Practical Dyspnea Assessment: Relationship Between the 0-10 Numerical Rating Scale and the Four-Level Categorical Verbal Descriptor Scale of Dyspnea Intensity.

CONTEXT: Measurement of dyspnea is important for clinical care and research. OBJECTIVES: To characterize the relationship between the 0-10 Numerical Rating Scale (NRS) and four-level categorical Verbal Descriptor Scale (VDS) for dyspnea assessment. METHODS: This was a substudy of a double-blind randomized controlled trial comparing palliative oxygen to room air for relief of refractory breathlessness in patients with life-limiting illness. Dyspnea was assessed with both a 0-10 NRS and a four-level categorical VDS over the one-week trial. NRS and VDS responses were analyzed in cross section and longitudinally. Relationships between NRS and VDS responses were portrayed using descriptive statistics and visual representations. RESULTS: Two hundred twenty-six participants contributed responses. At baseline, mild and moderate levels of breathlessness were reported by 41.9% and 44.6% of participants, respectively. NRS scores demonstrated increasing mean and median levels for increasing VDS intensity, from a mean (SD) of 0.6 (±1.04) for VDS none category to 8.2 (1.4) for VDS severe category. The Spearman correlation coefficient was strong at 0.78 (P < 0.0001). Based on the distribution of NRS scores within VDS categories, we calculated test characteristics of two different cutpoint models. Both models yielded 75% correct translations from NRS to VDS; however, Model A was more sensitive for moderate or greater dyspnea, with fewer misses downcoded. CONCLUSION: There is strong correlation between VDS and NRS measures for dyspnea. Proposed practical cutpoints for the relationship between the dyspnea VDS and NRS are 0 for none, 1-4 for mild, 5-8 for moderate, and 9-10 for severe.

Importance of health information technology, electronic health records, and continuously aggregating data to comparative effectiveness research and learning health care.

Rapidly accumulating clinical information can support cancer care and discovery. Future success depends on information management, access, use, and reuse. Electronic health records (EHRs) are highlighted as a critical component of evidence development and implementation, but to fully harness the potential of EHRs, they need to be more than electronic renderings of the traditional paper medical chart. Clinical informatics and structured accessible secure data captured through EHR systems provide mechanisms through which EHRs can facilitate comparative effectiveness research (CER). Use of large linked administrative databases to answer comparative questions is an early version of informatics-enabled CER familiar to oncologists. An updated version of informatics-enabled CER relies on EHR-derived structured data linked with supplemental information to provide patient-level information that can be aggregated and analyzed to support hypothesis generation, comparative assessment, and personalized care. As implementation of EHRs continues to expand, electronic databases containing information collected via EHRs will continuously aggregate; aggregating data enhanced with real-time analytics can provide point-of-care evidence to oncologists, tailored to patient-level characteristics. The system learns when clinical care informs research, and insights derived from research are reinvested in care. Challenges must be overcome, including interoperability, standardization, access, and development of real-time analytics.

Improving the management of dyspnea in the community using rapid learning approaches.

Patients with chronic pulmonary disease often suffer from breathlessness or dyspnea. Traditional evidence generation techniques to expand upon current treatment paradigms are limited by the significant delay between study initiation and clinical implementation of findings. Rapid learning health care is a novel approach to health care delivery that relies on intelligent and continuous integration of clinical and research data sets to deliver personalized medicine using the most current evidence available. Results of important studies in the management of chronic respiratory disease are presented in brief; however, the focus of this review is on evidence supporting the implementation of a rapid learning model for symptom management. Recent findings suggest that a rapid learning system is feasible and acceptable to patients with advanced illness, helps monitor symptoms overtime, facilitates study of the impact of novel interventions, and can identify unrecognized needs and concerns. A rapid learning model improves comprehensive assessment, timeliness of intervention, and accrual of contemporaneous data to support best practice that tailors care specific to the needs of patients as their disease and lifestyle change overtime. Using the rapid learning health care model, data collected in the process of routine care can simultaneously function both as clinical information and as a resource for research on patient-centered experiences and outcomes.

Heparin-induced thrombocytopenia in cancer.

Heparin-induced thrombocytopenia is a common and clinically important drug-induced complication that can cause life- and limbthreatening thrombosis. Epidemiologically, the disease has been studied in many different clinical settings, but little is known about it in cancer patients, a population at increased risk for thrombosis and thus exposure to heparin products. Additionally, thrombocytopenia is a common finding in cancer patients. The convergence of these variables highlights the importance of an increased understanding of the disease in cancer patients.

Anti-CCP antibody and rheumatoid factor concentrations predict greater disease activity in men with rheumatoid arthritis.

OBJECTIVE: To examine associations of anti-cyclic citrullinated peptide (aCCP) antibody and rheumatoid factor (RF) concentrations with future disease activity in men with rheumatoid arthritis (RA). METHODS: Outcome measures were examined in male US veterans with RA and included (1) proportion of observations in remission (disease activity score (DAS28) < or =2.6); (2) remission for > or =3 consecutive months; and (3) area under the curve (AUC) for DAS28. The associations of autoantibody concentration (per 100 unit increments) with outcomes were examined using multivariate regression. RESULTS: 826 men with RA were included in the analysis; the mean (SD) age was 65 (10.5) years and follow-up was for 2.6 (1.3) years. Most were aCCP (75%) and RF (80%) positive. After multivariate adjustment, aCCP (OR 0.93; 95% CI 0.89 to 0.96) and RF concentrations (OR 0.92; 95% CI 0.90 to 0.94) were associated with a lower odds of remission, a lower proportion of observation in remission (p=0.017 and p=0.002, respectively) and greater AUC DAS28 (p=0.092 and p=0.007, respectively). Among patients with discordant autoantibody status, higher concentrations of both aCCP and RF trended towards an inverse association with remission (OR 0.93; 95% CI 0.83 to 1.05 and OR 0.80; 95% CI 0.59 to 1.10, respectively). CONCLUSIONS: Higher aCCP concentrations (particularly in RF-positive patients) are associated with increased disease activity in US veterans with RA, indicating that aCCP concentration is predictive of future disease outcomes in men.