Tag: statistics

BMC Nurs. 2022 Dec 30;21(1):375. doi: 10.1186/s12912-022-01165-w.

ABSTRACT

BACKGROUND: Standard precautions are minimum infection control practices used to prevent the transmission of diseases and applied to all patient care. Nursing students are at high risk of exposure to occupational biologic hazards because they are obligated to provide care to patients admitted with unknown infection statuses. Compliance with standard precautions is an effective and efficient means of infection prevention. However, their compliance with standard precautions among nursing students is not known in Ethiopia. Therefore, this study aimed to assess compliance with standard precautions and associated factors among undergraduate BSc nursing students at governmental universities located in the Amhara Region, northwest Ethiopia.

METHODS: An institutional-based cross-sectional study was conducted among undergraduate BSc nursing students at the governmental universities located in Amhara Region, northwest Ethiopia, from April 15 to May 15, 2021. A simple random sampling technique was used to select 423 samples. Descriptive statistics were presented in text, tables, and charts. Multicollinearity and model fitness were checked. All variables were entered into multivariable logistic regression and a P-value of < 0.05 was considered to identify statistically significant factors.

RESULT: Around 221 (53.4%) of the study participants were males. Good compliance of nursing students towards standard precautions was 56.3% (95% CI = 51.4-60.9), which is significantly associated with good knowledge (AOR = 2.52, 95% CI = 1.61-3.94), a perceived safe workplace climate (AOR = 2.15, 95% CI = 1.24-3.71), and training or seminars related to standard precautions in the last six months (AOR = 1.52, 95% CI = 1.01-2.29).

CONCLUSION: The overall compliance of nursing students with standard precautions was low, with nearly half of the nursing students failing to comply with standard precautions. The major factors associated with good compliance were good knowledge, a perceived safe workplace, and having seminars or training in the last six months. Training, enhancing knowledge, and creating a safe hospital environment are recommended to improve nursing students’ compliance with standard precautions.

PMID:36581879 | DOI:10.1186/s12912-022-01165-w

Alzheimers Res Ther. 2022 Dec 29;14(1):198. doi: 10.1186/s13195-022-01151-z.

ABSTRACT

BACKGROUND: Efavirenz is an anti-HIV drug, and cytochrome P450 46A1 (CYP46A1) is a CNS-specific enzyme that metabolizes cholesterol to 24-hydroxycholesterol (24HC). We have previously shown that allosteric CYP46A1 activation by low-dose efavirenz in a transgenic mouse model of Alzheimer’s disease (AD) enhanced both cholesterol elimination and turnover in the brain and improved animal performance in memory tests. Here, we sought to determine whether CYP46A1 could be similarly activated by a low-dose efavirenz in human subjects. METHODS: This pilot study enrolled 5 subjects with early AD. Participants were randomized to placebo (n = 1) or two daily efavirenz doses (50 mg and 200 mg, n = 2 for each) for 20 weeks and evaluated for safety and CYP46A1 target engagement (plasma 24HC levels). A longitudinal mixed model was used to ascertain the statistical significance of target engagement. We also measured 24HC in CSF and conducted a unique stable isotope labeling kinetics (SILK) study with deuterated water to directly measure CYP46A1 activity changes in the brain.

RESULTS: In subjects receiving efavirenz, there was a statistically significant within-group increase (P ≤ 0.001) in the levels of plasma 24HC from baseline. The levels of 24HC in the CSF of subjects on the 200-mg dose of efavirenz were also increased. Target engagement was further supported by the labeling kinetics of 24HC by deuterated water in the SILK study. There were no serious adverse effects in any subjects.

CONCLUSIONS: Our findings suggest efavirenz target engagement in human subjects with early AD. This supports the pursuit of a larger trial for further determination and confirmation of the efavirenz dose that exerts maximal enzyme activation, as well as evaluation of this drug’s effects on AD biomarkers and clinical symptomatology.

TRIAL REGISTRATION: ClinicalTrials.gov, NCT03706885.

PMID:36581878 | DOI:10.1186/s13195-022-01151-z

Trials. 2022 Dec 30;23(1):1067. doi: 10.1186/s13063-022-07042-w.

ABSTRACT

BACKGROUND: Preoperative carbohydrates (CHO) supplement has been widely investigated in nondiabetic patients undergoing a variety of surgeries. It has been proved that preoperative CHO could alleviate postoperative insulin resistance (IR) and improve patients’ well-being in nondiabetic patients. However, it remains controversial whether preoperative CHO could yield similar effects in diabetic patients. Till now, seldom has the administration of preoperative CHO been investigated in diabetic patients and there are limited studies reporting IR and postoperative recovery of diabetic patients undergoing cardiac surgery.

METHODS AND ANALYSIS: We present a prospective, single-center, single-blind, randomized, no-treatment controlled trial of preoperative CHO on diabetic patients undergoing off-pump coronary artery bypass grafting (OPCAB). A total of 62 patients will be enrolled and randomized to either Group CHO or Group control (CTRL). Patients in Group CHO will consume CHO fluid containing 50 g carbohydrates orally the evening before surgery (20:00-24:00) while their counterparts in Group CTRL will be fasted after 20:00 the evening before surgery. The primary endpoint is postoperative IR assessed via homeostasis model assessment (HOMA). The secondary endpoints are postoperative levels of potential mediators relating to IR including inflammatory factors and stress reaction characterized by serum cortisol. Exploratory endpoints are in-hospital clinical endpoints. Continuous variables will be compared by Student’s t-test or Mann-Whitney U test. Categorical variables will be compared with χ² test or Fisher’s exact test. All tests in the present study are two-tailed and P<0.05 is considered statistically significant. All analyses will be performed with R 4.0.4.

DISCUSSION: This is the first prospective randomized controlled trial of preoperative CHO in diabetic patients undergoing cardiac surgery, with the hypothesis that preoperative CHO could improve postoperative IR and promote postoperative recovery. The research may assist in improving the clinical outcomes of diabetic patients undergoing OPCAB.

TRIAL REGISTRATION: The trial has been prospectively registered with ClinicalTrials.gov ( https://register.

CLINICALTRIALS: gov ) and Chinese Clinical Trial Registry ( http://www.chictr.org.cn ). Registry number is NCT05540249 and ChiCTR2000029664 respectively. Registered on Sept. 14, 2022.

CLINICAL TRIALS UNIT: Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.

PMID:36581874 | DOI:10.1186/s13063-022-07042-w

BMC Neurol. 2022 Dec 29;22(1):505. doi: 10.1186/s12883-022-03027-z.

ABSTRACT

BACKGROUND: Community-based exercise is a continuation and complement to inpatient rehabilitation for Parkinson’s disease and does not require a professional physical therapist or equipment. The effects, parameters, and forms of each exercise are diverse, and the effect is affected by many factors. A meta-analysis was conducted to determine the effect and the best parameters for improving motor symptoms and to explore the possible factors affecting the effect of community-based exercise. METHODS: We conducted a comprehensive search of six databases: PEDro, PubMed/Medline, CENTRAL, Scopus, Embase, and WOS. Studies that compared community-based exercise with usual care were included. The intervention mainly included dance, Chinese martial arts, Nordic walking, and home-based exercise. The primary outcome measure was the Unified Parkinson’s Disease Rating Scale part III (UPDRS-III) score. The mean difference (95% CI) was used to calculate the treatment outcomes of continuous outcome variables, and the I² statistic was used to estimate the heterogeneity of the statistical analysis. We conducted subgroup analysis and meta-regression analysis to determine the optimal parameters and the most important influencing factors of the exercise effect. RESULTS: Twenty-two studies that enrolled a total of 809 subjects were included in the analysis. Exercise had a positive effect on the UPDRS-III (MD = -5.83; 95% CI, -8.29 to -3.37), Timed Up and Go test (MD = -2.22; 95% CI -3.02 to -1.42), UPDRS ((MD = -7.80; 95% CI -10.98 to -6.42), 6-Minute Walk Test (MD = 68.81; 95% CI, 32.14 to 105.48), and Berg Balance Scale (MD = 4.52; 95% CI, 2.72 to 5.78) scores. However, the heterogeneity of each included study was obvious. Weekly frequency, age, and duration of treatment were all factors that potentially influenced the effect.

CONCLUSIONS: This meta-analysis suggests that community-based exercise may benefit motor function in patients with PD. The most commonly used modalities of exercise were tango and tai chi, and the most common prescription was 60 min twice a week. Future studies should consider the influence of age, duration of treatment, and weekly frequency on the effect of exercise.

PROSPERO TRIAL REGISTRATION NUMBER: CRD42022327162.

PMID:36581847 | DOI:10.1186/s12883-022-03027-z

BMC Health Serv Res. 2022 Dec 29;22(1):1593. doi: 10.1186/s12913-022-08915-1.

ABSTRACT

BACKGROUND: Pragmatic primary care trials aim to test interventions in “real world” health care settings, but clinics willing and able to participate in trials may not be representative of typical clinics. This analysis compared patients in participating and non-participating clinics from the same health systems at baseline in the PRimary care Opioid Use Disorders treatment (PROUD) trial.

METHODS: This observational analysis relied on secondary electronic health record and administrative claims data in 5 of 6 health systems in the PROUD trial. The sample included patients 16-90 years at an eligible primary care visit in the 3 years before randomization. Each system contributed 2 randomized PROUD trial clinics and 4 similarly sized non-trial clinics. We summarized patient characteristics in trial and non-trial clinics in the 2 years before randomization (“baseline”). Using mixed-effect regression models, we compared trial and non-trial clinics on a baseline measure of the primary trial outcome (clinic-level patient-years of opioid use disorder (OUD) treatment, scaled per 10,000 primary care patients seen) and a baseline measure of the secondary trial outcome (patient-level days of acute care utilization among patients with OUD).

RESULTS: Patients were generally similar between the 10 trial clinics (n = 248,436) and 20 non-trial clinics (n = 341,130), although trial clinics’ patients were slightly younger, more likely to be Hispanic/Latinx, less likely to be white, more likely to have Medicaid/subsidized insurance, and lived in less wealthy neighborhoods. Baseline outcomes did not differ between trial and non-trial clinics: trial clinics had 1.0 more patient-year of OUD treatment per 10,000 patients (95% CI: – 2.9, 5.0) and a 4% higher rate of days of acute care utilization than non-trial clinics (rate ratio: 1.04; 95% CI: 0.76, 1.42).

CONCLUSIONS: trial clinics and non-trial clinics were similar regarding most measured patient characteristics, and no differences were observed in baseline measures of trial primary and secondary outcomes. These findings suggest trial clinics were representative of comparably sized clinics within the same health systems. Although results do not reflect generalizability more broadly, this study illustrates an approach to assess representativeness of clinics in future pragmatic primary care trials.

PMID:36581845 | DOI:10.1186/s12913-022-08915-1

BMC Med Educ. 2022 Dec 29;22(1):903. doi: 10.1186/s12909-022-03961-z.

ABSTRACT

BACKGROUND: The UK academic foundation programme (AFP) is a competitive programme for medical graduates and forms the initial stage of the integrated clinical academic pathway. The application is complex and targeted education is beneficial. As online technologies improve, virtual medical education is becoming more common. Currently, webinar education, particularly that of webinar series, are poorly evidenced. An online course was created to investigate the acceptability and effectiveness of webinars for medical education.

METHODS: A six-part, one-hour sessional webinar course was developed following a focus group with academic foundation doctors. A pre- and post-course cross-sectional questionnaire study evaluated participant demographics, webinar opinion and self-rated understanding of the AFP via Google Form (Google, USA). Where applicable a five-point Likert scale (1-Strongly disagree to 5-strongly agree) was utilised and analysis using non-parametric paired statistical analysis.

RESULTS: Medical students (n=303) from 35 UK universities completed the pre-course questionnaire. Most students had not received targeted education on the AFP. They rated webinars useful for education (mean=4.2 s.d. 0.7). After the course, participants (n=66) expressed it was significantly convenient (mean=4.7), effective (mean=4.7) and suitably interactive (mean=4.4) (p<0.001 compared to neutral). Participants preferred short sessions over multiple days to the concept of a full-day event (mean=4.6 vs 3.1, p<0.001). Paired analysis of participants completing both forms (n=47) demonstrates a significant increase in self-rated understanding of AFP content, portfolio building, application process, acute clinical scenarios, interview technique and overall confidence in acquiring an AFP post (p<0.001). Follow-up identified 43 participants who completed the course were successful in their AFP application. This represents 7.8% of all successful AFP applicants in 2021.

CONCLUSIONS: This study evidences an accessible and effective webinar series for AFP education. Comprehensive webinar courses for similar topics and demographics may provide valuable utility in the provision of future medical education.

TRIAL REGISTRATION: Ethics requirements were waived for this study by Bristol University Ethics Committee. All participants in this study consented for anonymous use of their data. As such the trial is not registered.

PMID:36581834 | DOI:10.1186/s12909-022-03961-z

BMC Public Health. 2022 Dec 29;22(1):2453. doi: 10.1186/s12889-022-14657-w.

ABSTRACT

BACKGROUND: Public health dashboards have been used in the past to communicate and guide local responses to outbreaks, epidemics, and a host of various health conditions. During the first year of the COVID-19 pandemic, dashboards proliferated but the availability and quality differed across the world. This study aimed to evaluate the quality, access, and end-user experience of one such dashboard in the Western Cape province, South Africa.

METHODS: We analysed retrospective aggregate data on viewership over time for the first year since launch of the dashboard (30 April 2020 – 29 April 2021) and conducted a cross-sectional survey targeting adult users of the dashboard at one year post the initial launch. The self-administered, anonymous questionnaire with a total of 13 questions was made available via an online digital survey tool for a 2-week period (6 May 2021 – 21 May 2021).

RESULTS: After significant communication by senior provincial political leaders, adequate media coverage and two waves of COVID-19 the Western Cape public COVID-19 dashboard attracted a total of 2,248,456 views during its first year. The majority of these views came from Africa/South Africa with higher median daily views during COVID-19 wave periods. A total of 794 participants responded to the survey questionnaire. Reported devices used to access the dashboard differed statistically between occupational status groups with students tending toward using mobile devices whilst employed and retired participants tending toward using desktop computers/laptops. Frequency of use increases with increasing age with 65.1% of those > 70 years old viewing it daily. Overall, 76.4% of respondents reported that the dashboard influenced their personal planning and behaviour. High Likert score ratings were given for clarity, ease of use and overall end-user experience, with no differences seen across the various age groups surveyed.

CONCLUSION: The study demonstrated that both the availability of data and an understanding of end-user need is critical when developing and delivering public health tools that may ultimately garner public trust and influence individual behaviour.

PMID:36581823 | DOI:10.1186/s12889-022-14657-w

BMC Bioinformatics. 2022 Dec 29;23(1):564. doi: 10.1186/s12859-022-05119-6.

ABSTRACT

BACKGROUND: Identifying drug-target interactions (DTIs) plays a key role in drug development. Traditional wet experiments to identify DTIs are expensive and time consuming. Effective computational methods to predict DTIs are useful to narrow the searching scope of potential drugs and speed up the process of drug discovery. There are a variety of non-negativity matrix factorization based methods to predict DTIs, but the convergence of the algorithms used in the matrix factorization are often overlooked and the results can be further improved.

RESULTS: In order to predict DTIs more accurately and quickly, we propose an alternating direction algorithm to solve graph regularized non-negative matrix factorization with prior knowledge consistency constraint (ADA-GRMFC). Based on known DTIs, drug chemical structures and target sequences, ADA-GRMFC at first constructs a DTI matrix, a drug similarity matrix and a target similarity matrix. Then DTI prediction is modeled as the non-negative factorization of the DTI matrix with graph dual regularization terms and a prior knowledge consistency constraint. The graph dual regularization terms are used to integrate the information from the drug similarity matrix and the target similarity matrix, and the prior knowledge consistency constraint is used to ensure the matrix decomposition result should be consistent with the prior knowledge of known DTIs. Finally, an alternating direction algorithm is used to solve the matrix factorization. Furthermore, we prove that the algorithm can converge to a stationary point. Extensive experimental results of 10-fold cross-validation show that ADA-GRMFC has better performance than other state-of-the-art methods. In the case study, ADA-GRMFC is also used to predict the targets interacting with the drug olanzapine, and all of the 10 highest-scoring targets have been accurately predicted. In predicting drug interactions with target estrogen receptors alpha, 17 of the 20 highest-scoring drugs have been validated.

PMID:36581822 | DOI:10.1186/s12859-022-05119-6

Proc Natl Acad Sci U S A. 2023 Jan 3;120(1):e2214423119. doi: 10.1073/pnas.2214423119. Epub 2022 Dec 29.

NO ABSTRACT

PMID:36580595 | DOI:10.1073/pnas.2214423119

Proc Natl Acad Sci U S A. 2023 Jan 3;120(1):e2214972120. doi: 10.1073/pnas.2214972120. Epub 2022 Dec 29.

ABSTRACT

Regression learning is one of the long-standing problems in statistics, machine learning, and deep learning (DL). We show that writing this problem as a probabilistic expectation over (unknown) feature probabilities – thus increasing the number of unknown parameters and seemingly making the problem more complex-actually leads to its simplification, and allows incorporating the physical principle of entropy maximization. It helps decompose a very general setting of this learning problem (including discretization, feature selection, and learning multiple piece-wise linear regressions) into an iterative sequence of simple substeps, which are either analytically solvable or cheaply computable through an efficient second-order numerical solver with a sublinear cost scaling. This leads to the computationally cheap and robust non-DL second-order Sparse Probabilistic Approximation for Regression Task Analysis (SPARTAn) algorithm, that can be efficiently applied to problems with millions of feature dimensions on a commodity laptop, when the state-of-the-art learning tools would require supercomputers. SPARTAn is compared to a range of commonly used regression learning tools on synthetic problems and on the prediction of the El Niño Southern Oscillation, the dominant interannual mode of tropical climate variability. The obtained SPARTAn learners provide more predictive, sparse, and physically explainable data descriptions, clearly discerning the important role of ocean temperature variability at the thermocline in the equatorial Pacific. SPARTAn provides an easily interpretable description of the timescales by which these thermocline temperature features evolve and eventually express at the surface, thereby enabling enhanced predictability of the key drivers of the interannual climate.

PMID:36580592 | DOI:10.1073/pnas.2214972120