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Nevin Manimala Statistics

Machine learning to predict untreated dental caries in adolescents

BMC Oral Health. 2024 Mar 9;24(1):316. doi: 10.1186/s12903-024-04073-4.

ABSTRACT

OBJECTIVE: This study aimed to predict adolescents with untreated dental caries through a machine-learning approach using three different algorithms METHODS: Data came from an epidemiological survey in the five largest cities in Mato Grosso do Sul, Brazil. Data on sociodemographic characteristics, consumption of unhealthy foods and behaviours (use of dental floss and toothbrushing) were collected using Sisson’s theoretical model, in 615 adolescents. For the machine learning, three different algorithms were used: (1) XGboost; (2) decision tree and (3) logistic regression. The epidemiological baseline was used to train and test predictions to detect individuals with untreated dental caries, through eight main predictor variables. Analyzes were performed using the R software (R Foundation for Statistical Computing, Vienna, Austria). The Ethics Committee approved the study..

RESULTS: For the 615 adolescents, xgboost performed better with an area under the curve (AUC) of 84% versus 81% for the decision tree algorithm. The most important variables were the use of dental floss, unhealthy food consumption, self-declared race and exposure to fluoridated water.

CONCLUSIONS: Family health teams can improve the work process and use artificial intelligence mechanisms to predict adolescents with untreated dental caries, and, in this way, schedule dental appointments for the treatment of adolescents earlier.

PMID:38461227 | DOI:10.1186/s12903-024-04073-4

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Optimization of the seat position for a personal vehicle equipped with a crankset: pilot study

Sci Rep. 2024 Mar 9;14(1):5822. doi: 10.1038/s41598-024-56446-y.

ABSTRACT

The aim of the study was to optimize the seat for a personal vehicle equipped with a crankset mechanism, meant for everyday use. The inclination of the seat backrest was selected on the basis of theoretical considerations. Then dynamic tests were carried out on a group of young, healthy men in order to verify the ergonomic aspects of the seat position in relation to the crankset and determine the efficiency of the human-mechanism system with a load of 50 W. The data obtained from the dynamic tests were subject to statistical analysis. Research has shown that higher seat positions result in statistically higher efficiencies. In addition, a holistic analysis of the personal vehicle design problem shows that the upper position of the seat is also the best. The results of the research can be used to optimize personal vehicles using human force as a drive.

PMID:38461198 | DOI:10.1038/s41598-024-56446-y

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Predictors of HBsAg seroclearance in patients with chronic HBV infection treated with pegylated interferon-α: a systematic review and meta-analysis

Hepatol Int. 2024 Mar 9. doi: 10.1007/s12072-024-10648-8. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: The identification of reliable predictors for hepatitis B surface antigen (HBsAg) seroclearance remains controversial. We aimed to summarize potential predictors for HBsAg seroclearance by pegylated interferon-α (PegIFNα) in patients with chronic HBV infection.

METHODS: A systematic search of the Cochrane Library, Embase, PubMed, and Web of Science databases was conducted from their inception to 28 September 2022. Meta-analyses were performed following the PRISMA statement. Predictors of HBsAg seroclearance were evaluated based on baseline characteristics and on-treatment indicators.

RESULTS: This meta-analysis encompasses 27 studies, including a total of 7913 patients. The findings reveal several factors independently associated with HBsAg seroclearance induced by PegIFNα-based regimens. These factors include age (OR = 0.961), gender (male vs. female, OR = 0.537), genotype (A vs. B/D; OR = 7.472, OR = 10.738), treatment strategy (combination vs. monotherapy, OR = 2.126), baseline HBV DNA (OR = 0.414), baseline HBsAg (OR = 0.373), HBsAg levels at week 12 and 24 (OR = 0.384, OR = 0.294), HBsAg decline from baseline to week 12 and 24 (OR = 6.689, OR = 6.513), HBsAg decline from baseline ≥ 1 log10 IU/ml and ≥ 0.5 log10 IU/ml at week 12 (OR = 18.277; OR = 4.530), and ALT elevation at week 12 (OR = 3.622). Notably, subgroup analysis suggests no statistical association between HBsAg levels at week 12 and HBsAg seroclearance for treatment duration exceeding 48 weeks. The remaining results were consistent with the overall analysis.

CONCLUSIONS: This is the first meta-analysis to identify predictors of HBsAg seroclearance with PegIFNα-based regimens, including baseline and on-treatment factors, which is valuable in developing a better integrated predictive model for HBsAg seroclearance to guide individualized treatment and achieve the highest cost-effectiveness of PegIFNα.

PMID:38461186 | DOI:10.1007/s12072-024-10648-8

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A Koopman operator-based prediction algorithm and its application to COVID-19 pandemic and influenza cases

Sci Rep. 2024 Mar 9;14(1):5788. doi: 10.1038/s41598-024-55798-9.

ABSTRACT

Future state prediction for nonlinear dynamical systems is a challenging task. Classical prediction theory is based on a, typically long, sequence of prior observations and is rooted in assumptions on statistical stationarity of the underlying stochastic process. These algorithms have trouble predicting chaotic dynamics, “Black Swans” (events which have never previously been seen in the observed data), or systems where the underlying driving process fundamentally changes. In this paper we develop (1) a global and local prediction algorithm that can handle these types of systems, (2) a method of switching between local and global prediction, and (3) a retouching method that tracks what predictions would have been if the underlying dynamics had not changed and uses these predictions when the underlying process reverts back to the original dynamics. The methodology is rooted in Koopman operator theory from dynamical systems. An advantage is that it is model-free, purely data-driven and adapts organically to changes in the system. While we showcase the algorithms on predicting the number of infected cases for COVID-19 and influenza cases, we emphasize that this is a general prediction methodology that has applications far outside of epidemiology.

PMID:38461184 | DOI:10.1038/s41598-024-55798-9

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Emergency Department Take-Home Naloxone Improves Access Compared with Pharmacy-Dispensed Naloxone

J Emerg Med. 2023 Dec 3:S0736-4679(23)00581-4. doi: 10.1016/j.jemermed.2023.11.020. Online ahead of print.

ABSTRACT

BACKGROUND: Opioid overdose is a major cause of mortality in the United States. In spite of efforts to increase naloxone availability, distribution to high-risk populations remains a challenge.

OBJECTIVE: To assess the effects of multiple different naloxone distribution methods on patient obtainment of naloxone in the emergency department (ED) setting.

METHODS: Naloxone was provided to patients in three 12-month phases between February 2020 and February 2023. In Phase 1, physicians could offer patients electronic prescriptions, which were filled in a nearby in-hospital discharge pharmacy. In Phase 2, physicians directly provided patients with take-home naloxone at discharge. In Phase 3, distribution was expanded to allow ED staff to hand patients take-home naloxone at time of discharge. The total number of prescriptions, rate of prescription filling, and amount of take-home naloxone kits provided to patients were then statistically analyzed using 95% confidence intervals (CI) and chi-squared testing.

RESULTS: In Phase 1, 348 naloxone prescriptions were written, with 133 (95% CI 112.5-153.5) filled. In Phase 2, 327 (95% CI 245.5-408.5) take-home naloxone kits were given to patients by physicians. In Phase 3, 677 (95% CI 509.5-844.5) take-home naloxone kits were provided to patients by ED staff. There were statistically significant increases in naloxone distribution from Phase 1 to Phase 2, and Phase 2 to Phase 3.

CONCLUSIONS: Take-home naloxone increases access when compared with naloxone prescriptions in the ED setting. A multidisciplinary approach combined with the removal of regulatory and administrative barriers allowed for further increased distribution of no-cost naloxone to patients.

PMID:38461132 | DOI:10.1016/j.jemermed.2023.11.020

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The Healthy Eating Index-2015 and All-Cause/Cause-Specific Mortality: A Systematic Review and Dose-Response Meta-Analysis

Adv Nutr. 2024 Feb 23:100166. doi: 10.1016/j.advnut.2023.100166. Online ahead of print.

ABSTRACT

This meta-analysis was undertaken to determine the predictive value of Healthy Eating Index (HEI)-2015 in all-cause, cancer-cause, and cardiovascular disease (CVD)-cause mortality. This review was registered with PROSPERO as CRD42023421585. PubMed and Web of Science were searched for articles published by September 15, 2023. The hazard ratio (HR) was calculated with exact confidence intervals (CIs) of 95%. Statistical heterogeneity among studies was measured by Cochran’s Q test (χ2) and the I2 statistic. Eighteen published studies were finally identified in this meta-analysis. The results showed that the HEI-2015 was associated with all-cause mortality either as a categorical variable (HR: 0.80; 95% CI: 0.79, 0.82) or continuous variable (HR: 0.90; 95% CI: 0.88, 0.92). The HEI-2015 was also associated with cancer-cause mortality as categorical variable (HR: 0.81; 95% CI: 0.78, 0.83) or continuous variable (HR: 0.90; 95% CI: 0.81, 0.99). The categorical HEI-2015 was also independently correlated with decreasing CVD-cause mortality (HR: 0.81; 95% CI: 0.75, 0.87). A nonlinear dose-response relation between the HEI-2015 and all-cause mortality was found. In the linear dose-response analysis, the risk of mortality from cancer decreased by 0.42% per 1 score increment of the HEI-2015 and the risk of CVD-cause mortality decreased by 0.51% with the increment of the HEI-2015 per 1 score. Our analysis indicated a significant relationship between the HEI-2015 and all-cause, cancer-cause, and CVD-cause mortality.

PMID:38461130 | DOI:10.1016/j.advnut.2023.100166

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Analysis of retreatment with monoclonal antibodies in chronic/episodic migraine: Real world data

Farm Hosp. 2024 Mar 8:S1130-6343(24)00023-0. doi: 10.1016/j.farma.2024.02.003. Online ahead of print.

ABSTRACT

OBJECTIVE: To analyze the response to retreatment in patients with chronic/episodic migraine who discontinued therapy with erenumab/fremanezumab after 1 year of treatment.

METHODS: Observational, retrospective, single-center, multidisciplinary study in patients with chronic/episodic migraine who received therapy with erenumab/fremanezumab for at least 1 year and discontinued it after achieving an adequate response (optimization). The evaluation of the response after retreatment included the following variables: DMM, MIDAS, and HIT-6 scales at the beginning of retreatment and 3 months later. The response was evaluated in different subgroups (episodic/chronic, erenumab/fremanezumab, and time until retreatment).

RESULTS: 48 patients were included. 70.8% (n=34) required retreatment with mAb, with a median of 3.9 (2.9-6.4) months until reintroduction. Clinical response after retreatment was achieved in 67.6% (n=23) of patients. No statistically significant differences were found in the analyzed subgroups.

CONCLUSION: Interruption of treatment with erenumab/fremanezumab for chronic/episodic migraine produces a clinical worsening of the disease requiring retreatment in most cases, approximately after 4 months. Two out of three patients respond positively after restarting monoclonal therapy. This response does not appear to be related to the type of migraine, the specific monoclonal antibody prescribed, or the time to retreatment.

PMID:38461112 | DOI:10.1016/j.farma.2024.02.003

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The IRELAnD study-investigating the role of early low-dose aspirin in diabetes mellitus: a double-blinded, placebo-controlled, randomized trial

Am J Obstet Gynecol MFM. 2024 Mar 8:101297. doi: 10.1016/j.ajogmf.2024.101297. Online ahead of print.

ABSTRACT

BACKGROUND: Although aspirin therapy is being increasingly advocated with the intention of risk modification for a wide range of pregnancy complications, women with prepregnancy diabetes mellitus are commonly excluded from clinical trials.

OBJECTIVE: The primary aim of this study was to examine the effect of aspirin therapy on a composite measure of adverse perinatal outcome in pregnancies complicated by pregestational diabetes mellitus.

STUDY DESIGN: A double-blinded, placebo-controlled randomized trial was conducted at 6 university-affiliated perinatology centers. Women with type 1 diabetes mellitus or type 2 diabetes mellitus of at least 6 months’ duration were randomly allocated to 150-mg daily aspirin or placebo from 11 to 14 weeks’ gestation until 36 weeks. Established vascular complications of diabetes mellitus, including chronic hypertension or nephropathy, led to exclusion from the trial. The primary outcome was a composite measure of placental dysfunction (preeclampsia, fetal growth restriction, preterm birth <34 weeks’ gestation, or perinatal mortality). The planned sample size was 566 participants to achieve a 35% reduction in the primary outcome, assuming 80% statistical power. Secondary end points included maternal and neonatal outcomes and determination of insulin requirements across gestation. Data were centrally managed using ClinInfo and analyzed using SAS 9.4. The 2 treatment groups were compared using t tests or chi-square tests, as required, and longitudinal data were compared using a repeated-measures analysis.

RESULTS: From February 2020 to September 2022, 191 patients were deemed eligible, 134 of whom were enrolled (67 randomized to aspirin and 67 to placebo) with a retrospective power of 64%. A total of 101 (80%) women had type 1 diabetes mellitus and 25 (20%) had type 2 diabetes mellitus. Reaching the target sample size was limited by the impact of the COVID-19 pandemic. Baseline characteristics were similar between the aspirin and placebo groups. Treatment compliance was very high and similar between groups (97% for aspirin, 94% for placebo). The risk of the composite measure of placental dysfunction did not differ between groups (25% aspirin vs 21% placebo; P=.796). Women in the aspirin group had significantly lower insulin requirements throughout pregnancy compared with the placebo group. Insulin requirements in the aspirin group increased on average from 0.7 units/kg at baseline to 1.1 units/kg by 36 weeks’ gestation (an average 83% within-patient increase), and increased from 0.7 units/kg to 1.3 units/kg (a 181% within-patient increase) in the placebo group, over the same gestational period (P=.002). Serial hemoglobin A1c levels were lower in the aspirin group than in the placebo group, although this trend did not reach statistical significance.

CONCLUSION: In this multicenter, double-blinded, placebo-controlled randomized trial, aspirin did not reduce the risk of adverse perinatal outcome in pregnancies complicated by prepregnancy diabetes mellitus. Compared with the placebo group, aspirin-treated patients required significantly less insulin throughout pregnancy, indicating a beneficial effect of aspirin on glycemic control. Aspirin may exert a plausible placenta-mediated effect on pregestational diabetes mellitus that is not limited to its antithrombotic properties.

PMID:38461094 | DOI:10.1016/j.ajogmf.2024.101297

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What do parents of nonverbal and minimally verbal autistic children think about genomic autism research?

Autism. 2024 Mar 9:13623613231213431. doi: 10.1177/13623613231213431. Online ahead of print.

ABSTRACT

In Summer 2021, a genomic study of autism, Spectrum 10 K, was paused due to backlash from the autistic and autism communities. This raised important questions about how these communities perceive genomic research. The Personal Experiences of Autism and Perceptions of DNA-based research study was established to address this issue among a range of sub-groups within these communities. Twenty parents of nonverbal or minimally verbal autistic children took part in the current study. Data were provided in diverse formats including online interviews, telephone interviews, and writing. This approach was co-produced with autistic experts by experience and involved a parent of a minimally verbal autistic child. Data were analysed using reflexive Thematic Analysis. We found that participants were supportive of autism research, including some genomic research, as long as it is designed to support autistic people and is ethical and transparent. However, while some believed that polygenic scores, genomic predictors of the statistical probability of being autistic, would be helpful, others argued that this would only be true in an ideal world and that the world is too far from ideal. Participants felt excluded from the autistic and autism communities and that the dominant voices in those communities do not represent them or their children. We concluded that genomic researchers need to work with the autistic and autism communities to design future work, and that it is important to ensure a representative range of voices are heard.

PMID:38459822 | DOI:10.1177/13623613231213431

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Canadian intensive care unit nurses’ responses to moral distress during the COVID-19 pandemic, and their recommendations for mitigative interventions

J Adv Nurs. 2024 Mar 9. doi: 10.1111/jan.16135. Online ahead of print.

ABSTRACT

AIMS: To describe intensive care unit nurses’ experiences of moral distress during the COVID-19 pandemic, and their recommendations for mitigative interventions.

DESIGN: Interpretive description.

METHODS: Data were collected with a purposeful sample of 40 Canadian intensive care unit nurses between May and September 2021. Nurses completed a demographic questionnaire, the Measure of Moral Distress-Healthcare Professionals survey and in-depth interviews. Quantitative data were analysed using descriptive statistics. Qualitative data were categorized and synthesized using reflexive thematic analysis and rapid qualitative analysis.

RESULTS: Half of the nurses in this sample reported moderate levels of moral distress. In response to moral distress, nurses experienced immediate and long-term effects across multiple health domains. To cope, nurses discussed varied reactions, including action, avoidance and acquiescence. Nurses provided recommendations for interventions across multiple organizations to mitigate moral distress and negative health outcomes.

CONCLUSION: Nurses reported that moral distress drove negative health outcomes and attrition in response to moral events in practice. To change these conditions of moral distress, nurses require organizational investments in interventions and cultures that prioritize the inclusion of nursing perspectives and voices.

IMPLICATIONS FOR THE PROFESSION: Nurses engage in a variety of responses to cope with moral distress. They possess valuable insights into the practice issues central to moral distress that have significant implications for all members of the healthcare teams, patients and systems. It is essential that nurses’ voices be included in the development of future interventions central to the responses to moral distress.

REPORTING METHOD: This study adheres to COREQ guidelines.

IMPACT: What Problem did the Study Address? Given the known structural, systemic and environmental factors that contribute to intensive care unit nurses’ experiences of moral distress, and ultimately burnout and attrition, it was important to learn about their experiences of moral distress and their recommendations for organizational mitigative interventions. Documentation of these experiences and recommendations took on a greater urgency during the context of a global health emergency, the COVID-19 pandemic, where such contextual influences on moral distress were less understood. What Were the Main Findings? Over half of the nurses reported a moderate level of moral distress. Nurses who were considering leaving nursing practice reported higher moral distress scores than those who were not considering leaving. In response to moral distress, nurses experienced a variety of outcomes across several health domains. To cope with moral distress, nurses engaged in patterns of action, avoidance and acquiescence. To change the conditions of moral distress, nurses desire organizational interventions, practices and culture changes situated in the amplification of their voices. Where and on Whom Will the Research Have an Impact on? These findings will be of interest to: (1) researchers developing and evaluating interventions that address the complex phenomenon of moral distress, (2) leaders and administrators in hospitals, and relevant healthcare and nursing organizations, and (3) nurses interested in leveraging evidence-informed recommendations to advocate for interventions to address moral distress. What Does this Paper Contribute to the Wider Global Community? This paper advances the body of scientific work on nurses’ experiences of moral distress, capturing this phenomenon within the unique context of a global health emergency. Nurses’ levels of moral distress using Measure of Moral Distress-Healthcare Professional survey were reported, serving as a comparator for future studies seeking to measure and evaluate intensive care unit nurses’ levels of moral distress. Nurses’ recommendations for mitigative interventions for moral distress have been reported, which can help inform future interventional studies.

PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

PMID:38459779 | DOI:10.1111/jan.16135