Tag: statistics

Drug Alcohol Depend. 2021 Dec 30;231:109245. doi: 10.1016/j.drugalcdep.2021.109245. Online ahead of print.

ABSTRACT

BACKGROUND: Prescription drug misuse remains a persistent problem in the United States. Residents living in disadvantaged neighborhoods are at greater risk of substance abuse such as alcohol, tobacco, or drugs. However, whether neighborhood disadvantage affects prescription drug misuse remains underexplored.

METHODS: This study uses data on 3444 mothers from the Fragile Families and Child Wellbeing Study to examine the role of neighborhood disadvantage in prescription drug misuse. In addition, we examine whether social support and neighborhood collective efficacy (social cohesion and social control) explain this relationship. The analysis uses multivariate logistic regression and delineated between the following neighborhoods: affluent (3% poverty), low poverty (3-10%), moderate poverty (10-20%), and high poverty neighborhoods (20% or more).

RESULTS: Mothers living in moderately poor neighborhoods were more than twice as likely (odds = 2.17, 95% CI: 1.43-3.27) to misuse prescription drugs than mothers living in neighborhoods with high poverty. Mothers living in neighborhoods with high poverty did not have a statistically significant difference in prescription drug misuse than those living in affluent or low poverty neighborhoods. Social support and neighborhood collective efficacy did not explain these associations. The association between moderate poverty and prescription drug misuse was mostly direct and there was no indirect association.

CONCLUSION: The study highlights the higher risk of prescription drug misuse among mothers living in neighborhoods with moderate poverty. Interventions aimed at reducing opioid misuse should focus on demographic groups that are more vulnerable such as low-income mothers living in disadvantaged neighborhoods.

PMID:34998251 | DOI:10.1016/j.drugalcdep.2021.109245

Int J Pharm Pract. 2022 Jan 6:riab079. doi: 10.1093/ijpp/riab079. Online ahead of print.

ABSTRACT

OBJECTIVES: The main objective of this study was to assess community pharmacists’ thoughts regarding the role they can play in effectively integrating deprescribing into clinical practice in Ireland. The aim was to assess pharmacists’ (1) knowledge of deprescribing, (2) confidence in deprescribing, (3) attitudes towards deprescribing and (iv) barriers and facilitators to deprescribing in a community pharmacy setting.

METHODS: An online questionnaire was disseminated to pharmacists currently registered with the Pharmaceutical Society of Ireland, with instruction only to complete if working in community pharmacy. Statistical analysis was conducted on the quantitative data, whereas thematic analysis was carried out on the open-ended responses.

KEY FINDINGS: Results indicate good knowledge scores and positive attitudes surrounding deprescribing, with demographic factors having no significant effect on results. Although deprescribing knowledge is high, willingness to engage is hindered by obstacles such as time. Remuneration was identified as an enabler for deprescribing. Interdisciplinary educational opportunities and bidirectional communication channels with prescribers are viewed as the major facilitators of deprescribing.

CONCLUSIONS: Community pharmacists demonstrate that they possess sufficient knowledge, confidence and willingness to play a greater role in facilitating deprescribing. To enable this role expansion, enablers such as education and funding need to be implemented, to overcome barriers such as insufficient time. Further studies are required to assess community pharmacists’ deprescribing competence, to demonstrate their ability to fulfil this role in clinical practice in Ireland.

PMID:34998277 | DOI:10.1093/ijpp/riab079

J Clin Neurosci. 2022 Jan 5;96:74-79. doi: 10.1016/j.jocn.2021.11.037. Online ahead of print.

ABSTRACT

It is challenging to predict neurological outcomes of acute spinal cord injury (SCI) considering issues such as spinal shock and injury heterogeneity. Deep learning-based radiomics (DLR) were developed to quantify the radiographic characteristics automatically using a convolutional neural network (CNN), and to potentially allow the prognostic stratification of patients. We aimed to determine the functional prognosis of patients with cervical SCI using machine learning approach based on MRI and to assess the ability to predict the neurological outcomes. We retrospectively analyzed the medical records of SCI patients (n=215) who had undergone MRI and had an American Spinal cord Injury Association Impairment Scale (AIS) assessment at 1 month after injury, enrolled with a total of 294 MR images. Sagittal T2-weighted MR images were used for the CNN training and validation. The deep learning framework TensorFlow was used to construct the CNN architecture. After we calculated the probability of the AIS grade using the DLR, we built the identification model based upon the random forest using 3 features: the probability of each AIS grade obtained by the DLR method, age, and the initial AIS grade at admission. We performed a statistical evaluation between the actual and predicted AIS. The accuracy, precision, recall and f1 score of the ensemble model based on the DLR and RF were 0.714, 0.590, 0.565 and 0.567, respectively. The present study demonstrates that prediction of the short-term neurological outcomes for acute cervical spinal cord injury based on MRI using machine learning is feasible.

PMID:34998207 | DOI:10.1016/j.jocn.2021.11.037

Comput Biol Med. 2021 Dec 17;141:105148. doi: 10.1016/j.compbiomed.2021.105148. Online ahead of print.

ABSTRACT

Operating rooms are among the most high-risk and vital parts of a hospital. Therefore, one of the most fundamental tasks of risk management is maintaining the safety of operating rooms. Resilience engineering (RE) can be introduced as a model for overcoming problems, and it seeks ways to raise success rates by focusing on and addressing complexities. To this end, an RE-based framework is presented to evaluate the performance of operating rooms. First, the RE indicators are identified, and the relative importance of each is calculated via the best-worst method (BWM). Subsequently, the required data are collected from operating room experts using a standard questionnaire. Next, a data envelopment analysis (DEA) method is employed to evaluate the performance of operating rooms in the study case. Lastly, drawing upon the sensitivity analysis and statistical tests, the effect of each RE indicator is examined on the surgical department. Accordingly, some improvement approaches are proposed. Besides, SWOT (strengths, weaknesses, opportunities, and threats) analysis is used to extract appropriate strategies to improve performance. To the best of our knowledge, this paper is the first to evaluate the performance of operating rooms quantitatively in terms of RE indicators, and the framework presented in this paper can have practical applications in different operating rooms.

PMID:34998085 | DOI:10.1016/j.compbiomed.2021.105148

Neoplasia. 2022 Jan 5;24(2):155-164. doi: 10.1016/j.neo.2021.12.008. Online ahead of print.

ABSTRACT

BACKGROUND: Most ovarian cancer patients are diagnosed at an advanced stage and have a high mortality rate. Current screening strategies fail to improve prognosis because markers that are sensitive for early stage disease are lacking. This medical need justifies the search for novel approaches using utero-tubal lavage as a proximal liquid biopsy.

METHODS: In this study, we explore the extracellular transcriptome of utero-tubal lavage fluid obtained from 26 ovarian cancer patients and 48 controls using messenger RNA (mRNA) capture and small RNA sequencing.

RESULTS: We observed an enrichment of ovarian and fallopian tube specific messenger RNAs in utero-tubal lavage fluid compared to other human biofluids. Over 300 mRNAs and 41 miRNAs were upregulated in ovarian cancer samples compared with controls. Upregulated genes were enriched for genes involved in cell cycle activation and proliferation, hinting at a tumor-derived signal.

CONCLUSION: This is a proof-of-principle that mRNA capture sequencing of utero-tubal lavage fluid is technically feasible, and that the extracellular transcriptome of utero-tubal lavage should be further explored in larger cohorts to assess the diagnostic value of the biomarkers identified in this study.

IMPACT: Proximal liquid biopsy from the gynecologic tract is a promising source for mRNA and miRNA biomarkers for diagnosis of early-stage ovarian cancer.

PMID:34998206 | DOI:10.1016/j.neo.2021.12.008

J Mech Behav Biomed Mater. 2022 Jan 3;126:105071. doi: 10.1016/j.jmbbm.2021.105071. Online ahead of print.

ABSTRACT

The present study was investigated the production dental guides by using additive manufacturing stereolithography (SLA) technology, and the dimensional aperture values of the dental guides for dental implant treatment using artificial intelligence technology. The aim of this study is to benefit from artificial neural networks (ANNs) to classify the results obtained from the new production freedom of SLA by changing the existing design concept of dental guides. In the study, the Three Dimensional (3D) anatomical model was designed by using Mimics programme the data obtained from the Cone Beam Computed Tomography (CBCT) images of the patient. Three different dental guide designs were performed using the 3-Matic programme for dental implant treatment on the obtained 3D anatomical model. Dental guide designs and mandible model were produced with a SLA 3D printer, and a data set was created using a 3D scanner. The dimensional aperture values were obtained by performing the 3D registration process between the mandible and dental guides. The data set was analyzed both statistically with Jamovi 2.0.0 software and ANNs. The results showed that the minimum and maximum aperture values obtained from the dental guides were very close to each other, indicating that the guides were compatible with the mandible bone. The statistical results showed that the dimensional aperture values decrease in proportion to the values with minimum arithmetic mean value in the data set, and it was determined that the dental guide-3 was the most suitable model for the mandible. When all test data in the confusion matrix obtained from ten different aritificial neural network models created using ANNs were examined, it was been seen that ANN model-5 was the most successful model with an accuracy rate of 99%.

PMID:34998070 | DOI:10.1016/j.jmbbm.2021.105071

J Environ Manage. 2022 Jan 5;305:114427. doi: 10.1016/j.jenvman.2021.114427. Online ahead of print.

ABSTRACT

Soil organic carbon (SOC) is a key soil quality indicator, as it is a source and storage of plant nutrients and plays a vital role in soil fertility and productivity maintenance. Intensification of agriculture is known to cause SOC decline; however, much of the evidence stems from field-scale experimental trials. The primary aim of this study is to investigate how more than 20 years of agricultural land use intensification in Bangladesh has influenced SOC levels at landscape levels. This was achieved by revisiting in 2012 four sub-sites from the Brahmaputra and Ganges alluviums which were previously sampled (1989-92) by the Soil Resource Development Institute and collecting 190 new samples. These were located at different elevations and subjected to differing amounts of inundation. The SOC was determined using the same method, potassium dichromate wet oxidation, used in the 1989-92 campaign. A comparison of the SOC in the 2012 samples with their historic levels (1989-92) revealed that overall SOC declined significantly across both alluviums as well at their four sub-sites. Further analysis, however, showed that SOC has declined more at higher sites. The higher sites are inundated to a limited level, which makes them suitable for growing multiple crops. Among the land types considered here, the low land sites (because of their topographical position) remain inundated for a greater part of the year, allowing a maximum of only one crop of submerged rice. As a result of reduced biomass decomposition due to anaerobic conditions when inundated, and lower land use/cropping intensity, SOC accretion has occurred in the lower land sites. The SOC levels in South Asian countries are inherently low and agricultural land use intensification fuelled by growing food production demand is causing further SOC loss, which has the potential to jeopardise food security and increase the environmental impact of agriculture.

PMID:34998063 | DOI:10.1016/j.jenvman.2021.114427

J Mech Behav Biomed Mater. 2022 Jan 1;126:105053. doi: 10.1016/j.jmbbm.2021.105053. Online ahead of print.

ABSTRACT

OBJECTIVES: To investigate the volumetric and vertical loss of occlusal splints manufactured by conventional (heat-cure), subtractive (CAD/CAM) and additive (3D-printing) methods.

METHODS: Six occlusal splint materials were investigated (n = 126), using three manufacturing methods: heat-cured, CAD/CAM and 3D-printed built-in three different printing angles (0°,45°and 90°). Block-on-ring wear testing was performed with extracted human molars as the antagonist. All samples were tested with an applied force of 49N at 1 Hz and 60RPM in artificial saliva at 37 °C for six and 12 months. Scanning electron microscopy images were analysed to evaluate the wear on the tooth enamel and in the splint material. Volumetric and vertical wear loss were statistically analysed.

RESULTS: The lowest volumetric and vertical loss was observed in CAD-CAM materials (6.44 ± 1.77 mm³ and 48.3 ± 7.14 μm) with no statistical significance to the heat-cured material (17.22 ± 9.23 mm³ and 148 ± 121.1 μm) after 12 months (p < 0.172). The mean volumetric loss of 3D printed materials ranged from 0.25 ± 0.15 mm³ to 0.29 ± 0.1 4mm³ with no statistical difference, whereas, the differences in vertical loss from 131.63 ± 44.1 μm to 493 ± 79.19 μm were statistically significant (p < 0.001). The highest vertical loss was observed in the KeySplint Soft 3D printed at 90° (385.35 ± 82.37 μm), whereas FreePrint Splint 2.0 with a build angle of 0° had the highest volumetric loss (204.59 ± 25.67 mm³).

CONCLUSION: CAD-CAM material had the highest wear resistance followed by heat-cured material.KeySplint Soft and FreePrint Splint 2.0 3D printed materials would be preferred for patients that do not have severe bruxing episodes. No significant wear of human enamel after six and 12 months was observed under SEM for any tested materials.

PMID:34998068 | DOI:10.1016/j.jmbbm.2021.105053

Behav Res Ther. 2021 Dec 1;149:104011. doi: 10.1016/j.brat.2021.104011. Online ahead of print.

ABSTRACT

In recent years, network approaches to psychopathology have sparked much debate and have had a significant impact on how mental disorders are perceived in the field of clinical psychology. However, there are many important challenges in moving from theory to empirical research and clinical practice and vice versa. Therefore, in this article, we bring together different points of view on psychological networks by methodologists and clinicians to give a critical overview on these challenges, and to present an agenda for addressing these challenges. In contrast to previous reviews, we especially focus on methodological issues related to temporal networks. This includes topics such as selecting and assessing the quality of the nodes in the network, distinguishing between- and within-person effects in networks, relating items that are measured at different time scales, and dealing with changes in network structures. These issues are not only important for researchers using network models on empirical data, but also for clinicians, who are increasingly likely to encounter (person-specific) networks in the consulting room.

PMID:34998034 | DOI:10.1016/j.brat.2021.104011

Trop Med Int Health. 2022 Jan 8. doi: 10.1111/tmi.13718. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the impact of meningococcal C conjugate (MCC) vaccine in Brazil.

METHODS: Ecological study assessing all invasive meningococcal disease (IMD) and meningococcal C disease (MenC) cases reported in all age groups, from 2001 to 2019. MCC was implemented in 2010. Data were collected on the DATASUS platform. Joinpoint regression was performed to assess the Annual Percent Change (APC) of the incidence rate.

RESULTS: IMD incidence decreased in all Brazilian regions from 2001 onwards, without apparent additional reduction attributable to MCC vaccine in the North, Northeast and South. The higher and statistically significant APC reduction in all age groups, in the North and South, and in children <5 years, in the Northeast, occurred between 2001-2011 (-15.4%), 2004-2012 (-14.4%), and 2001-2013 (-10.3%), respectively, before MCC vaccine implementation. Annual incidence of MenC in under 5 years significantly fell in the North (-6.8%; 2011-2018), Southeast (-40.6%; 2010-2015) and Midwest (-48.6%; 2010-2014), which may be attributable to MCC implementation.

CONCLUSION: IMD and MenC behaved differently after MCC vaccine implementation in Brazil during this 18-year time-series analysis. This suggests that the control of IMD should be based on multiple public health care measures and considered on a regional basis.

PMID:34997999 | DOI:10.1111/tmi.13718