Tag: pubmed

Behav Res Methods. 2023 Nov 28. doi: 10.3758/s13428-023-02273-4. Online ahead of print.

ABSTRACT

Attentional engagement is known to vary on a moment-to-moment basis. However, few self-report methods can effectively capture dynamic fluctuations in attentional engagement over time. In the current paper, we evaluated the utility of stimulated recall, a method wherein individuals are asked to remember their subjective states while using a mnemonic cue, for the measurement of temporal changes in attentional engagement. Participants were asked to watch a video lecture, during which we assessed their in-the-moment levels of attentional engagement using intermittent thought probes. Then, we used stimulated recall by cueing participants with short video clips from the lecture to retrospectively assess the levels of attentional engagement they had experienced when they first watched those clips within the lecture. Experiment 1 assessed the statistical overlap between in-the-moment and video-stimulated ratings. Experiment 2 assessed the generalizability of video-stimulated recall across different types of lectures. Experiment 3 assessed the impact of presenting video-stimulated probe clips in non-chronological order. Experiment 4 assessed the effect of video-stimulated recall on its own. Across all experiments, we found statistically robust correspondence between in-the-moment and video-stimulated ratings of attentional engagement, illustrating a strong convergence between these two methods of assessment. Taken together, our findings indicate that stimulated recall provides a new and practical methodological approach that can accurately capture dynamic fluctuations in subjective attentional states over time.

PMID:38017200 | DOI:10.3758/s13428-023-02273-4

NPJ Digit Med. 2023 Nov 28;6(1):223. doi: 10.1038/s41746-023-00967-9.

ABSTRACT

It is uncommon for risk groups defined by statistical or artificial intelligence (AI) models to be chosen by jointly considering model performance and potential interventions available. We develop a framework to rapidly guide choice of risk groups in this manner, and apply it to guide breast cancer screening intervals using an AI model. Linear programming is used to define risk groups that minimize expected advanced cancer incidence subject to resource constraints. In the application risk stratification performance is estimated from a case-control study (2044 cases, 1:1 matching), and other parameters are taken from screening trials and the screening programme in England. Under the model, re-screening in 1 year for the highest 4% AI model risk, in 3 years for the middle 64%, and in 4 years for 32% of the population at lowest risk, was expected to reduce the number of advanced cancers diagnosed by approximately 18 advanced cancers per 1000 diagnosed with triennial screening, for the same average number of screens in the population as triennial screening for all. Sensitivity analyses found the choice of thresholds was robust to model parameters, but the estimated reduction in advanced cancers was not precise and requires further evaluation. Our framework helps define thresholds with the greatest chance of success for reducing the population health burden of cancer when used in risk-adapted screening, which should be further evaluated such as in health-economic modelling based on computer simulation models, and real-world evaluations.

PMID:38017184 | DOI:10.1038/s41746-023-00967-9

Metabolomics. 2023 Nov 28;20(1):1. doi: 10.1007/s11306-023-02066-y.

ABSTRACT

AIMS: To identify metabolite and lipid biomarkers of diabetes in the Indian subpopulation in newly diagnosed diabetic and long-term diabetic individuals. To utilize the global polar metabolomic and lipidomic profiles to predict the susceptibility of an individual to diabetes using machine learning algorithms.

MATERIALS AND METHODS: 87 individuals, including healthy, newly diabetic, and long-term diabetics on medication, were included in the study. Post consent, their serum was used to isolate polar metabolome and lipidome. NMR and LCMS were used to identify the polar metabolites and lipids, respectively. Statistical analysis was done to determine significantly altered molecules. NMR and LCMS comprehensive data were utilized to generate diabetic models using machine learning algorithms. 10 more individuals (pre-diabetic) were recruited, and their polar metabolomic and lipidomic profiles were generated. Pre-diabetic metabolic profiles were then utilized to predict the diabetic status of the metabolome and lipidome beyond glucose levels.

RESULTS: Mannose, Betaine, Xanthine, Triglyceride (38:1), Sphingomyelin (d63:7), and Phosphatidic acid (37:2) are some of the top key biomarkers of diabetes. The predictive model generated showed the receiver operating characteristic area under the curve (ROC-AUC) as 1 on both test and validation data indicating excellent accuracy. This model then predicted the diabetic closeness of the metabolism of pre-diabetic individuals based on probability scores.

CONCLUSION: Polar metabolic and lipid profile of diabetic individuals is very different from that of healthy individuals. Lipid profile alters before the polar metabolic profile in diabetes-susceptible individuals. Without regard to glucose, the diabetic closeness of the metabolism of any individual can be determined.

PMID:38017183 | DOI:10.1007/s11306-023-02066-y

Sci Rep. 2023 Nov 28;13(1):20991. doi: 10.1038/s41598-023-48378-w.

ABSTRACT

The aim of this research was to determine the impact of the architecture of digital technologies in university teacher training as a catalyst for change and educational innovation. Methodologically, it is framed in a quantitative approach with a pre-experimental design and an explanatory level, with a sample of 269 teachers out of a total population of 450 at the university. The results show a significant impact of the architecture of digital technologies as a catalyst for change in university teacher training, with an increase of 22.88% from pre-test to post-test. The statistical significance of the results is supported by a P-value of 0.000, which means that it is less than the established significance level (α = 0.05), leading to the acceptance of hypothesis H1: The architecture of digital technologies as a catalyst for change in university teacher education has an impact. In conclusion, the architecture of digital technologies, consisting of the two academic pillar systems: the academic management system and the virtual learning system, contribute to the development of digital skills in key areas such as digital literacy, communication and collaboration, digital content creation and problem solving in virtual environments.

PMID:38017148 | DOI:10.1038/s41598-023-48378-w

Leukemia. 2023 Nov 28. doi: 10.1038/s41375-023-02068-8. Online ahead of print.

ABSTRACT

Clinical outcome of patients with acute myeloid leukemia (AML) is associated with demographic and genetic features. Although the associations of acquired genetic alterations with patients’ sex have been recently analyzed, their impact on outcome of female and male patients has not yet been comprehensively assessed. We performed mutational profiling, cytogenetic and outcome analyses in 1726 adults with AML (749 female and 977 male) treated on frontline Alliance for Clinical Trials in Oncology protocols. A validation cohort comprised 465 women and 489 men treated on frontline protocols of the German AML Cooperative Group. Compared with men, women more often had normal karyotype, FLT3-ITD, DNMT3A, NPM1 and WT1 mutations and less often complex karyotype, ASXL1, SRSF2, U2AF1, RUNX1, or KIT mutations. More women were in the 2022 European LeukemiaNet intermediate-risk group and more men in adverse-risk group. We found sex differences in co-occurring mutation patterns and prognostic impact of select genetic alterations. The mutation-associated splicing events and gene-expression profiles also differed between sexes. In patients aged <60 years, SF3B1 mutations were male-specific adverse outcome prognosticators. We conclude that sex differences in AML-associated genetic alterations and mutation-specific differential splicing events highlight the importance of patients’ sex in analyses of AML biology and prognostication.

PMID:38017103 | DOI:10.1038/s41375-023-02068-8

Sci Rep. 2023 Nov 28;13(1):20935. doi: 10.1038/s41598-023-48296-x.

NO ABSTRACT

PMID:38017095 | DOI:10.1038/s41598-023-48296-x

Sci Rep. 2023 Nov 28;13(1):20970. doi: 10.1038/s41598-023-48032-5.

ABSTRACT

Muscular strength represents a specific component of health-related fitness. Hand grip strength is used as a simple and dynamic marker of maximum voluntary force of the hand and to estimate overall strength. Today, little is known about the relationship between grip strength and health in forcibly displaced populations. In the present study, we examined whether grip strength is associated with various health outcomes in a sample of forcibly displaced people living in a Greek refugee camp. The present analyses are part of a larger pragmatic randomized controlled trial. In this paper, cross-sectional baseline data of 143 participants (71 men, 72 women) will be presented. In addition to grip strength, the following physical and mental health outcomes were assessed: body weight and body composition, blood pressure, total cholesterol, low- and high-density lipoprotein cholesterol, triglycerides, blood glucose levels (HbA1c), post-traumatic stress disorder (PTSD) symptoms, depressive and anxiety symptoms, pain, and quality of life. Linear regression analyses were carried out to examine how grip strength is associated with the health outcomes, separately for absolute and normalized grip strength scores. Grip strength was positively and strongly associated with percentage muscle mass (normalized grip strength: Stand. B = 0.58, p < .001), whereas a negative association existed for percentage body fat (normalized grip strength: Stand. B = – 0.58, p < .001). No statistically significant associations occurred between grip strength and the other cardiovascular risk markers. In contrast, we found that participants with higher normalized grip strength reported higher levels of PTSD (normalized grip strength: Stand. B = 0.36, p < .05) and depressive symptoms (normalized grip strength: Stand. B = 0.29, p < .05). No significant association occurred between grip strength, anxiety, pain and quality of life. Measuring grip strength in forcibly displaced people can be a useful way to assess their overall muscle strength. Grip strength tests are easy to implement, and results can be used to assess the effects of specific intervention measures. Nevertheless, our results question the usefulness of grip strength as a marker of cardiovascular health and mental wellbeing in a refugee camp setting.

PMID:38017094 | DOI:10.1038/s41598-023-48032-5

Public Health. 2023 Nov 27;226:84-90. doi: 10.1016/j.puhe.2023.10.040. Online ahead of print.

ABSTRACT

OBJECTIVES: The association between asthma and COVID-19 mortality remains inconclusive. We examined the association between asthma and clinical outcomes of patients with COVID-19.

STUDY DESIGN: A case-control study based on a surveillance cohort in Harris County, Texas.

METHODS: Using the data of 21,765 patients who reported having at least one chronic health condition, we investigated the association between asthma and COVID-19 severity, characterized primarily by hospitalization and death. Unconditional logistic regression models were used to estimate the multivariable odds ratio (mOR) and its 95 % confidence interval (CI) of COVID-19 severity associated with asthma and other chronic lung diseases, adjusting for demographic and other comorbidities. A P-value < 0.005 was considered statistically significant after correcting multiple testing.

RESULTS: In total, 3034 patients (13.9 %) had asthma, and 774 (3.56 %) had other chronic lung diseases. The case death rate among patients with asthma and other chronic lung diseases was 0.75 % and 19.0 %, respectively. Compared to patients without the respective conditions, patients with asthma had lower odds of death (mOR = 0.44, 95 % CI: 0.27-0.69), while patients with other chronic lung diseases had higher odds of hospitalization (mOR = 2.02, 95 % CI: 1.68-2.42) and death (mOR = 1.95, 95 % CI: 1.52-2.49) (P-values < 0.005). Risk factors for COVID-19 mortality included older age, male gender, diabetes, obesity, hypertension, cardiovascular disease, active cancer, and chronic kidney disease.

CONCLUSIONS: The public health surveillance data suggested that preexisting asthma was inversely associated with COVID-19 mortality.

PMID:38016200 | DOI:10.1016/j.puhe.2023.10.040

Drug Alcohol Depend. 2023 Nov 23;254:111037. doi: 10.1016/j.drugalcdep.2023.111037. Online ahead of print.

ABSTRACT

BACKGROUND: Previous studies have highlighted the association between cannabis use and diabetes and its complications; however, the causality remains ambiguous.

METHODS: Univariate Mendelian randomization (MR), multivariate MR, mediation MR, and linkage disequilibrium score (LDSC) analysis to assess the causal relationship between cannabis use and 12 diabetic phenotypes. Summary statistics for lifetime cannabis use (N = 184,765) and cannabis use disorder (CUD) (N = 374,287) from genome-wide association studies. The primary method used was inverse-variance-weighted (IVW). A range of sensitivity analyses ensured the robustness of the results.

RESULTS: LDSC analysis revealed a significant genetic correlation between CUD and T2DM, as well as between lifetime cannabis use and four diabetic phenotypes (P < 0.05). After correction by false discovery rate (FDR), the primary IVW analysis indicates that the genetically predicted CUD is positively associated with the risk of diabetic hypoglycemia (OR = 1.11, 95% CI 1.04-1.20, P = 0.003, P_FDR = 0.04) and proliferative diabetic retinopathy (PDR) (OR = 1.12, 95% CI 1.04-1.19, P = 4.89×10^-4, P_FDR =0.01). Additionally, suggestive evidence links CUD with increased risks of diabetic nephropathy, type 1 diabetes mellitus (T1DM), diabetic retinopathy, and T1DM associated with diabetic ketoacidosis (P < 0.05 & P_FDR > 0.05). No causal relationship was detected between lifetime cannabis use and diabetic phenotypes (P > 0.05 & P_FDR > 0.05). Multivariable and mediation MR analyses revealed that glycated hemoglobin A1c partially mediates the causal effect of CUD on PDR and diabetic hypoglycemia.

CONCLUSION: This MR study suggests that CUD may have a causal role in several diabetic disease phenotypes.

PMID:38016197 | DOI:10.1016/j.drugalcdep.2023.111037

Rev Med Inst Mex Seguro Soc. 2023 Sep 18;61(Suppl 2):S295-S300.

ABSTRACT

BACKGROUND: Patients with thoracolumbar fractures with TLICS 4 classification are at the limit of surgical fixation with regards to conservative treatment; however, results in our environment are not known, which is why this study has innovative characteristics.

OBJECTIVE: To determine the quality of life in patients with TLICS 4 thoracolumbar fractures using traditional fixation with regards to no fixation in a third level hospital.

MATERIAL AND METHODS: A cohort prospective study was carried out in patients with TLICS 4 classification thoracolumbar fractures using traditional fixation with regards to no fixation in beneficiaries from the Mexican Institute for Social Security. The SF-12 instrument, which assessed quality of life, was administered; age, sex, days of hospitalization, time of spinal cord injury were searched in the patients’ medical history. It was used descriptive and inferential statistics using Student’s t or Mann-Whitney U.

RESULTS: 20 patients participated and 9 had traditional fixation (45%). All patients had type E spinal cord injuries according to the International Standards for Neurological Classification of Spinal Cord Injury. Mean age of non-fixation was 42.2 ± 12.9 and of fixation 44.9 ± 10.2; in non-fixation 6 (67%) were male. The quality of life score was 29.1 ± 0.9 in the conservative treatment and 28.7 ± 1.3 in the surgical treatment, p < 0.462.

CONCLUSIONS: No differences in quality of life were observed in patients with TLICS 4 thoracolumbar fractures using traditional fixation with regards to no fixation.

PMID:38016177