Tag: statistics

J Affect Disord. 2022 Jan 2:S0165-0327(21)01451-8. doi: 10.1016/j.jad.2021.12.134. Online ahead of print.

ABSTRACT

OBJECTIVE: To compare the efficacy and discontinuation of augmentation agents in adult patients with treatment-resistant depression (TRD). We conducted a systematic review and network meta-analyses (NMA) to combine direct and indirect comparisons of augmentation agents.

METHODS: We included randomized controlled trials comparing one active drug with another or with placebo following a treatment course up to 24 weeks. Twenty-one agents were included: stimulants, atypical antipsychotics, thyroid hormones, antidepressants, mood stabilizers and olanzapine-fluoxetine combination. Data for response/remission and all-cause discontinuation rates were analyzed. We estimated effect-size by relative risk using pairwise and NMA with random-effects model.

RESULTS: A total of 63 studies (N=12108) with 21 augmentation agents were included. Our findings from the NMA for response rates, compared to placebo, were significant for: liothyronine, nortriptyline, aripiprazole, brexpiprazole, quetiapine, lithium, modafinil, olanzapine+fluoxetine, cariprazine, and lisdexamphetamine. For remission rates, compared to placebo, were significant for: statistically higher findings were found for: thyroid hormone(T4), aripiprazole, risperidone, quetiapine, and olanzapine+fluoxetine. Compared to placebo, ziprasidone, mirtazapine, and cariprazine had statistically significant higher discontinuation rates. Overall, 24% studies were rated as having low risk of bias(RoB), 63% had moderate RoB and 13% had high RoB.

LIMITATIONS: Heterogeneity in TRD definitions, variable trial duration and methodological clinical design of older studies and small number of trials per comparisons.

CONCLUSIONS: In reviewing more than 20 studies this NMA suggests a superiority of the regulatory approved adjunctive atypical antipsychotics, thyroid hormones, dopamine compounds (modafinil and lisdexamphetamine) and lithium. Acceptability was lower with ziprasidone, mirtazapine, and cariprazine. Further research and head-to-head studies should be considered to strengthen the best available options for TRD.

PMID:34986373 | DOI:10.1016/j.jad.2021.12.134

Ann Phys Rehabil Med. 2022 Jan 2:101626. doi: 10.1016/j.rehab.2021.101626. Online ahead of print.

ABSTRACT

OBJECTIVES: Sports-related concussions (SRCs) are a concern for high school athletes. Understanding factors contributing to SRC recovery time may improve clinical management. However, the complexity of the many clinical measures of concussion data precludes many traditional methods. This study aimed to answer the question What is the utility of modeling clinical concussion data using machine-learning algorithms for predicting SRC recovery time and protracted recovery?

METHODS: This was a retrospective case series of participants aged 8 to 18 years with a diagnosis of SRC. A 6-part measure was administered to assess pre-injury risk factors, initial injury severity, and post-concussion symptoms, including the Vestibular Ocular Motor Screening (VOMS) measure, King-Devick Test and C3 Logix Trails Test data. These measures were used to predict recovery time (days from injury to full medical clearance) and binary protracted recovery (recovery time > 21 days) according to several sex-stratified machine-learning models. The ability of the models to discriminate protracted recovery was compared to a human-driven model according to the area under the receiver operating characteristic curve (AUC).

RESULTS: For 293 males (mean age 14.0 years) and 362 females (mean age 13.7 years), the median (interquartile range) time to recover from an SRC was 26 (18-39) and 21 (14-31) days, respectively. Among 9 machine-learning models trained, the gradient boosting on decision-tree algorithms achieved the best performance to predict recovery time and protracted recovery in males and females . The models’ performance improved when VOMS data were used in conjunction with the King-Devick Test and C3 Logix Trails Test data. For males and females, the AUC was 0.84 and 0.78 versus 0.74 and 0.73, respectively, for statistical models for predicting protracted recovery.

CONCLUSIONS: Machine-learning models were able to manage the complexity of the vestibular-ocular motor system data. These results demonstrate the clinical utility of machine-learning models to inform prognostic evaluation for SRC recovery time and protracted recovery.

PMID:34986402 | DOI:10.1016/j.rehab.2021.101626

Virus Res. 2022 Jan 2:198671. doi: 10.1016/j.virusres.2021.198671. Online ahead of print.

ABSTRACT

Capripoxvirus diseases are listed as reportable diseases by World Organisation for Animal Health (OIE). Lumpy skin disease virus (LSDV) and sheeppox virus (SPPV), which can only be distinguished by molecular analysis, cause moderately, severe, or sometimes fatal infections in cattle and sheep. Even though vaccines are the most effective way to control the infection, their effectiveness may decrease in some cases. Therefore, it is significant to explore antiviral drugs against these diseases along with the vaccine. This study aimed to investigate the antiviral efficiency of ivermectin (IVM) at different stages in vitro replication of LSDV and SPPV. For this purpose, viral titers (TCID₅₀/mL) of viruses not treated with IVM (0.0 μM) and treated with non-cytotoxic concentrations of IVM (1.0 and 2.5 μM) were compared during a nine-day (216h) post-infection period by viral titration assay. At 2.5 μM concentrations of IVM, the mean viral titer was significantly (P<0.05) reduced by approximately three logs for the replication stage of LSDV and SPPV. To evaluate the antiviral activity of IVM against LSDV and SPPV by treatment at the virus attachment and penetration stages, the titers of the virus either untreated or treated with 2,5μM IVM were compared by virus titration assay. The number of infectious virions for LSDV and SPPV were decreased by 99.82% and 99.87% at the viral replication stage, 68.38% and 25.01% at the attachment stage, and 57.83% and 0.0% at the penetration stage, respectively. It was determined that ivermectin was statistically more effective on LSDV than SPPV at the virus attachment and penetration stage (P<0.05). This study found that the drug IVM can inhibit capripoxviruses, including LSDV and SPPV at various stages of the propagation. Moreover, this research predicted the in vitro antiviral ability of IVM against capripoxvirus infection for the first time.

PMID:34986368 | DOI:10.1016/j.virusres.2021.198671

mSphere. 2022 Jan 5:e0097821. doi: 10.1128/msphere.00978-21. Online ahead of print.

ABSTRACT

Horizontal transfer of bacterial plasmids generates genetic variability and contributes to the dissemination of the genes that enable bacterial cells to develop antimicrobial resistance (AMR). Several aspects of the conjugative process have long been known, namely, those related to the proteins that participate in the establishment of cell-to-cell contact and to the enzymatic processes associated with the processing of plasmid DNA and its transfer to the recipient cell. In this work, we describe the roles of newly identified proteins that influence the conjugation of several plasmids. Genes encoding high-molecular-weight bacterial proteins that contain one or several immunoglobulin-like domains (Big) are located in the transfer regions of several plasmids that usually harbor AMR determinants. These Big proteins are exported to the external medium and target two extracellular organelles: the flagella and conjugative pili. The plasmid gene-encoded Big proteins facilitate conjugation by reducing cell motility and facilitating cell-to-cell contact by binding both to the flagella and to the conjugative pilus. They use the same export machinery as that used by the conjugative pilus components. In the examples characterized in this paper, these proteins influence conjugation at environmental temperatures (i.e., 25°C). This suggests that they may play relevant roles in the dissemination of plasmids in natural environments. Taking into account that they interact with outer surface organelles, they could be targeted to control the dissemination of different bacterial plasmids carrying AMR determinants. IMPORTANCE Transmission of a plasmid from one bacterial cell to another, in several instances, underlies the dissemination of antimicrobial resistance (AMR) genes. The process requires well-characterized enzymatic machinery that facilitates cell-to-cell contact and the transfer of the plasmid. Our paper identifies novel plasmid gene-encoded high-molecular-weight proteins that contain an immunoglobulin-like domain and are required for plasmid transmission. They are encoded by genes on different groups of plasmids. These proteins are exported outside the cell. They bind to extracellular cell appendages such as the flagella and conjugative pili. Expression of these proteins reduces cell motility and increases the ability of the bacterial cells to transfer the plasmid. These proteins could be targeted with specific antibodies to combat infections caused by AMR microorganisms that harbor these plasmids.

PMID:34986320 | DOI:10.1128/msphere.00978-21

mSphere. 2022 Jan 5:e0073021. doi: 10.1128/msphere.00730-21. Online ahead of print.

ABSTRACT

While differences in human virulence have been reported across nontyphoidal Salmonella (NTS) serovars and associated subtypes, a rational and scalable approach to identify Salmonella subtypes with differential ability to cause human diseases is not available. Here, we used NTS serovar Saintpaul (S. Saintpaul) as a model to determine if metadata and associated whole-genome sequence (WGS) data in the NCBI Pathogen Detection (PD) database can be used to identify (i) subtypes with differential likelihoods of causing human diseases and (ii) genes and single nucleotide polymorphisms (SNPs) potentially responsible for such differences. S. Saintpaul SNP clusters (n = 211) were assigned different epidemiology types (epi-types) based on statistically significant over- or underrepresentation of human clinical isolates, including human associated (HA; n = 29), non-human associated (NHA; n = 23), and other (n = 159). Comparative genomic analyses identified 384 and 619 genes overrepresented among isolates in 5 HA and 4 NHA SNP clusters most significantly associated with the respective isolation source. These genes included 5 HA-associated virulence genes previously reported to be present on Gifsy-1/Gifsy-2 prophages. Additionally, premature stop codons in 3 and 7 genes were overrepresented among the selected HA and NHA SNP clusters, respectively. Tissue culture experiments with strains representing 4 HA and 3 NHA SNP clusters did not reveal evidence for enhanced invasion or intracellular survival for HA strains. However, the presence of sodCI (encoding a superoxide dismutase), found in 4 HA and 1 NHA SNP clusters, was positively correlated with intracellular survival in macrophage-like cells. Post hoc analyses also suggested a possible difference in intracellular survival among S. Saintpaul lineages. IMPORTANCE Not all Salmonella isolates are equally likely to cause human disease, and Salmonella control strategies may unintentionally focus on serovars and subtypes with high prevalence in source populations but are rarely associated with human clinical illness. We describe a framework leveraging WGS data in the NCBI PD database to identify Salmonella subtypes over- and underrepresented among human clinical cases. While we identified genomic signatures associated with HA/NHA SNP clusters, tissue culture experiments failed to identify consistent phenotypic characteristics indicative of enhanced human virulence of HA strains. Our findings illustrate the challenges of defining hypo- and hypervirulent S. Saintpaul and potential limitations of phenotypic assays when evaluating human virulence, for which in vivo experiments are essential. Identification of sodCI, an HA-associated virulence gene associated with enhanced intracellular survival, however, illustrates the potential of the framework and is consistent with prior work identifying specific genomic features responsible for enhanced or reduced virulence of nontyphoidal Salmonella.

PMID:34986312 | DOI:10.1128/msphere.00730-21

J Clin Ultrasound. 2022 Jan 5. doi: 10.1002/jcu.23126. Online ahead of print.

ABSTRACT

PURPOSE: To evaluate the efficacy and safety of magnetic resonance imaging (MRI)-based comparing with computed tomography (CT)-based selection for intravenous thrombolysis in patients with acute ischemic stroke (AIS).

METHODS: Totally 462 consecutive AIS patients treated with intravenous thrombolysis within a 4.5 h window from Jan. 2016 to Dec. 2019 were enrolled. The primary endpoint was the good functional outcome defined by a modified Rankin Scale (mRS) of 0-2 at 3 months. Secondary outcomes include the excellent functional outcome defined by a mRS of 0-1 at 3 months, occurrences of symptomatic intracranial hemorrhage (SICH), 7-day mortality, and 3-month mortality.

RESULTS: Overall 172 patients received MRI and 290 received CT before they were treated with thrombolysis. The difference in the good or excellent functional outcome was not statistically significant between MRI and CT groups (both P > 0.05). The incidences of 7-day mortality (3.5% vs. 8.6%, P < 0.01), 30-day mortality (12.8% vs. 21.0%, P = 0.03), and SICH (12.2% vs. 20.3%, P < 0.01) were obviously lower for MRI-based regimen compared with CT-based regimen. Multivariate logistic regression indicated that MRI-based regimen was significantly associated with a lower risk of 7-day mortality (OR = 0.72, 95% CI: 0.53-0.91; P < 0.01), 30-day mortality (OR = 0.58, 95% CI: 0.47-0.73; P < 0.01), and SICH (OR = 0.44, 95% CI: 0.20-0.65; P < 0.01) after controlling for potential confounding factors.

CONCLUSION: Despite MRI-based thrombolysis was not demonstrated to be associated with the good functional outcome, it significantly reduced risks of mortality and SICH in patients with AIS compared with CT-based thrombolysis.

PMID:34986280 | DOI:10.1002/jcu.23126

Bioinformatics. 2022 Jan 5:btac004. doi: 10.1093/bioinformatics/btac004. Online ahead of print.

ABSTRACT

SUMMARY: Bayesian inference in biological modeling commonly relies on Markov chain Monte Carlo (MCMC) sampling of a multidimensional and non-Gaussian posterior distribution that is not analytically tractable. Here, we present the implementation of a practical MCMC method in the open-source software package PyBioNetFit (PyBNF), which is designed to support parameterization of mathematical models for biological systems. The new MCMC method, am, incorporates an adaptive move proposal distribution. For warm starts, sampling can be initiated at a specified location in parameter space and with a multivariate Gaussian proposal distribution defined initially by a specified covariance matrix. Multiple chains can be generated in parallel using a computer cluster. We demonstrate that am can be used to successfully solve real-world Bayesian inference problems, including forecasting of new Coronavirus Disease 2019 case detection with Bayesian quantification of forecast uncertainty.

AVAILABILITY AND IMPLEMENTATION: PyBNF version 1.1.9, the first stable release with am, is available at PyPI and can be installed using the pip package-management system on platforms that have a working installation of Python 3. PyBNF relies on libRoadRunner and BioNetGen for simulations (e.g., numerical integration of ordinary differential equations defined in SBML or BNGL files) and Dask.Distributed for task scheduling on Linux computer clusters. The Python source code can be freely downloaded/cloned from GitHub and used and modified under terms of the BSD-3 license (https://github.com/lanl/pybnf). Online documentation covering installation/usage is available (https://pybnf.readthedocs.io/en/latest/). A tutorial video is available on YouTube (https://www.youtube.com/watch?v=2aRqpqFOiS4&t=63s).

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34986226 | DOI:10.1093/bioinformatics/btac004

Mil Med. 2022 Jan 5:usab543. doi: 10.1093/milmed/usab543. Online ahead of print.

ABSTRACT

INTRODUCTION: According to the Military Health System Traumatic Brain Injury (TBI) Center of Excellence, 51,261 service members suffered moderate to severe TBI in the last 21 years. Moderate to severe TBI in service members is usually related to blast injury in combat operations, which necessitates medical evacuation to higher levels of care. Prevention of secondary insult, and mitigation of the unique challenges associated with the transport of TBI patients in a combat setting are important in reducing the morbidity and mortality associated with this injury. The primary goal of this study was a secondary analysis comparing the impact of time to transport on clinical outcomes for TBI patients without polytrauma versus TBI patients with polytrauma transported out of the combat theater via Critical Care Air Transport Teams (CCATT). Our secondary objective was to describe the occurrence of in-flight events and interventions for TBI patients without polytrauma versus TBI with polytrauma to assist with mission planning for future transports.

MATERIALS AND METHODS: We performed a secondary analysis of a retrospective cohort of 438 patients with TBI who were evacuated out of theater by CCATT from January 2007 to May 2014. Polytrauma was defined as abbreviated injury scale (AIS) of at least three to another region in addition to head/neck. Time to transport was defined as the time (in days) from injury to CCATT evacuation out of combat theater. We calculated descriptive statistics and examined the associations between time to transport and preflight characteristics, in-flight interventions and events, and clinical outcomes for TBI patients with and without polytrauma.

RESULTS: We categorized patients into two groups, those who had a TBI without polytrauma (n = 179) and those with polytrauma (n = 259). Within each group, we further divided those that were transported within 1 day of injury, in 2 days, and 3 or more days. Patients with TBI without polytrauma transported in 1 or 2 days were more likely to have a penetrating injury, an open head injury, a preflight Glascow Coma Score (GCS) of 8 or lower, and be mechanically ventilated compared to those transported later. Patients without polytrauma who were evacuated in 1 or 2 days required more in-flight interventions compared to patients without polytrauma evacuated later. Patients with polytrauma who were transported in 2 days were more likely to receive blood products, and patients with polytrauma who were evacuated within 1 day were more likely to have had at least one episode of hypotension en route. Polytrauma patients who were evacuated in 2-3 days had higher hospital days compared to polytrauma with earlier evacuations. There was no significant difference in mortality between any of the groups.

CONCLUSIONS: In patients with moderate to severe TBI transported via CCATT, early evacuation was associated with a higher rate of in-flight hypotension in polytrauma patients. Furthermore, those who had TBI without polytrauma that were evacuated in 1-2 days received more in-flight supplementary oxygen, blood products, sedatives, and paralytics. Given the importance of minimizing secondary insults in patients with TBI, recognizing this in this subset of the population may help systematize ways to minimize such events. Traumatic Brain Injury patients with polytrauma may benefit from further treatment and stabilization in theater prior to CCATT evacuation.

PMID:34986265 | DOI:10.1093/milmed/usab543

J Pediatr Psychol. 2022 Jan 5:jsab132. doi: 10.1093/jpepsy/jsab132. Online ahead of print.

ABSTRACT

OBJECTIVE: To provide national norms and percentiles for both research and clinical scoring modalities of the Vanderbilt Attention Deficit/Hyperactivity Disorder (ADHD) Diagnostic Parent Rating Scale (VADPRS) for a representative sample of children ages 5-12 in the United States.

METHOD: The five clinical subscales of the VADPRS were completed by 1,570 caregivers of children ages 5-12 in the United States, with children representative of the national population on key demographic variables including race, sex, ethnicity, family income, and family educational level. Descriptive statistics and measures of internal consistency of both dimensional and symptom count scoring were provided for each of the five clinical subscales of the inventory, as well as percentiles and group comparisons for select dimensional scoring subscales based on age and child sex.

RESULTS: Measures of internal consistency for each subscale using both scoring modalities of the VADPRS ranged from high to acceptable. There were statistically significant differences among the different subscales for both age (ADHD hyperactivity, anxiety/depression) and sex [both presentations of ADHD, oppositional defiant disorder (ODD)] for the total sample. These differences, however, were modest in magnitude and unlikely to be clinically meaningful.

CONCLUSIONS: This study enhances the research and clinical utility of the VADPRS by providing national norms and percentiles for each of its subscales. Differences between age and sex across the sample were statistically significant for two of the subscales (Hyperactivity and Anxiety/Depression) with additional subscales significant for sex alone (Inattentive and ODD), but these differences were not substantial enough to indicate a need for separate cut-offs for screening purposes.

PMID:34986222 | DOI:10.1093/jpepsy/jsab132

Phys Chem Chem Phys. 2022 Jan 5. doi: 10.1039/d1cp05072a. Online ahead of print.

ABSTRACT

Nucleophilicity provides important information about the chemical reactivity of organic molecules. Experimental determination of the nucleophilicity parameter is a tedious and resource-intensive approach. Herein, we present a novel machine learning protocol that uses key structural descriptors to predict the nucleophilicities of organic molecules, which agree well with the experimental values. A data driven approach was used where quantum mechanical molecular and thermodynamic descriptors from a wide range of structurally diverse nucleophiles and relevant solvents were extracted and modelled using advanced algorithms against the experimentally available nucleophilicity values. Despite the structural diversity of nucleophiles, we are able to achieve statistically robust models with a high predictive power using tree-based and neural network algorithms trained on an in-house developed unique dataset consisting of 752 nucleophilicity values and 27 molecular descriptors.

PMID:34986215 | DOI:10.1039/d1cp05072a