Disease-specific Diagnosis Research Articles

Association of the Area Deprivation Index With Dementia Basic Workup and Diagnosis in Central and Western Virginia: A Cross-Sectional Study.

The Area Deprivation Index (ADI) provides a validated and multidimensional metric of areal disadvantage. Our goals were to determine if the ADI influences the likelihood of receiving workup based on published guidelines and an etiologic diagnosis of dementia in Central and Western Virginia. We collected deidentified data from the electronic health record of individuals aged 50-105 years diagnosed with dementia at the University of Virginia (UVA) Medical Center (2016-2021) and at Carillion Clinic (2018-2021). Visit-specific ICD-10 codes were used to classify each dementia diagnosis as "disease-specific" (e.g., Alzheimer disease) or "general" (e.g., unspecified dementia). Following the American Academy of Neurology guidelines, we considered the evaluation performed as "adequate" if patients had vitamin B12, thyroid-stimulating hormone, and brain CT or magnetic resonance imaging within 6 months of the initial diagnosis. Census tract ADI was linked to study participants using the unique census tract identifier derived from the participants' home addresses at the time of diagnosis. Statistical modeling occurred under a Bayesian paradigm implemented using a standard code in R. The study included 13,431 individuals diagnosed with dementia at UVA (n = 7,152) and Carillion Clinic (n = 6,279). Of those, 32.5% and 20.4% received "disease-specific" diagnoses at UVA and Carillion Clinic and 8.2% and 20.4% underwent "adequate" workup, respectively. The adjusted relationship between census tract ADI and the likelihood of a disease-specific diagnosis was U-shaped: Residence in moderately disadvantaged areas was associated with the lowest likelihood of disease-specific diagnosis. Most patients diagnosed with dementia did not receive an adequate evaluation or an etiologic diagnosis. Those living in locations just above the national median ADI levels had the lowest likelihood of receiving an etiologic diagnosis, lower than those in the least and most deprived areas. Renewed awareness efforts among providers are needed to increase compliance with diagnostic guidelines.

Acute patients discharged without an established diagnosis: risk of mortality and readmission of nonspecific diagnoses compared to disease-specific diagnoses.

Nonspecific discharge diagnoses after acute hospital courses represent patients discharged without an established cause of their complaints. These patients should have a low risk of adverse outcomes as serious conditions should have been ruled out. We aimed to investigate the mortality and readmissions following nonspecific discharge diagnoses compared to disease-specific diagnoses and assessed different nonspecific subgroups. Register-based cohort study including hospital courses beginning in emergency departments across 3 regions of Denmark during March 2019-February 2020. We identified nonspecific diagnoses from the R- and Z03-chapter in the ICD-10 classification and excluded injuries, among others-remaining diagnoses were considered disease-specific. Outcomes were 30-day mortality and readmission, the groups were compared by Cox regression hazard ratios (HR), unadjusted and adjusted for socioeconomics, comorbidity, administrative information and laboratory results. We stratified into short (3-<12h) or lengthier (12-168h) hospital courses. We included 192,185 hospital courses where nonspecific discharge diagnoses accounted for 50.7% of short and 25.9% of lengthier discharges. The cumulative risk of mortality for nonspecific vs. disease-specific discharge diagnoses was 0.6% (0.6-0.7%) vs. 0.8% (0.7-0.9%) after short and 1.6% (1.5-1.7%) vs. 2.6% (2.5-2.7%) after lengthier courses with adjusted HRs of 0.97 (0.83-1.13) and 0.94 (0.85-1.05), respectively. The cumulative risk of readmission for nonspecific vs. disease-specific discharge diagnoses was 7.3% (7.1-7.5%) vs. 8.4% (8.2-8.6%) after short and 11.1% (10.8-11.5%) vs. 13.7% (13.4-13.9%) after lengthier courses with adjusted HRs of 0.94 (0.90-0.98) and 0.95 (0.91-0.99), respectively. We identified 50 clinical subgroups of nonspecific diagnoses, of which Abdominal pain (n = 12,462; 17.1%) and Chest pain (n = 9,599; 13.1%) were the most frequent. The subgroups described differences in characteristics with mean age 41.9 to 80.8 years and mean length of stay 7.1 to 59.5h, and outcomes with < 0.2-8.1% risk of 30-day mortality and 3.5-22.6% risk of 30-day readmission. In unadjusted analyses, nonspecific diagnoses had a lower risk of mortality and readmission than disease-specific diagnoses but had a similar risk after adjustments. We identified 509 clinical subgroups of nonspecific diagnoses with vastly different characteristics and prognosis.

Histological and functional assessment of a Takotsubo cardiomyopathy model established by immobilization stress.

Takotsubo cardiomyopathy (TTC), also known as stress-induced cardiomyopathy, resembles acute heart failure syndrome but lacks disease-specific diagnosis and treatment strategies. TTC accounts for approximately 5-6% of all suspected cases of acute coronary syndrome in women. At present, animal models of TTC are often created by large amounts of exogenous catecholamines such as isoproterenol. However, isoproterenol injection cannot fully simulate the onset of stress-induced cardiomyopathy in humans since stress is not an instantaneous event. Rats were immobilized for 6h per day for 1-14 days. To examine whether the TTC model was successful, echocardiography was employed; Elisa detected serum sympathetic activation markers; and the Open-Field test (OFT) was used to analyze behavioral changes in rats after stress. Western blot and histology were used to assess sympathetic remodeling, inflammation levels, and fibrosis; qRT-PCR was used to explore the levels of fibrosis and myocardial hypertrophy. The electrical stability of ventricular was determined by electrophysiological testing. The rats showed severe stress behavior and local sympathetic remodeling of the heart after only 1 day of stress. After 3 days of stress, the induction of ventricular tachyarrhythmia increased prominently. The highest incidence of TTC in rats was at 5 days of immobilization stress. The pathological left ventricular remodeling caused by immobilization (IMO) stress includes inflammatory infiltration, fibrosis, and myocardial hypertrophy. Our study confirms the hypothesis that IMO stress can mimic Takotsubo cardiomyopathy, and the various effects on the heart depending on the duration of IMO stress. We observed the highest incidence of TTC occurred after 5 days of stress. Furthermore, there is a gradual occurrence of electrical and structural remodeling as the stress duration prolongs.

Surgical lung biopsy for suspected interstitial lung disease with video-assisted thoracoscopic surgery is safe, providing exact histological and disease specific diagnosis for tailoring treatment.

Surgical lung biopsy (SLB) is required for diagnosis in patients with suspected interstitial lung disease (ILD) if other less invasive diagnostic methods are non-conclusive. We evaluated the outcome of SLB by using centralized databases in a whole-nation patient-cohort. A population-based retrospective study on 68 consecutive patients (mean age 58 years, 58.8% males) that underwent SLB in Iceland between the years 2008 and 2020. Patient information was obtained from patient charts and peri- and postoperative complications were registered together with 30- and 90-day mortality. Computed tomography (CT) scans, histological biopsies and spirometry results were reviewed, and overall survival (Kaplan-Meier) estimated. Mean follow-up was 61.3 months (range, 3-155 months). Out of 68 SLB-patients 41 (60.3%) had preoperatively undergone non-conclusive transbronchial biopsies (TBB) obtained with bronchoscopy. Spirometry showed forced vital capacity (FVC) 3.0 L and forced expiratory volume in 1 second (FEV1) 2.3 L, or 73.0% and 71.6% of predicted value, respectively. Video-assisted thoracoscopic surgery (VATS) technique was used in all cases and provided a histologic and disease specific diagnosis in 92.6% of cases; most often being nonspecific interstitial pneumonia (NSIP) (29.4%) and usual interstitial pneumonia (UIP) (23.5%). One patient (1.5%) sustained a major postoperative complication (excessive bleeding) and seven patients (10.3%) minor complications. Median chest tube time and length of stay was 1 and 2 days, respectively. No patients died <90 days postoperatively. Overall survival at 1 and 5 years was 95.6% and 73.5%, respectively, and 5-year survival for NSIP and UIP was 85% and 43.7%, respectively. Long-term mortality for UIP was four times higher when compared with NSIP and other diagnosis. Lung biopsy with VATS-technique provided a definitive histological and disease specific diagnosis in majority of cases. The procedure is safe, reflected in low complication-rates and short hospital stay, and can therefore be used to diagnose and tailor treatment of ILD patients.

Obstacles and expectations of rare disease patients and their families in Türkiye: ISTisNA project survey results.

Rare disease patients constitute a significant part of the healthcare system of all countries. However, the information on the experiences during disease processes and daily life of rare disease patients is still limited. So far, there is a small number of studies conducted in Türkiye, and they mainly cover specific issues like education or anxiety. Here we present a comprehensive survey analysis conducted among the patients and their families within the scope of the Istanbul Solution Platform for Undiagnosed and Rare Diseases-ISTisNA project. A total of 498 individuals responded to the survey, and 58% of the participants answered all questions. The majority of the patients were in the age range of 1-10 years (44.7%), and 91% of all the patients had a precise diagnosis. The diagnosis rate in the first 6 months was 69%, and almost 10% of the patients remained undiagnosed. The mothers were the primary caregivers (72%). Nearly 30% of the caregivers had to quit their jobs and 25% of the patients (0-18 years) had to leave school. Accessing physicians with relevant specialization and reaching treatments/medications/supplements were the two main obstacles the participants mentioned, with a frequency of 81% and 73%, respectively. Around 50% of participants noted that they commonly faced difficulties at work/school and in their social lives. The highest expectation or priority was the establishment of rare disease-specific diagnosis and treatment centers, accurate and detailed information on diseases in the Turkish language, and easy access to physicians, treatments, and supportive therapies. To the best of our knowledge, this is the most comprehensive survey conducted on the rare disease community in Türkiye. These results show that regardless of the country, the individuals affected by rare diseases and their families have similar problems and expectations. On the other hand, regional and country-specific issues are still in the line to be solved. These studies can provide a deeper insight into rare diseases and guide the activities of Türkiye's national rare disease action plan.

Genome-wide DNA methylation profiling and exome sequencing resolved a long-time misdiagnosed case.

The search for aetiology of Mendelian disorders is traditionally based on the observation of clinical phenotypes and molecular screening of associated genes. However, a disease-specific diagnosis can be challenging. In this study we detail how the combinatorial genomic and epigenomic assessment allowed to find the underlying molecular event of a clinical case that remained misdiagnosed for years. The individual was referred as affected by an atypical form of Kabuki syndrome with a variant of uncertain significance in the KMT2D gene. However, significant inconsistencies with this diagnosis emerged upon familial segregation of the variant and after the clinical re-evaluation. Therefore, we applied an epigenomic strategy by studying the DNA methylation profile which resulted not consistent with the Kabuki syndrome episignature or with any other disorder-specific episignature described so far, providing strong evidence that the Kabuki syndrome diagnosis does not apply. This result led us to further investigate for epigenetic machinery diseases by using a multigene panel for chromatinopathies. Since this analysis yielded negative results, we applied a whole exome sequencing and identified a de novo pathogenic variant in the CTNNB1 gene associated to NEDSDV syndrome, a neurodevelopmental disorder characterized by intellectual disability and craniofacial anomalies. Based on molecular results and the updated clinical features, we confirmed the NEDSDV diagnosis. Our findings show that the combination of genomic and epigenomics strategies, along with a deeper analysis of clinical phenotype, may provide a significant improvement in the diagnostic protocols for rare genetic disorders and help resolve long-time misdiagnosed and unsolved case.

«In the post period of covid -19 diseasespecific clinical-laboratory properties and diagnosis of pyelonephritis in children»

«In the post period of covid -19 diseasespecific clinical-laboratory properties and diagnosis of pyelonephritis in children»

Identifying COVID-19-Specific Transcriptomic Biomarkers with Machine Learning Methods.

COVID-19, a severe respiratory disease caused by a new type of coronavirus SARS-CoV-2, has been spreading all over the world. Patients infected with SARS-CoV-2 may have no pathogenic symptoms, i.e., presymptomatic patients and asymptomatic patients. Both patients could further spread the virus to other susceptible people, thereby making the control of COVID-19 difficult. The two major challenges for COVID-19 diagnosis at present are as follows: (1) patients could share similar symptoms with other respiratory infections, and (2) patients may not have any symptoms but could still spread the virus. Therefore, new biomarkers at different omics levels are required for the large-scale screening and diagnosis of COVID-19. Although some initial analyses could identify a group of candidate gene biomarkers for COVID-19, the previous work still could not identify biomarkers capable for clinical use in COVID-19, which requires disease-specific diagnosis compared with other multiple infectious diseases. As an extension of the previous study, optimized machine learning models were applied in the present study to identify some specific qualitative host biomarkers associated with COVID-19 infection on the basis of a publicly released transcriptomic dataset, which included healthy controls and patients with bacterial infection, influenza, COVID-19, and other kinds of coronavirus. This dataset was first analysed by Boruta, Max-Relevance and Min-Redundancy feature selection methods one by one, resulting in a feature list. This list was fed into the incremental feature selection method, incorporating one of the classification algorithms to extract essential biomarkers and build efficient classifiers and classification rules. The capacity of these findings to distinguish COVID-19 with other similar respiratory infectious diseases at the transcriptomic level was also validated, which may improve the efficacy and accuracy of COVID-19 diagnosis.

Clinical translation of computational brain models: understanding the salience of trust in clinician–researcher relationships

ABSTRACT Computational brain models use machine learning, algorithms and statistical models to harness big data for delivering disease-specific diagnosis or prognosis for individuals. While intended to support clinical decision-making, their translation into clinical practice remains challenging despite efforts to improve implementation through training clinicians and clinical staff in their use and benefits. Drawing on the specific case of neurology, we argue that existing implementation efforts are insufficient for the responsible translation of computational models. Our research based on a collective seven-year engagement with the Human Brain Project, participant observation at workshops and conferences, and expert interviews, suggests that relationships of trust between clinicians and researchers (modellers, data scientists) are essential to the meaningful translation of computational models. In particular, efforts to increase model transparency, strengthen upstream collaboration, and integrate clinicians' perspectives and tacit knowledge have the potential to reinforce trust building and increase translation of technologies that are beneficial to patients.

Risk of Incident Type 2 Diabetes Mellitus Among Patients With Rheumatoid Arthritis: A Population‐Based Cohort Study

To examine the risk of incident type 2 diabetes mellitus (DM) among patients with rheumatoid arthritis (RA) versus the risk among 4 different comparison cohorts. Using a large US commercial insurance database, Optum Clinformatics Data Mart (2005-2017), we identified patients with RA based on ≥2 diagnoses for RA and use of ≥1 disease-modifying antirheumatic drug. We selected 4 comparison cohorts with ≥2 disease-specific diagnoses and ≥1 dispensing of disease-specific drugs: 1) general non-RA patients, 2) patients with hypertension, 3) patients with osteoarthritis (OA), and 4) patients with psoriatic arthritis (PsA). The index date was the disease-specific drug dispensing date. Patients with RA were matched to the comparator cohorts (except PsA) for age as of the index date, sex, and index date. The primary outcome was incident type 2 DM, defined as a new diagnosis of type 2 DM plus a new dispensing of antidiabetic drugs. A multivariable Cox proportional hazards model estimated hazard ratios of incident type 2 DM among RA versus each of the comparison cohorts, accounting for >40 baseline covariates. A total of 449,327 RA, general non-RA, hypertension, OA, or PsA patients were selected. During the median of 1.6 (range 0.6-3.3) years of follow-up, the incidence rate of type 2 DM was the lowest in the RA cohort (7.0 per 1,000 person-years) and highest (12.3 per 1,000 person-years) in the hypertension cohort. After adjusting for >40 baseline covariates, we found that RA was associated with a 24-35% lower risk of incident type 2 DM compared to 4 comparison groups. In this large population-based cohort study, patients with RA had a lower rate of incident type 2 DM compared to the general non-RA, hypertension, OA, and PsA cohorts.

The Clinical Application of Oncomine Myeloid Next Generation Sequencing (NGS): Comparison of Cytogenetics and NGS in Patients with Suspected Myelodysplastic Syndrome

Background: A common referral to hematology is for patients with suspected myelodysplastic syndrome (MDS) or cytopenias of undetermined origin. We recently implemented a Next Generation Sequencing (NGS) panel which covers a wide spectrum of genes related to the major myeloid disorders, including DNA based gene sequencing and RNA based gene fusion analysis, as a tier one clinical diagnostic test (Levy et al. Eur. J. Haematol 2019). We compared the diagnostic and prognostic information derived from conventional cytogenetics and NGS testing as well as the clinical impact on management in this patient group. Methods: We identified all new cases with suspected MDS or cytopenias of undetermined origin referred between January 2018 to February 2019 that had both NGS and cytogenetic testing at London Health Sciences Centre, a tertiary care centre servicing a population of approximately 2.5 million in Southwestern Ontario, Canada. From the retrospective review of electronic medical record, patient demographics, diagnosis and management were ascertained. Diagnosis was based on the 2016 WHO classification and the ICD-10.Previously reported definitions for ICUS, IDUS, CHIP, and CCUSwere also adopted (Bejar et al. Leukemia 2017). Patients not meeting these criteria were defined as either cytopenia not yet determined (NYD) or secondary to other systemic disease. The impact of NGS and cytogenetics results on diagnosis, prognosis, and management of each disease were assessed by referring to the latest National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines in Oncology. Either a bone marrow (BM) or peripheral blood (PB) sample from each patient was assessed by the Oncomine Myeloid NGS panel (Thermo-Fisher, MA, USA), which examines DNA sequence variants in 40 genes (17 full genes and 23 hotspot genes) along with an RNA-based panel of 29 fusion driver genes and their over 600 fusion partners. Patients' BM samples were also tested by the conventional cytogenetic G-banding method. Results: Of the 1100 samples assessed by NGS, 178 met the study inclusion criteria. Overall, 120 (67.4%) patients had both cytogenetics and NGS performed on their BM samples. Of those 120 patients, 41 (34.2%) had DNA mutations, 17 (14.2%) had cytogenetic abnormalities, 22 (18.3%) had both molecular and cytogenetic findings, and 40 (33.3%) had neither abnormality identified. NGS Information contributed in diagnosing 13 (10.8%) patients, while cytogenetics in 6 (5%) patients. In addition, of 38 patients who were diagnosed as MDS with good/intermediate risk cytogenetics, 24 (63.2%) harbored poor prognostic risk mutations as detected by NGS (Table), influencing the management of disease. Additionally, 22 (12.4%) of all patients had NGS testing using PB and cytogenetics using BM samples, and of these 13 (52.2%) patients had NGS abnormalities. Finally, 36 (20.2%) of all patients had only NGS testing by PB samples. Of those, 12 (33.3%) were found to harbor at least one gene mutation including ASXL1, TP53, ZRSR2, and STAG1 suggesting poor prognostic significance for diagnoses of MDS, or JAK2, SF3B1 which could support a disease specific diagnosis. Conclusion: NGS had enhanced diagnostic capabilities including classification of newly described entities such as ICUS or CCUS and more importantly yielded additional prognostic information compared to cytogenetics alone for this patient population. Cytogenetic findings were mainly aneuploidy or deletions, either clinically evident constitutional abnormalities such as Trisomy 21 and +X in Klinefelter syndrome, or loss of Y chromosome in a small proportion of cells and thus of questionable clinical significance. Based on this information consideration should be given to using the NGS panel as the primary molecular diagnostic and prognostic tool with karyotyping being reserved for subsets of patients being assessed for suspected MDS or cytopenias of undetermined origin. Disclosures Hsia: Amgen: Honoraria; Jansen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees.

Flow Cytometry for Diagnosis of Primary Immune Deficiencies-A Tertiary Center Experience From North India.

Flow cytometry has emerged as a useful technology that has facilitated our understanding of the human immune system. Primary immune deficiency disorders (PIDDs) are a heterogeneous group of inherited disorders affecting the immune system. More than 350 genes causing various PIDDs have been identified. While the initial suspicion and recognition of PIDDs is clinical, laboratory tools such as flow cytometry and genetic sequencing are essential for confirmation and categorization. Genetic sequencing, however, are prohibitively expensive and not readily available in resource constrained settings. Flow cytometry remains a simple, yet powerful, tool for multi-parametric analysis of cells. While it is confirmatory of diagnosis in certain conditions, in others it helps in narrowing the list of putative genes to be analyzed. The utility of flow cytometry in diagnosis of PIDDs can be divided into four major categories: (a) Enumeration of lymphocyte subsets in peripheral blood. (b) Detection of intracellular signaling molecules, transcription factors, and cytokines. (c) Functional assessment of adaptive and innate immune cells (e.g., T cell function in severe combined immune deficiency and natural killer cell function in familial hemophagocytic lymphohistiocytosis). (d) Evaluation of normal biological processes (e.g., class switching in B cells by B cell immunophenotyping). This review focuses on use of flow cytometry in disease-specific diagnosis of PIDDs in the context of a developing country.

The quality of the sickness certificate. A case control study of patients with symptom and disease specific diagnoses in primary health care in Sweden

Objective: To compare information in sickness certificates and rehabilitation activities for patients with symptom diagnoses vs patients with disease specific diagnoses.Design: Retrospective case control study 2013–2014.Setting: Primary health care, Sweden.Subjects. Patients with new onset sickness certificates with symptom diagnoses n = 222, and disease specific diagnoses (controls), n = 222.Main outcome measures: Main parameters assessed were: information about body function and activity limitation in certificates, duration of sick leave, certificate renewals by telephone, diagnostic investigations, health care utilisation, contacts between patients, rehabilitation coordinators, social insurance officers, employers and occurrence of rehabilitation plans.Results: Information about body function and activity limitation was sufficient according to guidelines in half of all certificates, less in patients with symptom diagnoses compared to controls (44% vs. 56%, p = 0.008). Patients with symptom diagnoses had shorter sick leave than controls (116 vs. 151 days p = 0.018) and more certificates issued by telephone (23% vs. 15% p = 0.038). Furthermore, they underwent more diagnostic investigations (32% vs. 18%, p < 0.001) and the year preceding sick leave they had more visits to health care (82% vs. 68%, p < 0.001), but less follow-up (16% vs. 26%, p < 0.008). In both groups contacts related to rehabilitation and with employers were scarce.Conclusion: Certificates with symptom diagnoses compared to disease specific diagnoses could be used as markers for insufficient certificate quality and for patients with higher health care utilisation. Overall, the information in half of the certificates was insufficient and early contacts with employers and rehabilitation activities were in practice missing.KEY POINTSSymptom diagnoses are proposed as markers of sickness certification quality. We investigated this by comparing certificates with and without symptom diagnoses.Certificates with symptom diagnoses lacked information to a higher degree compared to certificates with disease specific diagnoses.Regardless of diagnoses, early contacts between patients, rehabilitation coordinators and social insurance officers were rare and contacts with employers were absent.

Is the clinical lipidomics a potential goldmine?

Clinical lipidomics is a new extension of lipidomics to study lipid profiles, pathways, and networks by characterizing and quantifying the complete lipid molecules in cells, biopsy, or body fluids of patients. It undoubtfully has more values if lipidomics can be integrated with the data of clinical proteomic, genomic, and phenomic profiles. A number of challenges, e.g., instability, specificity, and sensitivity, in lipidomics have to be faced and overcome before clinical application. The association of lipidomics data with gene expression and sequencing of lipid-specific proteins/enzymes should be furthermore clarified. Therefore, clinical lipidomics is expected to be more stable during handling, sensitive in response to changes, specific for diseases, efficient in data analyses, and standardized in measurements, in order to meet clinical needs. Clinical lipidomics will become a more important approach in clinical applications and will be the part of “natural” measures for early diagnosis and progress of disease. Thus, clinical lipidomics will be one of the most powerful approaches for disease-specific diagnosis and therapy, once the mystery of lipidomic profiles and metabolic enzymes is deciphered.

Using Self-reports or Claims to Assess Disease Prevalence: It's Complicated.

Two common ways of measuring disease prevalence include: (1) using self-reported disease diagnosis from survey responses; and (2) using disease-specific diagnosis codes found in administrative data. Because they do not suffer from self-report biases, claims are often assumed to be more objective. However, it is not clear that claims always produce better prevalence estimates. Conduct an assessment of discrepancies between self-report and claims-based measures for 2 diseases in the US elderly to investigate definition, selection, and measurement error issues which may help explain divergence between claims and self-report estimates of prevalence. Self-reported data from 3 sources are included: the Health and Retirement Study, the Medicare Current Beneficiary Survey, and the National Health and Nutrition Examination Survey. Claims-based disease measurements are provided from Medicare claims linked to Health and Retirement Study and Medicare Current Beneficiary Survey participants, comprehensive claims data from a 20% random sample of Medicare enrollees, and private health insurance claims from Humana Inc. Prevalence of diagnosed disease in the US elderly are computed and compared across sources. Two medical conditions are considered: diabetes and heart attack. Comparisons of diagnosed diabetes and heart attack prevalence show similar trends by source, but claims differ from self-reports with regard to levels. Selection into insurance plans, disease definitions, and the reference period used by algorithms are identified as sources contributing to differences. Claims and self-reports both have strengths and weaknesses, which researchers need to consider when interpreting estimates of prevalence from these 2 sources.

Importance of an Interprofessional Team Approach in Achieving Improved Management of the Dizzy Patient.

Because of its multifaceted nature, dizziness is difficult for clinicians to diagnose and manage independently. Current treatment trends suggest that patients are often referred to the otolaryngologist for intervention despite having a nonotologic disorder. Additionally, many individuals with atypical presentations are often misdiagnosed and spend a significant amount of time waiting for consultation by the otolaryngologist. Few studies have alluded that implementation of an interprofessional team approach in the diagnosis and management of the dizzy patient can improve clinical decision-making. However, to the authors' knowledge, there is no information specifically quantifying the outcomes and potential benefits of using an interprofessional balance care team approach. To compare dizziness diagnoses trends and referral practices with and without the use of an interprofessional management approach within a university healthcare system. Over the course of a 3-yr period, a retrospective review of the diagnosis and management of dizziness was performed with and without implementation of an interprofessional team. To observe potential differences, year 3 incorporated the interprofessional management approach while years 1-2 did not. The two periods were then compared to each other. A total of 134 patients referred to a university hearing clinic for a vestibular and balance function evaluation. Diagnoses and management trends were examined with descriptive statistics (percentages and frequencies). Fisher's exact tests, analysis of contingency tables, were conducted to evaluate the influence of interprofessional management on dizziness diagnoses and treatment patterns. Results demonstrated that before implementation of an interprofessional team approach, (1) referring clinicians used unspecific dizziness diagnosis codes (e.g., dizziness and giddiness), (2) a low number of patients with dizziness were referred for balance function testing, (3) diagnoses remained unspecific following the balance function assessment, and (4) the most frequently occurring vestibular diagnoses were unilateral vestibular hypofunction and benign paroxysmal positional vertigo. Following the use of an interprofessional management approach, it was determined that (1) disease-specific diagnoses increased, (2) patients with dizziness were referred for balance function testing mainly by otolaryngologists, (3) dizziness was considered to be multifaceted for a greater number of patients, (4) a larger percentage of patients were referred to a specialist other than the otolaryngologist as a result of their diagnosis, and (5) patients reported reduction or resolution of their symptoms. An interprofessional management approach for the dizzy patient can lead to more specific diagnoses and provide alternative referral pathways to other health-care professionals (e.g., audiologists, physical therapists, and pharmacists) in an effort to reduce over-referral to one specialist. Future studies should address the utility of an interprofessional team approach in the overall management of patients with dizziness.

Modification of the GOLD recommendations for chronic obstructive pulmonary disease to broaden their usage in Turkey

ABSTRACTDespite the introduction of numerous national and international COPD guidelines designed to provide clinicians with optimal evidence-based disease management strategies, COPD remains an underdiagnosed and poorly treated disease. The Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines recommend disease specific diagnosis and management strategies, and they are widely used internationally. In this short report we present the outcomes of a meeting of respiratory experts in Turkey who reviewed the GOLD guidelines and their applicability to the Turkish healthcare system. In particular, we were interested to investigate the possibility of developing a simplified version of the combined assessment model which we believe will be more acceptable to Turkish pulmonologists and will increase its use in everyday clinical practice.

Flow Cytometry, a Versatile Tool for Diagnosis and Monitoring of Primary Immunodeficiencies.

Genetic defects of the immune system are referred to as primary immunodeficiencies (PIDs). These immunodeficiencies are clinically and immunologically heterogeneous and, therefore, pose a challenge not only for the clinician but also for the diagnostic immunologist. There are several methodological tools available for evaluation and monitoring of patients with PIDs, and of these tools, flow cytometry has gained prominence, both for phenotyping and functional assays. Flow cytometry allows real-time analysis of cellular composition, cell signaling, and other relevant immunological pathways, providing an accessible tool for rapid diagnostic and prognostic assessment. This minireview provides an overview of the use of flow cytometry in disease-specific diagnosis of PIDs, in addition to other broader applications, which include immune phenotyping and cellular functional measurements.

Clinical applications of next-generation sequencing in histocompatibility and transplantation.

Next-generation sequencing (NGS) can overcome traditional methodological barriers to facilitate detailed studies of large genomes. Here, we summarize recent NGS-based developments in histocompatibility and transplantation, and highlight the dynamic range of clinical applications achievable on this platform. Multiple NGS-based protocols have been established to achieve unambiguous human leukocyte antigen genotyping. These methods are presently engaged to serve the high-throughput demand of large bone marrow registries; however, the scalable nature of NGS makes it an equally attractive technology for select applications within solid organ transplantation. Recently, the exquisite sensitivity of NGS has been leveraged to perform noninvasive allograft monitoring by tracking the dynamics of donor-derived cell-free DNA. Further, NGS-based T-cell receptor and immunoglobulin heavy chain repertoire profiling appear to be useful in clarifying disease-specific diagnoses in certain complex allograft pathology; detecting/quantifying minimal residual disease following allogeneic stem cell transplantation; and tracking donor-reactive T cells to understand the mechanism of tolerance in kidney transplant recipients. NGS is superior to classical Sanger sequencing in its throughput, sensitivity, and the ability to provide phase-defined sequence data. These unique properties allow its broad application to diverse areas in clinical transplantation.

Bioengineering silicon quantum dot theranostics using a network analysis of metabolomic and proteomic data in cardiac ischaemia

Metabolomic profiling is ideally suited for the analysis of cardiac metabolism in healthy and diseased states. Here, we show that systematic discovery of biomarkers of ischemic preconditioning using metabolomics can be translated to potential nanotheranostics. Thirty-three patients underwent percutaneous coronary intervention (PCI) after myocardial infarction. Blood was sampled from catheters in the coronary sinus, aorta and femoral vein before coronary occlusion and 20 minutes after one minute of coronary occlusion. Plasma was analysed using GC-MS metabolomics and iTRAQ LC-MS/MS proteomics. Proteins and metabolites were mapped into the Metacore network database (GeneGo, MI, USA) to establish functional relevance. Expression of 13 proteins was significantly different (p<0.05) as a result of PCI. Included amongst these was CD44, a cell surface marker of reperfusion injury. Thirty-eight metabolites were identified using a targeted approach. Using PCA, 42% of their variance was accounted for by 21 metabolites. Multiple metabolic pathways and potential biomarkers of cardiac ischemia, reperfusion and preconditioning were identified. CD44, a marker of reperfusion injury, and myristic acid, a potential preconditioning agent, were incorporated into a nanotheranostic that may be useful for cardiovascular applications. Integrating biomarker discovery techniques into rationally designed nanoconstructs may lead to improvements in disease-specific diagnosis and treatment.