Search Results (12)

Objectives: Despite optimal local control obtained with neoadjuvant chemoradiotherapy (CRT), data on overall survival (OS) and disease-free survival (DFS) of local advanced rectal cancer patients are still equivocal. This meta-analysis aimed to estimate the pathological complete response (pCR), regression rate, DFS, and OS probabilities of rectal cancer patients treated with a second chemotherapy drug added to fluoropyrimidine and long-term radiotherapy. Methods: Computerized bibliographic searches of MEDLINE, PUBMED, Web of Science and the Cochrane Central Register of Controlled Trials databases (1970–2023) were supplemented with hand searches of reference lists. Studies were included if they were randomised controlled trials (RCTs) comparing intensified chemotherapy with CRT to preoperative CRT and if they had patients with resectable, histologically proven rectal adenocarcinoma without metastases. Results: Eighteen RCTs (7695 patients) were analysed. Data on population, intervention, and outcomes were extracted from each RCT, following the intention-to-treat method, by three independent observers and combined using the DerSimonian and Laird methods. A chemotherapy with two drug and long-term radiotherapy CRT, compared to preoperative CRT (fluoropyrimidine and long-term radiotherapy), significantly increases the rate of pathological complete response (OR 1.37 (95% CI, 1.16–1.63) p = 0.0003) and the regression rate (OR 1.57 (95% CI, 1.16–2.14) p < 0.00001). Furthermore, it increases DFS (HR 0.87 (95% CI, 0.79 to 0.95) p = 0.002 and OS HR 0.84 (95% CI, 0.74 to 0.95) p = 0.007). The risk of severe adverse events (≥G3) is increased OR 1.96 (95% CI 1.35–2.85), p = 0.0005. Conclusions: In patients with resectable rectal cancer, intensified chemotherapy can reduce by 13% the risk of disease progression and by 16% the risk of death. Full article

This paper proposes the GD (Geometric Distribution) algorithm, a novel approach to enhance the default Adaptive Data Rate (ADR) mechanism in the Long-Range Wide Area Network (LoRaWAN). By leveraging the Probability Mass Function (PMF) of the GD model, the algorithm effectively addresses biased node distributions encountered in real-world scenarios. Its ability to finely adjust the weight factor (w) or the probability of success in allocating SFs enables the optimization of spreading factor (SF) allocation, thereby achieving the optimal Data Extraction Rate (DER). To evaluate the algorithm’s performance, simulations were conducted using the fixed node pattern derived from actual dairy farm locations in Ratchaburi province, Thailand. Comparative analyses were performed against the uniform random node pattern and existing algorithms, including the ADR, EXPLoRa, QCVM, and SD. The GD algorithm significantly outperformed existing methodologies for both fixed and uniform random node patterns, achieving a 14.3% and 4.8% improvement in DER over the ADR, respectively. While the GD algorithm consistently demonstrated superior DER values across varying coverage areas and payload sizes, it incurred a slight increase in energy consumption due to node allocations to higher SFs. Therefore, the trade-off between DER and energy consumption must be carefully weighed against the specific application. Full article

Objective: To systematically review and meta-analyze the predictive value of the Fournier gangrene severity index (FGSI), the simplified FGSI (SFGSI), and the Uludag FGSI (UFGSI) on mortality in patients affected by Fournier’s Gangrene (FG). Methods: A search was performed in PubMed, Web of Science, Embase, and the Cochrane Library, from January 2000 to May 2023, to identify original cohorts comparing data between surviving and non-surviving FG patients. The statistical analysis consisted of two parts. First, the mean and standard deviation (SD) of the FGSI, SFGSI, and UFGSI at admission were extrapolated from each study, and the pooled mean difference (MD) with 95% confidence interval (95% CI) was obtained using the Der Simonian–Laird random-effect model. Second, to evaluate the accuracy of the FGSI, SFGSI, and UFSGI in predicting mortality, true positive (TP), false positive (FP), true negative (TN), and false negative (FN) values were extracted where possible and reported in 2 × 2 contingency tables. The sensitivity, specificity, and AUC values were pooled, and summary receiver operating characteristic (SROC) curves were constructed. Results: Overall, forty studies comprising 2257 patients were included. The pooled analysis revealed that the FGSI, SFGSI, and UFGSI values at admission were higher in non-survivors than survivors (MD: 5.53 (95% CI: 4.68–6.37); MD: 2.41 (95% CI: 1.06–3.77); and MD: 5.47 (95% CI: 3.68–7.26), respectively). Moreover, the AUC values of the FGSI, SFGSI, and UFGSI were 0.90 (95% CI: 0.87–0.92), 0.84 (95% CI: 0.80–0.87), and 0.94 (95% CI: 0.92–0.96), respectively. Conclusions: The higher scores of the FGSI, SFGSI, and UFGSI on admission were associated with mortality. Moreover, when comparing accuracy rates, the UFGSI exhibited the highest AUC value. Full article

Background: The care provided in general practice to intravenous drug users (IDUs) with hepatitis C (HCV) extends beyond opioid substitution therapy. An aggregated analysis of HCV service utilization within general practice specifically related to diagnosis and treatment outcomes remains unknown from previous literature. Aims: This study aims to estimate the prevalence of HCV and analyze data related to the diagnosis and treatment-related outcomes of HCV patients with a history of intravenous drug use in the general practice setting. Design and setting: A systematic review and meta-analysis in general practice. Methods: This review included studies published in the following databases: EMBASE, PubMed, and Cochrane Central Register of Controlled Trials. Two reviewers independently extracted data in standard forms in Covidence. A meta-analysis was done using a DerSimonian and Laird random-effects model with inverse variance weighting. Results: A total of 20,956 patients from 440 general practices participated in the 18 selected studies. A meta-analysis of 15 studies showed a 46% (95% confidence interval (CI), 26–67%) prevalence rate of hepatitis C amongst IDUs. Genotype information was available in four studies and treatment-related outcomes in 11 studies. Overall, treatment uptake was 9%, with a cure rate of 64% (95% CI, 43–83%). However, relevant information, such as specific treatment regimens, treatment duration and doses, and patient comorbidities, was poorly documented in these studies. Conclusion: The prevalence of HCV in IDUs is 46% in general practice. Only ten studies reported HCV-related treatment outcomes; however, the overall uptake rate was below 10%, with a cure rate of 64%. Likewise, the genotypic variants of HCV diagnoses, medication types, and doses were poorly reported, suggesting a need for further research into this aspect of care within this patient group to ensure optimal treatment outcomes. Full article

Currently, there is no clear consensus regarding the role of active surveillance (AS) in the management of intermediate-risk prostate cancer (IRPC) patients. We aim to analyse data from the available literature on the outcomes of AS in the management of IRPC patients and compare them with low-risk prostate cancer (LRPC) patients. A comprehensive literature search was performed, and relevant data were extracted. Our primary outcome was treatment-free survival, and secondary outcomes were metastasis-free survival, cancer-specific survival, and overall survival. The DerSimonian–Laird random-effects method was used for the meta-analysis. Out of 712 studies identified following an initial search, 25 studies were included in the systematic review. We found that both IRPC and LRPC patients had nearly similar 5, 10, and 15 year treatment-free survival rate, 5 and 10 year metastasis-free survival rate, and 5 year overall survival rate. However, cancer-specific survival rates at 5, 10, and 15 years were significantly lower in IRPC compared to LRPC group. Furthermore, IRPC patients had significantly inferior long-term overall survival rate (10 and 15 year) and metastasis-free survival rate (15 year) compared to LRPC patients. Both the clinicians and the patients can consider this information during the informed decision-making process before choosing AS. Full article

The implementation of smart networks has made great progress due to the development of the Internet of Things (IoT). LoRa is one of the most prominent technologies in the Internet of Things industry, primarily due to its ability to achieve long-distance transmission while consuming less power. In this work, we modeled different environments and assessed the performances of networks by observing the effects of various factors and network parameters. The path loss model, the deployment area size, the transmission power, the spreading factor, the number of nodes and gateways, and the antenna gain have a significant effect on the main performance metrics such as the energy consumption and the data extraction rate of a LoRa network. In order to examine these parameters, we performed simulations in OMNeT++ using the open source framework FLoRa. The scenarios which were investigated in this work include the simulation of rural and urban environments and a parking area model. The results indicate that the optimization of the key parameters could have a huge impact on the deployment of smart networks. Full article

Partial least squares regression (PLSR) prediction models were developed using hyperspectral imaging for noninvasive detection of the five most representative functional components in Brassica juncea leaves: chlorophyll, carotenoid, phenolic, glucosinolate, and anthocyanin contents. The region of interest for functional component analysis was chosen by polygon selection and the extracted average spectra were used for model development. For pre-processing, 10 combinations of Savitzky–Golay filter (S. G. filter), standard normal variate (SNV), multiplicative scatter correction (MSC), 1st-order derivative (1st-Der), 2nd-order derivative (2nd-Der), and normalization were applied. Root mean square errors of calibration (RMSEP) was used to assess the performance accuracy of the constructed prediction models. The prediction model for total anthocyanins exhibited the highest prediction level (R_V² = 0.8273; RMSEP = 2.4277). Pre-processing combination of SNV and 1st-Der with spectral data resulted in high-performance prediction models for total chlorophyll, carotenoid, and glucosinolate contents. Pre-processing combination of S. G. filter and SNV gave the highest prediction rate for total phenolics. SNV inclusion in the pre-processing conditions was essential for developing high-performance accurate prediction models for functional components. By enabling visualization of the distribution of functional components on the hyperspectral images, PLSR prediction models will prove valuable in determining the harvest time. Full article

Background The presence of atrial fibrillation (AF) in patients with heart failure with preserved ejection fraction (HFpEF) dramatically increases higher morbidity and mortality. Recent studies have suggested that early rhythm control may alleviate the burden of poor outcomes. Currently, there remain limited data on whether rhythm or rate control has better efficacy. This study sought to compare both strategies in HFpEF patients with AF. Methods Databases were searched throughout 2020. Studies that reported cardiovascular outcomes amongst HFpEF patients with AF who received either rhythm or rate control were included. Estimates of the effects from the individual studies were extracted and combined using random-effects, a generic inverse variance method of DerSimonian and Laird. Results Five observational studies were included in the analysis, consisting of 16,953 patients, 13.8% of whom were receiving rhythm control. In comparison with rate control, rhythm control was associated with decreased overall mortality rates (pooled RR 0.85, 95% CI 0.75–0.95, with I² = 0%, p value = 0.009). Conclusions In HFpEF patients with AF, rhythm control was associated with lower mortality, compared to rate control. Further studies are warranted to validate our observation. Full article

Adenocarcinoma of the gastroesophageal junction (AEG) ranks among the most common cancers in the Western world with increasing incidence. However, the prognostic influence and applicability of the Lauren classification was not examined in detail before. The purpose of this analysis was to analyze the oncologic outcomes of GE-junction cancer related to the Lauren histotype in a large single center cohort. Data from the prospectively documented database of the Klinikum Rechts der Isar (TUM School of Medicine) for patients undergoing curatively intended oncologic resection for GE-junction cancer between 1984 and 2018 were extracted. Univariate and multivariate regression analyses were performed to identify predictors for overall survival. Kaplan-Meier analyses were done to investigate the survival rates according to the Lauren histotype. After identification of two distinct histologic categories with prognostic implications, propensity score matching (PSM) was performed to balance for confounders and evaluate its oncologic outcomes retrospectively. In the time period indicated, 1710 patients were treated for GE-junction cancer. Exclusion criteria were: R2-resections (n = 134), metastatic disease (n = 296), 30-day mortality (n = 45), Siewert type I (n = 21), and missing/incomplete data (n = 61). Finally, 1153 patients were analyzed. In a multiple variable analysis, age, UICC-stage, all Lauren histotypes, R-stage, and postoperative complications were significant predictors of overall survival. Kaplan Meier analysis demonstrated significant survival differences between intestinal, diffuse, and mixed Lauren-histotypes (p = 0.001 and p = 0.029). Survival rates were comparable between non-classifiable and intestinal Lauren-types (p = 0.16) and between diffuse and mixed types (p = 0.56). When combining non-classifiable, well, and moderately differentiated Lauren-types and combining poorly differentiated intestinal, diffuse, and mixed types, two highly prognostic groups were identified (p < 0.0001). This was confirmed after PSM for possible confounders. The Lauren histotypes demonstrate highly prognostic value after oncologic resection of GE-junction cancer (Siewert type II and type III) in a single center Western patient cohort. A simplified histotype classification based on Lauren subtypes revealed a clear distinction of prognostic groups and should be considered for further evaluation. Full article

Low Power Wide Area Networks (LPWAN) enable a growing number of Internet-of-Things (IoT) applications with large geographical coverage, low bit-rate, and long lifetime requirements. LoRa (Long Range) is a well-known LPWAN technology that uses a proprietary Chirp Spread Spectrum (CSS) physical layer, while the upper layers are defined by an open standard—LoRaWAN. In this paper, we propose a simple yet effective method to improve the Quality-of-Service (QoS) of LoRaWAN networks by fine-tuning specific radio parameters. Through a Mixed Integer Linear Programming (MILP) problem formulation, we find optimal settings for the Spreading Factor (SF) and Carrier Frequency (CF) radio parameters, considering the network traffic specifications as a whole, to improve the Data Extraction Rate (DER) and to reduce the packet collision rate and the energy consumption in LoRa networks. The effectiveness of the optimization procedure is demonstrated by simulations, using LoRaSim for different network scales. In relation to the traditional LoRa radio parameter assignment policies, our solution leads to an average increase of 6% in DER, and a number of collisions 13 times smaller. In comparison to networks with dynamic radio parameter assignment policies, there is an increase of 5%, 2.8%, and 2% of DER, and a number of collisions 11, 7.8 and 2.5 times smaller than equal-distribution, Tiurlikova’s (SOTA), and random distribution, respectively. Regarding the network energy consumption metric, the proposed optimization obtained an average consumption similar to Tiurlikova’s, and 2.8 times lower than the equal-distribution and random dynamic allocation policies. Furthermore, we approach the practical aspects of how to implement and integrate the optimization mechanism proposed in LoRa, guaranteeing backward compatibility with the standard protocol. Full article

Background: Kidney transplantation in patients with atypical hemolytic uremic syndrome (aHUS) is frequently complicated by recurrence, resulting in thrombotic microangiopathy in the renal allograft and graft loss. We aimed to assess the use of eculizumab in the prevention and treatment of aHUS recurrence after kidney transplantation. Methods: Databases (MEDLINE, EMBASE and Cochrane Database) were searched through February 2019. Studies that reported outcomes of adult kidney transplant recipients with aHUS treated with eculizumab were included. Estimated incidence rates from the individual studies were extracted and combined using random-effects, generic inverse variance method of DerSimonian and Laird. Protocol for this systematic review has been registered with PROSPERO (International Prospective Register of Systematic Reviews; no. CRD42018089438). Results: Eighteen studies (13 cohort studies and five case series) consisting of 380 adult kidney transplant patients with aHUS who received eculizumab for prevention and treatment of post-transplant aHUS recurrence were included in the analysis. Among patients who received prophylactic eculizumab, the pooled estimated incidence rates of recurrent thrombotic microangiopathy (TMA) after transplantation and allograft loss due to TMA were 6.3% (95%CI: 2.8–13.4%, I² = 0%) and 5.5% (95%CI: 2.9–10.0%, I² = 0%), respectively. Among those who received eculizumab for treatment of post-transplant aHUS recurrence, the pooled estimated rates of allograft loss due to TMA was 22.5% (95%CI: 13.6–34.8%, I² = 6%). When the meta-analysis was restricted to only cohort studies with data on genetic mutations associated with aHUS, the pooled estimated incidence of allograft loss due to TMA was 22.6% (95%CI: 13.2–36.0%, I² = 10%). We found no significant publication bias assessed by the funnel plots and Egger’s regression asymmetry test (p > 0.05 for all analyses). Conclusions: This study summarizes the outcomes observed with use of eculizumab for prevention and treatment of aHUS recurrence in kidney transplantation. Our results suggest a possible role for anti-C5 antibody therapy in the prevention and management of recurrent aHUS. Full article

Cooking loss (CL) is a critical quality attribute directly relating to meat juiciness. The potential of the hyperspectral imaging (HSI) technique was investigated for non-invasively classifying and visualizing the CL of fresh broiler breast meat. Hyperspectral images of total 75 fresh broiler breast fillets were acquired by the system operating in the visible and near-infrared (VNIR, 400–1000 nm) range. Mean spectra were extracted from regions of interest (ROIs) determined by pure muscle tissue pixels. CL was firstly measured by calculating the weight loss in cooking, and then fillets were grouped into high-CL and low-CL according to the threshold of 20%. The classification methods partial least square-discriminant analysis (PLS-DA) and radial basis function-support vector machine (RBF-SVM) were applied, respectively, to determine the optimal spectral calibration strategy. Results showed that the PLS-DA model developed using the data, that is, first-order derivative (Der1) of VNIR full spectra, performed best with correct classification rates (CCRs) of 0.90 and 0.79 for the calibration and prediction sets, respectively. Furthermore, to simplify the optimal PLS-DA model and make it practical, effective wavelengths were individually selected using uninformative variable elimination (UVE) and competitive adaptive reweighted sampling (CARS). Through performance comparison, the CARS-PLS-DA combination was identified as the optimal method and the PLS-DA model built with 18 informative wavelengths selected by CARS resulted in good CCRs of 0.86 and 0.79. Finally, classification maps were created by predicting CL categories of each pixel in the VNIR hyperspectral images using the CARS-PLS-DA model, and the general CL categories of fillets were readily discernible. The overall results were encouraging and showed the promising potential of the VNIR HSI technique for classifying fresh broiler breast fillets into different CL categories. Full article