Tag: nevin manimala

ASAIO J. 2022 May 24. doi: 10.1097/MAT.0000000000001775. Online ahead of print.

ABSTRACT

A retrospective study was performed examining the trend of inflammatory markers, including D-dimers, in 29 COVID-19 patients requiring veno-venous (VV) extracorporeal membrane oxygenation (ECMO) support. We observed that COVID-19 patients with pre-cannulation D-dimer levels >3,000 ng/mL had a significantly shorter time from admission to cannulation (4.78 vs. 8.44 days, p = 0.049) compared to those with D-dimer <3,000 ng/mL. Furthermore, patients with D-dimer >3,000 ng/mL had a trend of lower pH (7.24 vs. 7.33), higher pCO2 (61.33 vs. 50.69), and higher vasoactive inotropic score (7.23 vs. 3.97) at time of cannulation, however, these were not statistically significant. This cohort of patients also required a longer duration of ECMO support (51.44 vs. 31.25 days). However, 13 patients required at least one ECMO-circuit exchange and 16 patients did not require any exchanges. There was a consistent drop in D-dimer values after every circuit exchange, which was not observed in any of the other examined inflammatory markers, including ferritin, lactate dehydrogenase, or C-reactive protein. We propose that elevated D-dimer levels (>3,000 ng/mL) reflect increased disease severity in COVID-19, and predict a longer ECMO course. Once on ECMO, however, the D-Dimer level consistently decreased with every circuit exchange, which may reflect thrombus within the oxygenator rather than just disease severity.

PMID:35609187 | DOI:10.1097/MAT.0000000000001775

Perm J. 2021 Oct 25;26(1):11-20. doi: 10.7812/TPP/21.024.

ABSTRACT

INTRODUCTION: Effective, equity-promoting interventions implemented by health care systems are needed to address health care disparities and population-level health disparities. We evaluated the impact of a clinical decision support tool to improve evidence-based thiazide diuretic prescribing among Black patients to address racial disparities in hypertension control.

METHODS: We employed an interrupted time series design and qualitative interviews to evaluate the implementation of the tool. Our primary outcome measure was the monthly rate of thiazide use among eligible patients before and after implementation of the tool (January 2013-December 2016). We modeled month-to-month changes in thiazide use for Black and White patients, overall, and by sex and medical center racial composition. We conducted key informant interviews to identify modifiable facilitators and barriers to implementation of the tool across medical centers.

RESULTS: Of the 318,720 patients, 15.5% were Black. We observed no change in thiazide use or blood pressure control following the implementation of the tool in either racial subgroup. There was a slight but statistically significant reduction (2.32 percentage points, p < 0.01) in thiazide use among Black patients following the removal the tool that was not observed among White patients. Factors affecting the tool’s implementation included physician and pharmacist resistance to thiazide use and a lack of ongoing promotion of the tool.

DISCUSSION: The clinical decision support tool was insufficient to change prescribing practices and improve blood pressure control among Black patients.

CONCLUSIONS: Future interventions should consider physician attitudes about thiazide prescribing and the importance of multilevel approaches to address hypertension disparities.

PMID:35609161 | DOI:10.7812/TPP/21.024

Transplantation. 2022 May 9. doi: 10.1097/TP.0000000000004171. Online ahead of print.

ABSTRACT

BACKGROUND: Much of our understanding regarding geographic issues in transplantation is based on statistical techniques that do not formally account for geography and is based on obsolete boundaries such as donation service area.

METHODS: We applied spatial epidemiological techniques to analyze liver-related mortality and access to liver transplant services at the county level using data from the Centers for Disease Control and Prevention and Scientific Registry of Transplant Recipients from 2010 to 2018.

RESULTS: There was a significant negative spatial correlation between transplant rates and liver-related mortality at the county level (Moran’s I, -0.319; P = 0.001). Significant clusters were identified with high transplant rates and low liver-related mortality. Counties in geographic clusters with high ratios of liver transplants to liver-related deaths had more liver transplant centers within 150 nautical miles (6.7 versus 3.6 centers; P < 0.001) compared with all other counties, as did counties in geographic clusters with high ratios of waitlist additions to liver-related deaths (8.5 versus 2.5 centers; P < 0.001). The spatial correlation between waitlist mortality and overall liver-related mortality was positive (Moran’s I, 0.060; P = 0.001) but weaker. Several areas with high waitlist mortality had some of the lowest overall liver-related mortality in the country.

CONCLUSIONS: These data suggest that high waitlist mortality and allocation model for end-stage liver disease do not necessarily correlate with decreased access to transplant, whereas local transplant center density is associated with better access to waitlisting and transplant.

PMID:35609185 | DOI:10.1097/TP.0000000000004171

Int J Dermatol. 2022 May 24. doi: 10.1111/ijd.16278. Online ahead of print.

ABSTRACT

BACKGROUND: Erysipeloid cutaneous leishmaniasis (ECL) is known as the chronic form of cutaneous leishmaniasis (CL). However, keeping its clinical presentation in view, there is a need to revisit this form of the disease.

AIMS: To describe ECL in view of clinical features and treatment modalities.

METHODS: We include a case series seen in Sfax (Southern Tunisia) from January 2017 to January 2021. All patients clinically suggestive and laboratory confirmed with a diagnosis of CL were registered. Patients of all age groups and of either gender having cutaneous lesions resembling erysipela on the face were included in the study. Different demographic features of the patients and clinical aspects were identified. Descriptive statistics were used for analysis.

RESULTS: Of 1300 registered patients with CL, 40 (3%) were diagnosed as ECL. Ages ranged from 15 to 65 years, and duration of lesions varied from 15 to 180 days. All patients had lesions over the face. Clinically, a painful infiltrated inflammatory placard of the central facial area with a butterfly shape was observed in 14 cases, as well as zones of the cheekbone (11 cases), cheekbone and nose (5 cases), cheekbone and eyelid (8 cases), and cheekbone with ear (2 cases). Several therapeutic methods were prescribed with a sufficient result with no recurrence.

CONCLUSION: ECL is a rare presentation that typically occurs on the face, looking like erysipelas, in patients who are native from an endemic region of CL.

PMID:35609142 | DOI:10.1111/ijd.16278

IEEE Trans Biomed Eng. 2022 May 24;PP. doi: 10.1109/TBME.2022.3176224. Online ahead of print.

ABSTRACT

Fluorescence lifetime imaging is a valuable technique for probing characteristics of wide ranging samples and sensing of the molecular environment. However, the desire to measure faster and reduce effects such as photo bleaching in optical photon-count measurements for lifetime estimation lead to inevitable effects of convolution with the instrument response functions and noise, causing a degradation of the lifetime accuracy and precision. To tackle the problem, this paper presents a robust and computationally efficient framework for recovering fluorophore sample decay from the histogram of photon-count arrivals modelled as a decaying single-exponential function. In the proposed approach, the temporal histogram data is first decomposed into multiple bins via an adaptive multi-bin signal representation. Then, at each level of the multi-resolution temporal space, decay information including both the amplitude and the lifetime of a single-exponential function is rapidly decoded based on a novel statistical estimator. Ultimately, a game-theoretic model consisting of two players in an “amplitude-lifetime” game is constructed to be able to robustly recover optimal fluorescence decay signal from a set of fused multi-bin estimates. In addition to theoretical demonstrations, the efficiency of the proposed framework is experimentally shown on both synthesised and real data in different imaging circumstances. On a challenging low photon-count regime, our approach achieves about 28% improvement in bias than the best competing method. On real images, the proposed method processes data on average around 63 times faster than the gold standard least squares fit. Implementation codes are available to researchers.

PMID:35609109 | DOI:10.1109/TBME.2022.3176224

IEEE Trans Cybern. 2022 May 24;PP. doi: 10.1109/TCYB.2022.3166975. Online ahead of print.

ABSTRACT

Clusters in real data are often restricted to low-dimensional subspaces rather than the entire feature space. Recent approaches to circumvent this difficulty are often computationally inefficient and lack theoretical justification in terms of their large-sample behavior. This article deals with the problem by introducing an entropy incentive term to efficiently learn the feature importance within the framework of center-based clustering. A scalable block-coordinate descent algorithm, with closed-form updates, is incorporated to minimize the proposed objective function. We establish theoretical guarantees on our method by Vapnik-Chervonenkis (VC) theory to establish strong consistency along with uniform concentration bounds. The merits of our method are showcased through detailed experimental analysis on toy examples as well as real data clustering benchmarks.

PMID:35609103 | DOI:10.1109/TCYB.2022.3166975

IEEE Trans Image Process. 2022 May 24;PP. doi: 10.1109/TIP.2022.3176210. Online ahead of print.

ABSTRACT

Denoising videos in real-time is critical in many applications, including robotics and medicine, where varying-light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone of our method is a novel, remarkably simple, temporal network of cascaded blocks with forward block output propagation. We train our architecture with short, long, and global residual connections by minimizing the restoration loss of pairs of frames, leading to a more effective training across noise levels. It is robust to heavy noise following Poisson-Gaussian noise statistics. The algorithm is evaluated on RAW and RGB data. We propose a denoising algorithm that requires no future frames to denoise a current frame, reducing its latency considerably. The visual and quantitative results show that our algorithm achieves state-of-the-art performance among efficient algorithms, achieving from two-fold to two-orders-of-magnitude speed-ups on standard benchmarks for video denoising.

PMID:35609095 | DOI:10.1109/TIP.2022.3176210

PLoS One. 2022 May 24;17(5):e0268472. doi: 10.1371/journal.pone.0268472. eCollection 2022.

ABSTRACT

BACKGROUND: Economically underdeveloped areas in western China are hotspots of tuberculosis, especially among students. However, the related spatial and temporal patterns and influencing factors are still unclear and there are few studies to analyze the causes of pulmonary tuberculosis in students from the perspective of space.

METHODS: We collected data regarding the reported incidence of pulmonary tuberculosis (PTB) among students at township level in Nanning, from 2012 to 2018. The reported incidence of pulmonary tuberculosis among students in Nanning was analyzed using spatial autocorrelation and spatial scan statistical analysis to depict hotspots of PTB incidence and spatial and temporal clustering. Spatial panel data of the reported incidence rates and influencing factors at district and county levels in Nanning were collected from 2015 to 2018. Then, we analyzed the spatial effects of incidence and influencing factors using the spatial Durbin model to explore the mechanism of each influencing factor in areas with high disease prevalence under spatial effects.

RESULTS: From 2012 to 2018, 1609 cases of PTB were reported among students in Nanning, with an average annual reported incidence rate of 14.84/100,000. Through the Joinpoint regression model, We observed a steady trend in the percentage of cases reported each year (P>0.05). There was spatial autocorrelation between the annual reported incidence and the seven-years average reported incidence from 2012 to 2018. The high-incidence area was distributed in the junction of six urban areas and spread to the periphery, with the junction at the center. The population of college students, per capita financial expenditure on health, per capita gross domestic product, and the number of health technicians per 1,000 population were all influencing factors in the reported incidence of PTB among students.

CONCLUSION: We identified spatial clustering of the reported incidence of PTB among students in Nanning, mainly located in the urban center and its surrounding areas. The clustering gradually decreased from the urban center to the surrounding areas. Spatial effects influenced the reported incidence of PTB. The population density of college students, per capita health financial expenditure, gross domestic product (GDP) per capita, and the number of health technicians per 1,000 were all influencing factors in the reported incidence of PTB among students.

PMID:35609085 | DOI:10.1371/journal.pone.0268472

PLoS One. 2022 May 24;17(5):e0264210. doi: 10.1371/journal.pone.0264210. eCollection 2022.

ABSTRACT

The development of robust nutrient management strategies have played a crucial role in improving crop productivity, profitability and nutrient use efficiency. Therefore, the implementation of efficient nutrient management stratigies is important for food security and environmental safety. Amongst the essential plant nutrients, managing nitrogen (N) and potassium (K) in wheat (Triticum aestivum L.) based production systems is citically important to maximize profitable production with minimal negative environmental impacts. We investigated the effects of different fertilizer-N (viz. 0-240 kg N ha-1; N0-N240) and fertilizer-K (viz. 0-90 kg K ha-1; K0-K90) application rates on wheat productivity, nutrient (N and K) use efficiency viz. partial factor productivity (PFPN/K), agronomic efficiency (AEN/K), physiological efficiency (PEN/K), reciprocal internal use efficiency (RIUEN/K), and profitability in terms of benefit-cost (B-C) ratio, gross returns above fertilizer cost (GRAFC) and the returns on investment (ROI) on fertilizer application. These results revealed that wheat productivity, plant growth and yield attributes, nutrients uptake and use efficiency increased significantly (p<0.05)with fertilizer-N application, although the interaction effect of N x K application was statistically non-significant (p<0.05). Fertilizer-N application at 120 kg N ha-1 (N120) increased the number of effective tillers (8.7%), grain yield (17.3%), straw yield (15.1%), total N uptake (25.1%) and total K uptake (16.1%) than the N80. Fertilizer-N application significantly increased the SPAD reading by ~4.2-10.6% with fertilizer-N application (N80-N240), compared with N0. The PFPN and PFPK increased significantly with fertilizer-N and K application in wheat. The AEN varied between 12.3 and 22.2 kg kg-1 with significantly higher value of 20.8 kg kg-1 in N120. Fertilizer-N application at higher rate (N160) significantly decreased the AEN by ~16.3% over N120. The N120treatment increased the AEK by ~52.6% than N80 treatment. Similarly the RIUEN varied between 10.6 and 25.6 kg Mg-1 grain yield, and increased significantly by ~80.2% with N120 as compared to N0 treatment. The RIUEK varied between 109 and 15.1 kg Mg-1 grain yield, and was significantly higher in N120 treatment. The significant increase in mean gross returns (MGRs) by ~17.3% and mean net returns (MNRs) by ~24.1% increased the B-C ratio by ~15.1% with N120 than the N80 treatment. Fertilizer-N application in N120 treatment increased the economic efficiency of wheat by ~24.1% and GRAFC by ~16.9%. Grain yield was significantly correlated with total N uptake (r = 0.932**, p<0.01), K uptake (r = 0.851**), SPAD value (r = 0.945**), green seeker reading (r = 0.956**), and the RIUEN (r = 0.910**). The artificial neural networks (ANNs) showed highly satisfactory performance in training and simulation of testing data-set on wheat grain yield. The calculated mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE) for wheat were 0.0087, 0.834 and 0.052, respectively. The well trained ANNs model was capable of producing consistency for the training and testing correlation (R2 = 0.994**, p<0.01) between the predicted and actual values of wheat grain yield, which implies that ANN model succeeded in wheat grain yield prediction.

PMID:35609063 | DOI:10.1371/journal.pone.0264210

PLoS One. 2022 May 24;17(5):e0268971. doi: 10.1371/journal.pone.0268971. eCollection 2022.

ABSTRACT

BACKGROUND: Patient’s knowledge about dispensed medications is one of the major factors that determine the rational use of medicines.

OBJECTIVES: This study aimed to assess exit-knowledge of ambulatory patients about their dispensed medications and associated factors at the outpatient pharmacy of Mizan-Tepi University Teaching Hospital, Southwest Ethiopia.

METHODS: A hospital-based cross-sectional study design was conducted from August to October 2021. Study subjects were selected by random sampling technique and were interviewed using a structured interview questionnaire. Binary logistic regression was used to identify factors associated with exit knowledge. At a 95% confidence interval (CI), p≤0.05 was considered statistically significant.

RESULT: Of the total 400 participants, 116 (29.0%) participants had sufficient exit-knowledge about their dispensed medication. Patients with higher educational level had increased exit knowledge of dispensed medications than those with no formal education (AOR: 5.590; 95% CI 1.019-30.666). Also, the nature of illness as being chronic significantly enlarged the odds (AOR 5.807; 95% CI 2.965-11.372) of having sufficient exit-knowledge. Participants who reported, “I do not know” and “I did not get enough information from the pharmacist” had lower odds (AOR 0.374; 95% CI: 0.142-0.982) and (AOR 0.166; 95% CI 0.062-0.445) of sufficient exit-knowledge in comparison to those who responded “I got enough information from the pharmacist” respectively. Furthermore, the odd of sufficient exit-knowledge was 7.62 times higher in those who claimed prescribing doctor as the source of information.

CONCLUSION: The majority of patients had insufficient exit-knowledge about their dispensed medications. Educational status, nature of the disease, perceived sufficiency of pharmacist knowledge, and source of information were significantly associated with exit knowledge.

PMID:35609061 | DOI:10.1371/journal.pone.0268971