Encapsulation of Human-Bone-Marrow-Derived Mesenchymal Stem Cells in Small Alginate Beads Using One-Step Emulsification by Internal Gelation: In Vitro, and In Vivo Evaluation in Degenerate Intervertebral Disc Model.

Cell microencapsulation in gel beads contributes to many biomedical processes and pharmaceutical applications. Small beads (<300 µm) offer distinct advantages, mainly due to improved mass transfer and mechanical strength. Here, we describe, for the first time, the encapsulation of human-bone-marrow-derived mesenchymal stem cells (hBM-MSCs) in small-sized microspheres, using one-step emulsification by internal gelation. Small (127−257 µm) high-mannuronic-alginate microspheres were prepared at high agitation rates (800−1000 rpm), enabling control over the bead size and shape. The average viability of encapsulated hBM-MSCs after 2 weeks was 81 ± 4.3% for the higher agitation rates. hBM-MSC-loaded microspheres seeded within a glycosaminoglycan (GAG) analogue, which was previously proposed as a mechanically equivalent implant for degenerate discs, kept their viability, sphericity, and integrity for at least 6 weeks. A preliminary in vivo study of hBM-MSC-loaded microspheres implanted (via a GAG-analogue hydrogel) in a rat injured intervertebral disc model demonstrated long-lasting viability and biocompatibility for at least 8 weeks post-implantation. The proposed method offers an effective and reproducible way to maintain long-lasting viability in vitro and in vivo. This approach not only utilizes the benefits of a simple, mild, and scalable method, but also allows for the easy control of the bead size and shape by the agitation rate, which, overall, makes it a very attractive platform for regenerative-medicine applications.

Mitral Valve Prolapse, Psychoemotional Status, and Quality of Life: Prospective Investigation in the Current Era.

OBJECTIVE: The purpose of this study is to investigate whether mitral valve prolapse is associated with the patient's psychoemotional status and health-related quality of life. METHODS: Mitral valve prolapse and mitral regurgitation were prospectively and comprehensively assessed in 281 patients (age 61 ± 13 years; 63% men); 216 patients with mitral valve prolapse were compared with 65 without mitral valve prolapse (of similar age and sex). Simultaneously, we assessed the patient's psychoemotional status (anxiety, depression, posttraumatic stress symptoms), health-related quality of life, and perceived severity of illness using validated questionnaires. RESULTS: Twenty-nine percent of the patients had either no or mild mitral regurgitation (area of effective regurgitant orifice ≤0.2), and 71% had clinically significant mitral regurgitation (moderate/severe). Stratifying patients into no/mild vs moderate/severe mitral regurgitation revealed no differences in psychoemotional status or mental health-related quality of life between patients with mitral valve prolapse vs those without mitral valve prolapse within each subgroup; no/mild mitral regurgitation and moderate/severe mitral regurgitation (all P ≥ .5). In multivariate analysis, mitral valve prolapse was not independently associated with psychoemotional status or health-related quality of life (all P ≥ .4). In addition, while objective severity of the illness was not related to psychoemotional status or health-related quality of life (all P ≥ .2), the patient's perceived severity of illness predicted in and of itself all psychoemotional (all P < .03) and quality-of-life outcomes (all P < .003). CONCLUSION: Mitral valve prolapse is not a determinant of the patient's psychoemotional status or quality of life. Psychoemotional status and health-related quality of life are determined by the patient's perception of the severity of the mitral valve disease, rather than by the presence of mitral valve prolapse.

Psychoemotional and quality of life response to mitral operations in patients with mitral regurgitation: a prospective study.

BACKGROUND: Severe mitral regurgitation (MR) is associated with frequent alteration of psychoemotional status (PES), with anxiety and stress symptoms related to health-related quality of life (HR-QOL). Yet, it is unknown whether surgical correction of MR leads to improvement or deterioration in PES and HR-QOL. METHODS: We prospectively performed comprehensive MR assessment and administered questionnaires assessing PES and HR-QOL in 131 patients (aged 60 years; 75% men) before and 6 months after operation for organic MR and compared them to 62 patients who did not undergo operation for mitral disease and 36 normal controls of similar age assessed with the same methods. RESULTS: Baseline PES was poorer preoperatively in patients undergoing mitral operation compared with patients who did not undergo mitral operation and normal controls (anxiety and posttraumatic stress [PTS]; both p < 0.01) with poorer physical HR-QOL (p < 0.01). Six months later, all these psychoemotional variables improved (all p ≤ 0.02) in the patients who underwent mitral operation, whereas no change was observed in the other 2 groups (all p > 0.1). Improvement after mitral repair resulted in postoperative normalization of emotional and physical well-being, with similar scores among all groups (all p ≥ 0.4). At 6-month follow-up, no difference in improvement in PES and HR-QOL was noted according to the surgical approach (robotic versus sternotomy, all p ≥ 0.2). CONCLUSIONS: Patients with severe organic MR present with frequent psychoemotional alterations and HR-QOL deterioration, in contrast to patients who do not undergo mitral operation and normal controls. After mitral operation, notable improvement results in normalization of emotional and physical well-being. Quantification of emotional and physical well-being provides important outcome measures in patients with organic MR and uncovers important benefits provided by surgical correction of MR.

A Coordinated Patient Transport System for ICU Patients Requiring Surgery: Impact on Operating Room Efficiency and ICU Workflow.

PURPOSE: Transfer of intensive care unit (ICU) patients to the operating room (OR) is a resource-intensive, time-consuming process that often results in patient throughput inefficiencies, deficiencies in information transfer, and suboptimal nurse to patient ratios. This study evaluates the implementation of a coordinated patient transport system (CPTS) designed to address these issues. METHODS: Using data from 1,557 patient transfers covering the 2006-2010 period, interrupted time series and before and after designs were used to analyze the effect of implementing a CPTS at Mayo Clinic, Rochester. RESULTS: Using a segmented regression for the interrupted time series, on-time OR start time deviations were found to be significantly lower after the implementation of CPTS (p < .0001). The implementation resulted in a fourfold improvement in on-time OR starts (p < .01) while significantly reducing idle OR time (p < .01). CONCLUSION: A coordinated patient transfer process for moving patient from ICUs to ORs can significantly improve OR efficiency, reduce nonvalue added time, and ensure quality of care by preserving appropriate care provider to patient ratios.

Improving patient access in nuclear medicine: a case study of PET scanner scheduling.

We used the systems engineering technique of discrete event simulation modeling to assist in increasing patient access to positron emission tomographic examinations in the Department of Nuclear Medicine at Mayo Clinic, Rochester. The model was used to determine the best universal slot length to address the specific access challenges of a destination medical center such as Mayo Clinic. On the basis of the modeling, a new schedule was implemented in April 2012 and our before and after data analysis shows an increase of 2.4 scans per day. This was achieved without requiring additional resources or negatively affecting patient waiting, staff satisfaction (as evaluated by day length), or examination quality.

Psycho-emotional manifestations of valvular heart diseases: prospective assessment in mitral regurgitation.

OBJECTIVE: To define the prevalence and consequences of post-traumatic stress disorder (PTSD) as an emotional response to cardiac diseases in patients with mitral regurgitation. METHODS: We prospectively enrolled 186 patients with moderate or severe organic mitral regurgitation, presenting class I (absent) or II (minimal) dyspnea, who were compared with 80 controls of similar age (38 with completely normal cardiac function; 42 with mild mitral-valve prolapse; all with no, or at most mild, mitral regurgitation). Mitral-regurgitation severity and consequences were comprehensively measured, simultaneously with PTSD, anxiety, and depression. RESULTS: PTSD prevalence was higher in mitral-regurgitation patients vs controls (23% vs 9%, P <.01). Although mitral-regurgitation objective severity (regurgitant volume 77.8 ± 28.9 vs 79.0 ± 27.5 mL, P = .8) and objective consequences (left-atrial volume 59.1 ± 20.9 vs 54.02 ± 15.6 mL, P = .1; right-ventricular systolic pressure 34.1 ± 11.4 vs 32.9 ± 7.2 mm Hg, P = .6) were similar with and without PTSD (all P ≥.1), patients with PTSD were more symptomatic (class II 74 vs 38%; fatigue 71% vs 38%, both P <.0001) and had higher anxiety and depressions scores (P <.0001). CONCLUSIONS: PTSD is prevalent in organic moderate or severe mitral-regurgitation patients but is not determined by objective mitral-regurgitation severity or consequences. PTSD is linked to anxiety and depression and to symptoms usually considered cardiac, such as dyspnea. Thus, PTSD and psycho-emotional manifestations, linked to symptoms, represent important responses to chronic-valve disease that may affect clinical outcomes.

Recovery bed planning in cardiovascular surgery: a simulation case study.

Recovery beds for cardiovascular surgical patients in the intensive care unit (ICU) and progressive care unit (PCU) are costly hospital resources that require effective management. This case study reports on the development and use of a discrete-event simulation model used to predict minimum bed needs to achieve the high patient service level demanded at Mayo Clinic. In addition to bed predictions that incorporate surgery growth and new recovery protocols, the model was used to explore the effects of smoothing surgery schedules and transferring long-stay patients from the ICU. The model projected bed needs that were 30 % lower than the traditional bed-planning approach and the options explored by the practice could substantially reduce the number of beds required.

Readmissions after implantation of axial flow left ventricular assist device.

OBJECTIVES: The purpose of this study was to determine the occurrence and causes of readmissions after implantation of axial flow left ventricular assist device (LVAD). BACKGROUND: Based on the REMATCH (Randomized Evaluation of Mechanical Assistance for the Treatment of Congestive Heart Failure) study experience, readmissions after LVAD implantation are thought to be frequent. METHODS: We retrospectively analyzed admissions to our facility in a cohort of 115 patients implanted between January 2008 and July 2011 with the HeartMate II axial flow LVAD, of whom 42 were bridged to transplant. To account for repeated events, Andersen-Gill models were used to determine possible predictors. RESULTS: The patients were followed for 1.4 ± 0.9 years. There were 224 readmissions in 83 patients. The overall readmission rate was 1.64 ± 1.97 per patient-year of follow-up. The readmission rate for the first 6 months was 2.0 ± 2.3 and decreased to 1.2 ± 2.1 during subsequent follow-up. Leading causes were bleeding (66 readmissions in 34 patients), mostly gastrointestinal bleed (51 in 27 patients), cardiac (51 in 36 patients, most for HF or arrhythmia), infections (32 in 25 patients) of which 6 were pump related, and thrombosis (20 in 15 patients) including 13 readmissions due to hemolysis. Preoperative variables associated with (fewer) readmissions in a multivariate model include residence within our hospital-extended referral zone of Minnesota and the neighboring states (hazard ratio: 0.66; 95% confidence interval: 0.48 to 0.91; p = 0.011), hemoglobin (hazard ratio: 0.91, 95% confidence interval: 0.84 to 0.99; p = 0.027) and N-terminal pro-B-type natriuretic peptide (hazard ratio: 0.98; 95% confidence interval: 0.96 to 1.0 per 1,000-unit increase, p = 0.022). C-statistic for the model: 0.63. CONCLUSIONS: Readmission rates after axial flow LVAD implantation decrease during the first 6 months and then stabilize. The leading causes are bleeding, cardiac (heart failure and arrhythmia), infections, and thrombosis.

MEDAL: measuring of emergency departments' adaptive load.

We propose an innovative approach for measuring real-time operational load within emergency departments. Medical informatics, operations researchers, and other decision makers in the health care field have yet to come to an agreement regarding standardized matrices for measuring operational load within emergency departments. As a result, it is difficult to develop methods and approaches for reducing operational load. We propose a flexible framework based on neural networks. These networks can calculate user-tuned load value, based on a set of well-defined operational and clinical indicators. The operational load value is calculated by learning the weights of the raw operational indicators within a particular emergency department.

Ways to reduce patient turnaround time and improve service quality in emergency departments.

PURPOSE: Recent years have witnessed a fundamental change in the function of emergency departments (EDs). The emphasis of the ED shifts from triage to saving the lives of shock-trauma rooms equipped with state-of-the-art equipment. At the same time walk-in clinics are being set up to treat ambulatory type patients. Simultaneously ED overcrowding has become a common sight in many large urban hospitals. This paper recognises that in order to provide quality treatment to all these patient types, ED process operations have to be flexible and efficient. The paper aims to examine one major benchmark for measuring service quality--patient turnaround time, claiming that in order to provide the quality treatment to which EDs aspire, this time needs to be reduced. DESIGN/METHODOLOGY/APPROACH: This study starts by separating the process each patient type goes through when treated at the ED into unique components. Next, using a simple model, the impact each of these components has on the total patient turnaround time is determined. This in turn, identifies the components that need to be addressed if patient turnaround time is to be streamlined. FINDINGS: The model was tested using data that were gathered through a comprehensive time study in six major hospitals. The analysis reveals that waiting time comprises 51-63 per cent of total patient turnaround time in the ED. Its major components are: time away for an x-ray examination; waiting time for the first physician's examination; and waiting time for blood work. ORIGINALITY/VALUE: The study covers several hospitals and analyses over 20,000 process components; as such the common findings may serve as guidelines to other hospitals when addressing this issue.