Tag: pubmed

Comput Methods Programs Biomed. 2021 Nov 6;213:106509. doi: 10.1016/j.cmpb.2021.106509. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: The schizophrenia diagnosis represents a difficult task because of the confusing descriptions of symptoms given by the patient, their similarity among several disorders, the lower familiarity with genetic predisposition, and the probably inadequate response to the treatment. Neuro-biological markers of schizophrenia, as a quantitative relationship between the psychiatrist’s reports and the biology of the brain, could be used. Functional Magnetic Resonance Imaging (fMRI) obtain the subject’s performance in cognitive tasks and may find significant differences between the patient’s data and controls. The input data of classifiers may imply alterations in diagnosis; therefore, it is essential to ensure an adequate representation to describe the entire dataset classified.

METHODS: We propose a supervoxels-based representation calculated by two main steps: the short-range connectivity, supervoxels’ generation using a Fuzzy Iterative Clustering algorithm, and the long-range connectivity, employing Detrended Cross-Correlation Analysis among supervoxels. The unrelated supervoxels, through a statistical test based on critical points calculated empirically, are removed. The remainder supervoxels are the input for feature selectors to extract the discriminative supervoxels. We implement support vector machine classifiers using the correlation coefficient of the significant supervoxels. The dataset of 1.5 Tesla was downloaded from the SchizConnect site, where the fMRI data, during an auditory oddball task, was acquired. We calculate the performance of the classifiers using a leave-one-out cross-validation and compute the area under the Receiver Operating Characteristic curve and a permutation test to ensure no bias in the classifiers.

RESULTS: According to the permutation test, with p-values less than the significance level of 0.05, the classifiers extract discriminative class structure from data where no bias is shown. Our supervoxels-based representation gets the maximum values of sensitivity, specificity, and accuracy of 92.9%, 100%, and 96.4%, respectively. The discriminative brain regions, to discern among patients and controls, are extracted; these regions also are mentioned by the related works.

CONCLUSIONS: The proposed representation, based on supervoxels, is a data-driven model that does not use predefined models of the signal nor pre-relocated brain regions of interest. The results are competitive against the related works, and the relevant supervoxels are related to the schizophrenia diagnosis.

PMID:34800805 | DOI:10.1016/j.cmpb.2021.106509

J Surg Res. 2021 Nov 17;270:471-476. doi: 10.1016/j.jss.2021.10.007. Online ahead of print.

ABSTRACT

BACKGROUND: Pandemic related changes have radically altered the delivery of medical teaching. The practical skills of medicine which students should be proficient in at time of graduation have tended to require in-person tutelage, with reduced access resulting in the risk of skill deficits in newly qualified doctors. Small group teaching sessions are amenable to a virtual mode of delivery, with the ability of the virtual platform to confer practical skills unproven. The objective of the study was to evaluate the use of teleproctoring in acquisition of suturing skills in medical students.

METHODS: This was a single blinded two- armed randomized control trial. Medical students undergoing clinical rotations in their penultimate and final years who were able to complete the suturing tutorial were invited to participate in this study. Control groups underwent conventional suturing training under direct supervision, with the interventional group undergoing the tutorial in a remote learning setting via live streaming. Pre- and post-test assessment was carried out using validated suturing Global Rating Scale tool.

RESULTS: A total of 24 participants were recruited, with 23 participants completing the task. Adequacy of sampling was demonstrated in both groups using Box’s M test (P = 0.9). Participants’ individual and composite scores were comparable at baseline (P = 0.28) and following the tutorial (P = 0.52). Participants improved to a statistically significant degree regardless of method of teaching delivery, in all skill parameters (P < 0.001).

CONCLUSIONS: Teleproctoring is an effective tool in the provision of teaching basic suturing skills in medical students. Research on its use in more complex practical skills is warranted.

PMID:34800793 | DOI:10.1016/j.jss.2021.10.007

J Equine Vet Sci. 2021 Oct 14;108:103794. doi: 10.1016/j.jevs.2021.103794. Online ahead of print.

ABSTRACT

Analysis of the cerebrospinal fluid (CSF) is important as a complementary test in horses with neurologic diseases, and sequential analysis may provide information about the treatment response or evolution and quantitative measures of the CSF drug concentration during treatment. The aim of this study was to compare erythrocyte and nucleated cell counts and protein concentration in multiple CSF samples obtained sequentially from two different puncture sites in clinically healthy horses. Eight and 12 horses, with no evidence of neurologic disease, were subjected to CSF collection from the atlanto-occipital (AO) and C1-C2 spaces, respectively. Cytologic and chemical analyses were performed on the CSF obtained at five sampling times (T1, T2, T3, T4, and T5). Repeated measures models were used to compare the mean erythrocyte count, nucleated cell count, and total protein concentration between the AO and C1-C2 groups at each sampling time. C1-C2 CSF had a significantly higher total protein concentration at T1 and T4 than that of AO CSF. All total protein concentration values remained within the reference interval (<90 mg/dL) for all sampling times and groups. No statistical difference was present between results at T2, T3, T4, and T5 and at T1 in both groups for all analyses. In conclusion, five consecutive AO or C1-C2 CSF collections with at least a 7-d interval did not result in alterations in the CSF erythrocyte and nucleated cell counts and total protein concentrations and did not interfere with the CSF analysis results.

PMID:34800797 | DOI:10.1016/j.jevs.2021.103794

J Environ Manage. 2021 Nov 11;302(Pt B):114085. doi: 10.1016/j.jenvman.2021.114085. Online ahead of print.

ABSTRACT

The coronavirus disease 2019 (COVID-19) has been first reported in December 2019 and rapidly spread worldwide. As other severe acute respiratory syndromes, it is a widely discussed topic whether seasonality affects the COVID-19 infection spreading. This study presents two different approaches to analyse the impact of social activity factors and weather variables on daily COVID-19 cases at county level over the Continental U.S. (CONUS). The first one is a traditional statistical method, i.e., Pearson correlation coefficient, whereas the second one is a machine learning algorithm, i.e., random forest regression model. The Pearson correlation is analysed to roughly test the relationship between COVID-19 cases and the weather variables or the social activity factor (i.e. social distance index). The random forest regression model investigates the feasibility of estimating the number of county-level daily confirmed COVID-19 cases by using different combinations of eight factors (county population, county population density, county social distance index, air temperature, specific humidity, shortwave radiation, precipitation, and wind speed). Results show that the number of daily confirmed COVID-19 cases is weakly correlated with the social distance index, air temperature and specific humidity through the Pearson correlation method. The random forest model shows that the estimation of COVID-19 cases is more accurate with adding weather variables as input data. Specifically, the most important factors for estimating daily COVID-19 cases are the population and population density, followed by the social distance index and the five weather variables, with temperature and specific humidity being more critical than shortwave radiation, wind speed, and precipitation. The validation process shows that the general values of correlation coefficients between the daily COVID-19 cases estimated by the random forest model and the observed ones are around 0.85.

PMID:34800764 | DOI:10.1016/j.jenvman.2021.114085

Gynecol Obstet Fertil Senol. 2021 Nov 17:S2468-7189(21)00305-6. doi: 10.1016/j.gofs.2021.11.004. Online ahead of print.

ABSTRACT

OBJECTIVE: The prediction model M6 classifies pregnancy of unknown location (PUL) into a lor-risk or a high-risk group in developing ectopic pregnancy (EP). The aim of this study was to validate the two step M6 model’s ability to classify PUL in French women.

MATERIAL AND METHODS: All women with a diagnosis of PUL over a year were included in this single center retrospective study. Patients with a diagnosis of EP at the first consultation of with incomplete data were excluded. For each patient, the M6 model calculator was used to classified them into “high risk of EP” and “low risk of EP” group. The reference standard was the final diagnostic: failed PUL (FPUL), intrauterine pregnancy (IUP) of EP. The statistical measures of the test’s performance were calculated.

RESULTS: Over the period, 255 womens consulted for a PUL, 197 has been included in the study. Final diagnosis were: 94 FPUL (94/197 ; 47,7%), 74 IUP (74/197 ; 37,6%) et 29 EP (29/197 ; 14,7%). The first step of the M6 model classified 16 women in the FPUL group of which 15 (15/16; 93,7%) correctly. The second step of the M6 model classified 181 women: 90 (90/181; 49,7%) in the “high risk of EP” group of which 63 (63/90; 70%) were FPUL/IUP and 27 (27/90; 30%) were EP. 91 (91/181; 50,3%) was classified in the “low risk of EP” group of which 90 (90/91; 98,9%) were FPUL/IUP and 1 (1/91; 1,1%) were EP. EP were correctly classified with sensitivity of 96,4%, negative predictive value of 98,9%, specificity of 58,8% and positive predictive value of 30,0 %.

CONCLUSIONS: The prediction model of PUL M6 classified EP in “high risk of EP group” with a sensitivity of 96,4%. It classified 50,3% of PUL in a “low risk of EP” group with a negative predictive value of 98,9%.

PMID:34800739 | DOI:10.1016/j.gofs.2021.11.004

Asian J Psychiatr. 2021 Nov 5;67:102919. doi: 10.1016/j.ajp.2021.102919. Online ahead of print.

ABSTRACT

The purpose of this study was to identify the attitude of South Korean medical school students towards psychiatry and to analyze how lectures and clinical clerkship in psychiatry effect changes in students’ attitudes. A total of 100 medical school students were recruited as subjects in the study, 86 of whom completed psychiatry lectures and underwent psychiatry clerkship from March 2015 to August 2018. The participating students completed a survey, which included demographic data, specialty choice, and attitude towards psychiatry. Subjects who completed lectures and clinical clerkship in psychiatry showed positive changes in attitude towards psychiatry in the following items: “Among mental health professionals, psychiatrists have the most authority and influence” (p = 0.002), “Psychiatrists frequently abuse their legal power to hospitalize patients against their will” (p < 0.001), and “Many people who could not obtain a residency position in other specialties eventually enter psychiatry” (p = 0.028). However, negative changes in attitude towards psychiatry were shown in the following item: “On average, psychiatrists make as much money as most other doctors” (p = 0.008). Also, specific medical school factors scored positively overall. Although it was not statistically significant, the questionnaire item “During my psychiatry rotation, psychiatry residents were good role models” was more positively observed by students after completion of psychiatry lectures and clerkship. After each curriculum, certain attitudes toward psychiatry were positively changed, but others either remained unchanged or were negatively changed. By using these study results to revise the current curriculum, medical school students’ attitude towards psychiatry can be improved.

PMID:34800754 | DOI:10.1016/j.ajp.2021.102919

Ann Hepatol. 2021 Nov 17:100556. doi: 10.1016/j.aohep.2021.100556. Online ahead of print.

ABSTRACT

INTRODUCTION AND OBJECTIVES: Cause of mortality in patients with chronic liver diseases (CLDs) may differ based on underlying etiology of liver disease. Our aim was to assess different causes of death in patients with the most common types of CLD using a national database from the United States.

MATERIALS AND METHODS: Death data from 2008 and 2018 from the National Vital Statistics System (NVSS) by the National Center for Health Statistics (NCHS) were used. The rank of cause-of-death for each etiology of CLDs was assessed. Causes of death were classified by the ICD-10 codes. Liver-related deaths included liver cancer, cirrhosis and CLDs.

RESULTS: Among a total of 2,826,531 deaths in 2018, there were 85,807 (3.04%) with underlying CLD (mean age at death 63.0 years, 63.8% male, 70.8% white). Liver-related mortality was the leading cause of death for all types of CLD [45.8% in non-alcoholic fatty liver disease (NAFLD), 53.0% in chronic hepatitis C (CHC), 57.8% in chronic hepatitis B (CHB), 81.8% in alcoholic liver disease (ALD)]. This was followed by death from cardiac causes (NAFLD 10.3%, CHC 9.1%, CHB 4.6%, ALD 4.2%) and extrahepatic cancer (NAFLD 7.0%, CHC 11.9%, CHB 14.9%, ALD 2.1%). Although liver cancer was the leading cause of cancer death, lung, colorectal and pancreatic cancer were also common causes of cancer death.

CONCLUSIONS: Among deceased patients with CLD, underlying liver disease was the leading cause of death. Among solid cancers, liver cancer was the leading cause of cancer-related mortality.

PMID:34800721 | DOI:10.1016/j.aohep.2021.100556

World Neurosurg. 2021 Nov 17:S1878-8750(21)01748-4. doi: 10.1016/j.wneu.2021.11.045. Online ahead of print.

ABSTRACT

OBJECTIVE: The treatment of multiple intracranial aneurysms (MIAs) involves various modalities and sometimes requires staged operations. This study aimed to prove the efficacy and safety of one-stage multiple craniotomies (OSMC) for multiple cerebral aneurysms.

METHODS: We retrospectively reviewed the medical records of the patients who underwent treatment for intracranial aneurysms between May 2003 and April 2020. The surgical results, complications, and lengths of hospital stay were compared between the patients who underwent OSMC and those who underwent multi-stage multiple craniotomies (MSMC).

RESULTS: The demographic characteristics of the OSMC and MSMC groups (n=82 and 43, respectively) were similar. There were no statistically significant differences between the two groups when the amount of blood transfused, complications, and surgical results were compared (p=n.s. for all); however, the operation time and hospitalization period (353.9 min vs. 490.3 min and 12.3 days vs. 21.8 days, respectively; p=0.001 for both) were shorter in the OSMC group. The treatment cost (17,000 USD vs. 22,000 USD, p=0.001) was lower in the OSMC group.

CONCLUSIONS: OSMC for aneurysm clipping in patients with MIAs is a relatively safe and economical method. Furthermore, it has good clinical outcomes. This new surgical method is worthwhile in that it can be applied to patients who are afraid to undergo multiple surgeries, and we suggest it is an efficient, low-cost option for the treatment of MIAs.

PMID:34800734 | DOI:10.1016/j.wneu.2021.11.045

J Acad Nutr Diet. 2021 Nov 17:S2212-2672(21)01470-2. doi: 10.1016/j.jand.2021.11.008. Online ahead of print.

ABSTRACT

BACKGROUND: Evening eating has been associated with higher energy intake and lower nutrient density. However, these qualities may not characterize all late evening (LE) eating patterns.

OBJECTIVE: We sought to characterize U.S. adults’ LE eating patterns on a given day and identify differences, if any, in pattern-specific associations with, and impact on, daily energy intake and total diet quality.

DESIGN: LE eating patterns, energy intakes, and HEI scores were identified using Day-1 dietary recall data from the cross-sectional National Health and Nutrition Examination Survey 2013-2016.

PARTICIPANTS/SETTING: The sample included adults age ≥20 years (n=9,861). “LE reporters” were respondents who consumed foods/beverages between 20:00 h and 23:59 h on the intake day.

MAIN OUTCOME MEASURES: Energy intake and HEI-2015 scores by LE status/pattern and the impact of LE consumption on these measures.

STATISTICAL ANALYSES: Cluster analysis assigned individuals to LE eating patterns based on the LE energy contribution of food/beverage groups. Regression models estimated energy intake and HEI-2015 scores; estimates were compared between LE reporters and non-reporters. Similarly, LE’s contribution to total energy and the difference in total HEI inclusive versus exclusive of LE consumption were estimated and compared among patterns.

RESULTS: Among U.S adults, 64.4% were LE reporters. Eleven LE patterns were identified; the six most prevalent patterns (representing 89% of LE reporters) were further analyzed. Daily energy intake in all prevalent patterns except the fruit pattern exceeded that of non-reporters by ≥268 kcal (unadjusted; p<0.001), varying by pattern. Conversely, total HEI score did not differ from that of non-reporters (51.0) in any pattern except the fruit pattern, where it was higher (57.4, unadjusted; p<0.001). Generally, LE consumption’s impact on energy was high and its impact on HEI scores was low.

CONCLUSIONS: Late evening food/beverage consumption is common among U.S. adults, and LE patterns are not monolithic in their associations with, and impact on, total energy intake and dietary quality.

PMID:34800696 | DOI:10.1016/j.jand.2021.11.008

Infect Genet Evol. 2021 Nov 17:105143. doi: 10.1016/j.meegid.2021.105143. Online ahead of print.

ABSTRACT

North Central Nigeria is one region in Nigeria with a significant incidence of malaria caused majorly by Plasmodium falciparum. This study utilizes the msp1 and msp2 genes of P. falciparum to examine its diversity and multiplicity of infection (MOI). Blood samples were collected from 247 children across selected healthcare facilities in Minna, from infants and children aged 6 months to 17 years. Of the total collection, 143 (58%) of the children were infected with P. falciparum with parasite density ≥ 1000 μl, and from which fifty (50) samples was randomly selected and presented for PCR for the characterization of msp1 and msp2 gene using nested-PCR method. Overall, 57 msp1 genotypes, including K1, MAD20 and RO33 were identified, ranging from (250-1000 bp), (100-500 bp) and (400-500 bp), respectively. In addition, 54 different msp2 genotypes of FC27 and 3D7 alleles ranging from (100-900 bp) and (100-800 bp), respectively were selected. A monoclonal infection of 39% and a polyclonal infection of 61% was recorded, however, a particularity about this study is the polyclonal nature of RO33. Determination of gene diversity revealed MAD20 as the predominant allele for msp1 with a mean MOI of 1.35 and FC27 for msp2 with 1.72 MOI. The overall MOI recorded for the study was 1.60. There was, however, no statistical significance difference between MOI and age of the child (P > 0.05). Meanwhile, findings from this study revealed P. falciparum populations were not genetically diverse with Heterozygosity (He) index of 0.0636. However, a significant level gene diversity within the antigenic markers of msp1 and msp2 was observed with He index of 0.714 and 0.830, respectively. This study has demonstrated the potential of gene diversity and MOI of P. falciparum, as important markers for assessing differences in malaria transmission intensity. Continuous malaria genetic surveillance is therefore recommended as a fundamental tool for monitoring changes in gene types and for intervention programs’ effectiveness.

PMID:34800712 | DOI:10.1016/j.meegid.2021.105143