Tag: statistics

Technol Health Care. 2023 Mar 23. doi: 10.3233/THC-220563. Online ahead of print.

ABSTRACT

BACKGROUND: Pedodontists and general practitioners may need support in planning the early orthodontic treatment of patients with mixed dentition, especially in borderline cases. The use of machine learning algorithms is required to be able to consistently make treatment decisions for such cases.

OBJECTIVE: This study aimed to use machine learning algorithms to facilitate the process of deciding whether to choose serial extraction or expansion of maxillary and mandibular dental arches for early treatment of borderline patients suffering from moderate to severe crowding.

METHODS: The dataset of 116 patients who were previously treated by senior orthodontists and divided into two groups according to their treatment modalities were examined. Machine Learning algorithms including Multilayer Perceptron, Linear Logistic Regression, k-nearest Neighbors, Naïve Bayes, and Random Forest were trained on this dataset. Several metrics were used for the evaluation of accuracy, precision, recall, and kappa statistic.

RESULTS: The most important 12 features were determined with the feature selection algorithm. While all algorithms achieved over 90% accuracy, Random Forest yielded 95% accuracy, with high reliability values (kappa = 0.90).

CONCLUSION: The employment of machine learning methods for the treatment decision with or without extraction in the early treatment of patients in the mixed dentition can be particularly useful for pedodontists and general practitioners.

PMID:36970921 | DOI:10.3233/THC-220563

Technol Health Care. 2023 Mar 23. doi: 10.3233/THC-220488. Online ahead of print.

ABSTRACT

BACKGROUND: The incidence of anxiety in patients with breast cancer is high, which seriously affects the physical and mental health of patients.

OBJECTIVE: This study aimed to investigate the effect of acupoint stimulation on the anxiety of patients with breast cancer during operations and in the waiting period for intraoperative frozen section analysis.

METHODS: Sixty patients with breast cancer experiencing anxiety who met the inclusion and exclusion criteria were randomly divided into the experimental group and the control group. The patients in the control group received routine nursing, and the patients in the experimental group were given acupoint stimulation on the basis of routine nursing. The HAMD scores, blood pressure readings, and heart rates were recorded before admission at one hour before the operation and in the waiting period for intraoperative frozen section analysis.

RESULTS: The HAMD scores, blood pressure readings, and heart rates of the two groups showed an upward trend at all time points, and the differences were statistically significant. Compared with the control group, there were significant differences in indices detected at one hour before the operation and in the waiting period for intraoperative frozen section analysis.

CONCLUSION: Acupoint stimulation therapy can effectively alleviate anxiety in patients with breast cancer.

PMID:36970919 | DOI:10.3233/THC-220488

Technol Health Care. 2023 Mar 23. doi: 10.3233/THC-220245. Online ahead of print.

ABSTRACT

BACKGROUND: Orbital blowout fracture is common in ocular trauma. Accurate measurement of orbital volume after fracture is key in improving intraocular correction.

OBJECTIVE: This study aims to explore the impact of 3D reconstruction technology in restoring normal exophthalmos in patients with old orbital wall fractures.

METHODS: A total of 31 patients were randomly divided into an experimental group (n= 15) and a control group (n= 16). For orbital wall repair and reconstruction, the conventional group used the conventional surgical scheme, and the 3D group used 3D printing technology.

RESULTS: There was no statistical difference between the preoperative mean extraocular muscle volume of the healthy eye and the affected eye. However, the mean orbital volume (24.76 vs 27.11, P= 0.005) and mean retrobulbar fat volume (17.53 vs 16.42, P= 0.006) were significantly different between the healthy eye and the affected eye. After an average follow-up of 16 weeks, the differences in pre- and post-surgery exophthalmos in the two groups were 0.42 ± 0.08 mm and 1.63 ± 0.51 mm, respectively. The difference between the two groups was statistically significant (t= 4.42, P= 0.003). The complications were not statistically different.

CONCLUSION: Using 3D reconstruction technology preoperatively can significantly improve exophthalmos in patients with old orbital wall fractures.

PMID:36970917 | DOI:10.3233/THC-220245

J Alzheimers Dis. 2023 Mar 21. doi: 10.3233/JAD-221001. Online ahead of print.

ABSTRACT

BACKGROUND: Preclinical Alzheimer’s disease (AD) is one possible cause of subjective cognitive decline (SCD). Normal task performance despite ongoing neurodegeneration is typically considered as neuronal compensation, which is reflected by greater neuronal activity. Compensatory brain activity has been observed in frontal as well as parietal regions in SCD, but data are scarce, especially outside the memory domain.

OBJECTIVE: To investigate potential compensatory activity in SCD. Such compensatory activity is particularly expected in participants where blood-based biomarkers indicated amyloid positivity as this implies preclinical AD.

METHODS: 52 participants with SCD (mean age: 71.00±5.70) underwent structural and functional neuroimaging (fMRI), targeting episodic memory and spatial abilities, and a neuropsychological assessment. The estimation of amyloid positivity was based on plasma amyloid-β and phosphorylated tau (pTau181) measures.

RESULTS: Our fMRI analyses of the spatial abilities task did not indicate compensation, with only three voxels exceeding an uncorrected threshold at p < 0.001. This finding was not replicated in a subset of 23 biomarker positive individuals.

CONCLUSION: Our results do not provide conclusive evidence for compensatory brain activity in SCD. It is possible that neuronal compensation does not manifest at such an early stage as SCD. Alternatively, it is possible that our sample size was too small or that compensatory activity may be too heterogeneous to be detected by group-level statistics. Interventions based on the individual fMRI signal should therefore be explored.

PMID:36970895 | DOI:10.3233/JAD-221001

Perm J. 2023 Mar 27:1-10. doi: 10.7812/TPP/22.135. Online ahead of print.

ABSTRACT

Introduction Transthyretin amyloid cardiomyopathy (ATTR-CM) is a progressive, infiltrative form of heart failure (HF). Nevertheless, ATTR-CM is a largely underrecognized and misdiagnosed condition. This study’s objective was to develop an efficient model to assess the chance of ATTR-CM in patients with HF. Methods This was an observational study of patients with HF who had a confirmed diagnosis of ATTR-CM and those with HF but without known ATTR-CM between January 1, 2019, and July 1, 2021. Patient characteristics were extracted from administrative and claims electronic databases and compared between the groups. A propensity score for having ATTR-CM was modeled. Samples of 50 control patients with the highest and lowest propensity scores were adjudicated to assess whether further workup to evaluate for ATTR-CM was warranted for each patient. The sensitivity and specificity of the model were calculated. Results Thirty-one patients with confirmed ATTR-CM and 7620 patients without known ATTR-CM were included in the study. Patients with ATTR-CM were more likely to be Black and to have atrial flutter/fibrillation, cardiomegaly, HF with preserved ejection fraction, pericardial effusion, carpal tunnel syndrome, joint disorders, and lumbar spinal stenosis and to use a diuretic (all p < 0.05). A propensity model with 16 inputs was developed (c-statistic = 0.875). The model’s sensitivity and specificity were 71.9% and 95.2%, respectively. Conclusion The propensity model developed in this study provided an efficient means for identifying patients with HF who are more likely to have ATTR-CM and may warrant further workup.

PMID:36970848 | DOI:10.7812/TPP/22.135

Philos Trans A Math Phys Eng Sci. 2023 May 15;381(2247):20220143. doi: 10.1098/rsta.2022.0143. Epub 2023 Mar 27.

ABSTRACT

In this paper, we start by reviewing exchangeability and its relevance to the Bayesian approach. We highlight the predictive nature of Bayesian models and the symmetry assumptions implied by beliefs of an underlying exchangeable sequence of observations. By taking a closer look at the Bayesian bootstrap, the parametric bootstrap of Efron and a version of Bayesian thinking about inference uncovered by Doob based on martingales, we introduce a parametric Bayesian bootstrap. Martingales play a fundamental role. Illustrations are presented as is the relevant theory. This article is part of the theme issue ‘Bayesian inference: challenges, perspectives, and prospects’.

PMID:36970832 | DOI:10.1098/rsta.2022.0143

Philos Trans A Math Phys Eng Sci. 2023 May 15;381(2247):20220144. doi: 10.1098/rsta.2022.0144. Epub 2023 Mar 27.

ABSTRACT

I discuss the benefits of looking through the ‘Bayesian lens’ (seeking a Bayesian interpretation of ostensibly non-Bayesian methods), and the dangers of wearing ‘Bayesian blinkers’ (eschewing non-Bayesian methods as a matter of philosophical principle). I hope that the ideas may be useful to scientists trying to understand widely used statistical methods (including confidence intervals and [Formula: see text]-values), as well as teachers of statistics and practitioners who wish to avoid the mistake of overemphasizing philosophy at the expense of practical matters. This article is part of the theme issue ‘Bayesian inference: challenges, perspectives, and prospects’.

PMID:36970830 | DOI:10.1098/rsta.2022.0144

Philos Trans A Math Phys Eng Sci. 2023 May 15;381(2247):20220155. doi: 10.1098/rsta.2022.0155. Epub 2023 Mar 27.

NO ABSTRACT

PMID:36970829 | DOI:10.1098/rsta.2022.0155

Philos Trans A Math Phys Eng Sci. 2023 May 15;381(2247):20220142. doi: 10.1098/rsta.2022.0142. Epub 2023 Mar 27.

ABSTRACT

Prediction has a central role in the foundations of Bayesian statistics and is now the main focus in many areas of machine learning, in contrast to the more classical focus on inference. We discuss that, in the basic setting of random sampling-that is, in the Bayesian approach, exchangeability-uncertainty expressed by the posterior distribution and credible intervals can indeed be understood in terms of prediction. The posterior law on the unknown distribution is centred on the predictive distribution and we prove that it is marginally asymptotically Gaussian with variance depending on the predictive updates, i.e. on how the predictive rule incorporates information as new observations become available. This allows to obtain asymptotic credible intervals only based on the predictive rule (without having to specify the model and the prior law), sheds light on frequentist coverage as related to the predictive learning rule, and, we believe, opens a new perspective towards a notion of predictive efficiency that seems to call for further research. This article is part of the theme issue ‘Bayesian inference: challenges, perspectives, and prospects’.

PMID:36970827 | DOI:10.1098/rsta.2022.0142

Endocr Metab Immune Disord Drug Targets. 2023 Mar 24. doi: 10.2174/1871530323666230324104737. Online ahead of print.

ABSTRACT

AIMS: This study aims to examine the associations between various non-insulin-based insulin resistance (nIIR) indices and subclinical atherosclerosis assessed by carotid intima-media thickness (cIMT) in young adults.

BACKGROUND: nIIR indices, e.g., serum triglycerides (TG) have been reported with an association with cIMT in middle- and old-aged adults.

OBJECTIVE: We examined the associations of various well-known nIIR indices reported before with cIMT in young adults.

METHODS: A total of 1,822 young adults free of diabetes in Taiwan were included in 2018-2020. nIIR indices were assessed by TG concentrations, the TyG index, defined as Ln (TG *fasting glucose/2), the TG/high-density lipoprotein cholesterol (HDL-C) ratio, defined as TG divided by HDL-C, and the metabolic score for IR (METS-IR), defined as Ln[(2*fasting glucose)+TG) * body mass index (BMI)/(Ln(HDL-C))]. Multivariable linear regression analyses with adjustments for age, sex, anthropometrics, smoking, alcohol consumption, blood pressure, and total cholesterol were used to determine the associations. For TG only, HDL-C and fasting glucose were additionally adjusted.

RESULTS: In the overall participants, there was an association between cIMT and TG (β: 0.057, p =0.04). In subgroup analyses, cIMT was associated with TG (β: 0.127, p =0.004), the TyG index (β: 0.119, p =0.01), and TG/HDL-C (β: 0.081, p =0.03) in the overweight /obese (BMI ≥25 kg/m2), while not in the normal weight individuals. However, cIMT was correlated with TG (β: 0.086, p =0.01) and TG/HDL-C (β: 0.077, p =0.01) in those without hyperuricemia, while not in those with hyperuricemia. No association between the METS-IR and cIMT in any young adult subgroups was observed.

CONCLUSION: This study highlights that some nIIR indices could be used to assess cIMT in young adults, particularly for those with obesity and those without hyperuricemia. The TG-based indices instead of the novel marker, METS-IR, are suggestive as stronger predictors of greater cIMT in young adults.

PMID:36967464 | DOI:10.2174/1871530323666230324104737