Using existing data to address important clinical questions in critical care

Objective: With important technological advances in healthcare delivery and the internet, clinicians and scientists now have access to overwhelming number of available databases capturing patients with critical illness. Yet investigators seeking to answer important clinical or research questions with existing data have few resources that adequately describe the available sources and the strengths and limitations of each. This article reviews an approach to selecting a database to address health services and outcomes research questions in critical care, examines several databases that are commonly used for this purpose, and briefly describes some strengths and limitations of each. Data Sources: Narrative review of the medical literature. Summary: The available databases that collect information on critically ill patients are numerous and vary in the types of questions they can optimally answer. Selection of a data source must not only consider accessibility, but also the quality of the data contained within the database, and the extent to which it captures the necessary variables for the research question. Questions seeking causal associations (e.g. effect of treatment on mortality) usually either require secondary data that contain detailed information about demographics, laboratories, and physiology to best address non-random selection or sophisticated study design. Purely descriptive questions (e.g. incidence of respiratory failure) can often be addressed using secondary data with less detail such as administrative claims. Though each database has its own inherent limitations, all secondary analyses will be subject to the same challenges of appropriate study design and good observational research. Conclusion: The literature demonstrates that secondary analyses can have significant impact on critical care practice. While selection of the optimal database for a particular question is a necessary part of high-quality analyses, it is not sufficient to guarantee an unbiased study. Thoughtful and well-constructed study design and analysis approaches remain equally important pillars of robust science. Only through responsible use of existing data will investigators ensure that their study has the greatest impact on critical care practice and outcomes.AHRQ K08 HS020672, NIH K08 HL091249Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106051/1/Cooke - Existing data in critical care.pd

Talk: Using Dialogic Talk in Science

This short article seeks to outline the value of talk in the promotion of teaching in primary science

Prediction of Critical Illness During Out-of-Hospital Emergency Care

CONTEXT: Early identification of nontrauma patients in need of critical care services in the emergency setting may improve triage decisions and facilitate regionalization of critical care. OBJECTIVES: To determine the out-of-hospital clinical predictors of critical illness and to characterize the performance of a simple score for out-of-hospital prediction of development of critical illness during hospitalization. DESIGN AND SETTING: Population-based cohort study of an emergency medical services (EMS) system in greater King County, Washington (excluding metropolitan Seattle), that transports to 16 receiving facilities. PATIENTS: Nontrauma, non-cardiac arrest adult patients transported to a hospital by King County EMS from 2002 through 2006. Eligible records with complete data (N = 144,913) were linked to hospital discharge data and randomly split into development (n = 87,266 [60%]) and validation (n = 57,647 [40%]) cohorts. MAIN OUTCOME MEASURE: Development of critical illness, defined as severe sepsis, delivery of mechanical ventilation, or death during hospitalization. RESULTS: Critical illness occurred during hospitalization in 5% of the development (n = 4835) and validation (n = 3121) cohorts. Multivariable predictors of critical illness included older age, lower systolic blood pressure, abnormal respiratory rate, lower Glasgow Coma Scale score, lower pulse oximetry, and nursing home residence during out-of-hospital care (P < .01 for all). When applying a summary critical illness prediction score to the validation cohort (range, 0-8), the area under the receiver operating characteristic curve was 0.77 (95% confidence interval [CI], 0.76-0.78), with satisfactory calibration slope (1.0). Using a score threshold of 4 or higher, sensitivity was 0.22 (95% CI, 0.20-0.23), specificity was 0.98 (95% CI, 0.98-0.98), positive likelihood ratio was 9.8 (95% CI, 8.9-10.6), and negative likelihood ratio was 0.80 (95% CI, 0.79- 0.82). A threshold of 1 or greater for critical illness improved sensitivity (0.98; 95% CI, 0.97-0.98) but reduced specificity (0.17; 95% CI, 0.17-0.17). CONCLUSIONS: In a population-based cohort, the score on a prediction rule using out-of-hospital factors was significantly associated with the development of critical illness during hospitalization. This score requires external validation in an independent populationPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85143/1/Seymour - JAMA-2010-747-54.pdf11

LAKE SEDIMENT ARCHIVES OF ATMOSPHERIC POLLUTION FROM THE PERUVIAN AND BOLIVIAN ANDES

Despite a richly-documented history of metallurgy following Hispanic conquest of the Inca, little is known concerning the loci and intensities of earlier metallurgical activities. Lake sediments offer one strategy to reconstruct this history because the deposition of trace elements associated with smelting form a continuous archive that can be assessed in the context of regional archaeology. To reconstruct regional histories of late Holocene atmospheric pollution, two lake sediment cores were collected from mining areas in the central Peruvian Andes. Lake sediment stratigraphies of elemental concentrations and isotopic ratios preserve a regional record of pre-Incan, Incan, and Colonial smelting practices. Our records provide the first evidence for intensive, pre-Colonial smelting in the central Peruvian Andes, and corroborate earlier findings from Bolivia. Surprisingly, smelting appears to have operated independent of oversight from the Wari (500 to 1000 AD) or Inca (1460 to 1532 AD) Empires. With Spanish arrival, smelting activity increased dramatically, only to be superseded by post-industrial pollution.The two central Andean records were compared to two Bolivian records of atmospheric pollution. Initial Pb enrichment in Bolivia occurs contemporaneously with records from Peru ca. 400 AD. In Bolivia, this coincides with the expansion of the Tiwanaku Empire (ca. 400 to 1000 AD). Inca expansion across both Peru and Bolivia (~1450 AD) led to increased metallurgical activity at all four study sites. Our findings demonstrate the usefulness of paleolimnological methods for reconstructing the timing and magnitude of smelting activity throughout the New World, and thus contribute directly to a fragmentary archaeological record

Hospital Variation in Utilization of Life‐Sustaining Treatments among Patients with Do Not Resuscitate Orders

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144225/1/hesr12651_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144225/2/hesr12651.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144225/3/hesr12651-sup-0001-AuthorMatrix.pd