and sociodemographic and health determinants of depressive symptoms among the scheduled tribe (ST) population aged ≥45 yr in India.

METHODS: The present study analyzed the Wave I data of the Longitudinal Ageing Study in India conducted between April 2017 to December 2018. The outcome variables in the present study were self-reported depressive symptoms. Two internationally recognised tools, the Centre for Epidemiologic Studies Depression scale (CES-D) and Composite International Diagnostic Interview-Short Form (CIDI-SF), were used to obtain the data, however, only the CES-D data are utilized in this study. The present study focused on 12,215 ST individuals aged ≥45 yr from whom information about depressive symptoms was collected and analyzed.

RESULTS: Nearly 25 per cent ST population aged 45 yr or older experienced depressive symptoms. The likelihood of experiencing depressive symptoms among the ST population aged ≥45 yr was negatively associated with 10 or more years of education and living with children and others and positively associated with experiencing multiple morbidity conditions.

INTERPRETATION CONCLUSIONS: Given the substantial burden of depression among the adult ST population, the present study lays emphasis on raising the awareness about depressive symptoms and strengthen the availability of mental health services among the ST community through intensive campaigns and engagement of ST individuals along with other key stakeholders. Higher education, living with spouse and children and a physically active lifestyle can play a crucial role in limiting depressive symptoms among the tribal adults (≥45 yr). It is paramount to regularly screen depressive symptoms and conduct more microlevel studies to evaluate socioeconomic and health determinants of depressive symptoms among ST communities living in different geographic regions.

PMID:38439123 | DOI:10.4103/ijmr.ijmr_3266_21

Nurs Open. 2024 Mar;11(3):e2126. doi: 10.1002/nop2.2126.

ABSTRACT

AIM: To explore the mediating role of psychological capital between authentic leadership and innovative behaviour among Chinese nurses.

DESIGN: A cross-sectional study.

METHODS: In December 2021, online surveys were delivered among nurses from 37 hospitals in Anhui Province by convenience sampling approach. The data was collected using the Chinese version of the Authentic Leadership Questionnaire, Nurse Psychological Capital Questionnaire and Nurse Innovative Behaviour Scale. The structural equation model and bootstrap test examined the mediating role of psychological capital between authentic leadership and innovative behaviour.

RESULTS: 3495 Chinese nurses from 37 Anhui Province hospitals participated in this study. The mean item score of authentic leadership was 3.25 (SD 0.83), psychological capital was 4.85 (SD 0.89), and innovative behaviour was 2.82 (SD 0.84). Authentic leadership perceived by nurses, psychological capital, and innovative behaviour were statistically significant and positively correlated with each other (r = 0.524 ~ 0.806, p < 0.01). Psychological capital significantly mediated the association between authentic leadership and innovative behaviour (β = 0.449, p < 0.001), and its mediating effect accounted for 76.75% of the total effect.

CONCLUSION: Results suggest the importance of developing nurse managers’ authentic leadership to foster nurses’ psychological capital and innovation behaviour.

PMID:38439120 | DOI:10.1002/nop2.2126

BMC Nutr. 2024 Mar 4;10(1):42. doi: 10.1186/s40795-024-00821-5.

ABSTRACT

BACKGROUND: The aim of this study was to determine the association between dietary mineral intake and Coronavirus-disease 2019 (COVID-19) infection and its associated hospitalization.

METHODS: This cohort study utilized the MASHAD study population, which comprised individuals aged 35-65. Upon recruitment in 2007, dietary intake was documented using a validated 65-item food frequency questionnaire (FFQ). Data on COVID-19 PCR test results was collected from all relevant medical centers in Mashhad between February 2020 and June 2022. The regression model included dietary minerals and employed the backward variable selection method, along with advanced data analysis techniques.

RESULTS: The final analysis involved 1957 participants, including 193 COVID-19-positive patients. The mean age was 49.71 and 50.28 years in the COVID-19-positive and negative groups, respectively (p = 0.12). Dietary intakes of magnesium, iron, and potassium were notably lower in COVID-19-positive patients (P < 0.05). Following adjustments for age and sex, dietary iron remained significantly associated with COVID-19 incidence (OR = 0.94, 95% CI: 0.90-0.98). Furthermore, a statistically significant relationship was observed between dietary zinc and hospitalization due to COVID-19 (OR = 0.69, 95% CI: 0.51-0.93). In dynamical system models, intakes of calcium, zinc, and iron below the cut-offs of 1138, 9.7, and 8.17 mg/day, respectively, were linked to an increased risk of COVID-19 incidence.

CONCLUSION: Higher dietary iron and zinc intake are associated with decreased risk of COVID-19 infection and hospitalization, respectively.

PMID:38439106 | DOI:10.1186/s40795-024-00821-5