Category: Nevin Manimala

PLoS One. 2021 Aug 6;16(8):e0253517. doi: 10.1371/journal.pone.0253517. eCollection 2021.

ABSTRACT

The dimensions of patient-centred care include not only clinical effectiveness and patient safety, but, importantly, the preferences of patients as consumers of healthcare services. A total of 249 participants were included in the study, with a balanced population proportional representation by age, gender, ethnicity and geographic region of New Zealand. An online questionnaire was used to identify participants’ decision-making process, and what factors and barriers for participants to seek dental treatment. Cross-tabulations, Spearman correlation analysis and Pearson Chi-Square analysis were used for the statistical analyses. Three most common reasons for visit were check-up (77%), clean (57%) and relief of pain 36%). A desire to treat a perceived problem was the most common encouraging factor to seek dental care. Cost was the most common barrier to seeking dental services. The majority of participants attended a private practice (84%), with convenience of location and referral from professionals the most likely to influence their choice. Participants felt the most important trait a dental practitioner could demonstrate was to discuss treatment options with them before any treatment. Dental check-up, teeth cleaning and relief of pain were the most common reasons for patients to choose dental services. Cost and ethnicity of the consumers had a significant impact on how dental services were perceived and sought. Dental practitioners may need to reorientate how they express value of oral health practice, not just in regard to communication with patients, but also with government funding agencies.

PMID:34358252 | DOI:10.1371/journal.pone.0253517

PLoS One. 2021 Aug 6;16(8):e0255735. doi: 10.1371/journal.pone.0255735. eCollection 2021.

ABSTRACT

PURPOSE: Establishing the reliability of a new method to check the mean retinal and choroidal reflectivity and using it to find retinal and choroid changes in amblyopia.

METHODS: Design: Retrospective case-control. Population: 28 subjects of which 10 were healthy controls (20 eyes): 8 with refractive errors, 1 with strabismus, and 1 with both. 18 patients with unilateral amblyopia included: 7 anisometropic, 6 isoametropic, 1 strabismic, and 4 combined. Mean participants’ age: 13.77 years ± 10.28. Observation procedures: SD-OCT and ImageJ. Main outcome measure: mean reflectivity of retinal and choroid layers. Amblyopic, fellow, and healthy eyes were compared.

RESULTS: The method of measuring reflectivity is good to excellent reliability for all regions of interest except the fourth. The mean reflectivity of the choriocapillaris and Sattler’s layer in amblyopic eyes were significantly lower than in healthy eyes (p = 0.003 and p = 0.008 respectively). The RNFL reflectivity was lower than that of fellow eyes (p = 0.025). Post-hoc pairwise comparisons showed statistically significant differences between amblyopic and healthy eyes for choriocapillaris (p = 0.018) and Sattler’s (p = 0.035), and between amblyopic and fellow eyes for RNFL (p = 0.039).

CONCLUSION: A decrease in reflectivity of the choriocapillaris and Sattler’s in amblyopic compared to healthy eyes, and a decrease in reflectivity of the RNFL in the amblyopic compared to fellow eyes, indicate that the pathophysiology is partly peripheral and might be bilateral.

PMID:34358257 | DOI:10.1371/journal.pone.0255735

PLoS One. 2021 Aug 6;16(8):e0254479. doi: 10.1371/journal.pone.0254479. eCollection 2021.

ABSTRACT

BACKGROUND: Sentinel physician surveillance in communities has played an important role in detecting early signs of epidemics. The traditional approach is to let the primary care physician voluntarily and actively report diseases to the health department on a weekly basis. However, this is labor-intensive work, and the spatio-temporal resolution of the surveillance data is not precise at all. In this study, we built up a clinic-based enhanced sentinel surveillance system named “Sentinel plus” which was designed for sentinel clinics and community hospitals to monitor 23 kinds of syndromic groups in Taipei City, Taiwan. The definitions of those syndromic groups were based on ICD-10 diagnoses from physicians.

METHODS: Daily ICD-10 counts of two syndromic groups including ILI and EV-like syndromes in Taipei City were extracted from Sentinel plus. A negative binomial regression model was used to couple with lag structure functions to examine the short-term association between ICD counts and meteorological variables. After fitting the negative binomial regression model, residuals were further rescaled to Pearson residuals. We then monitored these daily standardized Pearson residuals for any aberrations from July 2018 to October 2019.

RESULTS: The results showed that daily average temperature was significantly negatively associated with numbers of ILI syndromes. The ozone and PM2.5 concentrations were significantly positively associated with ILI syndromes. In addition, daily minimum temperature, and the ozone and PM2.5 concentrations were significantly negatively associated with the EV-like syndromes. The aberrational signals detected from clinics for ILI and EV-like syndromes were earlier than the epidemic period based on outpatient surveillance defined by the Taiwan CDC.

CONCLUSIONS: This system not only provides warning signals to the local health department for managing the risks but also reminds medical practitioners to be vigilant toward susceptible patients. The near real-time surveillance can help decision makers evaluate their policy on a timely basis.

PMID:34358241 | DOI:10.1371/journal.pone.0254479

PLoS Negl Trop Dis. 2021 Aug 6;15(8):e0009673. doi: 10.1371/journal.pntd.0009673. Online ahead of print.

ABSTRACT

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by hantavirus which was endemic Zhejiang Province, China. In this study, we aim to explore the changing epidemiology of HFRS in Zhejiang, identify high-risk areas and populations, and evaluate relevant policies and interventions to better improve HFRS control and prevention.

METHODS: Surveillance data on HFRS during 1963-2020 in Zhejiang Province were extracted from Zhejiang Provincial Center for Disease Control and Prevention archives and the Chinese Notifiable Disease Reporting System. The changing epidemiological characteristics of HFRS including seasonal distribution, geographical distribution, and demographic features, were analyzed using joinpoint regression, autoregressive integrated moving average model, descriptive statistical methods, and Spatio-temporal cluster analysis.

RESULTS: From 1963 to 2020, 114 071 HFRS cases and 1269 deaths were reported in Zhejiang Province. The incidence increased sharply from 1973 and peaked in 1986, then decreased steadily and maintained a stable incidence from 2004. HFRS cases were reported in all 11 prefecture-level cities of Zhejiang Province from 1963 to 2020. The joint region (Shengzhou, Xinchang, Tiantai, and surrounding areas), and Kaihua County are the most seriously affected regions throughout time. After 1990, the first HFRS incidence peak was in May-June, with another one from November to January. Most HFRS cases occurred in 21- (26.48%) and 30- years group (24.25%) from 1991 to 2004, but 41- (25.75%) and 51-years (23.30%) had the highest proportion from 2005 to 2020. Farmers accounted for most cases (78.10%), and cases are predominantly males with a male-to-female ratio of 2.6:1. It was found that the median time from onset to diagnosis was 6.5 days (IQR 3.75-10.42), and the time from diagnosis to disease report was significantly shortened after 2011.

CONCLUSIONS: We observed dynamic changes in the seasonal distribution, geographical distribution, and demographic features of HFRS, which should be well considered in the development of control and prevention strategies in future. Additional researches are warranted to elucidate the environmental, meteorological, and social factors associated with HFRS incidence in different decades.

PMID:34358248 | DOI:10.1371/journal.pntd.0009673

PLoS Negl Trop Dis. 2021 Aug 6;15(8):e0009593. doi: 10.1371/journal.pntd.0009593. Online ahead of print.

ABSTRACT

BACKGROUND: Brucellosis is widespread in Ethiopia with variable reported prevalence depending on the geographical area, husbandry practices and animal species. However, there is limited information on the disease prevalence amongst pastoral communities, whose life is intricately linked with their livestock.

METHODOLOGY: We conducted an integrated human-animal brucellosis sero-surveillance study in two adjacent pastoral regions, Afar and Somali region (SRS). This cross-sectional study included 13 woredas (districts) and 650 households. Blood samples were collected from people and livestock species (cattle, camel, goats and sheep). Sera were analyzed with C-ELISA for camels and shoats (sheep and goats), with I-ELISA for cattle and IgG ELISA for humans. Descriptive and inferential statistics analyses were performed.

RESULTS: A total of 5469 sera were tested by ELISA. Prevalence of livestock was 9.0% in Afar and 8.6% in SRS (ranging from 0.6 to 20.2% at woreda level). In humans, prevalence was 48.3% in Afar and 34.9% in SRS (ranging from 0.0 to 74.5% at woreda level). 68.4% of all households in Afar and 57.5% of households in SRS had at least one animal reactor. Overall, 4.1% of animals had a history of abortion. The proportion of animals with abortion history was higher in seropositive animals than in seronegative animals. Risk factor analysis showed that female animals were significantly at higher risk of being reactors (p = 0.013). Among the species, cattle had the least risk of being reactors (p = 0.014). In humans, there was a clear regional association of disease prevalence (p = 0.002). The older the people, the highest the odds of being seropositive.

CONCLUSION: Brucellosis is widespread in humans and animals in pastoral communities of Afar and SRS with the existence of geographical hotspots. No clear association was seen between human and particular livestock species prevalence, hence there was no indication as whether B. abortus or B. melitensis are circulating in these areas, which warrants further molecular research prior to embarking on a national control programs. Such programs will need to be tailored to the pastoral context.

PMID:34358232 | DOI:10.1371/journal.pntd.0009593

PLoS One. 2021 Aug 6;16(8):e0255269. doi: 10.1371/journal.pone.0255269. eCollection 2021.

ABSTRACT

The Sine-Cosine algorithm (SCA) is a population-based metaheuristic algorithm utilizing sine and cosine functions to perform search. To enable the search process, SCA incorporates several search parameters. But sometimes, these parameters make the search in SCA vulnerable to local minima/maxima. To overcome this problem, a new Multi Sine-Cosine algorithm (MSCA) is proposed in this paper. MSCA utilizes multiple swarm clusters to diversify & intensify the search in-order to avoid the local minima/maxima problem. Secondly, during update MSCA also checks for better search clusters that offer convergence to global minima effectively. To assess its performance, we tested the MSCA on unimodal, multimodal and composite benchmark functions taken from the literature. Experimental results reveal that the MSCA is statistically superior with regards to convergence as compared to recent state-of-the-art metaheuristic algorithms, including the original SCA.

PMID:34358237 | DOI:10.1371/journal.pone.0255269

PLoS Comput Biol. 2021 Aug 6;17(8):e1009275. doi: 10.1371/journal.pcbi.1009275. Online ahead of print.

ABSTRACT

In modern computational biology, there is great interest in building probabilistic models to describe collections of a large number of co-varying binary variables. However, current approaches to build generative models rely on modelers’ identification of constraints and are computationally expensive to infer when the number of variables is large (N~100). Here, we address both these issues with Super-statistical Generative Model for binary Data (SiGMoiD). SiGMoiD is a maximum entropy-based framework where we imagine the data as arising from super-statistical system; individual binary variables in a given sample are coupled to the same ‘bath’ whose intensive variables vary from sample to sample. Importantly, unlike standard maximum entropy approaches where modeler specifies the constraints, the SiGMoiD algorithm infers them directly from the data. Due to this optimal choice of constraints, SiGMoiD allows to model collections of a very large number (N>1000) of binary variables. Finally, SiGMoiD offers a reduced dimensional description of the data, allowing us to identify clusters of similar data points as well as binary variables. We illustrate the versatility of SiGMoiD using several datasets spanning several time- and length-scales.

PMID:34358223 | DOI:10.1371/journal.pcbi.1009275

PLoS One. 2021 Aug 6;16(8):e0253425. doi: 10.1371/journal.pone.0253425. eCollection 2021.

ABSTRACT

Statistical models for outcome prediction are central to traumatic brain injury research and critical to baseline risk adjustment. Glasgow coma score (GCS) and pupil reactivity are crucial covariates in all such models but may be measured at multiple time points between the time of injury and hospital and are subject to a variable degree of unreliability and/or missingness. Imputation of missing data may be undertaken using full multiple imputation or by simple substitution of measurements from other time points. However, it is unknown which strategy is best or which time points are more predictive. We evaluated the pseudo-R2 of logistic regression models (dichotomous survival) and proportional odds models (Glasgow Outcome Score-extended) using different imputation strategies on the The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study dataset. Substitution strategies were easy to implement, achieved low levels of missingness (<< 10%) and could outperform multiple imputation without the need for computationally costly calculations and pooling multiple final models. While model performance was sensitive to imputation strategy, this effect was small in absolute terms and clinical relevance. A strategy of using the emergency department discharge assessments and working back in time when these were missing generally performed well. Full multiple imputation had the advantage of preserving time-dependence in the models: the pre-hospital assessments were found to be relatively unreliable predictors of survival or outcome. The predictive performance of later assessments was model-dependent. In conclusion, simple substitution strategies for imputing baseline GCS and pupil response can perform well and may be a simple alternative to full multiple imputation in many cases.

PMID:34358231 | DOI:10.1371/journal.pone.0253425

Echocardiography. 2021 Aug 6. doi: 10.1111/echo.15170. Online ahead of print.

ABSTRACT

AIM: Chest computed tomography (CT) imaging plays a diagnostic and prognostic role in Coronavirus disease 2019 (COVID-19) patients. This study aimed to investigate and compare predictive capacity of main pulmonary artery diameter (MPA), ascending aorta diameter (AAo), and MPA-to-AAo ratio to determine in-hospital mortality in COVID-19 patients.

MATERIALS AND METHODS: This retrospective study included 255 hospitalized severe or critical COVID-19 patients. MPA was measured at the level of pulmonary artery bifurcation perpendicular to the direction of the vessel through transverse axial images and AAo was measured by using the same CT slice at its maximal diameter. MPA-to-AAo ratio was calculated by division of MPA to AAo.

RESULTS: Multivariate logistic regression model yielded MPA ≥29.15 mm (OR: 4.95, 95% CI: 2.01-12.2, p = 0.001), MPA (OR: 1.28, 95% CI: 1.13-1.46, p < 0.001), AAo (OR: .90, 95% CI: .81-.99, p = 0.040), and MPA-to-AAo ratio ≥.82 (OR: 4.67, 95% CI: 1.86-11.7, p = 0.001) as independent predictors of in-hospital mortality. Time-dependent multivariate Cox-proportion regression model demonstrated MPA ≥29.15 mm (HR: 1.96, 95% CI: 1.03-3.90, p = 0.047) and MPA (HR: 1.08, 95% CI: 1.01-1.17, p = 0.048) as independent predictors of in-hospital mortality, whereas AAo and MPA-to-AAo ratio did not reach statistical significance.

CONCLUSION: Pulmonary artery enlargement strongly predicts in-hospital mortality in hospitalized COVID-19 patients. MPA, which can be calculated easily from chest CT imaging, can be beneficial in the prognostication of these patients.

PMID:34355824 | DOI:10.1111/echo.15170

J Magn Reson Imaging. 2021 Aug 6. doi: 10.1002/jmri.27871. Online ahead of print.

ABSTRACT

BACKGROUND: CD8⁺ T cell in pancreatic ductal adenocarcinoma (PDAC) is closely related to the prognosis and treatment response of patients. Accurate preoperative CD8⁺ T-cell expression can better identify the population benefitting from immunotherapy.

PURPOSE: To develop and validate a machine learning classifier based on noncontrast magnetic resonance imaging (MRI) for the preoperative prediction of CD8⁺ T-cell expression in patients with PDAC.

STUDY TYPE: Retrospective cohort study.

POPULATION: Overall, 114 patients with PDAC undergoing MR scan and surgical resection; 97 and 47 patients in the training and validation cohorts. FIELD STRENGTH/SEQUENCE/3 T: Breath-hold single-shot fast-spin echo T2-weighted sequence and noncontrast T1-weighted fat-suppressed sequences.

ASSESSMENT: CD8⁺ T-cell expression was quantified using immunohistochemistry. For each patient, 2232 radiomics features were extracted from noncontrast T1- and T2-weighted images and reduced using the Wilcoxon rank-sum test and least absolute shrinkage and selection operator method. Linear discriminative analysis was used to construct radiomics and mixed models. Model performance was determined by its discriminative ability, calibration, and clinical utility.

STATISTICAL TESTS: Kaplan-Meier estimates, Student’s t-test, the Kruskal-Wallis H test, and the chi-square test, receiver operating characteristic curve, and decision curve analysis.

RESULTS: A log-rank test showed that the survival duration in the CD8-high group (25.51 months) was significantly longer than that in the CD8-low group (22.92 months). The mixed model included all MRI characteristics and 13 selected radiomics features, and the area under the curve (AUC) was 0.89 (95% confidence interval [CI], 0.77-0.92) and 0.69 (95% CI, 0.53-0.82) in the training and validation cohorts. The radiomics model included 13 radiomics features, which showed good discrimination in the training cohort (AUC, 0.85; 95% CI, 0.77-0.92) and the validation cohort (AUC, 0.76; 95% CI, 0.61-0.87).

DATA CONCLUSIONS: This study developed a noncontrast MRI-based radiomics model that can preoperatively determine CD8⁺ T-cell expression in patients with PDAC and potentially immunotherapy planning.

EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

PMID:34355834 | DOI:10.1002/jmri.27871