Conjunctions of Among Constraints

Many existing global constraints can be encoded as a conjunction of among constraints. An among constraint holds if the number of the variables in its scope whose value belongs to a prespecified set, which we call its range, is within some given bounds. It is known that domain filtering algorithms can benefit from reasoning about the interaction of among constraints so that values can be filtered out taking into consideration several among constraints simultaneously. The present pa- per embarks into a systematic investigation on the circumstances under which it is possible to obtain efficient and complete domain filtering algorithms for conjunctions of among constraints. We start by observing that restrictions on both the scope and the range of the among constraints are necessary to obtain meaningful results. Then, we derive a domain flow-based filtering algorithm and present several applications. In particular, it is shown that the algorithm unifies and generalizes several previous existing results.Comment: 15 pages plus appendi

Constraint Programming for LNG Ship Scheduling and Inventory Management

Abstract We propose a constraint programming approach for the optimization of inventory routing in the liquefied natural gas industry. We present two constraint programming models that rely on a disjunctive scheduling representation of the problem. We also propose an iterative search heuristic to generate good feasible solutions for these models. Computational results on a set of largescale test instances demonstrate that our approach can find better solutions than existing approaches based on mixed integer programming, while being 4 to 10 times faster on average

Deep Learning-Based Grading of Ductal Carcinoma In Situ in Breast Histopathology Images

Ductal carcinoma in situ (DCIS) is a non-invasive breast cancer that can progress into invasive ductal carcinoma (IDC). Studies suggest DCIS is often overtreated since a considerable part of DCIS lesions may never progress into IDC. Lower grade lesions have a lower progression speed and risk, possibly allowing treatment de-escalation. However, studies show significant inter-observer variation in DCIS grading. Automated image analysis may provide an objective solution to address high subjectivity of DCIS grading by pathologists. In this study, we developed a deep learning-based DCIS grading system. It was developed using the consensus DCIS grade of three expert observers on a dataset of 1186 DCIS lesions from 59 patients. The inter-observer agreement, measured by quadratic weighted Cohen's kappa, was used to evaluate the system and compare its performance to that of expert observers. We present an analysis of the lesion-level and patient-level inter-observer agreement on an independent test set of 1001 lesions from 50 patients. The deep learning system (dl) achieved on average slightly higher inter-observer agreement to the observers (o1, o2 and o3) ($\kappa_{o1,dl}=0.81, \kappa_{o2,dl}=0.53, \kappa_{o3,dl}=0.40$) than the observers amongst each other ($\kappa_{o1,o2}=0.58, \kappa_{o1,o3}=0.50, \kappa_{o2,o3}=0.42$) at the lesion-level. At the patient-level, the deep learning system achieved similar agreement to the observers ($\kappa_{o1,dl}=0.77, \kappa_{o2,dl}=0.75, \kappa_{o3,dl}=0.70$) as the observers amongst each other ($\kappa_{o1,o2}=0.77, \kappa_{o1,o3}=0.75, \kappa_{o2,o3}=0.72$). In conclusion, we developed a deep learning-based DCIS grading system that achieved a performance similar to expert observers. We believe this is the first automated system that could assist pathologists by providing robust and reproducible second opinions on DCIS grade

Continuity of care for patients with de novo metastatic cancer during the COVID-19 pandemic:A population-based observational study

During the COVID-19 pandemic recommendations were made to adapt cancer care. This population-based study aimed to investigate possible differences between the treatment of patients with metastatic cancer before and during the pandemic by comparing the initial treatments in five COVID-19 periods (weeks 1–12 2020: pre-COVID-19, weeks 12–20 2020: 1st peak, weeks 21–41 2020: recovery, weeks 42–53 2020: 2nd peak, weeks 1–20 2021: prolonged 2nd peak) with reference data from 2017 to 2019. The proportion of patients receiving different treatment modalities (chemotherapy, hormonal therapy, immunotherapy or targeted therapy, radiotherapy primary tumor, resection primary tumor, resection metastases) within 6 weeks of diagnosis and the time between diagnosis and first treatment were compared by period. In total, 74,208 patients were included. Overall, patients were more likely to receive treatments in the COVID-19 periods than in previous years. This mainly holds for hormone therapy, immunotherapy or targeted therapy and resection of metastases. Lower odds were observed for resection of the primary tumor during the recovery period (OR 0.87; 95% CI 0.77–0.99) and for radiotherapy on the primary tumor during the prolonged 2nd peak (OR 0.84; 95% CI 0.72–0.98). The time from diagnosis to the start of first treatment was shorter, mainly during the 1st peak (average 5 days, p &lt;.001). These findings show that during the first 1.5 years of the COVID-19 pandemic, there were only minor changes in the initial treatment of metastatic cancer. Remarkably, time from diagnosis to first treatment was shorter. Overall, the results suggest continuity of care for patients with metastatic cancer during the pandemic.</p

Population-based impact of COVID-19 on incidence, treatment, and survival of patients with pancreatic cancer

Background: The COVID-19 pandemic has put substantial strain on the healthcare system of which the effects are only partly elucidated. This study aimed to investigate the impact on pancreatic cancer care. Methods: All patients diagnosed with pancreatic cancer between 2017 and 2020 were selected from the Netherlands Cancer Registry. Patients diagnosed and/or treated in 2020 were compared to 2017–2019. Monthly incidence was calculated. Patient, tumor and treatment characteristics were analyzed and compared using Chi-squared tests. Survival data was analyzed using Kaplan–Meier and Log-rank tests. Results: In total, 11019 patients were assessed. The incidence in quarter (Q)2 of 2020 was comparable with that in Q2 of 2017–2019 (p = 0.804). However, the incidence increased in Q4 of 2020 (p = 0.031), mainly due to a higher incidence of metastatic disease (p = 0.010). Baseline characteristics, surgical resection (15% vs 16%; p = 0.466) and palliative systemic therapy rates (23% vs 24%; p = 0.183) were comparable. In 2020, more surgically treated patients received (neo)adjuvant treatment compared to 2017–2019 (73% vs 67%; p = 0.041). Median overall survival was comparable (3.8 vs 3.8 months; p = 0.065). Conclusion: This nationwide study found a minor impact of the COVID-19 pandemic on pancreatic cancer care and outcome. The Dutch health care system was apparently able to maintain essential care for patients with pancreatic cancer

A Multifactorial Approach for Surveillance of Shigella spp. and Entero-Invasive Escherichia coli Is Important for Detecting (Inter)national Clusters

Shigella spp. and entero-invasive Escherichia coli (EIEC) can cause mild diarrhea to dysentery. In Netherlands, although shigellosis is a notifiable disease, there is no laboratory surveillance for Shigella spp. and EIEC in place. Consequently, the population structure for circulating Shigella spp. and EIEC isolates is not known. This study describes the phenotypic and serological characteristics, the phenotypic and genetic antimicrobial resistance (AMR) profiles, the virulence gene profiles, the classic multi-locus sequence types (MLST) and core genome (cg)MLST types, and the epidemiology of 414 Shigella spp. and EIEC isolates collected during a cross-sectional study in Netherlands in 2016 and 2017. S. sonnei (56%), S. flexneri (25%), and EIEC (15%) were detected predominantly in Netherlands, of which the EIEC isolates were most diverse according to their phenotypical profile, O-types, MLST types, and cgMLST clades. Virulence gene profiling showed that none of the isolates harbored Shiga toxin genes. Most S. flexneri and EIEC isolates possessed nearly all virulence genes examined, while these genes were only detected in approximately half of the S. sonnei isolates, probably due to loss of the large invasion plasmid upon subculturing. Phenotypical resistance correlated well with the resistant genotype, except for the genes involved in resistance to aminoglycosides. A substantial part of the characterized isolates was resistant to antimicrobials advised for treatment, i.e., 73% was phenotypically resistant to co-trimoxazole and 19% to ciprofloxacin. AMR was particularly observed in isolates from male patients who had sex with men (MSM) or from patients that had traveled to Asia. Furthermore, isolates related to international clusters were also circulating in Netherlands. Travel-related isolates formed clusters with isolates from patients without travel history, indicating their emergence into the Dutch population. In conclusion, laboratory surveillance using whole genome sequencing as high-resolution typing technique and for genetic characterization of isolates complements the current epidemiological surveillance, as the latter is not sufficient to detect all (inter)national clusters, emphasizing the importance of multifactorial public health approaches

Combining Symmetry Breaking and Global Constraints

Abstract. We propose a new family of constraints which combine together lexicographical ordering constraints for symmetry breaking with other common global constraints. We give a general purpose propagator for this family of constraints, and show how to improve its complexity by exploiting properties of the included global constraints.

Heart failure and promotion of physical activity before and after cardiac rehabilitation (HF-aPProACH):a study protocol

Abstract Aims Lifestyle changes, such as increasing physical activity (PA), are a cornerstone of treatment of patients with chronic heart failure (HF). However, improving PA in HF patients is challenging, and low participation rates for cardiac rehabilitation (CR) as well as relapse to low PA levels after CR are major issues. We designed a randomized controlled trial to investigate if PA monitoring with motivational feedback before and after centre‐based CR in HF patients with reduced ejection fraction (HFrEF) will lead to a clinically meaningful increase in physical fitness. Methods and results A randomized controlled trial will be conducted in a sample of 180 HFrEF patients (New York Heart Association Class II/III) who are referred to 12‐week standard CR. Patients will be randomized (2:1) to (1) standard of care (SoC) plus wearing a PA monitoring device (Fitbit Charge 3) with personalized step goals, feedback and motivation or (2) SoC only. The intervention lasts ±7 months: 4–5 weeks before CR, 12 weeks during CR and 12 weeks after CR. Measurements will take place at three time points. The primary endpoint is the change in the distance in 6‐min walking test (6MWT) over the entire study period. Other endpoints include step count, grip strength, quality of life and all‐cause mortality or hospitalization. Conclusions HF‐aPProACH will provide novel information on the effectiveness of remote PA stimulation and feedback before, during and after standard CR using a commercially available device to improve physical fitness in HFrEF patients

Impact of the COVID-19 Pandemic on Colorectal Cancer Care in the Netherlands: A Population-based Study

Contains fulltext : 283493.pdf (Publisher’s version ) (Open Access)INTRODUCTION: The COVID-19 pandemic disrupted health care services worldwide. In the Netherlands, the first confirmed COVID-19 infection was on February 27, 2020. We aimed to investigate the impact of the pandemic on colorectal cancer care in the Netherlands. METHODS: Colorectal cancer patients who were diagnosed in 25 hospitals in weeks 2 to 26 of the year 2020 were selected from the Netherlands Cancer Registry (NCR) and divided in 4 periods. The average number of patients treated per type of initial treatment was analyzed by the Mantel-Haenszel test adjusted for age. Median time between diagnosis and treatment and between (neo)adjuvant therapy and surgery were analyzed by the Mann Whitney test. Percentages of (acute) resection, stoma and (neo)adjuvant therapy were compared using the Chi-squared test. RESULTS: In total, 1,653 patients were included. The patient population changed during the COVID-19 pandemic regarding higher stage and more clinical presentation with ileus at time of diagnosis. Slight changes were found regarding type of initial treatment. Median time between diagnosis and treatment decreased on average by 4.5 days during the pandemic. The proportion of colon cancer patients receiving a stoma significantly increased with 6.5% during the pandemic. No differences were found in resection rate and treatment with (neo)adjuvant therapy. CONCLUSION: Despite the disruptive impact of the COVID-19 pandemic on global health care, the impact on colorectal cancer care in the Netherlands was limited