Necrotizing fasciitis: a cumulative review and new techniques in emergency room diagnosis

Necrotizing fasciitis (NF) is a rare and life threating soft-tissue infection specific to the skin’s fascia layer. It is most often encountered in the peripheries, abdominal wall, and perineum and has numerous etiologies and associated pathogens. Early diagnosis and rapid surgical debridement are essential in treating NF as the infection progresses rapidly and mortality rate increases significantly with time. The current difficulty in initial diagnosis is due to the lack of obvious skin findings early on in the infection. Laboratory tests, including the laboratory risk indicator for necrotizing fasciitis (LRINEC) score, gas on imaging tests, and physical exam findings are the current clues to an early diagnosis but official diagnosis can only be confirmed by surgical exploration and discovery of a lack of resistance to dissection in the fascia layer. The LRINEC score analyzes one variable, specifically C-reactive protein (CRP), which is often not included in routine laboratory tests skin infections at the emergency department (ED). Furthermore, no specific set of physical exam findings has been distinctly associated with diagnosis of NF over other soft-tissue infections and the most specific imaging tests are too expensive for routine use. A new and modified LRINEC score based only on routine ED laboratory tests as well as an additional objective scoring system for physical exam findings are the next steps toward rapid diagnosis. This approach requires large-scale retrospective statistical analyses of NF cases across the country for identification of the most prevalent physical exam findings and abnormal laboratory values

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

Factors Influencing Access to Cochlear Implantation in Deaf and Hard-of-Hearing Children in Southern California.

ObjectiveTo determine the epidemiologic relationship of family demographics and educational resources with parental knowledge of and willingness for their children to receive cochlear implantation (CI) for deaf and hard-of-hearing (DHH) children.MethodsA total of 213 parents of DHH children were surveyed at local schools, specialized camps, and clinics in Southern California. Data on parents were solicited, including income, insurance status, education level, hearing status, primary language, and motivations towards CI.ResultsSixty-six surveys were included in the analysis. Three of these patients had already undergone CI, thus of the 63 children without CI, 59% had been presented with the option of CI by a healthcare professional and 27% were willing to have their child undergo CI. Willingness for children to undergo CI was statistically higher in families with an annual income less than $15,000 or more than$75,000 (p = 0.02), and children enrolled in specialized schools for DHH (p = 0.02). The leading reasons for unwillingness to undergo CI were risks of surgery (17%) and discouragement from others (14%).ConclusionA significant gap exists between the number of CI candidates and families and willingness to undergo CI. The difference could be related to socioeconomic status and the patient's school type. This underscores the importance of parental education through the use of a multi-disciplinary team to ensure all hearing rehabilitation options are explained

Factors Influencing Access to Cochlear Implantation in Deaf and Hard-of-Hearing Children in Southern California.

ObjectiveTo determine the epidemiologic relationship of family demographics and educational resources with parental knowledge of and willingness for their children to receive cochlear implantation (CI) for deaf and hard-of-hearing (DHH) children.MethodsA total of 213 parents of DHH children were surveyed at local schools, specialized camps, and clinics in Southern California. Data on parents were solicited, including income, insurance status, education level, hearing status, primary language, and motivations towards CI.ResultsSixty-six surveys were included in the analysis. Three of these patients had already undergone CI, thus of the 63 children without CI, 59% had been presented with the option of CI by a healthcare professional and 27% were willing to have their child undergo CI. Willingness for children to undergo CI was statistically higher in families with an annual income less than $15,000 or more than$75,000 (p = 0.02), and children enrolled in specialized schools for DHH (p = 0.02). The leading reasons for unwillingness to undergo CI were risks of surgery (17%) and discouragement from others (14%).ConclusionA significant gap exists between the number of CI candidates and families and willingness to undergo CI. The difference could be related to socioeconomic status and the patient's school type. This underscores the importance of parental education through the use of a multi-disciplinary team to ensure all hearing rehabilitation options are explained

Evaluating the Laboratory Risk Indicator to Differentiate Cellulitis from Necrotizing Fasciitis in the Emergency Department

Introduction: Necrotizing fasciitis (NF) is an uncommon but rapidly progressive infection that results in grossmorbidity and mortality if not treated in its early stages. The Laboratory Risk Indicator for Necrotizing Fasciitis(LRINEC) score is used to distinguish NF from other soft tissue infections such as cellulitis or abscess. Thisstudy analyzed the ability of the LRINEC score to accurately rule out NF in patients who were confirmed tohave cellulitis, as well as the capability to differentiate cellulitis from NF.Methods: This was a 10-year retrospective chart-review study that included emergency department (ED)patients ≥18 years old with a diagnosis of cellulitis or NF. We calculated a LRINEC score ranging from0-13 for each patient with all pertinent laboratory values. Three categories were developed per the originalLRINEC score guidelines denoting NF risk stratification: high risk (LRINEC score ≥8), moderate risk (LRINECscore 6-7), and low risk (LRINEC score ≤5). All cases missing laboratory values were due to the absence ofa C-reactive protein (CRP) value. Since the score for a negative or positive CRP value for the LRINEC scorewas 0 or 4 respectively, a LRINEC score of 0 or 1 without a CRP value would have placed the patient in the“low risk” group and a LRINEC score of 8 or greater without CRP value would have placed the patient in the“high risk” group. These patients missing CRP values were added to these respective groups.Results: Among the 948 ED patients with cellulitis, more than one-tenth (10.7%, n=102 of 948) weremoderate or high risk for NF based on LRINEC score. Of the 135 ED patients with a diagnosis of NF, 22patients had valid CRP laboratory values and LRINEC scores were calculated. Among the other 113 patientswithout CRP values, six patients had a LRINEC score ≥ 8, and 19 patients had a LRINEC score ≤ 1. Thus, atotal of 47 patients were further classified based on LRINEC score without a CRP value. More than half of theNF group (63.8%, n=30 of 47) had a low risk based on LRINEC ≤5. Moreover, LRINEC appeared to performbetter in the diabetes population than in the non-diabetes population.Conclusion: The LRINEC score may not be an accurate tool for NF risk stratification and differentiationbetween cellulitis and NF in the ED setting. This decision instrument demonstrated a high false positive ratewhen determining NF risk stratification in confirmed cases of celulitis and a high false negative rate in casesof confirmed NF

Facial Fractures Have Similar Outcomes When Managed by Either Otolaryngology or Plastic Surgery: Encounters From a Single Level I Trauma Center.

Study designRetrospective cohort.ObjectiveTraumatic facial fractures (FFs) often require specialty consultation with Plastic Surgery (PS) or Otolaryngology (ENT); however, referral patterns are often non-standardized and institution specific. Therefore, we sought to compare management patterns and outcomes between PS and ENT, hypothesizing no difference in operative rates, complications, or mortality.MethodsWe performed a retrospective analysis of patients with FFs at a single Level I trauma center from 2014 to 2017. Patients were compared by consulting service: PS vs. ENT. Chi-square and Mann-Whitney-U tests were performed.ResultsOf the 755 patients with FFs, 378 were consulted by PS and 377 by ENT. There was no difference in demographic data (P > 0.05). Patients managed by ENT received a longer mean course of antibiotics (9.4 vs 7.0 days, P = 0.008) and had a lower rate of open reduction internal fixation (ORIF) (9.8% vs. 15.3%, P = 0.017), compared to PS patients. No difference was observed in overall operative rate (15.1% vs. 19.8%), use of computed tomography (CT) imaging (99% vs. 99%), time to surgery (65 vs. 55 hours, P = 0.198), length of stay (LOS) (4 vs. 4 days), 30-day complication rate (10.6% vs. 7.1%), or mortality (4.5% vs. 2.6%) (all P > 0.05).ConclusionOur study demonstrated similar baseline characteristics, operative rates, complications, and mortality between FFs patients who had consultation by ENT and PS. This supports the practice of allowing both ENT and PS to care for trauma FFs patients, as there appears to be similar standardized care and outcomes. Future studies are needed to evaluate the generalizability of our findings

Electroencephalography Might Improve Diagnosis of Acute Stroke and Large Vessel Occlusion.

Background and purposeClinical methods have incomplete diagnostic value for early diagnosis of acute stroke and large vessel occlusion (LVO). Electroencephalography is rapidly sensitive to brain ischemia. This study examined the diagnostic utility of electroencephalography for acute stroke/transient ischemic attack (TIA) and for LVO.MethodsPatients (n=100) with suspected acute stroke in an emergency department underwent clinical exam then electroencephalography using a dry-electrode system. Four models classified patients, first as acute stroke/TIA or not, then as acute stroke with LVO or not: (1) clinical data, (2) electroencephalography data, (3) clinical+electroencephalography data using logistic regression, and (4) clinical+electroencephalography data using a deep learning neural network. Each model used a training set of 60 randomly selected patients, then was validated in an independent cohort of 40 new patients.ResultsOf 100 patients, 63 had a stroke (43 ischemic/7 hemorrhagic) or TIA (13). For classifying patients as stroke/TIA or not, the clinical data model had area under the curve=62.3, whereas clinical+electroencephalography using deep learning neural network model had area under the curve=87.8. Results were comparable for classifying patients as stroke with LVO or not.ConclusionsAdding electroencephalography data to clinical measures improves diagnosis of acute stroke/TIA and of acute stroke with LVO. Rapid acquisition of dry-lead electroencephalography is feasible in the emergency department and merits prehospital evaluation

Vascularized Fibular Epiphyseal Transfer for Pediatric Limb Salvage: Review of Applications and Outcomes

Summary:. Vascularized fibular epiphyseal transfer (VFET) offers a functional advantage in pediatric limb salvage due to the preservation of growth potential and an articular surface for remodeling. This review summarizes the available evidence on the clinical characteristics and outcomes of pediatric reconstruction applying VFET at different recipient sites and with varying techniques. VFET was used to reconstruct the proximal humerus, distal radius or ulna, proximal femur, distal fibula, calcaneus, and mandible. Although most often harvested on the anterior tibial artery, VFET has also been performed using the peroneal artery, the inferior lateral genicular artery, and a dual pedicle. Recipient site flap inset most often involved fixation with plates and/or screws as well as soft tissue reconstruction using a retained slip of biceps femoris tendon. Outcomes included limb growth, range of motion, and strength. The most common reported complications were bone flap fracture and peroneal nerve palsy. The anterior tibial artery was the most applied pedicle with reliable limb growth, but with the added risk of postoperative peroneal palsy. Bone flap fracture most often occurred at the proximal humerus and femur recipient sites. Plate fixation and the combined use of allograft had lower instances of bone flap fracture. This review highlights how the anticipated dynamic growth and remodeling this free flap offers in the long term must be weighed against its complexity and potential complications

A large, open source dataset of stroke anatomical brain images and manual lesion segmentations

Stroke is the leading cause of adult disability worldwide, with up to two-thirds of individuals experiencing long-term disabilities. Large-scale neuroimaging studies have shown promise in identifying robust biomarkers (e.g., measures of brain structure) of long-term stroke recovery following rehabilitation. However, analyzing large rehabilitation-related datasets is problematic due to barriers in accurate stroke lesion segmentation. Manually-traced lesions are currently the gold standard for lesion segmentation on T1-weighted MRIs, but are labor intensive and require anatomical expertise. While algorithms have been developed to automate this process, the results often lack accuracy. Newer algorithms that employ machine-learning techniques are promising, yet these require large training datasets to optimize performance. Here we present ATLAS (Anatomical Tracings of Lesions After Stroke), an open-source dataset of 304 T1-weighted MRIs with manually segmented lesions and metadata. This large, diverse dataset can be used to train and test lesion segmentation algorithms and provides a standardized dataset for comparing the performance of different segmentation methods. We hope ATLAS release 1.1 will be a useful resource to assess and improve the accuracy of current lesion segmentation methods

A large, open source dataset of stroke anatomical brain images and manual lesion segmentations.

Stroke is the leading cause of adult disability worldwide, with up to two-thirds of individuals experiencing long-term disabilities. Large-scale neuroimaging studies have shown promise in identifying robust biomarkers (e.g., measures of brain structure) of long-term stroke recovery following rehabilitation. However, analyzing large rehabilitation-related datasets is problematic due to barriers in accurate stroke lesion segmentation. Manually-traced lesions are currently the gold standard for lesion segmentation on T1-weighted MRIs, but are labor intensive and require anatomical expertise. While algorithms have been developed to automate this process, the results often lack accuracy. Newer algorithms that employ machine-learning techniques are promising, yet these require large training datasets to optimize performance. Here we present ATLAS (Anatomical Tracings of Lesions After Stroke), an open-source dataset of 304 T1-weighted MRIs with manually segmented lesions and metadata. This large, diverse dataset can be used to train and test lesion segmentation algorithms and provides a standardized dataset for comparing the performance of different segmentation methods. We hope ATLAS release 1.1 will be a useful resource to assess and improve the accuracy of current lesion segmentation methods