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Nevin Manimala Statistics

Corneal densitometry patterns in Descemet membrane endothelial keratoplasty and Descemet stripping automated keratoplasty

Int Ophthalmol. 2021 Mar 24. doi: 10.1007/s10792-021-01817-x. Online ahead of print.

ABSTRACT

PURPOSE: To compare corneal densitometry in a consecutive series of 52 endothelial keratoplasties (DMEK/DSAEK) using a Scheimpflug-based device after six months of follow-up.

METHODS: Corneal densitometry (CD) values of 102 eyes were divided into three main groups: 33 DMEKs, 19 DSAEKs, and 50 healthy eyes without previous ocular surgery. The CD values were then analyzed and compared between the groups. We measured three main layers in depth and four different concentric zones at 1, 3, and 6 months postoperatively.

RESULTS: In the DMEK group, total CD significantly decreased from 38.02 ± 10.21 grayscale units (GSU) to 31.13 ± 9.25 GSU (P < 0.01) between the first and the sixth month postoperative. In the DSAEK group, we found significant changes only between the first and three months after surgery (from 42.62 ± 9.31 GSU to 38.71 ± 10.53 GSU (P < 0.01). Regarding the concentric zones, CD in the DMEK group significantly decreased in the central zone from 33.55 ± 12.07 GSU to 30.63 ± 10.15 GSU (P < 0.01) and significantly increased in the periphery from 30.63 ± 10.15 GSU to 36.72 ± 9.37 GSU, (P < 0.01). The DSAEK group showed no changes in the central zone (from 36.91 ± 13.80 GSU to 36.14 ± 11.47 GSU, P = 0.52) and CD significantly increased in the periphery (41.91 ± 9.28 GSU, P < 0.01).

CONCLUSION: When comparing CD values in DMEK versus DSAEK, we found no differences by layers or at central-paracentral concentric zones, although CD differences in the peripheral zones were statistically significant. This finding may be attributed to the thicker graft at periphery with a delayed clearance and less anatomical interphase in DSAEK.

PMID:33763796 | DOI:10.1007/s10792-021-01817-x

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Nevin Manimala Statistics

Versatile knowledge guided network inference method for prioritizing key regulatory factors in multi-omics data

Sci Rep. 2021 Mar 24;11(1):6806. doi: 10.1038/s41598-021-85544-4.

ABSTRACT

Constantly decreasing costs of high-throughput profiling on many molecular levels generate vast amounts of multi-omics data. Studying one biomedical question on two or more omic levels provides deeper insights into underlying molecular processes or disease pathophysiology. For the majority of multi-omics data projects, the data analysis is performed level-wise, followed by a combined interpretation of results. Hence the full potential of integrated data analysis is not leveraged yet, presumably due to the complexity of the data and the lacking toolsets. We propose a versatile approach, to perform a multi-level fully integrated analysis: The Knowledge guIded Multi-Omics Network inference approach, KiMONo ( https://github.com/cellmapslab/kimono ). KiMONo performs network inference by using statistical models for combining omics measurements coupled to a powerful knowledge-guided strategy exploiting prior information from existing biological sources. Within the resulting multimodal network, nodes represent features of all input types e.g. variants and genes while edges refer to knowledge-supported and statistically derived associations. In a comprehensive evaluation, we show that our method is robust to noise and exemplify the general applicability to the full spectrum of multi-omics data, demonstrating that KiMONo is a powerful approach towards leveraging the full potential of data sets for detecting biomarker candidates.

PMID:33762588 | DOI:10.1038/s41598-021-85544-4

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Nevin Manimala Statistics

Forecasting influenza-like illness trends in Cameroon using Google Search Data

Sci Rep. 2021 Mar 24;11(1):6713. doi: 10.1038/s41598-021-85987-9.

ABSTRACT

Although acute respiratory infections are a leading cause of mortality in sub-Saharan Africa, surveillance of diseases such as influenza is mostly neglected. Evaluating the usefulness of influenza-like illness (ILI) surveillance systems and developing approaches for forecasting future trends is important for pandemic preparedness. We applied and compared a range of robust statistical and machine learning models including random forest (RF) regression, support vector machines (SVM) regression, multivariable linear regression and ARIMA models to forecast 2012 to 2018 trends of reported ILI cases in Cameroon, using Google searches for influenza symptoms, treatments, natural or traditional remedies as well as, infectious diseases with a high burden (i.e., AIDS, malaria, tuberculosis). The R2 and RMSE (Root Mean Squared Error) were statistically similar across most of the methods, however, RF and SVM had the highest average R2 (0.78 and 0.88, respectively) for predicting ILI per 100,000 persons at the country level. This study demonstrates the need for developing contextualized approaches when using digital data for disease surveillance and the usefulness of search data for monitoring ILI in sub-Saharan African countries.

PMID:33762599 | DOI:10.1038/s41598-021-85987-9

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Nevin Manimala Statistics

Methodological considerations for identifying multiple plasma proteins associated with all-cause mortality in a population-based prospective cohort

Sci Rep. 2021 Mar 24;11(1):6734. doi: 10.1038/s41598-021-85991-z.

ABSTRACT

Novel methods to characterize the plasma proteome has made it possible to examine a wide range of proteins in large longitudinal cohort studies, but the complexity of the human proteome makes it difficult to identify robust protein-disease associations. Nevertheless, identification of individuals at high risk of early mortality is a central issue in clinical decision making and novel biomarkers may be useful to improve risk stratification. With adjustment for established risk factors, we examined the associations between 138 plasma proteins measured using two proximity extension assays and long-term risk of all-cause mortality in 3,918 participants of the population-based Malmö Diet and Cancer Study. To examine the reproducibility of protein-mortality associations we used a two-step random-split approach to simulate a discovery and replication cohort and conducted analyses using four different methods: Cox regression, stepwise Cox regression, Lasso-Cox regression, and random survival forest (RSF). In the total study population, we identified eight proteins that associated with all-cause mortality after adjustment for established risk factors and with Bonferroni correction for multiple testing. In the two-step analyses, the number of proteins selected for model inclusion in both random samples ranged from 6 to 21 depending on the method used. However, only three proteins were consistently included in both samples across all four methods (growth/differentiation factor-15 (GDF-15), N-terminal pro-B-type natriuretic peptide, and epididymal secretory protein E4). Using the total study population, the C-statistic for a model including established risk factors was 0.7222 and increased to 0.7284 with inclusion of the most predictive protein (GDF-15; P < 0.0001). All multiple protein models showed additional improvement in the C-statistic compared to the single protein model (all P < 0.0001). We identified several plasma proteins associated with increased risk of all-cause mortality independently of established risk factors. Further investigation into the putatively causal role of these proteins for longevity is needed. In addition, the examined methods for identifying multiple proteins showed tendencies for overfitting by including several putatively false positive findings. Thus, the reproducibility of findings using such approaches may be limited.

PMID:33762603 | DOI:10.1038/s41598-021-85991-z

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Nevin Manimala Statistics

Bacterial Reduction in Oval-Shaped Root Canals After Different Irrigant Agitation Methods

Eur Endod J. 2021 Mar 8. doi: 10.14744/eej.2020.42204. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aimed to assess the antibacterial effect of Easy Clean®, passive ultrasonic irrigation and sonic irrigation against Enterococcus faecalis biofilm in oval-shaped canals.

METHODS: Fifty-five extracted human teeth with similar dimensions were selected. Access cavities were prepared and the root canals were instrumented using Wave One® Primary files (25.08). The root canals were then contaminated with an E. faecalis suspension following incubation for thirty days. The contaminated roots were divided into three experimental groups (n=15) according to the irrigant agitation protocol (Easy Clean, passive ultrassonic irrigation and sonic irrigation), in addition to a positive control group (n=5) and a negative control group (n=5). Microbiological samples were taken from the root canals before instrumentation (S1), after instrumentation (S2) and after the final irrigation protocol (S3). The samples were assayed and incubated for 48 hours in order to obtain the residual titer of E. faecalis cells. Viable cells were quantified by colony-forming units (CFU) measurement. The collected data was submitted to statistical analysis by using Shapiro-Wilk`s test, Wilcoxon paired test, Kruskal-Wallis test and Dunn’s post-hoc test. The level of significance was set at 5%.

RESULTS: All experimental groups presented significant reduction on bacterial load after instrumentation (P<0.05) with similar reduction among the groups. After the agitation protocols, significant reduction in bacterial load was demonstrated for all groups (P<0.05). However, no differences were shown among Easy Clean®, PUI and SI (P>0.05).

CONCLUSION: The results showed that all tested groups exhibited similar disinfection effectiveness. However, none of them was able to render all root canals free from microorganisms.

PMID:33762531 | DOI:10.14744/eej.2020.42204

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Nevin Manimala Statistics

Excess Mortality Associated With the COVID-19 Pandemic-Los Angeles County, March-September 2020

J Public Health Manag Pract. 2021 May-Jun 01;27(3):233-239. doi: 10.1097/PHH.0000000000001344.

ABSTRACT

OBJECTIVE: To more comprehensively estimate COVID-19-related mortality in Los Angeles County by determining excess all-cause mortality and pneumonia, influenza, or COVID (PIC) mortality.

DESIGN: We reviewed vital statistics data to identify deaths registered in Los Angeles County between March 15, 2020, and August 15, 2020. Deaths with an ICD-10 (International Classification of Diseases, Tenth Revision) code for pneumonia, influenza, or COVID-19 listed as an immediate or underlying cause of death were classified as PIC deaths. Expected deaths were calculated using negative binomial regression. Excess mortality was determined by subtracting the expected from the observed number of weekly deaths. The Department of Public Health conducts surveillance for COVID-19-associated deaths: persons who died of nontraumatic/nonaccidental causes within 60 days of a positive COVID-19 test result were classified as confirmed COVID-19 deaths. Deaths without a reported positive SARS-Cov-2 polymerase chain reaction result were classified as probable COVID-19 deaths if COVID-19 was listed on their death certificate or the death occurred 60 to 90 days of a positive test. We compared excess PIC deaths with the number of confirmed and probable COVID-19 deaths ascertained by surveillance.

SETTING: Los Angeles County.

PARTICIPANTS: Residents of Los Angeles County who died.

MAIN OUTCOME MEASURE: Excess mortality.

RESULTS: There were 7208 excess all-cause and 5128 excess PIC deaths during the study period. The Department of Public Health also reported 5160 confirmed and 323 probable COVID-19-associated deaths.

CONCLUSIONS: The number of excess PIC deaths estimated by our model was approximately equal to the number of confirmed and probable COVID-19 deaths identified by surveillance. This suggests our surveillance definition for confirmed and probable COVID-19 deaths might be sufficiently sensitive for capturing the true burden of deaths caused directly or indirectly by COVID-19.

PMID:33762539 | DOI:10.1097/PHH.0000000000001344

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Nevin Manimala Statistics

College Students’ Experiences of Race-Related Bias or Hatred in Their Lifetimes and COVID-19 Era

J Public Health Manag Pract. 2021 May-Jun 01;27(3):258-267. doi: 10.1097/PHH.0000000000001351.

ABSTRACT

OBJECTIVE: The primary aim of this study was to investigate whether students in minority race categories are more likely to experience race-related bias and hatred in their lifetime and since the onset of COVID-19, after controlling the effect of demographic and other variables.

METHODS: This quantitative study used primary data from the survey of 1249 college students at one of the universities in Georgia during April and May 2020. We performed multinomial logistic regression, computing 2 models for the 2 ordinal dependent variables concerning students’ experience of race-related bias and hatred-(a) during their lifetime and (b) since the onset of COVID-19 in March 2020-both measured as “never,” “rarely,” “sometimes,” and “fairly often or very often.”

RESULTS: During their lifetime, 47.5% of students had experienced some level of bias or hatred, ranging from “rarely” to “very often.” Since the onset of COVID-19 on March 2 in Georgia, in a short period of 1 to 2 months, 17.6% of students reported experiencing race-related bias or hatred. Univariate statistics revealed substantial differences in race-related bias and hatred by race, experienced during students’ lifetime as well as since the onset of COVID-19. Results of multinomial logistic regression showed that the odds of having experienced bias or hatred during their lifetime were significantly higher (P < .05) for the Black students than for White students (adjusted odds ratio [AOR] = 75.8, for very often or often vs never; AOR = 42 for sometimes vs never). Compared with White students, the odds of hatred and bias were also significantly higher for students who were Asian, multiple races, or another non-White race. The odds of having experienced race-related bias and hatred since the onset of COVID-19 were also higher for Black Asian, multiple races, and other non-White students.

CONCLUSIONS: This study adds critical scientific evidence about variation in the perception of bias and hatred that should draw policy attention to race-related issues experienced by college students in the United States.

PMID:33762541 | DOI:10.1097/PHH.0000000000001351

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Nevin Manimala Statistics

Author Correction: A data-driven simulation platform to predict cultivars’ performances under uncertain weather conditions

Nat Commun. 2021 Mar 24;12(1):1966. doi: 10.1038/s41467-021-22384-w.

NO ABSTRACT

PMID:33762573 | DOI:10.1038/s41467-021-22384-w

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Nevin Manimala Statistics

Alkaline phosphatase in pediatric patients with genu varum caused by vitamin D-deficient rickets

Endocr J. 2021 Mar 24. doi: 10.1507/endocrj.EJ20-0622. Online ahead of print.

ABSTRACT

An elevated serum alkaline phosphatase (ALP) level is one of the markers for the presence of rickets in children, but it is also associated with bone formation. However, its role in diagnosing genu varum in pediatric patients with vitamin D-deficient rickets is still unknown. To clarify the role of the serum ALP level in assessing the severity of genu varum, we retrospectively investigated this issue statistically using data on rickets such as serum intact parathyroid hormone (iPTH), 25-hydroxyvitamin D, 1,25-dihydroxyvitamin D, ALP, the level of creatinine as the percentage of the median according to age (%Cr), and the metaphyseal diaphyseal angle (MDA) in the lower extremities as an index of the severity of genu varum. A multiple regression analysis revealed that log ALP and %Cr values were negatively associated with MDA values. The former association was also confirmed by a linear mixed model, while iPTH was positively associated with MDA by path model analysis. To elucidate the association of ALP with MDA in the presence of iPTH, we investigated three-dimensional figures by neural network analysis. This indicated the presence of a biphasic association of ALP with MDA: the first phase increases while the second decreases MDA. The latter phenomenon is considered to be associated with the increase in bone formation due to the mechanical stress loaded on the lower extremities. These findings are important and informative for pediatricians to understand the significance of the serum ALP level in pediatric patients with genu varum caused by vitamin D deficiency.

PMID:33762518 | DOI:10.1507/endocrj.EJ20-0622

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Nevin Manimala Statistics

A Novel Risk Stratification System for Ischemic Stroke in Japanese Patients With Non-Valvular Atrial Fibrillation

Circ J. 2021 Mar 25. doi: 10.1253/circj.CJ-20-1075. Online ahead of print.

ABSTRACT

BACKGROUND: Recently, identification of independent risk factors for ischemic stroke in Japanese non-valvular atrial fibrillation (NVAF) patients was made by analyzing the 5 major Japanese registries: J-RHYTHM Registry, Fushimi AF Registry, Shinken Database, Keio interhospital Cardiovascular Studies, and the Hokuriku-Plus AF Registry.Methods and Results:The predictive value of the risk scheme in Japanese NVAF patients was assessed. Of 16,918 patients, 12,289 NVAF patients were analyzed (mean follow up, 649±181 days). Hazard ratios (HRs) of each significant, independent risk factor were determined by using adjusted Cox-hazard proportional analysis. Scoring system for ischemic stroke was created by transforming HR logarithmically and was estimated by c-statistic. During the 21,820 person-years follow up, 241 ischemic stroke events occurred. Significant risk factors were: being elderly (aged 75-84 years [E], HR=1.74), extreme elderly (≥85 years [EE], HR=2.41), having hypertension (H, HR=1.60), previous stroke (S, HR=2.75), type of AF (persistent/permanent) (T, HR=1.59), and low body mass index <18.5 kg/m2(L, HR=1.55) after adjusting for oral anticoagulant treatment. The score was assigned as follows: 1 point to H, E, L, and T, and 2 points to EE and S (HELT-E2S2score). The C-statistic, using this score, was 0.681 (95% confidence interval [CI]=0.647-0.714), which was significantly higher than those using CHADS2(0.647; 95% CI=0.614-0.681, P=0.027 for comparison) and CHA2DS2-VASc scores (0.641; 95% CI=0.608-0.673, P=0.008).

CONCLUSIONS: The HELT-E2S2score may be useful for identifying Japanese NVAF patients at risk of ischemic stroke.

PMID:33762526 | DOI:10.1253/circj.CJ-20-1075