Tag: statistics

Pain Ther. 2022 Sep 3. doi: 10.1007/s40122-022-00428-3. Online ahead of print.

ABSTRACT

INTRODUCTION: Recently, large channel endoscopic systems and full endoscopic visualization technique have been used to perform unilateral laminotomy for bilateral decompression (ULBD) treatment for lumbar central spinal stenosis (LCSS). However, various endoscopic systems possess different design parameters, which may affect the technical points and treatment outcomes. The object of this retrospective study was to compare the efficiency, safety, and effectiveness of ULBD under the iLESSYS Delta system versus the Endo-Surgi Plus system.

METHODS: In the period from October 2020 to April 2021, ULBD was performed using the iLESSYS Delta system or Endo-Surgi Plus system to treat LCSS. Patients were classified into two groups based on the endoscopy system employed. Patient demographics, perioperative indexes, complications, and imaging characteristics were reviewed. Clinical outcomes were quantified using back and leg visual analog scale (VAS) scores and Oswestry Disability Index (ODI) at the time points of follow-up.

RESULTS: Thirty-two patients were assigned to the iLESSYS Delta system group and 37 to the Endo-Surgi Plus system group. In the comparison between the two groups, the Endo-Surgi Plus system possessed a shorter incision length and operation time (p < 0.005), and no statistical differences in other aspects were observed. The dural sacs of both groups were significantly expanded postoperatively compared to preoperatively (p < 0.001). Both groups experienced improvements in VAS and ODI scores at all time points (p < 0.001) and equally low frequency of complications.

CONCLUSIONS: Current research suggests that both the Endo-Surgi Plus system and iLESSYS Delta system achieved favorable high safety and clinical outcomes in ULBD for treatment of LCSS. The use of a fully visualized trephine may have increased the efficiency of the Endo-Surgi Plus system. Moreover, the Endo-Surgi Plus system may be associated with a wider decompression range and indications.

PMID:36057015 | DOI:10.1007/s40122-022-00428-3

Breast Cancer. 2022 Sep 3. doi: 10.1007/s12282-022-01399-1. Online ahead of print.

ABSTRACT

BACKGROUND: Bevacizumab (BV) plus paclitaxel (PTX) is a treatment option in patients with HER2-negative metastatic breast cancer (mBC). We conducted an international pooled analysis with individual patient data to evaluate the effectiveness of BV + PTX as a first-line treatment for HER2-negative mBC patients under routine practice.

METHODS: A total of 2,474 mBC patients treated with BV + PTX from four prospective observational studies were analyzed. The primary endpoint was overall survival (OS). The other endpoints including identifying independent prognostic factors and validation of the modified Prognostic Factor Index (PFI) developed in the ATHENA trial.

RESULTS: Median follow-up time was 10.9 months (M). Median OS were 21.4 M (95% confidential interval 19.8-22.7 M). The seven independent prognostic factors (tumor subtype, age, ECOG performance status (PS), disease-free interval (DFI), liver metastases, number of metastatic organs, and prior anthracycline and/or taxane treatment) for OS found in this analysis included the five risk factors (RFs [DFI < 24 months, ECOG PS 2, liver metastases and/or > 3 metastasis organ sites, TNBC, prior anthracycline and/or taxane therapy]). High- (> 3 RFs [median OS 12.6 M]) and intermediate-risk groups (2 RFs [median OS 18.0 M]) had a significantly worse prognosis than the low-risk group (< 1 RF [median OS 27.4 M]), (p < 0.0001).

CONCLUSIONS: This international pooled analysis showed the effectiveness of first-line BV + PTX for HER2-negative mBC patients identifying seven independent prognostic factors as real-world evidence. The usefulness of the modified PFI developed in the ATHENA trial in predicting OS among patients receiving BV + PTX was also verified.

PMID:36057014 | DOI:10.1007/s12282-022-01399-1

Community Ment Health J. 2022 Sep 3. doi: 10.1007/s10597-022-01023-8. Online ahead of print.

ABSTRACT

This observational study compared the outcomes of consumers receiving community-based residential mental health rehabilitation support in Australia under a clinical staffing model and an integrated staffing model where Peer Support Workers are the majority component of the staffing profile. Reliable and clinically significant (RCS) change between admission and discharge in functional and clinical assessment measures were compared for consumers receiving care under the clinical (n = 52) and integrated (n = 93) staffing models. Covariate analyses examined the impact of known confounders on the outcomes of the staffing model groups. No statistically significant differences in RCS improvement were identified between the staffing models. However, logistic regression modelling showed that consumers admitted under the integrated staffing model were more likely to experience reliable improvement in general psychiatric symptoms and social functioning. The findings support the clinical and integrated staffing models achieving at least equivalent outcomes for community-based residential rehabilitation services consumers.

PMID:36057000 | DOI:10.1007/s10597-022-01023-8

Int Ophthalmol. 2022 Sep 3. doi: 10.1007/s10792-022-02504-1. Online ahead of print.

ABSTRACT

PURPOSE: Diabetic macular edema (DME) is a vision-threatening complication of diabetes mellitus due to increased vascular permeability. Patients are increasingly using YouTube videos to educate themselves about DME. This study analyzes the content and quality of YouTube videos about DME.

METHODS: Videos were searched in December 2021 for “diabetic macular edema.” The first 100 videos sorted by both relevance and view count were reviewed (n = 200). Quantitative metrics and content were collected. Two reviewers assessed videos using the JAMA (0-4), modified DISCERN (1-5), and Global Quality Scale (GQS, 1-5). Videos were sorted into author groups: 1 (academic institutions/organizations), 2 (private practices/organizations), and 3 (independent users; ophthalmologist users noted). Statistical analyses were deemed significant at a = 0.05.

RESULTS: One hundred four videos were included after applying exclusion criteria. Overall mean + standard deviations were 2.25 ± 0.83 (JAMA), 3.47 ± 0.55 (DISCERN), and 3.95 ± 0.95 (GQS). 51.9% of videos stated a definition, 32.7% mentioned screening, and 50% mentioned any DME risk factor. Healthcare professional-targeted videos had higher JAMA and DISCERN scores than patient-targeted videos (p < 0.05). Videos using ophthalmologists had higher JAMA and DISCERN scores than those lacking their presence (p < 0.05). JAMA scores significantly varied between author groups; within group 3, ophthalmologist-authored videos had higher DISCERN scores (p < 0.05).

CONCLUSION: Videos without ophthalmologists or targeted toward patients had poor quality and content coverage. The rising prevalence of diabetes, coupled with increased internet use for acquiring medical information, creates a strong need for high-quality information about DME.

PMID:36057009 | DOI:10.1007/s10792-022-02504-1

Environ Monit Assess. 2022 Sep 3;194(10):723. doi: 10.1007/s10661-022-10359-3.

ABSTRACT

During COVID-19, Shenyang implemented strict household isolation measures, resulting in a sharp reduction in anthropogenic emission sources, providing an opportunity to explore the impact of human activities on air pollution. The period from January to April of 2020 was divided into normal period, blockade period and resumption period. Combined with meteorological and pollutant data, mathematical statistics and spatial analysis methods were used to compare with the same period of 2015-2019. The results showed that PM_2.5, PM₁₀, NO₂ and O₃ increased by 32.6%, 13.2%, 4.65% and 22.7% in the normal period, among which the western area changed significantly. During the blockade period, the concentration of pollutants decreased by 35.79%, 35.87%, 32.45% and -4.84%, of which the central area changed significantly. During the resumption period, the concentration of pollutants increased by 21.8%, 8.7%, 5.7% and -6.3%, and the area with the largest change was located in the western. During the blockade period, a heavy pollution occurred with PM_2.5 as the main pollutant. The WRF-Chem model and the HYSPLIT model were used to reproduce the pollution occurrence process. The result showed that winds circulated as zonal winds during the pollution process at high altitudes. These winds were controlled by straight westerly and weak northwesterly airflows in front of the high pressure, and the ground was located behind the warm low pressure. Weather conditions were relatively stable. Thus, high temperatures (average > 10 ℃), high humidity (40%-60%) and slow wind (2 m/s) conditions prevailed for a long time in the Shenyang area. The unfavorable meteorological conditions lead to the occurrence of pollution. The backward trajectory showed that the potential source areas were concentrated in the urban agglomeration around Shenyang, and sporadic contributions came from North Korea.

PMID:36056993 | DOI:10.1007/s10661-022-10359-3

J Math Biol. 2022 Sep 3;85(3):25. doi: 10.1007/s00285-022-01770-y.

ABSTRACT

Skin contraction is an important biophysical process that takes place during and after recovery of deep tissue injury. This process is mainly caused by fibroblasts (skin cells) and myofibroblasts (differentiated fibroblasts which exert larger pulling forces and produce larger amounts of collagen) that both exert pulling forces on the surrounding extracellular matrix (ECM). Modelling is done in multiple scales: agent-based modelling on the microscale and continuum-based modelling on the macroscale. In this manuscript we present some results from our study of the connection between these scales. For the one-dimensional case, we managed to rigorously establish the link between the two modelling approaches for both closed-form solutions and finite-element approximations. For the multi-dimensional case, we computationally evidence the connection between the agent-based and continuum-based modelling approaches.

PMID:36056978 | DOI:10.1007/s00285-022-01770-y

World J Microbiol Biotechnol. 2022 Sep 3;38(11):215. doi: 10.1007/s11274-022-03385-3.

ABSTRACT

Plant metabolism interacts strongly with the plant microbiome. Glucosinolates, secondary metabolites synthesized by Brassica plants, are hydrolyzed by myrosinase into bioactive compounds of great importance in human health and plant protection. Compared with myrosinase from plant sources, myrosinase enzymes of microbial origin have not been extensively investigated. Therefore, seven endophytic strains corresponding to Bacillus sp. were isolated from Eruca vesicaria ssp. sativa plants that could hydrolyse glucosinolates (sinigrin) in the culture medium and showed myrosinase activity (0.08-19.92 U mL^-1). The bglA myrosinase-related gene encoding the 6-phospho-β-glucosidase (GH 1) from Bacillus sp. NGB-B10, the most active myrosinase-producing bacterium, was successfully identified. Response surface methodology (RSM) was applied to statistically optimize culture conditions for myrosinase production from Bacillus sp. strain NGB-B10. The Plackett-Burman design indicated that nitrogen concentration, incubation period, and agitation speed were the significant parameters in myrosinase production. The application of the Box-Behnken design of RSM resulted in a 10.03-fold increase in enzyme activity as compared to the non-optimized culture conditions. The myrosinase was partially purified by 40% fractionation followed by SDS-PAGE analysis which yielded two subunits that had a molecular weight of 38.6 and 35.0 KDa. The purified enzyme was stable under a broad range of pH (5.5-10) and temperatures (10-65 °C). The hydrolysis products released by bacterial myrosinase from some glucosinolate extracts had higher and/or equivalent in vitro antagonistic activity against several phytopathogenic fungi compared to the nystatin (a broad-spectrum antifungal agent). This study provides original information about a new source of bacterial myrosinase and affords an optimized method to enhance myrosinase production.

PMID:36056962 | DOI:10.1007/s11274-022-03385-3

Brief Bioinform. 2022 Sep 2:bbac354. doi: 10.1093/bib/bbac354. Online ahead of print.

ABSTRACT

Identifying genomic regions influenced by natural selection provides fundamental insights into the genetic basis of local adaptation. However, it remains challenging to detect loci under complex spatially varying selection. We propose a deep learning-based framework, DeepGenomeScan, which can detect signatures of spatially varying selection. We demonstrate that DeepGenomeScan outperformed principal component analysis- and redundancy analysis-based genome scans in identifying loci underlying quantitative traits subject to complex spatial patterns of selection. Noticeably, DeepGenomeScan increases statistical power by up to 47.25% under nonlinear environmental selection patterns. We applied DeepGenomeScan to a European human genetic dataset and identified some well-known genes under selection and a substantial number of clinically important genes that were not identified by SPA, iHS, Fst and Bayenv when applied to the same dataset.

PMID:36056746 | DOI:10.1093/bib/bbac354

Brief Bioinform. 2022 Sep 2:bbac375. doi: 10.1093/bib/bbac375. Online ahead of print.

ABSTRACT

Copy number variation (CNV) is a class of key biomarkers in many complex traits and diseases. Detecting CNV from sequencing data is a substantial bioinformatics problem and a standard requirement in clinical practice. Although many proposed CNV detection approaches exist, the core statistical model at their foundation is weakened by two critical computational issues: (i) identifying the optimal setting on the sliding window and (ii) correcting for bias and noise. We designed a statistical process model to overcome these limitations by calculating regional read depths via an exponentially weighted moving average strategy. A one-run detection of CNVs of various lengths is then achieved by a dynamic sliding window, whose size is self-adopted according to the weighted averages. We also designed a novel bias/noise reduction model, accompanied by the moving average, which can handle complicated patterns and extend training data. This model, called PEcnv, accurately detects CNVs ranging from kb-scale to chromosome-arm level. The model performance was validated with simulation samples and real samples. Comparative analysis showed that PEcnv outperforms current popular approaches. Notably, PEcnv provided considerable advantages in detecting small CNVs (1 kb-1 Mb) in panel sequencing data. Thus, PEcnv fills the gap left by existing methods focusing on large CNVs. PEcnv may have broad applications in clinical testing where panel sequencing is the dominant strategy. Availability and implementation: Source code is freely available at https://github.com/Sherwin-xjtu/PEcnv.

PMID:36056740 | DOI:10.1093/bib/bbac375

J Am Heart Assoc. 2022 Sep 3:e026603. doi: 10.1161/JAHA.122.026603. Online ahead of print.

ABSTRACT

Background Waveform parameters provide approximate data about aortic wave reflection. However, their association with cardiovascular events remains controversial and their role in cardiovascular prediction is unknown. Methods and Results We analyzed participants aged between 40 and 69 from the population-based CARTaGENE cohort. Baseline pulse wave analysis (central pulse pressure, augmentation index) and wave separation analysis (forward pressure, backward pressure, reflection magnitude) parameters were derived from radial artery tonometry. Associations between each parameter and major adverse atherosclerotic events (MACE; cardiovascular death, stroke, myocardial infarction) were obtained using adjusted Cox models. The incremental predictive value of each parameter compared with the 10-year atherosclerotic cardiovascular disease score alone was assessed using hazard ratios, c-index differences, continuous net reclassification indexes, and integrated discrimination indexes. From 17 561 eligible patients, 2315 patients had a MACE during a median follow-up of 10.1 years. Central pulse pressure, forward pressure, and backward pressure, but not augmentation index and reflection magnitude, were significantly associated with MACE after full adjustment. All parameters except forward pressure statistically improved MACE prediction compared with the atherosclerotic cardiovascular disease score alone. The greatest prediction improvement was seen with augmentation index and reflection magnitude but remained small in magnitude. These 2 parameters enhanced predictive performance more strongly in patients with low baseline atherosclerotic cardiovascular disease scores. Up to 5.7% of individuals were reclassified into a different risk stratum by adding waveform parameters to atherosclerotic cardiovascular disease scores. Conclusions Some waveform parameters are independently associated with MACEs in a population-based cohort. Augmentation index and reflection magnitude slightly improve risk prediction, especially in patients at low cardiovascular risk.

PMID:36056725 | DOI:10.1161/JAHA.122.026603