Tag: statistics

Front Microbiol. 2024 Mar 14;15:1334502. doi: 10.3389/fmicb.2024.1334502. eCollection 2024.

ABSTRACT

INTRODUCTION: Human papilloma virus (HPV) is the most common sexually transmitted infection worldwide. Cervicovaginal microbiota plays an important role in HPV infection and is associated with the development of squamous intraepithelial lesions (SIL). The natural history of cervical cancer involves reversible changes in the cervical tissue from a normal state, in which no neoplastic changes are detected in the squamous epithelium, to varying states of cellular abnormalities that ultimately lead to cervical cancer. Low-grade SIL (LSIL), like another cytological category – atypical squamous cells of undetermined significance (ASCUS), may progress to high-grade SIL (HSIL) and invasive cervical cancer or may regress to a normal state.

METHODS: In this work, we studied cervical canal microbiome in 165 HPV-positive and HPV-negative women of a reproductive age with ASCUS [HPV(+) n = 29; HPV(-) n = 11], LSIL [HPV(+) n = 32; HPV(-) n = 25], HSIL [HPV(+) n = 46], and the control group with negative for intraepithelial lesion malignancy (NILM) [HPV(-) n = 22].

RESULTS AND DISCUSSION: HPV16 is the most prevalent HPV type. We have not found any differences between diversity in studied groups, but several genus [like Prevotella (p-value = 0.026), Gardnerella (p-value = 0.003), Fannyhessea (p-value = 0.024)] more often occurred in HSIL group compared by NILM or LSIL regardless of HPV. We have found statistically significant difference in occurrence or proportion of bacterial genus in studied groups. We also identified that increasing of the ratio of Lactobacillus iners or age of patient lead to higher chance to HSIL, while increasing of the ratio of Lactobacillus crispatus lead to higher chance to LSIL. Patients with a moderate dysbiosis equally often had either of three types of vaginal microbial communities (CST, Community State Type) with the prevalence of Lactobacillus crispatus (CST I), Lactobacillus gasseri (CST II), and Lactobacillus iners (CST III); whereas severe dysbiosis is linked with CST IV involving the microorganisms genera associated with bacterial vaginosis and aerobic vaginitis: Gardnerella, Fannyhessea, Dialister, Sneathia, Anaerococcus, Megasphaera, Prevotella, Finegoldia, Peptoniphilus, Porphyromonas, Parvimonas, and Streptococcus.

PMID:38550866 | PMC:PMC10973545 | DOI:10.3389/fmicb.2024.1334502

J Clin Exp Hepatol. 2024 Jul-Aug;14(4):101393. doi: 10.1016/j.jceh.2024.101393. Epub 2024 Mar 5.

ABSTRACT

OBJECTIVE: This article aims to evaluate the intrareader and interreader agreement of ultrasound (US) gallbladder reporting and data system (GB-RADS) and validate the risk of malignancy in each GB-RADS category.

MATERIALS AND METHODS: This retrospective study comprised consecutive patients with nonacute gallbladder wall thickening who underwent US evaluation between January 2019 and December 2022. Three radiologists independently read the static US images and cine-loops for GB-RADS findings and assigned GB-RADS categories. The intraobserver (static images) and interobserver (static images and cine-loops) agreement was calculated using kappa statistics and Krippendorff’s alpha. Another radiologist assigned a consensus GB-RADS category. The percentage of malignancy in each GB-RADS category was calculated.

RESULTS: Static US images of 414 patients (median age, 56 years; 288 women, benign = 45.6% and malignant = 54.4%) and cine-loops of 50 patients were read. There was weak to moderate intrareader agreement for most GB-RADS findings and moderate intrareader agreement for the GB-RADS category for all readers. On static images, the interreader agreement was acceptable for GB-RADS categories. On cine-loops, the interreader agreement for GB-RADS findings and categories was better than static images. The percentage of malignancy was 1.2%, 37%, 71.1%, and 89.1% in GB-RADS 2, 3, 4, and 5 categories.

CONCLUSION: GB-RADS has moderate intrareader for GB-RADS categories. As originally proposed, the risk of malignancy is negligible in GB-RADS 2 category and highest in GB-RADS 5 category. However, the discriminatory performance of GB-RADS 3 and 4 categories is low. Larger multicenter studies with more readers must assess the reader agreement and validate the GB-RADS systems for wider clinical utilization.

PMID:38550799 | PMC:PMC10966770 | DOI:10.1016/j.jceh.2024.101393

Front Surg. 2024 Mar 14;11:1363551. doi: 10.3389/fsurg.2024.1363551. eCollection 2024.

ABSTRACT

BACKGROUND: This study aimed to evaluate the reference value of the femoral anterior tangent (FAT) line as a guidance of distal femoral rotation on magnetic resonance images (MRI).

METHODS: We retrospectively included 81 patients (106 knees) diagnosed as ailing from primary knee osteoarthritis. The indirect rotational axes including the FAT line, the perpendicular line to the anteroposterior axis (pAPA), and the posterior condylar axis (PCA) were identified on MRI, and their angles related to the clinical transepicondylar axis (cTEA) or surgical transepicondylar axis (sTEA) were measured. The patients were further divided into subgroups according to the Kellgren-Lawrence (K-L) grades, the joint-line convergence angle (JLCA), and the arithmetic hip-knee-ankle angle (aHKA) to assess the variance of different rotational reference axes.

RESULTS: The FAT line was -11.8° ± 3.6° internally rotated to the cTEA and -7.5° ± 3.6° internally rotated to the sTEA. The FAT/cTEA angle and the FAT/sTEA angle shared a similar frequency distribution pattern but a little greater variance to the pAPA/cTEA angle and the PCA/cTEA angle. The PCA/cTEA angle in the JLCA |x| ≥ 6° subgroup was significantly smaller than in the two other JLCA subgroups. The pAPA/cTEA angle and the PCA/cTEA angle also presented statistical significance within the aHKA subgroups. While the FAT/cTEA angle and the FAT/sTEA angle demonstrated superior stability among the different K-L grades, JLCA subgroups, and aHKA subgroups.

CONCLUSION: The FAT line was less affected by the degree of knee osteoarthritis and lower limb alignment, which could serve as a reliable alternative reference axis for the distal femoral rotational alignment in total knee arthroplasty.

PMID:38550792 | PMC:PMC10972973 | DOI:10.3389/fsurg.2024.1363551

J Am Stat Assoc. 2023;118(544):2315-2328. doi: 10.1080/01621459.2022.2044824. Epub 2022 Mar 27.

ABSTRACT

In this paper, we leverage over-parameterization to design regularization-free algorithms for the high-dimensional single index model and provide theoretical guarantees for the induced implicit regularization phenomenon. Specifically, we study both vector and matrix single index models where the link function is nonlinear and unknown, the signal parameter is either a sparse vector or a low-rank symmetric matrix, and the response variable can be heavy-tailed. To gain a better understanding of the role played by implicit regularization without excess technicality, we assume that the distribution of the covariates is known a priori. For both the vector and matrix settings, we construct an over-parameterized least-squares loss function by employing the score function transform and a robust truncation step designed specifically for heavy-tailed data. We propose to estimate the true parameter by applying regularization-free gradient descent to the loss function. When the initialization is close to the origin and the stepsize is sufficiently small, we prove that the obtained solution achieves minimax optimal statistical rates of convergence in both the vector and matrix cases. In addition, our experimental results support our theoretical findings and also demonstrate that our methods empirically outperform classical methods with explicit regularization in terms of both ℓ₂-statistical rate and variable selection consistency.

PMID:38550788 | PMC:PMC10977662 | DOI:10.1080/01621459.2022.2044824

Front Digit Health. 2024 Mar 14;6:1365345. doi: 10.3389/fdgth.2024.1365345. eCollection 2024.

ABSTRACT

OBJECTIVE: This umbrella review aims to ascertain the extent to which immersive Virtual Reality (VR) and Augmented Reality (AR) technologies improve specific competencies in healthcare professionals within medical education and training, in contrast to traditional educational methods or no intervention.

METHODS: Adhering to PRISMA guidelines and the PICOS approach, a systematic literature search was conducted across major databases to identify studies examining the use of VR and AR in medical education. Eligible studies were screened and categorized based on the PICOS criteria. Descriptive statistics and chi-square tests were employed to analyze the data, supplemented by the Fisher test for small sample sizes or specific conditions.

ANALYSIS: The analysis involved cross-tabulating the stages of work (Development and Testing, Results, Evaluated) and variables of interest (Performance, Engagement, Performance and Engagement, Effectiveness, no evaluated) against the types of technologies used. Chi-square tests assessed the associations between these categorical variables.

RESULTS: A total of 28 studies were included, with the majority reporting increased or positive effects from the use of immersive technologies. VR was the most frequently studied technology, particularly in the “Performance” and “Results” stages. The chi-square analysis, with a Pearson value close to significance (p = 0.052), suggested a non-significant trend toward the association of VR with improved outcomes.

CONCLUSIONS: The results indicate that VR is a prevalent tool in the research landscape of medical education technologies, with a positive trend toward enhancing educational outcomes. However, the statistical analysis did not reveal a significant association, suggesting the need for further research with larger sample sizes. This review underscores the potential of immersive technologies to enhance medical training yet calls for more rigorous studies to establish definitive evidence of their efficacy.

PMID:38550715 | PMC:PMC10973128 | DOI:10.3389/fdgth.2024.1365345

Pain Res Manag. 2024 Mar 20;2024:9989997. doi: 10.1155/2024/9989997. eCollection 2024.

ABSTRACT

BACKGROUND: Patients undergoing breast surgery are at risk of severe postoperative pain. Several opioid-sparing strategies exist to alleviate this condition. Regional anesthesia has long been a part of perioperative pain management for these patients.

AIM: This randomized study examined the benefits of interpectoral and pectoserratus plane block (IPP/PSP), also known as pectoralis nerve plain block, compared with advanced local anesthetic infiltration.

METHODS: We analyzed 57 patients undergoing partial mastectomy with sentinel node dissection. They received either an ultrasound-guided IPP/PSP block performed preoperatively by an anesthetist or local anesthetic infiltration performed by the surgeon before and during the surgery.

RESULTS: Pain measured with the numerical rating scale (NRS) indicated no statistically significant difference between the groups (IPP/PSP 1.67 vs. infiltration 1.97; p value 0.578). Intraoperative use of fentanyl was significantly lower in the IPP/PSP group (0.18 mg vs 0.21 mg; p value 0.041). There was no statistically significant difference in the length of stay in the PACU (166 min vs 175 min; p value 0.51). There were no differences in reported postoperative nausea and vomiting (PONV) between the groups. The difference in postoperative use of oxycodone in the PACU (p value 0.7) and the use of oxycodone within 24 hours postoperatively (p value 0.87) was not statistically significant.

CONCLUSIONS: Our study showed decreased intraoperative opioid use in the IPP/PSP group and no difference in postoperative pain scores up to 24 hours. Both groups reported low postoperative pain scores. This trial is registered with NCT04824599.

PMID:38550709 | PMC:PMC10977337 | DOI:10.1155/2024/9989997

Front Psychol. 2024 Mar 14;15:1355752. doi: 10.3389/fpsyg.2024.1355752. eCollection 2024.

ABSTRACT

INTRODUCTION: During the pandemic, young people experienced a general increase in stress levels in their home and school environments and in their relationships with peers and family, largely due to restrictions on freedom of movement and social isolation. The ability to identify sources of stress and respond positively to them, using both personal and environmental resources, seems to be key to maintaining an acceptable level of well-being. This study investigates the association between alexithymic traits, self-perceived well-being, and self-representations in adolescents as expressed via narrative metaphors during the COVID-19 epidemic.

METHODS: The sample comprised 229 Italian adolescents (51.1% females, mean age = 16.64). The research design was based on an exploratory, parallel, mixed-method approach. A semi-structured online interview was used as the major data gathering tool including both standardized quantitative questionnaire and open-ended questions. Data were analyzed by means of descriptive statistics, quantitative textual analysis and multidimensional co-word correspondence analysis.

RESULTS: Main findings reveal a general low level of perceived well-being associated with alexithymia, affecting adolescents’ lexical choices for their metaphors. Alexithymia-related low levels of well-being correspond to metaphors in which confusion and overpowering emotions predominate. Vivid pictures indicating vitality and a bright view on the future is often correlated with high levels of well-being.

DISCUSSION: Overall, these novel findings appear to show an interactive effect of perceived well-being and alexithymia on adolescents’ ability to identify and describe their own condition. Furthermore, metaphors emerge as powerful tools for investigating well-being in adolescents since closely related to inner states.

PMID:38550637 | PMC:PMC10973111 | DOI:10.3389/fpsyg.2024.1355752

Vet Med (Praha). 2024 Feb 27;69(2):42-51. doi: 10.17221/49/2023-VETMED. eCollection 2024 Feb.

ABSTRACT

Heart rate variability analyses using Poincaré plots can be useful for evaluating the autonomic nervous system function. However, the interpretation of the quantitative indicators of Poincaré plots remains controversial. Thus, few studies have verified the effectiveness of the quantitative indicators in veterinary medicine. This study aimed to verify the reliability of Poincaré plot indicators using pharmacological models in dogs. Four healthy beagles were used in this study. Each dog was treated with propranolol, atropine, and propranolol-atropine to block the sympathetic, parasympathetic, and sympathetic-parasympathetic functions, respectively. The quantitative indicators of the Poincaré plots were calculated based on data from 300 electrocardiogram beats collected before and after the administration of each drug and statistically analysed. The quantitative indicators of the Poincaré plots, such as the standard deviation perpendicular to the major axis (SD1), standard deviation along the major axis (SD2), and SD1 × SD2, significantly decreased after the drug administration in both the parasympathetic and sympathetic-parasympathetic blockade models. However, no significant differences were observed in SD1/SD2 between the groups. The Poincaré plots reflected the changes in the autonomic nervous system of dogs. In dogs, SD1, SD2, and SD1 × SD2 can detect a state in which parasympathetic nerve activity is suppressed.

PMID:38550620 | PMC:PMC10966429 | DOI:10.17221/49/2023-VETMED

Front Cell Infect Microbiol. 2024 Mar 14;14:1340610. doi: 10.3389/fcimb.2024.1340610. eCollection 2024.

ABSTRACT

BACKGROUND: Combination antiretroviral therapy (ART) has transformed human immunodeficiency virus (HIV) infection in people with HIV (PWH). However, a chronic state of immune activation and inflammation is maintained despite achieving HIV suppression and satisfactory immunological recovery. We aimed to determine whether the plasma metabolomic profile of PWH on long-term suppressive ART and immunologically recovered approximates the normality by comparison with healthy controls with similar age and gender.

METHODS: We carried out a cross-sectional study in 17 PWH on long-term ART (HIV-RNA <50 copies/mL, CD4⁺ ≥500 cells/mm³, and CD4⁺/CD8⁺ ≥1) and 19 healthy controls with similar age and gender. Metabolomics analysis was performed by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). The statistical association analysis was performed by principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and Generalized Linear Models (GLM) with a gamma distribution (log-link). Significance levels (p-value) were corrected for multiple testing (q-value).

RESULTS: PCA and PLS-DA analyses found no relevant differences between groups. Adjusted GLM showed 14 significant features (q-value<0.20), of which only three could be identified: lysophosphatidylcholine (LysoPC) (22:6) (q-value=0.148), lysophosphatidylethanolamine (LysoPE) (22:6) (q-value=0.050) and hydroperoxy-octadecatrienoic acid (HpOTrE)/dihydroperoxy-octadecatrienoic acid (DiHOTrE)/epoxy-octadecadienoic acid (EpODE) (q-value=0.136). These significant identified metabolites were directly correlated to plasma inflammatory biomarkers in PWH and negatively correlated in healthy controls.

CONCLUSION: PWH on long-term ART have a metabolomic profile that is almost normal compared to healthy controls. Nevertheless, residual metabolic alterations linked to inflammatory biomarkers persist, which could favor the development of age-related comorbidities among this population.

PMID:38550617 | PMC:PMC10972849 | DOI:10.3389/fcimb.2024.1340610

Transact Mach Learn Res. 2023 Sep;2023:https://openreview.net/forum?id=oud7Ny0KQy.

ABSTRACT

The ubiquity of missing values in real-world datasets poses a challenge for statistical inference and can prevent similar datasets from being analyzed in the same study, precluding many existing datasets from being used for new analyses. While an extensive collection of packages and algorithms have been developed for data imputation, the overwhelming majority perform poorly if there are many missing values and low sample sizes, which are unfortunately common characteristics in empirical data. Such low-accuracy estimations adversely affect the performance of downstream statistical models. We develop a statistical inference framework for regression and classification in the presence of missing data without imputation. Our framework, RIFLE (Robust InFerence via Low-order moment Estimations), estimates low-order moments of the underlying data distribution with corresponding confidence intervals to learn a distributionally robust model. We specialize our framework to linear regression and normal discriminant analysis, and we provide convergence and performance guarantees. This framework can also be adapted to impute missing data. In numerical experiments, we compare RIFLE to several state-of-the-art approaches (including MICE, Amelia, MissForest, KNN-imputer, MIDA, and Mean Imputer) for imputation and inference in the presence of missing values. Our experiments demonstrate that RIFLE outperforms other benchmark algorithms when the percentage of missing values is high and/or when the number of data points is relatively small. RIFLE is publicly available at https://github.com/optimization-for-data-driven-science/RIFLE.

PMID:38550611 | PMC:PMC10977932