Category: Statistics

Eur J Transl Myol. 2021 Aug 31. doi: 10.4081/ejtm.2021.9877. Online ahead of print.

ABSTRACT

In Multiple sclerosis (MS) it is important to preserve the residual physiological functions of subjects. The aim of the present study was to investigate the influence of nanotechnological device treatment combined with home-based training program (TP) on lactate level, hand grip strength and cervical mobility on MS patients. Seventeen MS patients were enrolled in the study and randomly assigned to an experimental group (EG) in which the Taopatch® nanotechnological device was applied or to a control group (CG). All the participants carried out a cervical range of motion (1) assessment and the hand grip test at baseline (T0) and after TP (T1), also investigating the lactate levels to figure out if there could be a correlation with the possible changes in the investigated parameters. The results showed no significant differences in both groups for ROM. As regards the hand grip test, EG showed a statistically significant improvement on strength for both hands, dominant (p = 0.01) and non-dominant (p = 0.04), while the CG showed an improvement only for the non-dominant hand (p = 0.001). No correlation was found between baseline lactate level and cervical ROM change. We can definitely conclude that exercise and Taopatch® can help to improve and maintain hand strength in MS subjects and also can prevent sedentary lifestyle during the COVID-19 pandemic time. These are preliminary results that need further investigations, possibly increasing sample size and lengthening time of intervention.

PMID:34498450 | DOI:10.4081/ejtm.2021.9877

Yeungnam Univ J Med. 2021 Sep 9. doi: 10.12701/yujm.2021.01123. Online ahead of print.

ABSTRACT

BACKGROUND: This study was aimed at comparing and analyzing the results of FractionLab (Varian/Mobius Medical System) with those of portal dosimetry that uses an electronic portal imaging device. Portal dosimetry is extensively used for patient-specific quality assurance (QA) in intensity-modulated radiotherapy (IMRT).

METHODS: The study includes 29 patients who underwent IMRT on a Novalis-Tx linear accelerator (Varian Medical System and BrainLAB) between June 2019 and March 2021. We analyzed the multileaf collimator (MLC) DynaLog files generated after portal dosimetry to evaluate the same condition using FractionLab. The results of the recently launched FractionLab at various gamma indices (0.1%/0.1 mm-1%/1 mm) are analyzed and compared with those of portal dosimetry (3%/3 mm).

RESULTS: The average gamma passing rates of portal dosimetry (3%/3 mm) and FractionLab are 98.1 (95.5%-100%) and 97.5% (92.3%-99.7%) at 0.6%/0.6 mm, respectively. The results of portal dosimetry (3%/3 mm) are statistically comparable with the QA results of FractionLab (0.6%/0.6 mm-0.9%/0.9 mm).

CONCLUSION: This paper presents the clinical performance of FractionLab by the comparison of the QA results of FractionLab using portal dosimetry with various gamma indexes when performing patient-specific QA in IMRT treatment. Further, the appropriate gamma index when performing patient-specific QA with FractionLab is provided.

PMID:34496467 | DOI:10.12701/yujm.2021.01123

J Clin Psychiatry. 2021 Sep 7;82(5):20m13831. doi: 10.4088/JCP.20m13831.

ABSTRACT

Objective: The DSM-5 criteria for avoidant/restrictive food intake disorder (ARFID) include ambiguities. Diagnostic criteria that allow for clinical judgment are essential for clinical practice. However, ambiguities can have major implications for treatment access and comparability and generalizability of research studies. The purpose of this study was to determine the degree to which distinct operationalizations of the diagnostic criteria for ARFID contribute to differences in the frequency of individuals who are eligible for the ARFID diagnosis.

Methods: Because criteria B, C, and D are rule-outs, we focused on criterion A, identified 19 potential operational definitions, and determined the extent to which these different methods impacted the proportion of individuals who met criteria for ARFID in a sample of children, adolescents, and young adults (n = 80; September 2016-February 2020) enrolled in an avoidant/restrictive eating study.

Results: Within each criterion, the proportion of individuals meeting diagnostic criteria differed significantly across the methodologies (all P values < .008). Using the strictest definition of each criterion, 50.0% (n = 40) of participants met criteria for ARFID. In contrast, under the most lenient definition of each criterion, the number nearly doubled, resulting in 97.5% (n = 78) meeting ARFID criteria.

Conclusions: Comparison of diagnostic definitions for ARFID among children, adolescents, and young adults confirmed a broad range of statistically distinct proportions within a single sample. Our findings support the need for additional contextual support and consensus among disciplines on operationalization in both research and clinical settings.

PMID:34496463 | DOI:10.4088/JCP.20m13831

Chronic Obstr Pulm Dis. 2021 Sep 8. doi: 10.15326/jcopdf.2021.0252. Online ahead of print.

ABSTRACT

PURPOSE: Pharmacotherapy is one cornerstone of Chronic Obstructive Pulmonary Disease (COPD) management. Published U.S. data seldom includes patient-reported COPD medication use and adherence. We add this patient perspective to the commonly reported administrative prescribing and fill data.

METHODS: This survey study used inhaler and nebulizer pictures and lists of oral COPD medication lists to query members of the COPD Foundation Patient-Powered Research Network, a national self-reported online registry. Medications used, adherence, inhaler education, cost concerns, previous exacerbations, and COPD Assessment Test scores were assessed and summarized using simple descriptive statistics and hazard ratios controlling for age, gender, and disease burden.

RESULTS: Respondents mean age was 68 years, 60% were women, >69% with the COPD Assessment Test (CAT) scores >15, and >50% reported 2 or more exacerbations in the past 12 months. Overall, >98% used one or more inhaled COPD medications, 7.6% rescue inhaler only, 17.3% bronchodilator therapy (11.1% dual), and 72.8% using corticosteroid containing therapies, including 53% triple therapy. Nebulizers were used by 59.4% and 34.8% use oral COPD medications. Reported adherence rates were high (80.1%), but 41% reported trouble paying for medications, with 20.1% reported missing medications due to cost.

CONCLUSIONS: In this population, COPD had a high burden with >50% of respondents using triple therapy, and one in eight maintenance oral corticosteroids. Self-reported adherence was high, but with significant costs concerns reported resulting in missed medications.

PMID:34496465 | DOI:10.15326/jcopdf.2021.0252

J Clin Psychiatry. 2021 Sep 7;82(5):20m13810. doi: 10.4088/JCP.20m13810.

ABSTRACT

Background: Etiologic differences between bipolar I disorder (BD-I) and bipolar II disorder (BD-II) have been challenged recently, and family epidemiologic studies may elucidate the matter. Nevertheless, it remains unclear whether BD-I and BD-II display different familial aggregation patterns within each bipolar disorder subtype and coaggregation with other psychiatric disorders.

Method: Per the Taiwan National Health Insurance Research Database (N = 23,258,175), patients with bipolar disorder were classified as having BD-I or BD-II based on the history of psychiatric hospitalization for a manic episode. During the study period (2001-2011), 184,958 first-degree relatives (FDRs) of patients with BD-I and BD-II were identified. By comparing patients with 1:4 age-, sex-, and kinship-matched samples without BD-I/BD-II probands, the relative risks (RRs) of major psychiatric disorders were estimated.

Results: FDRs of BD-I probands had a significantly higher risk of BD-I than those of BD-II probands (BD-I proband: RR = 15.80 vs BD-II proband: RR = 5.68, P < .001). The risk of BD-II was similar between FDRs of BD-I and BD-II probands (BD-I proband: RR = 6.48 vs BD-II proband: RR = 5.89, P = .1161). Familial aggregation was greater within each BD subtype than among cross-subtypes. Furthermore, FDRs of BD-I probands had an increased risk of schizophrenia (BD-I probands: RR = 5.83 vs BD-II probands: RR = 2.72, P < .001); FDRs of BD-II probands had a higher likelihood of attention-deficit/hyperactivity disorder (BD-II probands: 2.36 vs BD-I probands: 1.93, P = .0009).

Conclusions: The risk of psychiatric disorders is higher among the FDRs of patients with either BD-I or BD-II. Furthermore, the familial specificity of BD-I and BD-II assessed in this study may further the current understanding of etiologic boundaries between bipolar disorder subtypes.

PMID:34496462 | DOI:10.4088/JCP.20m13810

Neural Comput. 2021 May 13;33(6):1616-1655. doi: 10.1162/neco_a_01382.

ABSTRACT

Driver mental fatigue leads to thousands of traffic accidents. The increasing quality and availability of low-cost electroencephalogram (EEG) systems offer possibilities for practical fatigue monitoring. However, non-data-driven methods, designed for practical, complex situations, usually rely on handcrafted data statistics of EEG signals. To reduce human involvement, we introduce a data-driven methodology for online mental fatigue detection: self-weight ordinal regression (SWORE). Reaction time (RT), referring to the length of time people take to react to an emergency, is widely considered an objective behavioral measure for mental fatigue state. Since regression methods are sensitive to extreme RTs, we propose an indirect RT estimation based on preferences to explore the relationship between EEG and RT, which generalizes to any scenario when an objective fatigue indicator is available. In particular, SWORE evaluates the noisy EEG signals from multiple channels in terms of two states: shaking state and steady state. Modeling the shaking state can discriminate the reliable channels from the uninformative ones, while modeling the steady state can suppress the task-nonrelevant fluctuation within each channel. In addition, an online generalized Bayesian moment matching (online GBMM) algorithm is proposed to online-calibrate SWORE efficiently per participant. Experimental results with 40 participants show that SWORE can maximally achieve consistent with RT, demonstrating the feasibility and adaptability of our proposed framework in practical mental fatigue estimation.

PMID:34496386 | DOI:10.1162/neco_a_01382

J Neurol Surg A Cent Eur Neurosurg. 2021 Sep 8. doi: 10.1055/s-0041-1730965. Online ahead of print.

ABSTRACT

OBJECTIVE: Treatment for newly diagnosed isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) includes maximum safe resection, followed by adjuvant radio(chemo)therapy (RCx) with temozolomide. There is evidence that it is safe for GBM patients to prolong time to irradiation over 4 weeks after surgery. This study aimed at evaluating whether this applies to GBM patients with different levels of residual tumor volume (RV).

METHODS: Medical records of all patients with newly diagnosed GBM at our department between 2014 and 2018 were reviewed. Patients who received adjuvant radio (chemo) therapy, aged older than 18 years, and with adequate perioperative imaging were included. Initial and residual tumor volumes were determined. Time to irradiation was dichotomized into two groups (≤28 and >28 days). Univariate analysis with Kaplan-Meier estimate and log-rank test was performed. Survival prediction and multivariate analysis were performed employing Cox proportional hazard regression.

RESULTS: One hundred and twelve patients were included. Adjuvant treatment regimen, extent of resection, residual tumor volume, and O⁶-methylguanine DNA methyltransferase (MGMT) promoter methylation were statistically significant factors for overall survival (OS). Time to irradiation had no impact on progression-free survival (p = 0.946) or OS (p = 0.757). When stratified for different thresholds of residual tumor volume, survival predication via Cox regression favored time to irradiation below 28 days for patients with residual tumor volume above 2 mL, but statistical significance was not reached.

CONCLUSION: Time to irradiation had no significant influence on OS of the entire cohort. Nevertheless, a statistically nonsignificant survival prolongation could be observed in patients with residual tumor volume > 2 mL when admitted to radiotherapy within 28 days after surgery.

PMID:34496417 | DOI:10.1055/s-0041-1730965

Gesundheitswesen. 2021 Sep;83(8-09):e41-e48. doi: 10.1055/a-1531-5507. Epub 2021 Sep 8.

ABSTRACT

OBJECTIVE: Well-established mortality ratio methodology can contribute to a fuller picture of the SARS-CoV-2/COVID-19 burden of disease by revealing trends and informing mitigation strategies. This work examines respective data from Germany by way of example.

METHODS: Using monthly and weekly all-cause mortality data from January 2016 to June 2020 (published by the German Federal Statistical Institute) for all ages,<65 years and≥65 years, and specified for Germany’s federal states, we explored mortality as sequela of COVID-19. We analysed standardized mortality ratios (SMRs) comparing 2020 with 2016-2019 as reference years with a focus on trend detection.

RESULTS: In Germany as a whole, elevated mortality in April (most pronounced for Bavaria) declined in May. The states of Hamburg and Bremen had increased SMRs in all months under study. In Mecklenburg-Western Pomerania, decreased SMRs in January turned monotonically to increased SMRs by June. Irrespective of age group, this trend was pronounced and significant.

CONCLUSIONS: Increased SMRs in Hamburg and Bremen must be interpreted with caution because of potential upward distortions due to a “catchment bias”. A pronounced excess mortality in April across Germany was confirmed and a hitherto undetected trend of increasing SMRs for Mecklenburg-Western Pomerania was revealed. To meet the pandemic challenge and to benefit from research based on data collected in standardized ways, national authorities should regularly conduct SMR analyses. For independent analyses, national authorities should also expedite publishing raw mortality and population data, including detailed information on age, sex, and cause of death, in the public domain.

PMID:34496443 | DOI:10.1055/a-1531-5507

Neural Comput. 2021 May 13;33(6):1656-1697. doi: 10.1162/neco_a_01384.

ABSTRACT

We develop in this letter a framework of empirical gain maximization (EGM) to address the robust regression problem where heavy-tailed noise or outliers may be present in the response variable. The idea of EGM is to approximate the density function of the noise distribution instead of approximating the truth function directly as usual. Unlike the classical maximum likelihood estimation that encourages equal importance of all observations and could be problematic in the presence of abnormal observations, EGM schemes can be interpreted from a minimum distance estimation viewpoint and allow the ignorance of those observations. Furthermore, we show that several well-known robust nonconvex regression paradigms, such as Tukey regression and truncated least square regression, can be reformulated into this new framework. We then develop a learning theory for EGM by means of which a unified analysis can be conducted for these well-established but not fully understood regression approaches. This new framework leads to a novel interpretation of existing bounded nonconvex loss functions. Within this new framework, the two seemingly irrelevant terminologies, the well-known Tukey’s biweight loss for robust regression and the triweight kernel for nonparametric smoothing, are closely related. More precisely, we show that Tukey’s biweight loss can be derived from the triweight kernel. Other frequently employed bounded nonconvex loss functions in machine learning, such as the truncated square loss, the Geman-McClure loss, and the exponential squared loss, can also be reformulated from certain smoothing kernels in statistics. In addition, the new framework enables us to devise new bounded nonconvex loss functions for robust learning.

PMID:34496383 | DOI:10.1162/neco_a_01384

Neural Comput. 2021 May 13;33(6):1572-1615. doi: 10.1162/neco_a_01381.

ABSTRACT

An emerging paradigm proposes that neural computations can be understood at the level of dynamic systems that govern low-dimensional trajectories of collective neural activity. How the connectivity structure of a network determines the emergent dynamical system, however, remains to be clarified. Here we consider a novel class of models, gaussian-mixture, low-rank recurrent networks in which the rank of the connectivity matrix and the number of statistically defined populations are independent hyperparameters. We show that the resulting collective dynamics form a dynamical system, where the rank sets the dimensionality and the population structure shapes the dynamics. In particular, the collective dynamics can be described in terms of a simplified effective circuit of interacting latent variables. While having a single global population strongly restricts the possible dynamics, we demonstrate that if the number of populations is large enough, a rank R network can approximate any R-dimensional dynamical system.

PMID:34496384 | DOI:10.1162/neco_a_01381