18 research outputs found

    Prevalence of Disorders Recorded in Dogs Attending Primary-Care Veterinary Practices in England

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    Purebred dog health is thought to be compromised by an increasing occurence of inherited diseases but inadequate prevalence data on common disorders have hampered efforts to prioritise health reforms. Analysis of primary veterinary practice clinical data has been proposed for reliable estimation of disorder prevalence in dogs. Electronic patient record (EPR) data were collected on 148,741 dogs attending 93 clinics across central and south-eastern England. Analysis in detail of a random sample of EPRs relating to 3,884 dogs from 89 clinics identified the most frequently recorded disorders as otitis externa (prevalence 10.2%, 95% CI: 9.1-11.3), periodontal disease (9.3%, 95% CI: 8.3-10.3) and anal sac impaction (7.1%, 95% CI: 6.1-8.1). Using syndromic classification, the most prevalent body location affected was the head-and-neck (32.8%, 95% CI: 30.7-34.9), the most prevalent organ system affected was the integument (36.3%, 95% CI: 33.9-38.6) and the most prevalent pathophysiologic process diagnosed was inflammation (32.1%, 95% CI: 29.8-34.3). Among the twenty most-frequently recorded disorders, purebred dogs had a significantly higher prevalence compared with crossbreds for three: otitis externa (P = 0.001), obesity (P = 0.006) and skin mass lesion (P = 0.033), and popular breeds differed significantly from each other in their prevalence for five: periodontal disease (P = 0.002), overgrown nails (P = 0.004), degenerative joint disease (P = 0.005), obesity (P = 0.001) and lipoma (P = 0.003). These results fill a crucial data gap in disorder prevalence information and assist with disorder prioritisation. The results suggest that, for maximal impact, breeding reforms should target commonly-diagnosed complex disorders that are amenable to genetic improvement and should place special focus on at-risk breeds. Future studies evaluating disorder severity and duration will augment the usefulness of the disorder prevalence information reported herein

    Brain Perfusion and Diffusion Abnormalities in Children Treated for Posterior Fossa Brain Tumors

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    OBJECTIVE: To compare cerebral perfusion and diffusion in survivors of childhood posterior fossa brain tumor with neurologically normal controls and correlate differences with cognitive dysfunction. STUDY DESIGN: We analyzed retrospectively arterial spin-labeled cerebral blood flow (CBF) and apparent diffusion coefficient (ADC) in 21 patients with medulloblastoma (MB), 18 patients with pilocytic astrocytoma (PA), and 64 neurologically normal children. We generated ANCOVA models to evaluate treatment effects on the cerebral cortex, thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, nucleus accumbens, and cerebral white matter at time points an average of 5.7 years after original diagnosis. A retrospective review of patient charts identified 12 patients with neurocognitive data and in whom the relationship between IQ and magnetic resonance imaging variables was assessed for each brain structure. RESULTS: Patients with MB (all treated with surgery, chemotherapy, and radiation) had significantly lower global CBF relative to controls (10%-23% lower, varying by anatomic region, all adjusted P? CONCLUSIONS: The treatment for MB, but not PA, was associated with globally reduced CBF. Treatment in both tumor types was associated with diffusion abnormalities of the mesial temporal lobe structures. Despite significant perfusion abnormalities in patients with MB, diffusion, but not perfusion, correlated with cognitive outcomes

    Brain Perfusion and Diffusion Abnormalities in Children Treated for Posterior Fossa Brain Tumors

    No full text
    OBJECTIVE: To compare cerebral perfusion and diffusion in survivors of childhood posterior fossa brain tumor with neurologically normal controls and correlate differences with cognitive dysfunction. STUDY DESIGN: We analyzed retrospectively arterial spin-labeled cerebral blood flow (CBF) and apparent diffusion coefficient (ADC) in 21 patients with medulloblastoma (MB), 18 patients with pilocytic astrocytoma (PA), and 64 neurologically normal children. We generated ANCOVA models to evaluate treatment effects on the cerebral cortex, thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, nucleus accumbens, and cerebral white matter at time points an average of 5.7 years after original diagnosis. A retrospective review of patient charts identified 12 patients with neurocognitive data and in whom the relationship between IQ and magnetic resonance imaging variables was assessed for each brain structure. RESULTS: Patients with MB (all treated with surgery, chemotherapy, and radiation) had significantly lower global CBF relative to controls (10%-23% lower, varying by anatomic region, all adjusted P? CONCLUSIONS: The treatment for MB, but not PA, was associated with globally reduced CBF. Treatment in both tumor types was associated with diffusion abnormalities of the mesial temporal lobe structures. Despite significant perfusion abnormalities in patients with MB, diffusion, but not perfusion, correlated with cognitive outcomes

    A Prognostic Model of Surgical Site Infection Using Daily Clinical Wound Assessment

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    BACKGROUND: Surgical site infection (SSI) remains a common, costly, and morbid health care-associated infection. Early detection can improve outcomes, yet previous risk models consider only baseline risk factors (BF) not incorporating a proximate and timely data source-the wound itself. We hypothesize that incorporation of daily wound assessment improves the accuracy of SSI identification compared with traditional BF alone. STUDY DESIGN: A prospective cohort of 1,000 post open abdominal surgery patients at an academic teaching hospital were examined daily for serial features (SF), for example, wound characteristics and vital signs, in addition to standard BF, for example, wound class. Using supervised machine learning, we trained 3 NaĂŻve Bayes classifiers (BF, SF, and BF+SF) using patient data from 1 to 5 days before diagnosis to classify SSI on the following day. For comparison, we also created a simplified SF model that used logistic regression. Control patients without SSI were matched on 5 similar consecutive postoperative days to avoid confounding by length of stay. Accuracy, sensitivity/specificity, and area under the receiver operating characteristic curve were calculated on a training and hold-out testing set. RESULTS: Of 851 patients, 19.4% had inpatient SSIs. Univariate analysis showed differences in C-reactive protein, surgery duration, and contamination, but no differences in American Society of Anesthesiologists scores, diabetes, or emergency surgery. The BF, SF, and BF+SF classifiers had area under the receiver operating characteristic curves of 0.67, 0.76, and 0.76, respectively. The best-performing classifier (SF) had optimal sensitivity of 0.80, specificity of 0.64, positive predictive value of 0.35, and negative predictive value of 0.93. Features most associated with subsequent SSI diagnosis were granulation degree, exudate amount, nasogastric tube presence, and heart rate. CONCLUSIONS: Serial features provided moderate positive predictive value and high negative predictive value for early identification of SSI. Addition of baseline risk factors did not improve identification. Features of evolving wound infection are discernable before the day of diagnosis, based primarily on visual inspection

    Patient Perspectives on Post-Discharge Surgical Site Infections: Towards a Patient-Centered Mobile Health Solution

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    <div><p>Background</p><p>Post-discharge surgical site infections (SSI) are a major source of morbidity, expense and anxiety for patients. However, patient perceptions about barriers experienced while seeking care for post-discharge SSI have not been assessed in depth. We explored patient experience of SSI and openness to a mobile health (mHealth) wound monitoring “app” as a novel solution to address this problem.</p><p>Methods</p><p>Mixed method design with semi-structured interviews and surveys. Participants were patients who had post-discharge surgical wound complications after undergoing operations with high risk of SSI, including open colorectal or ventral hernia repair surgery. The study was conducted at two affiliated teaching hospitals, including an academic medical center and a level 1 trauma center.</p><p>Results</p><p>From interviews with 13 patients, we identified 3 major challenges that impact patients' ability to manage post-discharge surgical wound complications, including required knowledge for wound monitoring from discharge teaching, self-efficacy for wound monitoring at home, and accessible communication with their providers about wound concerns. Patients found an mHealth wound monitoring application highly acceptable and articulated its potential to provide more frequent, thorough, and convenient follow-up that could reduce post-discharge anxiety compared to the current practice. Major concerns with mHealth wound monitoring were lack of timely response from providers and inaccessibility due to either lack of an appropriate device or usability challenges.</p><p>Conclusions</p><p>Our findings reveal gaps and frustrations with post-discharge care after surgery which could negatively impact clinical outcomes and quality of life. To address these issues, we are developing mPOWEr, a patient-centered mHealth wound monitoring application for patients and providers to collaboratively bridge the care transition between hospital and home.</p></div

    Barriers and facilitators to coping with wound complications.

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    <p>Ten sub-themes identified from patient interviews related to coping with post-discharge wound complications, organized into 3 major themes. The color distribution of each bar represents the number of participants who considered each sub-theme to be a barrier (red) or a facilitator (green). Grey indicates that the participant did not mention the sub-theme.</p

    Comfort with mHealth application.

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    <p>Participants' comfort with 4 key elements of a wound-tracking mHealth application. Based on 4 survey questions, participants were either “Very comfortable” (dark green), “Somewhat comfortable” (light green), “Neither comfortable nor uncomfortable (grey), or “Somewhat uncomfortable” (light red). No participants selected “Very uncomfortable”.</p
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