Strategic placement of volunteer responder system defibrillators.

Volunteer responder systems (VRS) alert and guide nearby lay rescuers towards the location of an emergency. An application of such a system is to out-of-hospital cardiac arrests, where early cardiopulmonary resuscitation (CPR) and defibrillation with an automated external defibrillator (AED) are crucial for improving survival rates. However, many AEDs remain underutilized due to poor location choices, while other areas lack adequate AED coverage. In this paper, we present a comprehensive data-driven algorithmic approach to optimize deployment of (additional) public-access AEDs to be used in a VRS. Alongside a binary integer programming (BIP) formulation, we consider two heuristic methods, namely Greedy and Greedy Randomized Adaptive Search Procedure (GRASP), to solve the gradual Maximal Covering Location (MCLP) problem with partial coverage for AED deployment. We develop realistic gradually decreasing coverage functions for volunteers going on foot, by bike, or by car. A spatial probability distribution of cardiac arrest is estimated using kernel density estimation to be used as input for the models and to evaluate the solutions. We apply our approach to 29 real-world instances (municipalities) in the Netherlands. We show that GRASP can obtain near-optimal solutions for large problem instances in significantly less time than the exact method. The results indicate that relocating existing AEDs improves the weighted average coverage from 36% to 49% across all municipalities, with relative improvements ranging from 1% to 175%. For most municipalities, strategically placing 5 to 10 additional AEDs can already provide substantial improvements.

Turnaround time prediction for clinical chemistry samples using machine learning.

OBJECTIVES: Turnaround time (TAT) is an essential performance indicator of a medical diagnostic laboratory. Accurate TAT prediction is crucial for taking timely action in case of prolonged TAT and is important for efficient organization of healthcare. The objective was to develop a model to accurately predict TAT, focusing on the automated pre-analytical and analytical phase. METHODS: A total of 90,543 clinical chemistry samples from Erasmus MC were included and 39 features were analyzed, including priority level and workload in the different stages upon sample arrival. PyCaret was used to evaluate and compare multiple regression models, including the Extra Trees (ET) Regressor, Ridge Regression and K Neighbors Regressor, to determine the best model for TAT prediction. The relative residual and SHAP (SHapley Additive exPlanations) values were plotted for model evaluation. RESULTS: The regression-tree-based method ET Regressor performed best with an R2 of 0.63, a mean absolute error of 2.42 min and a mean absolute percentage error of 7.35%, where the average TAT was 30.09 min. Of the test set samples, 77% had a relative residual error of at most 10%. SHAP value analysis indicated that TAT was mainly influenced by the workload in pre-analysis upon sample arrival and the number of modules visited. CONCLUSIONS: Accurate TAT predictions were attained with the ET Regressor and features with the biggest impact on TAT were identified, enabling the laboratory to take timely action in case of prolonged TAT and helping healthcare providers to improve planning of scarce resources to increase healthcare efficiency.

Efficacy and safety profile of COVID-19 vaccine in cancer patients: a prospective, multicenter cohort study.

Aim: To compare the seropositivity rate of cancer patients with noncancer controls after inactive SARS-CoV-2 vaccination and evaluate the factors affecting seropositivity. Method: Spike IgG antibodies against SARS-CoV-2 were measured in blood samples of 776 cancer patients and 715 noncancer volunteers. An IgG level ≥50 AU/ml is accepted as seropositive. Results: The seropositivity rate was 85.2% in the patient group and 97.5% in the control group. The seropositivity rate and antibody levels were significantly lower in the patient group (p < 0.001). Age and chemotherapy were associated with lower seropositivity in cancer patients (p < 0.001). Conclusion: This study highlighted the efficacy and safety of the inactivated vaccine in cancer patients. Clinical Trials Registration: NCT04771559 (ClinicalTrials.gov).

Cancer patients are at high risk for infection with SARS-CoV-2 and of developing the associated disease, COVID-19, which therefore puts them in the priority group for vaccination. This study evaluated the efficacy and safety of inactive SARSCoV-2 vaccination, an inactivated virus vaccine, in cancer patients. The immune response rate, defined as seropositivity, was 85.2% in the cancer patient group and 97.5% in the control group. The levels of antibodies, which are blood markers of immune response to the vaccine, were also significantly lower in the patient group, especially in those older than 60 years and receiving chemotherapy. These results highlight the importance of determining the effective vaccine type and dose in cancer patients to protect them from COVID-19 without disrupting their cancer treatment.

Radiotherapy treatment scheduling considering time window preferences.

External-beam radiotherapy treatments are delivered by a linear accelerator (linac) in a series of high-energy radiation sessions over multiple days. With the increase in the incidence of cancer and the use of radiotherapy (RT), the problem of automatically scheduling RT sessions while satisfying patient preferences regarding the time of their appointments becomes increasingly relevant. While most literature focuses on timeliness of treatments, several Dutch RT centers have expressed their need to include patient preferences when scheduling appointments for irradiation sessions. In this study, we propose a mixed-integer linear programming (MILP) model that solves the problem of scheduling and sequencing RT sessions considering time window preferences given by patients. The MILP model alone is able to solve the problem to optimality, scheduling all sessions within the desired window, in reasonable time for small size instances up to 66 patients and 2 linacs per week. For larger centers, we propose a heuristic method that pre-assigns patients to linacs to decompose the problem in subproblems (clusters of linacs) before using the MILP model to solve the subproblems to optimality in a sequential manner. We test our methodology using real-world data from a large Dutch RT center (8 linacs). Results show that, combining the heuristic with the MILP model, the problem can be solved in reasonable computation time with as few as 2.8% of the sessions being scheduled outside the desired time window.

Tp-e interval, Tp-e/QT and Tp-e/QTc ratio in hypertensive patients with primary aldosteronism.

Introduction: There is no study evaluating the Tp-e/QT and Tp-e/QTc ratios with T wave peak to end interval (Tp-e interval) used for evaluation of cardiac arrhythmia risk and ventricular repolarization changes in patients with primary aldosteronism (PA). We aimed to investigate whether there was a change in Tp-e interval, Tp-e/QT and Tp-e/QTc ratios in patients with PA.Method: Thirty patients with newly diagnosed hypertension (HT) and PA and 30 patients with primary HT were included. Twelve-lead electrocardiography (ECG) was performed in all patients. Tp-e interval, Tp-e/QT and Tp-e/QTc ratios were measured in addition to routine measurements in ECG.Results: Sodium, potassium, and plasma renin activity (PRA) were significantly lower in patients with PA; systolic and diastolic blood pressure, plasma aldosterone, plasma aldosterone/PRA were significantly higher in patients with PA (p < .05 for each one). When ventricular repolarization parameters were examined; while QT and QTc interval were similar between two groups, Tp-e interval, Tp-e/QT and Tp-e/QTc ratio values were significantly higher in patients with PA (p < .05 for each one). Tp-e interval, Tp-e/QT and Tp-e/QTc ratio values were positively correlated with the serum calcium, aldosterone, and aldosterone/PRA levels and negatively correlated with serum sodium, potassium, renin levels (p < .05 for each one). In linear regression analyses, Tp-e interval, Tp-e/QT and Tp-e/QTc ratios were independently associated with the aldosterone/PRA ratio.Conclusion: Tp-e interval, Tp-e/QT and Tp-e/QTc were increased in hypertensive patients with PA and were independently associated with aldosterone/PRA levels. This may be related to the changing neuroendocrine state in patients with PA.

Morning blood pressure surge increases in patients with hypertensive primary hyperparathyroidism and is independently associated with serum calcium level.

Introduction: There is not enough data on the effects of primary hyperparathyroidism (pHPT) on morning blood pressure surge (MBPS) in the literature. We aimed to determine whether there was any change in MBPS value in patients with hypertensive pHPT and to determine the parameters related to MBPS.Method: 80 patients with newly diagnosed pHPT with hypertension (HT) and 80 controls with newly diagnosed hypertension were included. Routine laboratory examinations and ambulatory blood pressure monitoring (ABPM) were performed in all patients.Results: In patients with pHPT, blood urea nitrogen (BUN), triglyceride, hs-CRP, uric acid, serum calcium (Ca), parathormone (PTH), daytime SBP and MBPS levels are higher than others (p < 0.05). Body mass index (BMI) and Ca level were independently associated with MBPS. In patients with MBPS ≥ 25 mmHg, BMI, BUN, creatinine, uric acid, Ca and PTH levels were found to be higher than others. BMI values and Ca levels determine the patients with MBPS ≥ 25 mmHg (p < 0.05) independently. According to this analysis, increase in BMI (for each 1 unit) and Ca level (for each 0.1 mg/dL) was found to increase the probability of MBPS ≥ 25 mmHg by 17.8% and 7.7%, respectively. When the cut-off value for Ca was taken as 10 mg/dL, the patients with MBPS ≥ 25 mmHg were determined with 73.5% sensitivity and 73.1% specificity.Conclusion: MBPS significantly increases in patients with newly diagnosed hypertensive pHPT. This increase in MBPS is closely associated with increased Ca levels. In patients with pHPT, lowering the Ca level below 10 mg/dL may have clinical implications.

A critical review of laboratory performance indicators.

Healthcare budgets worldwide are under constant pressure to reduce costs while improving efficiency and quality. This phenomenon is also visible in clinical laboratories. Efficiency gains can be achieved by reducing the error rate and by improving the laboratory's layout and logistics. Performance indicators (PIs) play a crucial role in this process as they allow for performance assessment. This review aids in the process for selecting laboratory PIs-which is not trivial-by providing an overview of frequently used PIs in the literature that can also be used in clinical laboratories. We conducted a systematic review of the laboratory medicine literature on PIs. As the testing process in clinical laboratories can be viewed as a production process, we also reviewed the production processes literature on PIs. The reviewed literature relates to the design, optimization or performance assessment of such processes. The most frequently cited PIs relate to pre-analytical errors, timeliness, resource utilization, cost, and the amount of congestion. Their citation frequency in the literature is used as a proxy for their importance. PIs are discussed in terms of their definition, measurability and impact. The use of suitable PIs is crucial in production processes, including clinical laboratories. By also reviewing the production processes literature, additional relevant PIs for clinical laboratories were found. The PIs in the laboratory medicine literature mostly relate to laboratory errors, while the PIs in the production processes literature relate to the amount of congestion in the process.

Increased carotid-femoral pulse wave velocity and common carotid artery intima-media thickness obtained to assess target organ damage in hypertensive patients are closely related.

BACKGROUND: Increased carotid-femoral pulse wave velocity (CF-PWV) and increased carotid intima-media thickness (IMT) in hypertension (HT) patients are indicators of asymptomatic organ damage. The relationship between carotid IMT and CF-PWV has been shown; studies comparing CF-PWV and IMT values within different vascular regions are limited. We aimed to investigate the relationship between IMT value measured from different anatomical regions and CF-PWV, and the localization of IMT that determines increased CF-PWV best. METHODS: This study included 312 patients with HT. CF-PWV measurements with Doppler ultrasonography (USG). Vascular IMTs were measurements of common-internal carotid, brachial, and femoral arteries with B-mode USG (CC-IMT, IC-IMT, B-IMT, and F-IMT, respectively). Patients were divided into two groups according to their CF-PWV value (Increased CF-PWV >10 m/s and normal CF-PWV ≤10m/s). RESULTS: Increased CF-PWV was detected in 54 (17.3%) of HT patients. The patient group with increased CF-PWV was older, and their CC-IMT, IC-IMT and F-IMT values were found to be higher. The other 3 IMT increases excluding B-IMT were closely related to the CF-PWV increase. Only age and CC-IMT values were found to be most closely related to CF-PWV. CC-IMT and age were found to be independently associated with increased CF-PWV. CC-IMT (each-0.1 mm) and age (each year) were found to augment the development of increased CF-PWV by 50.3% and 14.6%, respectively. CONCLUSION: There is a close relationship between CC-IMT and CF-PWV increase in HT. It was thought that it would still be more useful to look at the increase of CC-IMT compared to other vascular regions for screening asymptomatic organ damage.

Improving workflow control in radiotherapy using discrete-event simulation.

BACKGROUND: In radiotherapy, minimizing the time between referral and start of treatment (waiting time) is important to possibly mitigate tumor growth and avoid psychological distress in cancer patients. Radiotherapy pre-treatment workflow is driven by the scheduling of the first irradiation session, which is usually set right after consultation (pull strategy) or can alternatively be set after the pre-treatment workflow has been completed (push strategy). The objective of this study is to assess the impact of using pull and push strategies and explore alternative interventions for improving timeliness in radiotherapy. METHODS: Discrete-event simulation is used to model the patient flow of a large radiotherapy department of a Dutch hospital. A staff survey, interviews with managers, and historical data from 2017 are used to generate model inputs, in which fluctuations in patient inflow and resource availability are considered. RESULTS: A hybrid (40% pull / 60% push) strategy representing the current practice (baseline case) leads to 12% lower average waiting times and 48% fewer first appointment rebooks when compared to a full pull strategy, which in turn leads to 41% fewer patients breaching the waiting time targets. An additional scenario analysis performed on the baseline case showed that spreading consultation slots evenly throughout the week can provide a 21% reduction in waiting times. CONCLUSIONS: A 100% pull strategy allows for more patients starting treatment within the waiting time targets than a hybrid strategy, in spite of slightly longer waiting times and more first appointment rebooks. Our algorithm can be used by radiotherapy policy makers to identify the optimal balance between push and pull strategies to ensure timely treatments while providing patient-centered care adapted to their specific conditions.

The effects of zoledronic acid on ECG: a prospective study on patients with bone metastatic cancer.

INTRODUCTION: There are controversial results in the risk of atrial fibrillation as well as arrhythmogenic potential of bis-phosphonates. METHOD: 37 patients and 40 healthy controls were evaluated prospectively with regard to the cardiac side effects related to the use of zoledronic acid (ZA) and its effects on electrocardiography (ECG) parameters. RESULT: As the basal ECG results of the patients diagnosed with cancer compared with the control group, it was determined that QT maximum was significantly lower, QT minimum was significantly higher. However; it was determined that QT disp, P max, P min, and P disp values were not significantly different. There was no statistically significant difference in P max, P min, P disp, QT max, QT min, QT disp values of the ECG parameters measured from cancer patients, before and 60 minutes after ZA therapy. CONCLUSION: There were no significant alterations in ECG in the acute period, indicated that ZA had no arrhythmia potential in the early period in patients with no underlying cardiac disease. However: patients receiving ZA should be monitored more closely because of the risk of arrhythmia which may ensue due to hypocalcemia, hypomagnesemia, or other chemotherapeutics.

Increasing cost-effectiveness of AEDs using algorithms to optimise location.

OBJECTIVES: Volunteer responder systems (VRSs) aim to decrease time to defibrillation by dispatching trained volunteers to automated external defibrillators (AEDs) and out-of-hospital cardiac arrest (OHCA) victims. AEDs are often underutilized due to poor placement. This study provides a cost-effectiveness analysis of adding AEDs at strategic locations to maximize quality-adjusted life years (QALYs). METHODS: We simulated combined volunteer, police, firefighter, and emergency medical service response scenarios to OHCAs, and applied our methods to a case study of Amsterdam, the Netherlands. We compared the competing strategies of placing additional AEDs, using steps of 40 extra AEDs (0, 40, …, 1480), in addition to the existing 369 AEDs. Incremental cost-effectiveness ratios (ICERs) were calculated for each increase in additional AEDs, from a societal perspective. The effect of AED connection and time to connection on survival to hospital admission and neurological outcome at discharge was estimated using logistic regression, using OHCA data from Amsterdam from 2006 to 2018. Other model inputs were obtained from literature. RESULTS: Purchasing up to 1120 additional AEDs (ICER €75,669/QALY) was cost-effective at a willingness-to-pay threshold of €80,000/QALY, when positioned strategically. Compared to current practice, adding 1120 AEDs resulted in a gain of 0.111 QALYs (95% CI 0.110-0.112) at an increased cost of €3792 per OHCA (95% CI €3778-€3807). Health benefits per AED diminished as more AEDs were added. CONCLUSIONS: Our study identified cost-effective strategies to position AEDs at strategic locations in a VRS. The case study findings advocate for a substantial increase in the number of AEDs in Amsterdam.

The role of serum asprosin levels in predicting the severity of coronary artery disease in patients with diabetes mellitus.

BACKGROUND: Asprosin is an emerging biomarker that plays a role in metabolic diseases. This study investigates asprosin as a predictive marker for coronary artery disease (CAD) severity in diabetic patients. METHODS: Diabetic patients (n = 181) and healthy controls (n = 60) were analyzed. CAD severity was assessed using SYNTAX score. Diabetic patients were divided into 3 groups. Group 1 = patients without CAD, group 2 = patients with low SYNTAX score, and group 3 = patients with moderate-high SYNTAX score. Asprosin levels were measured for all participants using an enzyme-linked immunosorbent assay (ELISA). RESULTS: Asprosin levels were significantly higher in patient group compared to control group (p < 0.001). Asprosin levels were significantly higher in group 3 compared to group 1 and group 2 (p = 0.002). In logistic regression analysis, asprosin levels independently predicted patients with moderate-high SYNTAX scores. According to this analysis, 1 ng/mL increase in asprosin level was found to increase the risk of having moderate-high SYNTAX score by 14.1%. When the threshold value of asprosin level was set as 22.17 ng/mL, it predicted patients with moderate-high SYNTAX score with 63.6% sensitivity and 62.6% specificity. In multivariate regression analysis, SYNTAX score independently correlated with asprosin level. CONCLUSION: This is the first study in the literature to demonstrate a positive correlation between asprosin levels and SYNTAX scores in diabetic patients with CAD. More comprehensive studies with larger groups are needed.

Investigating Users' Attitudes Toward Automated Smartwatch Cardiac Arrest Detection: Cross-Sectional Survey Study.

Background: Out-of-hospital cardiac arrest (OHCA) is a leading cause of mortality in the developed world. Timely detection of cardiac arrest and prompt activation of emergency medical services (EMS) are essential, yet challenging. Automated cardiac arrest detection using sensor signals from smartwatches has the potential to shorten the interval between cardiac arrest and activation of EMS, thereby increasing the likelihood of survival. Objective: This cross-sectional survey study aims to investigate users' perspectives on aspects of continuous monitoring such as privacy and data protection, as well as other implications, and to collect insights into their attitudes toward the technology. Methods: We conducted a cross-sectional web-based survey in the Netherlands among 2 groups of potential users of automated cardiac arrest technology: consumers who already own a smartwatch and patients at risk of cardiac arrest. Surveys primarily consisted of closed-ended questions with some additional open-ended questions to provide supplementary insight. The quantitative data were analyzed descriptively, and a content analysis of the open-ended questions was conducted. Results: In the consumer group (n=1005), 90.2% (n=906; 95% CI 88.1%-91.9%) of participants expressed an interest in the technology, and 89% (n=1196; 95% CI 87.3%-90.7%) of the patient group (n=1344) showed interest. More than 75% (consumer group: n= 756; patient group: n=1004) of the participants in both groups indicated they were willing to use the technology. The main concerns raised by participants regarding the technology included privacy, data protection, reliability, and accessibility. Conclusions: The vast majority of potential users expressed a strong interest in and positive attitude toward automated cardiac arrest detection using smartwatch technology. However, a number of concerns were identified, which should be addressed in the development and implementation process to optimize acceptance and effectiveness of the technology.

Wait!What does that mean?: Eliminating ambiguity of delays in healthcare from an OR/MS perspective.

Waiting time in healthcare is a significant problem that occurs across the world and often has catastrophic effects. There are various terms used for waiting time ("sojourn", "throughput" etc.) and there is no consensus on how these terms are defined. Ambiguous definitions of waiting time make it difficult to compare and measure the problems related to waiting times and delays in healthcare. We present a systematic search and review of the Operations Research and Management Science (ORMS) literature on delays in healthcare services. We search for articles from 2004 to 2019 and base our search strategy on a well-known healthcare planning and control decision taxonomy. An important step towards reducing the ambiguity in the definitions is to distinguish between access time and waiting time. We provide clear definitions and examples of access time and waiting time, and we classify our search results according to three categories: article type, healthcare service investigated and ORMS technique used to solve the delay problem. We find that half of the ORMS research on the waiting and access time problem is done on Ambulatory Care services. We provide tables for each healthcare service that highlight key definitions, the techniques that are used most often and the healthcare environment where the research is done. This research highlights the significant ORMS research that is done on access and waiting time in healthcare as well as the remaining research opportunities. Moreover, it provides a common language for the ORMS community to solve critical waiting time issues in healthcare.

Hereditary Hyperferritinemia-Cataract Syndrome in a Family With HFE-H63D Mutation.

Hereditary hyperferritinemia-cataract syndrome (HHCS) is a rare genetic condition characterized by persistent hyperferritinemia (usually ferritin >1,000 ng/mL) without tissue iron overload, with or without early-onset slow-progressing bilateral nuclear cataract. It was first identified as a new genetic disorder in 1995, and since then genetic sequencing studies have been carried out to identify associated mutations in affected families. New mutations around the world are still being reported in the iron-responsive element (IRE) of the L-ferritin gene (FTL) to this day. Many clinicians remain unaware of this rare condition. The co-occurrence of FTL mutations and hereditary hemochromatosis (HH) mutations, especially H63D, on the HFE gene has been reported in the literature, which often leads to a diagnosis of HH, missed diagnosis of HHCS, incorrect treatment with phlebotomies and the occurrence of associated iatrogenic iron deficiency anemia. We herein report the case of a 40-year-old woman with spontaneous facial freckling, bilateral cataracts, homozygosity for HFE H63D mutation, iron deficiency anemia, and hyperferritinemia, who has been treated with phlebotomy and iron chelation therapy to no avail. Eleven years after being diagnosed and treated for HH, a reevaluation of her clinical presentation, laboratory results, medical imaging, and family history led to the recognition that her case is explained not by HH, but by an alternative diagnosis, HHCS. Our main objective in this report is to increase clinical awareness about HHCS, an often-unknown differential diagnosis of hyperferritinemia without iron overload, and to prevent adverse medical interventions in HHCS patients.

Characterization of Laboratory Flow and Performance for Process Improvements via Application of Process Mining.

BACKGROUND: The rising level of laboratory automation provides an increasing number of logged events that can be used for the characterization of laboratory performance and process improvements. This abundance of data is often underutilized for improving laboratory efficiency. OBJECTIVES: The first aim of this descriptive study is to provide a structured approach for transforming raw laboratory data to data that is suitable for process mining. The second aim is to describe a process mining approach for mapping and characterizing the sample flow in a clinical chemistry laboratory to identify areas for improvement in the testing process. METHODS: Data were extracted from instrument log files and the middleware between laboratory instruments and information technology infrastructure. Process mining was used for automated process discovery and analysis. Laboratory performance was quantified in terms of relevant key performance indicators (KPIs): turnaround time, timeliness, workload, work-in-process, and machine downtime. RESULTS: The method was applied to two Dutch university hospital clinical chemistry laboratories. We identified areas where alternative routes might increase laboratory efficiency and observed the negative effects of machine downtime on laboratory performance. This encourages the laboratory to review sample routes in its analyzer lines, the routes of high priority samples during instrument downtime, as well as the preventive maintenance policy. CONCLUSION: This article provides the first application of process mining to event data from a medical diagnostic laboratory for automated process model discovery. Our study shows that process mining, with the use of relevant KPIs, provides valuable insights for laboratories that motivates the disclosure and increased utilization of laboratory event data, which in turn drive the analytical staff to intervene in the process to achieve the set performance goals. Our approach is vendor independent and widely applicable for all medical diagnostic laboratories.

Smartwatch based automatic detection of out-of-hospital cardiac arrest: Study rationale and protocol of the HEART-SAFE project.

Out-of-hospital cardiac arrest (OHCA) is a leading cause of mortality. Immediate detection and treatment are of paramount importance for survival and good quality of life. The first link in the 'chain of survival' after OHCA - the early recognition and alerting of emergency medical services - is at the same time the weakest link as it entirely depends on witnesses. About one half of OHCA cases are unwitnessed, and victims of unwitnessed OHCA have virtually no chance of survival with good neurologic outcome. Also in case of a witnessed cardiac arrest, alerting of emergency medical services is often delayed for several minutes. Therefore, a technological solution to automatically detect cardiac arrests and to instantly trigger an emergency response has the potential to save thousands of lives per year and to greatly improve neurologic recovery and quality of life in survivors. The HEART-SAFE consortium, consisting of two academic centres and three companies in the Netherlands, collaborates to develop and implement a technical solution to reliably detect OHCA based on sensor signals derived from commercially available smartwatches using artificial intelligence. In this manuscript, we describe the rationale, the envisioned solution, as well as a protocol outline of the work packages involved in the development of the technology.

Radiotherapy treatment scheduling: Implementing operations research into clinical practice.

BACKGROUND: Every week, radiotherapy centers face the complex task of scheduling hundreds of treatment sessions amongst the available linear accelerators. With the increase in cancer patient numbers, manually creating a feasible and efficient schedule has shown to be a difficult, time-consuming task. Although operations research models have been increasingly reported upon to optimize patient care logistics, there is almost no scientific evidence of implementation in practice. METHODS: A mathematical operations research model was adapted to generate radiotherapy treatment schedules in two Dutch centers. The model was iteratively adjusted to fulfill the technical and medical constraints of each center until a valid model was attained. Patient data was collected for the planning horizon of one week, and the feasibility of the obtained schedules was verified by the staff of each center. The resulting optimized solutions are compared with the ones manually developed in practice. RESULTS: The weekly schedule was improved in both centers by decreasing the average standard deviation between sessions' starting times from 103.0 to 50.4 minutes (51%) in one center, and the number of gaps in the schedule from 18 to 5 (72%) in the other. The number of patients requiring linac switching between sessions has also decreased from 71 to 0 patients in one center, and from 43 to 2 in the other. The automated process required 5 minutes and 1.5 hours of computation time to find an optimal weekly patient schedule, respectively, as opposed to approximately 1.5 days when performed manually for both centers. CONCLUSIONS: The practical application of a theoretical operations research model for radiotherapy treatment scheduling has provided radiotherapy planners a feasible, high-quality schedule in an automated way. Iterative model adaptations performed in small steps, early engagement of stakeholders, and constant communication proved to facilitate the implementation of operations research models into clinical practice.

Carotid-femoral pulse wave velocity is significantly increased in newly diagnosed hypertensive patients with primary hyperparathyroidism and significantly related with serum calcium level.

BACKGROUND: Primary hyperparathyroidism (PHP) is a rare cause of secondary hypertension (HT), but in patients with PHP, HT is very common and 20-80% of patients have HT. The aim of this study was to evaluate the change in carotid-femoral pulse wave velocity (CF-PWV) in hypertensive patients with PHP, and was to determine the clinical, laboratory, and echocardiographic parameters associated with CF-PWV. METHODS: The study included 83 newly diagnosed hypertensive patients with PHP and 83 patients with newly diagnosed essential HT without PHP. All patients underwent echocardiography and CF-PWV measurements. RESULTS: In patients with PHP, blood urea nitrogen, hs-CRP, uric acid, serum and urine calcium, parathyroid hormone level, CF-PWV value, LV wall thickness, LVMI, aortic and left atrium (LA) diameter, and presence of LVH and CF-PWV > 10 m/s were higher, and serum phosphorus levels were lower. Serum calcium, LA diameter, and LVMI values were closely correlated with CF-PWV. In the ROC analysis, the AUROC was calculated as 0.825 for calcium level to determine the patients with increased CF-PWV. When the serum calcium value was taken as 10 mg/dL, it was determined with CF-PWV > 10 m/s were 79.5% sensitivity and 78.2% specificity. CONCLUSION: CF-PWV significantly increases in newly diagnosed hypertensive patients with PHP and significantly related to serum calcium level. To protect against target organ damage, high serum calcium levels should be monitored as well as blood pressure in hypertensive patients with PHP.