Citations

Objectives: Dizziness, vertigo, and unsteadiness are common complaints of patients who present to primary care providers. These patients often are referred to otology for assessment and management. Unfortunately, there are a small number of specialists to manage these patients. However, there are several dizziness disorders that can be successfully managed by primary care providers if the disorder is properly identified. To assist in the identification of several of the most common dizziness disorders, we developed the dizziness symptom profile (DSP). The DSP is a self-report questionnaire designed to generate one or more differential diagnoses that can be combined with the patient’s case history and physical examination. Design: This report describes three investigations. Investigations 1 and 2 (i.e., exploratory and confirmatory investigations, N = 514) describe the development of the DSP. Investigation 3 (N = 195) is a validation study that describes the level of agreement between the DSP completed by the patient, and, the differential diagnosis of the otologist. Results: The final version of the DSP consists of 31 items. Preliminary findings suggest that the DSP is in agreement with the differential diagnoses of ear specialists for Meniere’s disease (100% agreement), vestibular migraine (95% agreement), and benign paroxysmal positional vertigo (82% agreement). Conclusions: Early results suggest that DSP may be useful in the creation of differential diagnoses for dizzy patients that can be evaluated and managed locally. This has the potential to reduce the burden on primary care providers and reduce delays in the diagnosis of common dizziness and vertigo disorders.

AbstractThis study examines the long‐term OS of relapsed AML patients who were enrolled to 9 successive ECOG‐ACRIN trials for newly diagnosed AML, during 1984‐2008. The objectives were to examine whether there is a trend of improvement in the survival of relapsed AML patients in the more recent studies and to search for prognostic factors that are associated with long‐term OS after relapse. A total of 3012 patients were enrolled, 1779 (59.1%) achieved CR1 and of these, 58.9% relapsed. The median follow‐up was 9.7 years. The median OS from relapse was 0.5 years and the 5‐year OS was 10 (±1)%. These results were similar even for the most recent studies. A multivariate model showed that age, cytogenetics at diagnosis, duration of CR1 and undergoing allogeneic transplantation were significantly associated with OS from relapse. Even among patients who relapsed with better prognostic factors; age < 40 and CR1 > 12 months, there was no significant OS difference between the studies. In conclusion, this large cohort appears to confirm that the survival of AML patients postrelapse continues to be dismal and has not improved during the past quarter of a century.

Purpose: Glaucoma specialists and optometrists who work in a team model at a single institution utilize a common definition of glaucoma progression and treatment algorithm. The purpose of this study was to assess the consistency of agreement in identifying glaucoma progression among glaucoma specialists and optometrists of 1 team. Methods: In total, 399 eyes of 200 patients age 18 or older with glaucoma were enrolled over 2 years. Clinical data, disc photographs, optical coherence tomography (OCT), and visual fields were independently reviewed by 2 masked optometrists and 2 masked fellowship-trained glaucoma specialists. Each eye was judged as progression or no progression of glaucomatous disease. The following were assessed: (1) agreement among optometrists; (2) agreement among glaucoma specialists; and (3) agreement among optometrists and glaucoma specialists. The frequency of use of testing modality to determine progression was also studied. κ statistics were used to evaluate agreements. Results: Optometrists agreed with each other for 74.2% of the eyes assessed (κ=0.42), whereas glaucoma specialists agreed with each other for 78.7% of eyes (κ=0.39). All 4 providers agreed with each other for 54.4% of the eyes evaluated (κ=0.37). Providers had the highest agreement when the progression decision was based on disc hemorrhage (92%) and the lowest agreement when based on OCT progression analysis (36%). Compared with optometrists, glaucoma specialists used OCT (P≤0.01) more frequently to determine disease progression. Conclusions: Fair to moderate agreement levels were found among providers in their assessment of glaucoma progression, suggesting that a team approach to glaucoma management may be effective. Further work is needed to investigate ways to optimize consistency within the glaucoma team.

Abstract In 2011, the National Institute on Aging and Alzheimer's Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer's disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer's Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer's Association Research Framework, Alzheimer's disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six‐stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker‐based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker‐based research should not be considered a template for all research into age‐related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β‐amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.

Background Optimal methods of mortality risk stratification in patients in the cardiac intensive care unit ( CICU ) remain uncertain. We evaluated the ability of the Sequential Organ Failure Assessment ( SOFA ) score to predict mortality in a large cohort of unselected patients in the CICU. Methods and Results Adult patients admitted to the CICU from January 1, 2007, to December 31, 2015, at a single tertiary care hospital were retrospectively reviewed. SOFA scores were calculated daily, and Acute Physiology and Chronic Health Evaluation ( APACHE )‐ III and APACHE ‐ IV scores were calculated on CICU day 1. Discrimination of hospital mortality was assessed using area under the receiver‐operator characteristic curve values. We included 9961 patients, with a mean age of 67.5±15.2 years; all‐cause hospital mortality was 9.0%. Day 1 SOFA score predicted hospital mortality, with an area under the receiver‐operator characteristic curve value of 0.83; area under the receiver‐operator characteristic curve values were similar for the APACHE ‐ III score, and APACHE ‐ IV predicted mortality ( P >0.05). Mean and maximum SOFA scores over multiple CICU days had greater discrimination for hospital mortality ( P <0.01). Patients with an increasing SOFA score from day 1 and day 2 had higher mortality. Patients with day 1 SOFA score <2 were at low risk of mortality. Increasing tertiles of day 1 SOFA score predicted higher long‐term mortality ( P <0.001 by log‐rank test). Conclusions The day 1 SOFA score has good discrimination for short‐term mortality in unselected patients in the CICU, which is comparable to APACHE ‐ III and APACHE ‐ IV . Advantages of the SOFA score over APACHE include simplicity, improved discrimination using serial scores, and prediction of long‐term mortality.