Citations

Abstract Amyotrophic lateral sclerosis is a neurodegenerative disorder, which is characterized by progressive upper and lower motor neuron signs and symptoms, resulting in progressive muscle weakness. There are very rare reports of magnetic resonance imaging (MRI) abnormalities within the nerve roots or plexus reported in amyotrophic lateral sclerosis. Here, we report a patient who presented with progressive left arm weakness and was found to have bilateral MRI plexus abnormalities. This report illustrates that MRI plexus abnormalities can be seen in amyotrophic lateral sclerosis, possibly before symptoms, and may have clinical value in the diagnostic process.

Purpose: Hospital readmissions after surgery are a focus of quality improvement efforts. Although some reflect appropriate care, others are potentially preventable readmissions (PPRs). We aim to describe the burden, timing, and factors associated with readmissions after complex cancer surgery. Methods: The Nationwide Readmissions Database (2013) was used to select patients undergoing a complex oncologic resection, which was defined as esophagectomy/gastrectomy, hepatectomy, pancreatectomy, colorectal resection, lung resection, or cystectomy. Readmissions within 30 days from discharge were analyzed. International Classification of Diseases (9th revision) primary diagnosis codes were reviewed to identify PPRs. Multivariable logistic regression analyses identified demographic, clinical, and hospital factors associated with readmissions. Results: Of the 59,493 eligible patients, 14% experienced a 30-day readmission, and 82% of these were deemed PPRs. Half of the readmissions occurred within the first 8 days of discharge. Infections (26%), GI complications (17%), and respiratory conditions (10%) accounted for most readmissions. Factors independently associated with an increased likelihood of readmission included Medicaid versus private insurance (odds ratio [OR], 1.32; 95% CI, 1.17 to 1.48), higher comorbidity score (OR, 1.5; 95% CI, 1.33 to 1.63), discharge to a facility (OR, 1.39; 95% CI, 1.29 to 1.51), prolonged length of stay (OR, 1.42; 95% CI, 1.32 to 1.52), and occurrence of a major in-hospital complication (OR, 1.24; 95% CI, 1.16 to 1.34). Conclusion: One in seven patients undergoing complex cancer surgery suffered a readmission within 30 days. We identified common causes of these and identified patients at high risk for such an event. These data can be used by physicians, administrators, and policymakers to develop strategies to decrease readmissions.

Study Design. Systematic review and meta-analysis of observational studies. Objective. The aim of the study is to evaluate different treatment modalities in the management of sacrococcygeal chordoma. Summary of Background Data. Chordomas are primary malignant bone tumors associated with considerable morbidity and mortality. Methods. We searched MEDLINE, EMBASE, Cochrane Central-Register of Controlled Trials, and Scopus from inception to July 2015. Eligible studies included patients with sacrococcygeal chordoma treated exclusively with surgery, radiotherapy, or both. Two reviewers independently assessed the eligibility of potential studies, risk of bias, and extracted data. Outcomes of interest were all-cause mortality, progression-free survival, and metastases. We analyzed further surgical outcomes by resection margin. All outcomes were assessed at 60 months and more than 60 months following intervention. Results. We included 33 noncomparative studies reporting on 501 patients (mean age 57 years). Overall mortality rate was (16%) after surgical resection with adjuvant radiotherapy and (28%) after surgical resection, and (43%) after radiotherapy (P = 0.28). All-cause mortality following wide surgical resection was (32%) compared to (40%) after marginal resection (P = 0.51). Overall progression-free survival rate was (58%) after surgical resection with adjuvant radiotherapy and (55%) after surgery (P = 0.92). However, at more than 60 months follow-up, progression-free survival rates were significantly higher (P = 0.024) following surgical resection with adjuvant radiotherapy (74%) in comparison to surgery (55%) and radiotherapy (36%). Overall progression-free survival rates were nonsignificantly higher after wide surgical resection (66%) than marginal resection (33%) (P = 0.16). However, at 60 months follow-up, progression-free survival rates were significantly higher following wide surgical resection (73%) than marginal resection (33%) (P = 0.047). Conclusion. Sacrococcygeal chordoma is a difficult to treat disease entity. Until comparative studies become available, wide surgical resection and multidisciplinary management are the recommended approaches to improve patient outcomes. Level of Evidence: 3

The hereditary spastic paraplegias (HSPs) are a heterogeneous group of disorders characterized by degeneration of the corticospinal and spinocerebellar tracts leading to progressive spasticity. One subtype, spastic paraplegia type 47 (SPG47 or HSP‐AP4B1), is due to bi‐allelic loss‐of‐function mutations in the AP4B1 gene. AP4B1 is a subunit of the adapter protein complex 4 (AP‐4), a heterotetrameric protein complex that regulates the transport of membrane proteins. Since 2011, 11 individuals from six families with AP4B1 mutations have been reported, nine of whom had homozygous mutations and were from consanguineous families. Here we report eight patients with AP4B1‐associated SPG47, the majority born to non‐consanguineous parents and carrying compound heterozygous mutations. Core clinical features in this cohort and previously published patients include neonatal hypotonia that progresses to spasticity, early onset developmental delay with prominent motor delay and severely impaired or absent speech development, episodes of stereotypic laughter, seizures including frequent febrile seizures, thinning of the corpus callosum, and delayed myelination/white matter loss. Given that some of the features of AP‐4 deficiency overlap with those of cerebral palsy, and the discovery of the disorder in non‐consanguineous populations, we believe that AP‐4 deficiency may be more common than previously appreciated.

Emergency Department (ED) is a complex care delivery environment in a hospital that provides time sensitive urgent and lifesaving care [1]. Emergency medicine is an unscheduled practice and therefore providers experience extreme fluctuations in their workload. ED crowding is a major concern that affects the efficacy of the ED workflow, which often is challenged by long wait times, overuse of observation units, patients either leaving without being seen by a provider and non-availability of inpatient beds to accommodate patients after diagnosis [2]. Evaluating ED workflow is a challenging task due to its chaotic nature, with some success using time-motion studies and novel capacity management tools are nowadays becoming common in ED to address workflow related issues [3]. Several studies reveal that Electronic Medical Record (EMR) adoption has not resulted in significant ED workflow improvements nor reduced the cost of ED operations. Since raw EMR data does not offer operational and clinical decision making insights, advanced EMR data analytics are often sought to derive actionable intelligence from EMR data that can provide insights to improve ED workflow. Improving ED workflow has been an important topic of research because of its great potential to optimize the urgent care needed for the patients and at the same time save time and cost. Radio Frequency Identification Device (RFID) is a wireless automatic identification and data capture technology device that has the potential for improving safety, preventing errors, saving costs, and increasing security and therefore improving overall organizational performance. RFID technology use in healthcare has opened a new space in healthcare informatics research that provides novel data to identify workflow process pitfalls and provide new directions [4]. The potential advantages of RFID adoption in healthcare and especially in ED has been well recognized to save costs and improve care delivery [5]. However, the large upfront infrastructure costs, need for an integrated health information technology (HIT), advanced analytical tools for big data analysis emerging from RFID and skilled data scientists to tackle the data to derive actionable intelligence discourage many hospitals from adoption RFID technology despite its potential advantages. Our recent pilot study on the RFID data analytics demonstrated the feasibility of quantifying and analyzing two novel variables such as ‘patient alone’ time defined as the total time a patient spends alone without interaction with a health care staff in the ED and ‘provider time’ defined as the total time a patient spends interacting with any health care staff [6]. The study motivated a more comprehensive big data analytics of RFID data which can provide better insights into optimizing ED workflow which can improve the quality of care in the ED and also reduce cost. In this work, the authors attempt to describe the RFID adoption in the ED at the Saint Mary’s Hospital at Mayo Clinic, in Rochester, MN, a level one trauma center both for children and adults as a step towards optimizing ED workflow.

Common approaches to emergency department (ED) staffing are to optimize shifts based on historical patient volume or arrival patterns. The former is problematic because historical patient volumes are based on the volumes during existing shifts. Therefore, optimizing shifts based on these volumes can replicate the inefficiencies in these shifts. The latter approach ignores queueing effects. To address the shortcomings of these commonly used approaches, we use classification and regression trees to identify thresholds for patient-to-staff ratios, which split the patient subpopulations into two groups that have different empirical cumulative distribution functions (ecdfs) for patients’ lengths of stay in the ED; one has an extended length and the other has a shorter length. We apply these thresholds and ecdfs to historical patient volumes to calculate an ideal patient volume. After accounting for arrival patterns of ED patients, ideal patient volumes represent the load on the entire ED if patient-to-staff ratios are always kept under the identified thresholds. We then use a mixed-integer programming model to minimize understaffing with respect to the ideal patient volumes. The ED at Mayo Clinic Saint Marys Hospital in Rochester, Minnesota, a trauma center for both adults and pediatrics, implemented the new shift templates in the fourth quarter of 2015. The templates resulted in statistically significant improvements in several patient-centered metrics. In particular, the median length of stay, door-to-provider time, and door-to-bed time decreased by 11, 2.7, and 3 minutes, respectively, despite a six percent increase in patient volume.