Tag: pubmed

Zhonghua Nei Ke Za Zhi. 2021 Oct 1;60(10):875-879. doi: 10.3760/cma.j.cn112138-20201228-01056.

ABSTRACT

Objective: To investigate the pathogen distribution and antimicrobial resistance among lower respiratory tract infections in patients with hematological malignancies. Methods: Sputum samples were collected from 967 patients with hematological malignancies and lower respiratory tract infections in Department of Hematology,the Second Hospital of Shanxi Medical University from January 2017 to July 2020. The pathogens and drug sensitivity reports were carried out by automatic bacterial identification instruments. WHONET 5.6 and SPSS 20.0 softwares were used for statistical analysis. Results: A total of 961 strains of pathogens were isolated, 516 (53.7%) pathogens were Gram-negative bacteria, mainly 118 strains of Klebsiella pneumonia (12.3%), 68 strains of Pseudomonas aeruginosa (7.1%), 67 strains of Acinetobacter baumannii (7.0%),52 strains of Stenotrophomonas maltophilia (5.4%), 43 strains of Escherichia coli (4.5%), and 42 strains of Enterbacter cloacae (4.4%). There were 171 (17.8%) strains of Gram-positive bacteria and 274 (28.5%) fungi. The drug resistance rates of Pseudomonas aeruginosa and Acinetobacter baumannii to carbapenem were 22.1%-31.3%. Stenotrophomonas maltophilia was sensitive to levofloxacin, compound sulfamethoxazole and minocycline. The antimicrobial resistance rates of these three enterobacteria to carbapenems, cefoperazone/sulbactam, piperacillin/tazobactam were low (<10%). The resistant Gram-positive bacteria to ticoplanin, vancomycin and linazolamide were not detected. Conclusion: The major pathogens related to lower respiratory tract infections in patients with hematological malignancies are gram-negative bacteria in our centre. Different pathogens appear different characteristics of antimicrobial resistance.

PMID:34551475 | DOI:10.3760/cma.j.cn112138-20201228-01056

Trends Psychiatry Psychother. 2021 Sep 21. doi: 10.47626/2237-6089-2020-0131. Online ahead of print.

ABSTRACT

INTRODUCTION: Anhedonia is a critical symptom of major depressive disorder and is defined as the reduced ability to experience pleasure. The Temporal Experience of Pleasure Scale (TEPS) is commonly used to measure anhedonia and presents satisfactory reliability.

OBJECTIVES: We aim to perform the transcultural adaptation of the Brazilian version of the TEPS and evaluate its psychometric properties.

METHOD: The cross-cultural adaptation was performed according to previously established protocols. Cronbach’s alpha internal consistency coefficient was used to establish the item’s degree of interrelation and coherence. Also, we used the intraclass correlation coefficient calculation to determine the stability of the scale after the proposed period and exploratory factor analysis to evaluate the structural factor and scale content. The principal component analysis estimation method determined the factors to be retained in the factorial model.

RESULTS: The participants have reported a good understanding and applicability of the Brazilian version of the TEPS. The results have shown a statistically significant correlation between the measures. The calculation of the intraclass correlation coefficient presented a significant value. The examination of the overall internal consistency of the scale showed a suitable Cronbach’s alpha value.

CONCLUSION: The proposed version of the TEPS scale in Portuguese presented a good understanding for the Brazilian population and reliability and validity regarding its psychometric characteristics.

PMID:34551464 | DOI:10.47626/2237-6089-2020-0131

Korean J Anesthesiol. 2021 Sep 23. doi: 10.4097/kja.21358. Online ahead of print.

ABSTRACT

Most diseases have more than two interventions or treatment methods, and the application of network meta-analysis (NMA) studies to compare and evaluate the superiority of each intervention or treatment method is increasing. Understanding the concepts and processes of systematic reviews and meta-analyses is essential to understanding NMA. As with systematic reviews and meta-analyses, NMA involves specifying the topic, searching for and selecting all related studies, and extracting data from the selected studies. To evaluate the effects of each treatment, NMA compares and analyzes three or more interventions or treatment methods using both direct and indirect evidence. There is a possibility of several biases when performing NMA. Therefore, key assumptions like similarity, transitivity, and consistency should be satisfied when performing NMA. Among these key assumptions, consistency can be evaluated and quantified by statistical tests. This review aims to introduce the concepts of NMA, analysis methods, and interpretation and presentation of the results of NMA. It also briefly introduces the emerging issues in NMA, including methods for evaluation of consistency.

PMID:34551467 | DOI:10.4097/kja.21358

Nature. 2021 Sep 22. doi: 10.1038/s41586-021-04014-z. Online ahead of print.

ABSTRACT

Throughout the COVID-19 pandemic, countries relied on a variety of ad-hoc border control protocols to allow for non-essential travel while safeguarding public health: from quarantining all travellers to restricting entry from select nations based on population-level epidemiological metrics such as cases, deaths or testing positivity rates^1,2. Here we report the design and performance of a reinforcement learning system, nicknamed ‘Eva’. In the summer of 2020, Eva was deployed across all Greek borders to limit the influx of asymptomatic travellers infected with SARS-CoV-2, and to inform border policies through real-time estimates of COVID-19 prevalence. In contrast to country-wide protocols, Eva allocated Greece’s limited testing resources based upon incoming travellers’ demographic information and testing results from previous travellers. By comparing Eva’s performance against modelled counterfactual scenarios, we show that Eva identified 1.85 times as many asymptomatic, infected travellers as random surveillance testing, with up to 2-4 times as many during peak travel, and 1.25-1.45 times as many asymptomatic, infected travellers as testing policies that only utilize epidemiological metrics. We demonstrate that this latter benefit arises, at least partially, because population-level epidemiological metrics had limited predictive value for the actual prevalence of SARS-CoV-2 among asymptomatic travellers and exhibited strong country-specific idiosyncrasies in the summer of 2020. Our results raise serious concerns on the effectiveness of country-agnostic internationally proposed border control policies³ that are based on population-level epidemiological metrics. Instead, our work represents a successful example of the potential of reinforcement learning and real-time data for safeguarding public health.

PMID:34551425 | DOI:10.1038/s41586-021-04014-z

J Osteopath Med. 2021 Sep 22. doi: 10.1515/jom-2021-0025. Online ahead of print.

ABSTRACT

CONTEXT: Sacroiliac dysfunction is characterized by a hypomobility of the range of motion of the joint, followed by a positional change regarding the relationship between the sacrum and the iliac. In general, the clinical tests that evaluate the sacroiliac joint (SIJ) and its dysfunctions lack validity and reliability values.

OBJECTIVES: This article aims to evaluate the construct validity and intra- and inter-rater reliability of the standing flexion test (STFT) and sitting flexion test (SIFT).

METHODS: In this prospective study, the sample consisted of 30 individuals of both sexes, and the evaluation team was composed of five researchers. The evaluations took place on two different days: first day, inter-rater reliability and construct validity; and second day, intra-rater reliability. The reference standard for the construct validity was 3-dimensional measurements obtained utilizing the BTS SMART-DX system. For statistical analysis, the percentage (%) agreement and the kappa statistic (K) were utilized.

RESULTS: The construct validity was determined for STFT (70% agreement; K=0.49; p<0.01) and SIFT (56.7% agreement; K=0.29; p<0.05). The intra-rater reliability was determined for STFT (66.3% agreement; K=0.43; p<0.01) and SIFT (56.7% agreement; K=0.38; p<0.01). The inter-rater reliability was determined for STFT (10% agreement; K=-0.02; p=0.825) and SIFT (13.3% agreement; K=0.01; p=0.836).

CONCLUSIONS: The STFT confirmed the construct validity and was reliable when applied by the same rater to healthy people, even if the rater had no experience. It was not possible to achieve minimum scores using the SIFT either for construct validity or reliability. We suggest that further studies be conducted to investigate the measurement properties of palpatory clinical tests for SIJ mobility, especially in symptomatic patients.

PMID:34551460 | DOI:10.1515/jom-2021-0025

Biomed Phys Eng Express. 2021 Sep 22. doi: 10.1088/2057-1976/ac2935. Online ahead of print.

ABSTRACT

Objective Extraction of temporal features of neuronal activity from electrophysiological data can be used for accurate classification of neural networks in healthy and pathologically perturbed conditions. In this study, we provide an extensive approach for the classification of humanin vitroneural networks with and without an underlying pathology, from electrophysiological recordings obtained using a microelectrode array (MEA) platform. Approach We developed a Dirichlet mixture (DM) Point Process statistical model able to extract temporal features related to neurons. We then applied a machine learning algorithm to discriminate between healthy control and pathologically perturbedin vitroneural networks. Main Results We found a high degree of separability between the classes using DM point process features (p-value <0.001 for all the features, paired t-test), which reaches 93.10 of accuracy (92.37 of ROC AUC) with the Random Forest classifier. In particular, results show a higher latency in firing for pathologically perturbed neurons (43 ± 16 ms vs 67 ± 31 ms,μ_IGfeature distribution). Significance Our approach has been successful in extracting temporal features related to the neurons’ behaviour, as well as distinguishing healthy from pathologically perturbed networks, including classification of responses to a transient induced perturbation.

PMID:34551397 | DOI:10.1088/2057-1976/ac2935

Cerebrovasc Dis Extra. 2021 Sep 22;11(3):87-91. doi: 10.1159/000519121. Online ahead of print.

ABSTRACT

BACKGROUND: Recent reports have suggested that atrial fibrillation (AF) is more prevalent in the large vessel occlusion (LVO) subgroup of acute ischaemic stroke patients. Given the association between left atrial enlargement (LAE) and AF, we sought to evaluate the feasibility of assessing LAE on non-gated CT and its association with LVO in the hyperacute stroke setting.

METHODS: We analysed our prospectively collected database that included all stroke patients referred for consideration of endovascular treatment between April 14, 2020, and May 21, 2020. During this period, a CT chest was included in our regional stroke protocol to aid triage of patients suspected for COVID-19 from which cardiac measurements were obtained. Patients were dichotomized into LVO and no-LVO groups, and LA measurements were trichotomized into normal, borderline, and enlarged. Univariate analyses were performed between groups.

RESULTS: Of the included 38 patients, 21 were categorized as LVO and 17 as no LVO. There was a statistically significant association between LAE and LVO (p = 0.028). No significant difference was demonstrated between groups for the baseline AF and other clinical characteristics, except for baseline NIHSS (p = 0.0005). There was excellent inter- and intra-rater reliability (ICC = 0.969) for LA measurements.

CONCLUSION: Our study provides preliminary data to suggest LAE is more prevalent in the LVO stroke subgroup at presentation and can be reliably assessed on non-gated CT in the hyperacute setting. These findings have potential implications for stratifying secondary management and may prompt a more rigorous pursuit of occult AF or other cardiac causes of stroke.

PMID:34551410 | DOI:10.1159/000519121

Comput Methods Programs Biomed. 2021 Sep 19;211:106400. doi: 10.1016/j.cmpb.2021.106400. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Hepatic fibrosis is the prominent characteristic of biliary atresia (BA), may even progress continually after Kasai procedure (KP). BA, as a devastating pediatric hepatic disease, mainly leads to newborn cholestasis, even liver cirrhosis, eventually hepatic failure. Earlier diagnosis of hepatic fibrosis, which used to be detected by liver biopsy commonly, is consistent with better outcomes of KP. Due to potential risks and uncertainty of liver biopsy, it is an urge to seek a safer and more precise evaluation method as alternative. The purpose of this study is to investigate the hemodynamics of hepatic artery (HA) in hepatic fibrosis of early BA based on computational fluid dynamics (CFD) for evaluating the value of CFD for hepatic fibrosis diagnosis.

METHODS: 40 patients were divided into three groups, including the control group, the abnormal liver function group and the mild to moderate hepatic fibrosis group. CFD was applied to quantify primary hemodynamic parameters of HA and related arteries, including blood flow distribution ratio (FDR), pressure, wall shear stress (WSS) and energy loss (EL). Statistical analyses were also performed to compare the differences amongst these above groups.

RESULTS: With the progression of hepatic fibrosis, the increasing tendency of hemodynamic parameters values of HA and related arteries were observed. Values of FDR, pressure, WSS and EL of the mild to moderate group was higher than those of the control group and the abnormal liver function group. There were significant differences on FDR_AA, FDR_HA and EL between the control group and the mild to moderate hepatic fibrosis group (t = 0.037, 0.030 and <0.001, P < 0.05).

CONCLUSION: Significant variations of HA hemodynamics acquired by CFD between the control group and the mild to moderate hepatic fibrosis group demonstrated the relationship between the progression of hepatic fibrosis and the hemodynamic disorder, and suggested that CFD had the potential to assist the diagnosis of hepatic fibrosis in early BA.

PMID:34551379 | DOI:10.1016/j.cmpb.2021.106400

Forensic Sci Int. 2021 Sep 14;328:110998. doi: 10.1016/j.forsciint.2021.110998. Online ahead of print.

ABSTRACT

Near Infrared (NIR) is a type of vibrational spectroscopy widely used in different areas to characterize substances. NIR datasets are comprised of absorbance measures on a range of wavelengths (λ). Typically noisy and correlated, the use of such datasets tend to compromise the performance of several statistical techniques; one way to overcome that is to select portions of the spectra in which wavelengths are more informative. In this paper we investigate the performance of the Random Forest (RF) classifier associated with several wavelength importance ranking approaches on the task of classifying product samples into categories, such as quality levels or authenticity. Our propositions are tested using six NIR datasets comprised of two or more classes of food and pharmaceutical products, as well as illegal drugs. Our proposed classification model, an integration of the χ² ranking score and the RF classifier, substantially reduced the number of wavelengths in the dataset, while increasing the classification accuracy when compared to the use of complete datasets. Our propositions also presented good performance when compared to competing methods available in the literature.

PMID:34551367 | DOI:10.1016/j.forsciint.2021.110998

Int J Nurs Stud. 2021 Sep 5;124:104084. doi: 10.1016/j.ijnurstu.2021.104084. Online ahead of print.

ABSTRACT

BACKGROUND: Nurses play a vitally important role in promoting equitable and essential care. China undertook bold reforms in its education and healthcare systems since 1990s. The effect of these reforms on the nursing workforce has not been assessed systematically.

OBJECTIVE: This study aims to assess the changing trends and the underlying challenges of the nursing workforce in Mainland China in the period of 1998-2018.

DESIGN: Retrospective data analysis.

METHODS: Data were acquired from the National Health Statistics Yearbook from 1999 to 2019. Descriptive statistics were used to analyze the nature of the nursing workforce in terms of quantity, quality, and structure. Non-parametric tests were used to compare doctors and nurses in terms of number and work experiences. Global Moran’s I index and hotspot analysis were applied to compare the equity in distribution of nurses at national and provincial levels.

RESULTS: From 1998 to 2018, the number of nurses increased from 1.22 to 4.10 million with an average rate of increase of 6.3% per annum. The ratio of doctors to nurses changed from 1: 0.61 to 1: 1.14, reaching 1: 1 in 2013. The main educational level of registered nurses elevated to associated degree (48.9%), and nurses with advanced titles increased at the most rapid rate. In 2018, 60.3% of nurses were younger than 35 years old. The Global Moran’s I index ranged from 0.211 to 0.198 (Z > 1.96, P < 0.05). Hotspot analysis showed the distribution of nurses was unequally concentrated in the northern region and with the highest distribution in Beijing.

CONCLUSIONS: Great improvement on the scale and the quality of nursing workforce over the past 20 years has been witnessed in China. However, the shortage of nurses, outflow of younger nurses and the imbalance distribution of nursing workforce among the country are emerging challenges. Plans should not be ignored on continuously cultivating more qualified nurses, retaining younger nurses, attracting nurses to work in rural areas and the northeast region. Tweetable abstract: The number of nurses in Mainland China increased greatly in the period of 1998-2018, with its improvement in quality, structure, and distribution. However, the shortage of nurses, nurse outflow and the imbalance in the distribution are underlying risks that influence nurse development.

PMID:34551370 | DOI:10.1016/j.ijnurstu.2021.104084