Category: Nevin Manimala

Headache. 2022 Jun 7. doi: 10.1111/head.14328. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate the relationship between self-reported triggers and the occurrence of migraine attacks using a smartphone application.

BACKGROUND: One of several issues around the study of migraine attack triggers is that limited available evidence supports whether self-reported triggers can induce a headache on a particular subject.

METHODS: This is an observational longitudinal cohort study of individuals with migraine registered to track their headaches prospectively using a smartphone application. For 90 days, participants entered daily data about triggers (potential triggers and premonitory symptoms) that may be associated with attack risk, as well as migraine symptoms. The statistical significance of univariate associations between each trigger and migraine recurrent events was determined for each individual. Statistically identified triggers were then compared to self-reported triggers.

RESULTS: In 328 individuals (290/328 [88.4%] female; mean [standard deviation] 4.2 [1.5] migraine attacks/month) the mean (standard deviation) number of triggers moderately or highly endorsed per individual was 28.0 (7.7) in individuals presented with up to 38 possible triggers. Of these, an average (standard deviation) of 2.2 (2.1) triggers per individual were statistically associated with increased risk of attacks. Even the most commonly endorsed triggers (sleep quality, stress, tiredness/fatigue, sleep duration, dehydration, neck pain, missed meals, eyestrain, mean barometric pressure, and anxiety) were statistically associated in fewer than one third of individuals suspecting each, with the exception of neck pain (117/302 [38.7%]).

CONCLUSIONS: Individuals with episodic migraine believe that many triggers contribute to their attacks; however, few of these withstand statistical testing at the individual level. Improved personal knowledge of potential triggers and premonitory symptoms may help individuals adopt behavioral changes to mitigate attack risk.

PMID:35670125 | DOI:10.1111/head.14328

JACC Heart Fail. 2022 May 25:S2213-1779(22)00302-X. doi: 10.1016/j.jchf.2022.05.004. Online ahead of print.

ABSTRACT

BACKGROUND: N-terminal pro-B type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hs-cTnT) are associated with disease severity and outcomes among patients with heart failure with preserved ejection fraction (HFpEF).

OBJECTIVES: We evaluated associations between both biomarkers and clinical outcomes in the Empagliflozin Outcome Trial in Patients with Chronic Heart Failure with Preserved Ejection Fraction (EMPEROR-Preserved) Trial.

METHODS: Of 5988 study participants, 5986 (99.9%) and 5825 (97.3%) had available baseline NT-proBNP and hs-cTnT; post-baseline NT-proBNP was also available. Baseline characteristics were expressed by biomarker quartiles. The effect of empagliflozin on cardiovascular death/HF hospitalization, the individual components, total HF hospitalizations, slope of decline of estimated glomerular filtration rate (eGFR) and a composite renal endpoint was examined across biomarker quartiles. Change in NT-proBNP across study visits as a function of treatment assignment was also assessed.

RESULTS: Higher baseline NT-proBNP and hs-cTnT concentrations were associated with more comorbidities and worse HF severity. Incidence rates for cardiac and renal outcomes were 2-5-fold higher among those in the highest vs lowest NT-proBNP or hs-cTnT quartiles. Empagliflozin consistently reduced the risk for cardiovascular events and reduced slope of eGFR decline across NT-proBNP or hs-cTnT quartiles. Empagliflozin treatment modestly lowered NT-proBNP; by 100 weeks the adjusted mean difference in NT-proBNP from placebo was 7%. Increase in NT-proBNP from baseline to 12-weeks was strongly associated with risk of CV death/HF hospitalization.

CONCLUSIONS: The benefit of empagliflozin on cardiac outcomes and decline of eGFR is preserved across the wide range of baseline NT-proBNP and hs-cTnT evaluated. Empagliflozin modestly reduces NT-proBNP in HFpEF.

PMID:35670067 | DOI:10.1016/j.jchf.2022.05.004

Pediatrics. 2022 Jun 7:e2021056052. doi: 10.1542/peds.2021-056052. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVES: Outcome prediction of preterm birth is important for neonatal care, yet prediction performance using conventional statistical models remains insufficient. Machine learning has a high potential for complex outcome prediction. In this scoping review, we provide an overview of the current applications of machine learning models in the prediction of neurodevelopmental outcomes in preterm infants, assess the quality of the developed models, and provide guidance for future application of machine learning models to predict neurodevelopmental outcomes of preterm infants.

METHODS: A systematic search was performed using PubMed. Studies were included if they reported on neurodevelopmental outcome prediction in preterm infants using predictors from the neonatal period and applying machine learning techniques. Data extraction and quality assessment were independently performed by 2 reviewers.

RESULTS: Fourteen studies were included, focusing mainly on very or extreme preterm infants, predicting neurodevelopmental outcome before age 3 years, and mostly assessing outcomes using the Bayley Scales of Infant Development. Predictors were most often based on MRI. The most prevalent machine learning techniques included linear regression and neural networks. None of the studies met all newly developed quality assessment criteria. Studies least prone to inflated performance showed promising results, with areas under the curve up to 0.86 for classification and R2 values up to 91% in continuous prediction. A limitation was that only 1 data source was used for the literature search.

CONCLUSIONS: Studies least prone to inflated prediction results are the most promising. The provided evaluation framework may contribute to improved quality of future machine learning models.

PMID:35670123 | DOI:10.1542/peds.2021-056052

Neuromodulation. 2022 Jun;25(4):578-587. doi: 10.1111/ner.13342. Epub 2022 Feb 15.

ABSTRACT

BACKGROUND: Transcranial direct current stimulation (tDCS) for working memory is an enticing treatment, but there is mixed evidence to date.

OBJECTIVES: We tested the effects of electric field strength from uniform 2 mA dosing on working memory change from prestimulation to poststimulation. Second, we statistically evaluated a reverse-calculation method of individualizing tDCS dose and its effect on normalizing electric field at the cortex.

MATERIALS AND METHODS: We performed electric field modeling on a data set of 28 healthy older adults (15 women, mean age = 73.7, SD = 7.3) who received ten sessions of active 2 mA tDCS (N = 14) or sham tDCS (N = 14) applied over bilateral dorsolateral prefrontal cortices (DLPFC) in a triple-blind design. We evaluated the relationship between electric field strength and working memory change on an N-back task in conditions of above-median, high electric field from active 2 mA (N = 7), below-median, low electric field from active 2 mA (N = 7), and sham (N = 14) at regions of interest (ROI) at the left and right DLPFC. We then determined the individualized reverse-calculation dose to produce the group average electric field and measured the electric field variance between uniform 2 mA doses vs individualized reverse-calculation doses at the same ROIs.

RESULTS: Working memory improvements from pre- to post-tDCS were significant for the above-median electric field from active 2 mA condition at the left DLPFC (mixed ANOVA, p = 0.013). Furthermore, reverse-calculation modeling significantly reduced electric field variance at both ROIs (Levene’s test; p < 0.001).

CONCLUSIONS: Higher electric fields at the left DLPFC from uniform 2 mA doses appear to drive working memory improvements from tDCS. Individualized doses from reverse-calculation modeling significantly reduce electric field variance at the cortex. Taken together, using reverse-calculation modeling to produce the same, high electric fields at the cortex across participants may produce more effective future tDCS treatments for working memory.

PMID:35670064 | DOI:10.1111/ner.13342

Histol Histopathol. 2022 Jun 7:18479. doi: 10.14670/HH-18-479. Online ahead of print.

ABSTRACT

OBJECTIVES: Ductal epithelial changes (lympho-epithelial lesions-LEL) in prostatic chronic inflammation (CI) are not well studied so far.

AIM: to investigate LEL immediately adjacent to prostatic CI.

METHODS: We studied LEL in 144 prostatic surgical and autopsy specimens in various types of prostatic CI: NIH-category IV prostatitis (histologic prostatitis-HP), nonspecific granulomatous prostatitis (NSGP), and the reactive lymphoid infiltrates in the vicinity of benign prostatic hyperplasia (BPH) and prostate adenocarcinoma (PCa). CI is scored as low and high grade (LG, HG) according to the severity of inflammation.

RESULTS: LEL was identified in all types of prostatic specimens and in all types of prostatic CI: in 70.9% of patients with HP; in 100% of cases with NSGP; in 68.7% and in 80% adjacent to BPH and PCa respectively. Statistical analysis showed a significant correlation of the presence of LEL with HG CI (p&#60;0.001). LEL showed strong membranous PD-L1 expression.

CONCLUSIONS: The study presents the first attempt to examine LEL in inflammatory human prostate. PD-L1 positive LEL have no diagnostic organ specificity, although they are a constant histological finding in HG prostatic CI. LEL, inducible after birth by CI, are an integral part of prostate-associated lymphoid tissue (PALT) and of the inflammatory prostatic microenvironment.

PMID:35670049 | DOI:10.14670/HH-18-479

Thorac Cancer. 2022 Jun 6. doi: 10.1111/1759-7714.14523. Online ahead of print.

ABSTRACT

BACKGROUND: A previous trial showed that autologous ex-vivo expanded NK cell (SNK01) treatment combined with pembrolizumab showed better efficacy than pembrolizumab monotherapy in advanced non-small cell lung cancer (NSCLC). This study was a 2-year follow-up of that previous study to determine the long-term efficacy of the combination treatment.

METHODS: This trial included 20 patients with advanced NSCLC with a PD-L1 tumor proportion score of 1% or greater who failed prior to front-line platinum-based therapy. The patients received pembrolizumab with low-dose SNK01 (2 × 10⁹ cells/dose) or high-dose SNK01 (4 × 10⁹ cells/dose), or pembrolizumab monotherapy. The primary study endpoint was overall survival (OS), and the secondary endpoint was progression-free survival (PFS).

RESULTS: Two patients were excluded following serious adverse events. Among the 11 patients who died, five were from the NK groups (41.6%, n = 5/12), and six received pembrolizumab monotherapy (100%, n = 6/6). The estimated 2-year survival rate was 58.3% versus 16.7% (pembrolizumab plus SNK01 vs. pembrolizumab monotherapy). The hazard ratio of pembrolizumab plus SNK01 compared with pembrolizumab monotherapy was 0.32 (95% CI: 0.1, 1.08, p-value: 0.066). Although the median PFS was significantly higher in the pembrolizumab plus SNK01 group than in the pembrolizumab alone group, OS and PFS did not differ statistically between patients who received low doses of NK cells and those who received high doses of NK cells.

CONCLUSIONS: Autologous NK cells can enhance the long-term OS and PFS for NSCLC. A larger study is needed to confirm this result. Clinical Research Information Service number: KCT0003463.

PMID:35670036 | DOI:10.1111/1759-7714.14523

Br J Math Stat Psychol. 2022 Jun 6. doi: 10.1111/bmsp.12275. Online ahead of print.

ABSTRACT

A family of score-based tests has been proposed in recent years for assessing the invariance of model parameters in several models of item response theory (IRT). These tests were originally developed in a maximum likelihood framework. This study discusses analogous tests for Bayesian maximum-a-posteriori estimates and multiple-group IRT models. We propose two families of statistical tests, which are based on an approximation using a pooled variance method, or on a simulation approach based on asymptotic results. The resulting tests were evaluated by a simulation study, which investigated their sensitivity against differential item functioning with respect to a categorical or continuous person covariate in the two- and three-parametric logistic models. Whereas the method based on pooled variance was found to be useful in practice with maximum likelihood as well as maximum-a-posteriori estimates, the simulation-based approach was found to require large sample sizes to lead to satisfactory results.

PMID:35670000 | DOI:10.1111/bmsp.12275

Transpl Int. 2022 May 20;35:10137. doi: 10.3389/ti.2022.10137. eCollection 2022.

ABSTRACT

Conditional marketing authorization (CMA) facilitates timely access to new drugs for illnesses with unmet clinical needs, such as late graft failure after kidney transplantation. Late graft failure remains a serious, burdensome, and life-threatening condition for recipients. This article has been developed from content prepared by members of a working group within the European Society for Organ Transplantation (ESOT) for a Broad Scientific Advice request, submitted by ESOT to the European Medicines Agency (EMA), and reviewed by the EMA in 2020. The article presents the rationale for using surrogate endpoints in clinical trials aiming at improving late graft failure rates, to enable novel kidney transplantation therapies to be considered for CMA and improve access to medicines. The paper also provides background data to illustrate the relationship between primary and surrogate endpoints. Developing surrogate endpoints and a CMA strategy could be particularly beneficial for studies where the use of primary endpoints would yield insufficient statistical power or insufficient indication of long-term benefit following transplantation.

PMID:35669977 | PMC:PMC9163307 | DOI:10.3389/ti.2022.10137

J Healthc Eng. 2022 May 28;2022:1460908. doi: 10.1155/2022/1460908. eCollection 2022.

ABSTRACT

Intended pregnancy is one of the significant indicators of women’s well-being. Globally, 74 million women become pregnant every year without planning. Unintended pregnancies account for 28% of all pregnancies among married women in Bangladesh. This study aimed to investigate the performance of six different machine learning (ML) algorithms applied to predict unintended pregnancies among married women in Bangladesh. From BDHS 2017-18, only 1129 pregnant women aged 15-49 were eligible for this study. An independent χ ² test had performed before we considered six popular ML algorithms, such as logistic regression (LR), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), naïve Bayes (NB), and elastic net regression (ENR) to predict the unintended pregnancy. Accuracy, sensitivity, specificity, Cohen’s Kappa statistic, and area under curve (AUC) value were used as model evaluation. The bivariate analysis result showed that women aged 30-49 years, poor, not educated, and living in male-headed households had a higher percentage of unintended pregnancy. We found various performance parameters for the classification of unintended pregnancy: LR accuracy = 79.29%, LR AUC = 72.12%; RF accuracy = 77.81%, RF AUC = 72.17%; SVM accuracy = 76.92%, SVM AUC = 70.90%; KNN accuracy = 77.22%, KNN AUC = 70.27%; NB accuracy = 78%, NB AUC = 73.06%; and ENR accuracy = 77.51%, ENR AUC = 74.67%. Based on the AUC value, we can conclude that of all the ML algorithms we investigated, the ENR algorithm provides the most accurate classification for predicting unwanted pregnancy among Bangladeshi women. Our findings contribute to a better understanding of how to categorize pregnancy intentions among Bangladeshi women. As a result, the government can initiate an effective campaign to raise contraception awareness.

PMID:35669979 | PMC:PMC9167128 | DOI:10.1155/2022/1460908

PeerJ. 2022 Jun 1;10:e13421. doi: 10.7717/peerj.13421. eCollection 2022.

ABSTRACT

BACKGROUND: Information regarding using a pig cadaver model for teaching purposes in dentistry is limited, especially for periodontal surgery procedures. The aim of this study was to assess the feasibility and efficacy of teaching crown lengthening surgical procedures using a prepared pig cadaver model.

METHODS: Mandibles of slaughtered pigs with subgingival crown fracture defects on two premolars and two molars on each side were prepared as periodontal surgery teaching cases. A resident group (n = 20) and an instructor group (n = 18) participated in assessing the efficacy of the model by completing questionnaires before and after training sessions. Data was either assessed descriptively or analyzed statistically with Wilcoxon signed-rank test with the significance level at α = 0.05.

RESULTS: Results revealed that all the knowledge points showed statistically significant improvements (p < 0.05) except for the procedure to determine the quantity of bone removal during osteotomy procedures. Most residents rated the efficacy of the model obtained with 9.0 out of 10 scale. The data of effectiveness of the pig cadaver model from the instructor group ranged from 7.4 ± 1.4 to 9.0 ± 1.0.

CONCLUSION: Results of this study support feasibility in using prepared pig cadaver models to teach crown lengthening surgical procedures to postgraduates.

PMID:35669955 | PMC:PMC9166679 | DOI:10.7717/peerj.13421