Nevin Manimala

J Aerosol Med Pulm Drug Deliv. 2021 Oct 12. doi: 10.1089/jamp.2021.0006. Online ahead of print.

ABSTRACT

Background: Inhaled drug delivery can be limited by heterogeneous dose distribution. An additive that would disperse drug over the internal surfaces of the lung after aerosol deposition could improve dosing uniformity and increase the treated area. Our previous studies demonstrated that surfactant additives can produce surface tension-driven (Marangoni) flows that effectively dispersed aerosol-delivered drugs over mucus surfaces. Here we sought to determine whether the addition of a surfactant would increase transport of an aerosol between lung regions and also improve dosing uniformity in human lungs. Methods: We compared the deposition and postdeposition dispersion of surfactant (10 mg/mL dipalmitoylphosphatidylcholine; DPPC) and saline-based liquid aerosols, admixed with Technetium 99m (Tc99m) diethylenetriaminepentaacetic acid, using gamma scintigraphy. Deposition images were obtained ex vivo in eight pairs of ventilated human lungs. The trachea was intubated and the mainstem bronchi were alternately clamped so that saline was delivered to one lung and then DPPC to the other (sides alternated). The lungs were continually imaged for 15 minutes during delivery. We assessed transport of the deposited aerosol by quantifying the percentage of Tc99m in each of four lung quadrants over time. We quantified dose uniformity within each lung quadrant by measuring the coefficient of variation (CV = standard deviation of the pixel associated radioactive counts/mean of the counts within each quadrant). Results: There was no change in the percentage of Tc99m in each quadrant over time, indicating no improvement in transport with the addition of the surfactant. The addition of surfactant was associated with a statistically significant decrease in CV in the lower inner lung quadrant at each of the three time points, indicating an improvement in dosing uniformity. Conclusion: These preliminary results indicate the possible utility of adding surfactant to aerosols to improve drug distribution uniformity to lower inner lung regions.

PMID:34647795 | DOI:10.1089/jamp.2021.0006

Psychol Methods. 2021 Oct 14. doi: 10.1037/met0000429. Online ahead of print.

ABSTRACT

The replicability crisis has drawn attention to numerous weaknesses in psychology and social science research practice. In this work we focus on three issues that cannot be addressed with replication alone, and which deserve more attention: Functional misspecification, structural misspecification, and unreliable interpretation of results. We demonstrate a number of possible consequences via simulation, and provide recommendations for researchers to improve their research practice. Psychologists and social scientists should engage with these areas of analytical and statistical improvement, as they have the potential to seriously hinder scientific progress. Every research question and hypothesis may present its own unique challenges, and it is only through an awareness and understanding of varied statistical methods for predictive and causal modeling, that researchers will have the tools with which to appropriately address them. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

PMID:34647760 | DOI:10.1037/met0000429

Psychol Methods. 2021 Oct 14. doi: 10.1037/met0000414. Online ahead of print.

ABSTRACT

Causal inference in psychological research is typically hampered by unobserved confounding. A copula-based method can be used to statistically control for this problem without the need for instruments or covariates, given relatively lenient distributional assumptions on independent variables and error terms. The current study aims to: (a) provide a user-friendly introduction to the copula method for psychology researchers, and (b) examine the degree of non-normality in the independent variables required for satisfactory performance. A Monte Carlo simulation study was used to assess the behavior of the copula method under various combinations of conditions (sample size, skewness of independent variables, effect size, and magnitude of confounding). In addition, an applied example from research on the effects of parental rearing on adult personality and life satisfaction was used to illustrate the method. Simulations revealed that the copula method performed better at higher levels of skewness in the independent variables, and that the impacts of lower skewness can be offset to some extent by larger sample size. When skewness and/or sample size is too small, the copula method is biased toward the uncorrected model. In the applied example, parental rejection/punishment predicted less adaptive personality and life satisfaction, with no evidence of confounding. For parental control/overprotection, there was evidence that confounding attenuated the estimated relationship with personality/life satisfaction. Copula adjustment is a promising method for handling unobserved confounding. The discussion focuses on how to proceed when assumptions are not quite met, and outlines potential avenues for future research. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

PMID:34647758 | DOI:10.1037/met0000414

Psychol Methods. 2021 Oct 14. doi: 10.1037/met0000422. Online ahead of print.

ABSTRACT

Theories can be represented as statistical models for empirical testing. There is a vast literature on model selection and multimodel inference that focuses on how to assess which statistical model, and therefore which theory, best fits the available data. For example, given some data, one can compare models on various information criterion or other fit statistics. However, what these indices fail to capture is the full range of counterfactuals. That is, some models may fit the given data better not because they represent a more correct theory, but simply because these models have more fit propensity-a tendency to fit a wider range of data, even nonsensical data, better. Current approaches fall short in considering the principle of parsimony (Occam’s Razor), often equating it with the number of model parameters. Here we offer a toolkit for researchers to better study and understand parsimony through the fit propensity of structural equation models. We provide an R package (ockhamSEM) built on the popular lavaan package. To illustrate the importance of evaluating fit propensity, we use ockhamSEM to investigate the factor structure of the Rosenberg Self-Esteem Scale. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

PMID:34647757 | DOI:10.1037/met0000422

J Neurosurg Sci. 2021 Oct 14. doi: 10.23736/S0390-5616.21.05477-1. Online ahead of print.

ABSTRACT

INTRODUCTION: The subarachnoid hemorrhage due to a ruptured brain aneurysm is a neurological emergency with high mobility and mortality. Hypertensive states are related to a bad prognosis and a higher risk of a ruptured aneurysm. However, the relationship between the blood pressure variability with the aneurysmal subarachnoid hemorrhage and its prognosis is quite unknown.

EVIDENCE ACQUISITION: A systematic review was performed across the databases. The following descriptors and related were used for the search: “blood pressure”, “arterial pressure”, variability, subarachnoid hemorrhage, hemorrhage, aneurysmal, aneurysmal subarachnoid hemorrhage. The following data were extracted: Glasgow Outcome Scale or Modified Rankin Scale, and blood pressure variabilities to categorize the prognosis.

EVIDENCE SYNTHESIS: 5 studies were selected. The blood pressure variability and the related outcome were assessed by mean systolic blood pressure and minimum systolic blood. The meta-analysis of mean systolic blood pressure (cut-off >95.3 mmHg) showed an odds ratio of 11.23 (CI 95%: 4,423 to 28,537) (p=<0.001), predicting the good outcome after the aneurysmal subarachnoid hemorrhage. The pooled analysis revealed AUC of the ROC predicting the good outcome was statistically significant (AUC:0.85, p<0.001). The pooled data analysis of minimum systolic blood pressure revealed an odds ratio of 6.43 (CI 95%:2.834-14.589, P <0,001) and AUC of the pooled ROC 0.931 (CI95%:0,851 to 1,000, P <0,001) to predict poor outcome. The funnel plot through Egger’s test for the analysis showed different grades of asymmetry.

CONCLUSIONS: The blood pressure variability (mean and minimum systolic blood pressure) is a good predictor and parameter in the aneurysmal subarachnoid hemorrhage prognosis and outcome prediction.

PMID:34647715 | DOI:10.23736/S0390-5616.21.05477-1

J Neurosurg Sci. 2021 Oct 14. doi: 10.23736/S0390-5616.21.05402-3. Online ahead of print.

ABSTRACT

INTRODUCTION: Post craniotomy pain management with opioids is challenging due to their side effects, which might mask neurological deterioration symptoms. Recently, intravenous (IV) acetaminophen has been tested in this population. This meta-analysis aimed to synthesize evidence from published randomized controlled trials (RCTs) about the efficacy of IV acetaminophen in reducing pain scores in postoperative craniotomy patients.

EVIDENCE ACQUISITION: A computer literature search of PubMed, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL) was conducted. We selected RCTs comparing IV acetaminophen versus placebo for postoperative pain management in craniotomy patients. Data on the visual analog scale (VAS), opioid requirements, hospital stay, and patients’ satisfaction weexretr acted and pooled as standardized mean difference (SMD) with the corresponding 95% confidence intervals (CI) in the meta-analysis model.

EVIDENCE SYNTHESIS: Five RCTs, with a total of 493 patients, were pooled in the final analysis. Patients in the IV acetaminophen group had significantly lower VAS pain scores compared to the placebo group (SMD -0.28, 95% CI [-0.46 to -0.10]). However, in terms of opioid requirement, hospital stay, and patients’ satisfaction, there were no statistically significant differences between both groups (P>0.05).

CONCLUSIONS: This meta-analysis provides class one evidence that IV Acetaminophen can significantly reduce postoperative pain in craniotomy patients with an excellent safety profile; however, there are not benefits in terms of hospital stay, opioid requirement, or patients’ satisfaction.

PMID:34647710 | DOI:10.23736/S0390-5616.21.05402-3

Minerva Pediatr (Torino). 2021 Oct 14. doi: 10.23736/S2724-5276.21.05896-1. Online ahead of print.

ABSTRACT

BACKGROUND: Cerebral palsy (CP) is the most common cause of physical disability in childhood defined as a group of permanent disorders of movement. The aim of this study was to determine the effects of 12-week aquatic exercise program on gross motor function, swimming skills, and walking ability in children with cerebral palsy.

METHODS: Eighteen children (Mean ± SD age: 12.3 ± 3 years) with cerebral palsy classified at Levels I, II and III on the Gross Motor Function Classification System were allocated to one group, where the first 12 weeks were a control period while another 12 weeks were an experimental period. The participants underwent the same battery of tests focusing gross motor function, swimming skills, and walking ability on three occasions.

RESULTS: Control period was stable with no significant changes in any of measurements. After the 12-week experimental program, a statistically significant improvement was determined in gross motor function (p=0.005), swimming skills (p=0.000), walking endurance and walking (p=0.000). No significant differences (p>0.05) were observed for walking efficiency.

CONCLUSIONS: The 12-week aquatic exercise program (3/week, 60 minutes), combining Halliwick method, swimming and walking activities may improve the gross motor function, swimming skills, walking endurance and velocity in ambulatory children with cerebral palsy.

PMID:34647700 | DOI:10.23736/S2724-5276.21.05896-1

J Evid Based Med. 2021 Oct 14. doi: 10.1111/jebm.12451. Online ahead of print.

NO ABSTRACT

PMID:34647687 | DOI:10.1111/jebm.12451

J Med Virol. 2021 Oct 14. doi: 10.1002/jmv.27394. Online ahead of print.

ABSTRACT

Like most vaccines, the effectiveness of COVID-19 vaccines developed so far is not 100% and a small percentage of fully vaccinated individuals still develop symptomatic or asymptomatic SARS-CoV-2 infections. ¹ In addition, the emerging of novel mutations is likely to help the virus evade vaccines especially in regions with low vaccination coverage. ² This article is protected by copyright. All rights reserved.

PMID:34647629 | DOI:10.1002/jmv.27394

Stat Med. 2021 Oct 14. doi: 10.1002/sim.9219. Online ahead of print.

ABSTRACT

Seasonal influenza infects between 10 and 50 million people in the United States every year. Accurate forecasts of influenza and influenza-like illness (ILI) have been named by the CDC as an important tool to fight the damaging effects of these epidemics. Multi-model ensembles make accurate forecasts of seasonal influenza, but current operational ensemble forecasts are static: they require an abundance of past ILI data and assign fixed weights to component models at the beginning of a season, but do not update weights as new data on component model performance is collected. We propose an adaptive ensemble that (i) does not initially need data to combine forecasts and (ii) finds optimal weights which are updated week-by-week throughout the influenza season. We take a regularized likelihood approach and investigate this regularizer’s ability to impact adaptive ensemble performance. After finding an optimal regularization value, we compare our adaptive ensemble to an equal-weighted and static ensemble. Applied to forecasts of short-term ILI incidence at the regional and national level, our adaptive model outperforms an equal-weighted ensemble and has similar performance to the static ensemble using only a fraction of the data available to the static ensemble. Needing no data at the beginning of an epidemic, an adaptive ensemble can quickly train and forecast an outbreak, providing a practical tool to public health officials looking for a forecast to conform to unique features of a specific season.

PMID:34647627 | DOI:10.1002/sim.9219