Tag: pubmed

Elife. 2022 Nov 1;11:e79027. doi: 10.7554/eLife.79027.

ABSTRACT

The brain encodes the statistical regularities of the environment in a task-specific yet flexible and generalizable format. Here, we seek to understand this process by bridging two parallel lines of research, one centered on sensorimotor timing, and the other on cognitive mapping in the hippocampal system. By combining functional magnetic resonance imaging (fMRI) with a fast-paced time-to-contact (TTC) estimation task, we found that the hippocampus signaled behavioral feedback received in each trial as well as performance improvements across trials along with reward-processing regions. Critically, it signaled performance improvements independent from the tested intervals, and its activity accounted for the trial-wise regression-to-the-mean biases in TTC estimation. This is in line with the idea that the hippocampus supports the rapid encoding of temporal context even on short time scales in a behavior-dependent manner. Our results emphasize the central role of the hippocampus in statistical learning and position it at the core of a brain-wide network updating sensorimotor representations in real time for flexible behavior.

PMID:36317500 | DOI:10.7554/eLife.79027

Anesth Pain Med (Seoul). 2022 Oct;17(4):429-433. doi: 10.17085/apm.22134. Epub 2022 Aug 1.

ABSTRACT

BACKGROUND: YouTube, the largest online video platform, has become increasingly popular as a source of health information to patients. The aim of the study was to assess whether Korean patients were well informed about spinal injection from YouTube.

METHODS: Search for the keyword “cheog-chu ju-sa” in Korean language was done, and the quality of the 51 videos with the highest number of views was evaluated independently by two pain management doctors.

RESULTS: The averages of global quality scores evaluated by the two doctors were 3.0 and 3.5 and modified DISCERN (mDISCERN) scores were 2.8 and 3.0, respectively. The Kappa statistic between the two doctors’ scores was 0.285 and 0.417.

CONCLUSIONS: The percentage of low-quality videos with a global quality score of 2 or less is 18-36%, which indicated that these videos might provide inaccurate or misleading medical information to the patient. Pain clinic doctors should be wary of medically misleading information available on online platforms, such as YouTube, and strive to create and distribute professional quality educational materials.

PMID:36317436 | DOI:10.17085/apm.22134

Anesth Pain Med (Seoul). 2022 Oct;17(4):412-419. doi: 10.17085/apm.22168. Epub 2022 Oct 26.

ABSTRACT

BACKGROUND: Patients with acute-on-chronic liver failure (ACLF) are critically ill and have high waiting-list mortality. Although studies demonstrated that appropriately treated coronary artery disease (CAD) should not be regarded as a contraindication to liver transplant (LT), data regarding long-term outcomes in critically ill liver LT recipients are lacking. The aim of this study was to compare the rates of all-cause death at 5 years following LT in patients with ACLF with or without CAD.

METHODS: Between 2010 and 2020, we evaluated 921 consecutive LT patients (MELD score, 32 ± 9) and ACLF classified by CLIF-C ACLF score. Up to 5-year all-cause death according to the CAD status was examined. CAD was defined as a preoperative history of coronary artery bypass graft or a percutaneous intervention and old myocardial infarction. Kaplan-Meier survival analysis was used.

RESULTS: Up to 5 years, 212 (23.0%) of all ACLF patients (n = 921) in whom 17 (29.3%) of 58 CAD patients died. In patients with CAD (6.3%, 58/921), the Kaplan-Meier cumulative mortality rate at 5 years was numerically higher but was not statistically significant when compared with those without CAD (32.9% vs. 23.5%, log-rank, P = 0.25). In subgr oup analysis, there were comparable risks of cumulative mortalities at 5 years across the stratification of ACLF grade 1, 2, and 3 (log-rank P = 0.062, P = 0.72, and P = 0.999, respectively).

CONCLUSIONS: All-cause mortality is high in patients with ACLF after LT but is not related to the presence of revascularized or treated CAD, across the stratification of ACLF grades.

PMID:36317434 | DOI:10.17085/apm.22168

Clin Cardiol. 2022 Nov 1. doi: 10.1002/clc.23915. Online ahead of print.

ABSTRACT

BACKGROUND: Data on the association of multimorbidity and functional impairment with cardiovascular (CV) and non-CV outcomes among older myocardial infarction (MI) patients are limited.

HYPOTHESIS: Multimorbidity and functional impairment among older MI patients are associated with CV and non-CV mortality.

METHODS: Patients aged ≥65 years, 1-3 years post-MI, and enrolled between June 2013 and Novemeber 2014 from 349 sites in 25 countries in the global TIGRIS registry were categorized by age, number of comorbidities, and presence and degree of functional impairment. Functional impairment was calculated using five-dimension EuroQol based on three domains-mobility, self-care, and usual activities. The association between age, number of comorbid conditions, and degree of functional impairment with 2-year incidence of CV and non-CV death was evaluated using Poisson regression analysis.

RESULTS: Older age was associated with higher number of comorbidities and functional impairment; after adjustment, increasing age was significantly associated with non-CV mortality (p = .03) but not CV mortality (p = .38). Greater functional impairment was associated with a higher rate and relatively equal magnitude risk of CV (rate ratios [RR] 1.52, 95% confidence intervals [CI]: 1.29-1.79, per one-step increase) and non-CV mortality (RR 1.42, 95% CI: 1.17-1.73). Multimorbidity was more strongly associated with CV mortality (RR 1.52, 95% CI: 1.38-1.67, per additional comorbidity) versus non-CV mortality (RR 1.29, 95% CI: 1.14-1.47, per additional comorbidity).

CONCLUSIONS: Multimorbidity and functional impairment are prevalent among older post-MI patients and are associated with increased CV and non-CV mortality. These findings highlight the importance of considering comorbid conditions and functional impairment as predictors of risk for adverse outcomes and aspects of medical decision making. Clinical Trial Registration: NCT01866904.

PMID:36317424 | DOI:10.1002/clc.23915

Neurourol Urodyn. 2022 Nov 1. doi: 10.1002/nau.25078. Online ahead of print.

ABSTRACT

INTRODUCTION: Patients with lower urinary tract symptoms (LUTS) can be subcategorized into polyuria, normal or oliguria groups. Polyuria may be caused by pathologies including diabetes mellitus (DM), chronic kidney disease (CKD), diabetes insipidus (DI), or primary polydipsia (PPD). While fluid restriction is appropriate for some, doing so in all may result in serious complications. This study investigates the prevalence of these pathologies in LUTS patients with polyuria.

MATERIALS AND METHODS: Two databases were retrospectively queried for men and women who filled out a lower urinary tract symptom score (LUTSS) questionnaire, 24-h bladder diary (24HBD) and were polyuric (>2.5 L/day). Patients were divided into four groups: poorly controlled DM, DI, an CKD grade 3 and PPD. One-way analysis of variance compared 24HBD and LUTSS questionnaires. Pearson correlation examined LUTSS and bother with 24-h voided volume (24 HVV), maximum voided volume (MVV) and total voids.

RESULTS: Among 814 patients who completed a 24HBD, 176 had polyuria (22%). Of the patients with complete data, 7.8% had poorly-controlled DM, 3.1% had DI, 4.7% had CKD grade 3% and 84.4% had PPD. Amongst the four different sub-groups, significant differences were seen in 24 HVV (p < 0.001), nocturnal urine volume (NUV) (p < 0.001), MVV (p = 0.003), daytime voids (p = 0.05), nocturnal polyuria index (NPi) (p < 0.001) and nocturia index (Ni) (p = 0.002). Significance was also seen between LUTSS and bother subscore (r = 0.68, p < 0.001), LUTSS and total voids (r = 0.29, p = 0.001) and bother sub-score and total voids (r = 0.21, p = 0.019).

CONCLUSIONS: 22% of patients with LUTS were found to have polyuria based on a 24HBD. Within this cohort, four sub-populations were identified as being demonstrating statistically significant differences in 24 HVV, NUV, MVV, daytime voids, NPi and Ni. Identifying the underlying etiology of polyuria should be carried out to safely treat patients with LUTS.

PMID:36317410 | DOI:10.1002/nau.25078

Epidemiol Health. 2022 Oct 24:e2022093. doi: 10.4178/epih.e2022093. Online ahead of print.

ABSTRACT

OBJECTIVES: According to previous findings, stressful life events (SLEs), and its subtypes are associated with depressive symptoms. However, few studies have explored potential models for events and incidental symptoms.

METHODS: The participants (men: 3,966 men; women: 5,709) were recruited from the Cardiovascular and Metabolic Diseases Etiology Research Center. SLEs were measured using a 47-item life experiences survey (LES) with a standardized protocol. Depressive symptoms were assessed using the Beck Depression Inventory II (BDI-II). The joint latent space item response models were performed by sex and age group (under 50 vs. 50+ years).

RESULTS: Among the LESs’ item, death/illness of close relatives, legal/sexual difficulties, family relationships, or social relationships shared latent positions with major depressive symptoms regardless of sex or age. We also observed a sex-specific domain; occupational and family-related items.

CONCLUSION: By projecting LES and BDI-II into the same interaction map in each subgroup, we could specify the association between specific LES and depressive symptoms.

PMID:36317403 | DOI:10.4178/epih.e2022093

Epidemiol Health. 2022 Oct 28:e2022096. doi: 10.4178/epih.e2022096. Online ahead of print.

ABSTRACT

OBJECTIVES: The Korea National Health and Nutrition Examination Survey (KNHANES) is a public health survey that assesses individual health and nutritional status and monitors the prevalence of major chronic diseases. In general, sampling weights are adjusted for unit non-responses and imputation for item non-responses. In this study, we proposed strategies for imputing item non-responses in the KNHANES in order to improve the usefulness of data, to minimize bias, and to increase statistical power.

METHODS: After applying some logical imputation, we adopted two separate imputation methods for each type of variables: unweighted sequential hot-deck imputation for categorical variables and sequential regression imputation for continuous variables. For variance estimation, multiple imputations were applied to the continuous variables. To evaluate the performance of the proposed strategies, we compared marginal distributions of imputed variables and the results multivariate regression analysis for the complete-case data and the expanded data with imputed values, respectively.

RESULTS: When comparing the marginal distributions, most of non-responses were imputed. The multivariable regression coefficients presented similar estimates; however, the standard errors decreased, resulting in a statistically significant P-values. Our evaluation shows that the proposed imputation strategies may cope with precision loss due to missing data, thus enhancing statistical power in the analysis of the KNHANES by providing expanded data with imputed values.

CONCLUSION: The proposed imputation strategy may enhance utility of data by increasing the number of complete-cases in the analysis while distorting the original distribution, thus laying a foundation to cope with the occurrence of item non-response in further surveys.

PMID:36317400 | DOI:10.4178/epih.e2022096

Stat Methods Med Res. 2022 Nov 1:9622802221134172. doi: 10.1177/09622802221134172. Online ahead of print.

ABSTRACT

We propose a flexible and scalable approximate Bayesian inference methodology for the Cox Proportional Hazards model with partial likelihood. The model we consider includes nonlinear covariate effects and correlated survival times. The proposed method is based on nested approximations and adaptive quadrature, and the computational burden of working with the log-partial likelihood is mitigated through automatic differentiation and Laplace approximation. We provide two simulation studies to show the accuracy of the proposed approach, compared with the existing methods. We demonstrate the practical utility of our method and its computational advantages over Markov Chain Monte Carlo methods through the analysis of Kidney infection times, which are paired, and the analysis of Leukemia survival times with a semi-parametric covariate effect and spatial variation.

PMID:36317395 | DOI:10.1177/09622802221134172

Stat Methods Med Res. 2022 Nov 1:9622802221133554. doi: 10.1177/09622802221133554. Online ahead of print.

ABSTRACT

Survival data with multiple outcomes are frequently encountered in biomedical investigations. An illustrative example comes from Alzheimer’s Disease Neuroimaging Initiative study where the cognitively normal subjects may clinically progress to mild cognitive impairment and/or Alzheimer’s disease dementia. Transition time from normal cognition to mild cognitive impairment and that from mild cognitive impairment to Alzheimer’s disease are expected to be correlated within subjects and the dependence is often accommodated by the frailty (random effects). Estimation in the frailty model unavoidably involves multiple integrations which may be intractable and hence leads to severe computational challenges, especially in the presence of high-dimensional covariates. In this paper, we propose efficient minorization-maximization algorithms in the frailty model for survival data with multiple outcomes. The alternating direction method of multipliers is further incorporated for simultaneous variable selection and homogeneity pursuit via regularization and fusion. Extensive simulation studies are conducted to assess the performance of the proposed algorithms. An application to the Alzheimer’s Disease Neuroimaging Initiative data is also provided to illustrate their practical utilities.

PMID:36317365 | DOI:10.1177/09622802221133554

Stat Med. 2022 Nov 1. doi: 10.1002/sim.9599. Online ahead of print.

ABSTRACT

There is a growing interest in current medical research to develop personalized treatments using a molecular-based approach. The broad goal is to implement a more precise and targeted decision-making process, relative to traditional treatments based primarily on clinical diagnoses. Specifically, we consider patients affected by Acute Myeloid Leukemia (AML), an hematological cancer characterized by uncontrolled proliferation of hematopoietic stem cells in the bone marrow. Because AML responds poorly to chemotherapeutic treatments, the development of targeted therapies is essential to improve patients’ prospects. In particular, the dataset we analyze contains the levels of proteins involved in cell cycle regulation and linked to the progression of the disease. We evaluate treatment effects within a causal framework represented by a Directed Acyclic Graph (DAG) model, whose vertices are the protein levels in the network. A major obstacle in implementing the above program is represented by individual heterogeneity. We address this issue through a Dirichlet Process (DP) mixture of Gaussian DAG-models where both the graphical structure as well as the allied model parameters are regarded as uncertain. Our procedure determines a clustering structure of the units reflecting the underlying heterogeneity, and produces subject-specific estimates of causal effects based on Bayesian Model Averaging (BMA). With reference to the AML dataset, we identify different effects of protein regulation among individuals; moreover, our method clusters patients into groups that exhibit only mild similarities with traditional categories based on morphological features.

PMID:36317356 | DOI:10.1002/sim.9599