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

Predicting sinusoidal obstruction syndrome after allogeneic stem cell transplantation with the EASIX biomarker panel

No biomarker panel is established for prediction of sinusoidal obstruction syndrome/veno-occlusive disease (SOS/VOD), a major complication of allogeneic stem cell transplantation (alloSCT). We compared the potential of the Endothelial Activation and Stress Index (EASIX), based on lactate dehydrogenase, creatinine, and thrombocytes, with that of the SOS/VOD CIBMTR clinical risk score to predict SOS/VOD in two independent cohorts. In a third cohort, we studied the impact of endothelium-active prophylaxis with pravastatin and ursodeoxycholic acid (UDA) on SOS/VOD risk. The cumulative incidence of SOS/VOD within 28 days after alloSCT in the training cohort (Berlin, 2013-2015, n=446) and in the validation cohort (Heidelberg, 2002-2009, n=380) was 9.6% and 8.4%, respectively. In both cohorts, EASIX assessed at the day of alloSCT (EASIX-d0) was significantly associated with SOS/VOD incidence (p<0.0001), overall survival (OS) and non-relapse mortality (NRM). In contrast, the CIBMTR score showed no statistically significant association with SOS/VOD incidence, and did not predict OS and NRM. In patients receiving pravastatin/UDA, the cumulative incidence of SOS/VOD was significantly lower at 1.7% (p<0.0001, Heidelberg, 2010-2015, n=359) than in the two cohorts not receiving pravastatin/UDA. The protective effect was most pronounced in patients with high EASIX-d0. The cumulative SOS/VOD incidence in the highest EASIX-d0 quartiles were 18.1% and 16.8% in both cohorts without endothelial prophylaxis as compared to 2.2% in patients with pravastatin/UDA prophylaxis (p<0.0001). EASIX-d0 is the first validated biomarker for defining a subpopulation of alloSCT recipients at high risk for SOS/VOD. Statin/UDA endothelial prophylaxis could constitute a prophylactic measure for patients at increased SOS/VOD risk

Evaluation of the partnership histories in the Centre for Population Change GHS time series dataset

A combined time series of the General Household Survey datasets from 1979 to 2007 has been compiled by the Centre for Population Change (CPC). This dataset includes, along with socio-economic variables, the demographic histories collected in the Family Information section of the GHS questionnaire over the GHS rounds covered, in harmonised form. The present paper evaluates both the internal consistency of the marriage and cohabitation histories and their correspondence with external sources.The data are weighted using new weights generated by CPC for the analysis of these data. Overall, cumulative proportions married by each age for the cohorts of 1951-55 to 1966-70 correspond well with ONS figures for England and Wales, though there are some systematic disparities in selected years. As found in an earlier study, retrospective estimates from the 2000-07 histories of the proportions cohabiting at a point in time are somewhat above the cross-sectional estimates at survey 5 and 10years before

The Magnitude of Androgen Receptor Positivity in Breast Cancer Is Critical for Reliable Prediction of Disease Outcome

Purpose: Consensus is lacking regarding the androgen receptor (AR) as a prognostic marker in breast cancer. The objectives of this study were to comprehensively review the literature on AR prognostication and determine optimal criteria for AR as an independent predictor of breast cancer survival. Experimental Design: AR positivity was assessed by immunostaining in two clinically validated primary breast cancer cohorts [training cohort, n = 219; validation cohort, n = 418; 77% and 79% estrogen receptor alpha (ERα) positive, respectively]. The optimal AR cut-point was determined by ROC analysis in the training cohort and applied to both cohorts. Results: AR was an independent prognostic marker of breast cancer outcome in 22 of 46 (48%) previous studies that performed multivariate analyses. Most studies used cut-points of 1% or 10% nuclear positivity. Herein, neither 1% nor 10% cut-points were robustly prognostic. ROC analysis revealed that a higher AR cut-point (78% positivity) provided optimal sensitivity and specificity to predict breast cancer survival in the training (HR, 0.41; P = 0.015) and validation (HR, 0.50; P = 0.014) cohorts. Tenfold cross-validation confirmed the robustness of this AR cut-point. Patients with ERα-positive tumors and AR positivity ≥78% had the best survival in both cohorts (P 0.87) had the best outcomes (P < 0.0001). Conclusions: This study defines an optimal AR cut-point to reliably predict breast cancer survival. Testing this cut-point in prospective cohorts is warranted for implementation of AR as a prognostic factor in the clinical management of breast cancer

Development and validation of a risk score for chronic kidney disease in HIV infection using prospective cohort data from the D:A:D study.

Chronic kidney disease (CKD) is a major health issue for HIV-positive individuals, associated with increased morbidity and mortality. Development and implementation of a risk score model for CKD would allow comparison of the risks and benefits of adding potentially nephrotoxic antiretrovirals to a treatment regimen and would identify those at greatest risk of CKD. The aims of this study were to develop a simple, externally validated, and widely applicable long-term risk score model for CKD in HIV-positive individuals that can guide decision making in clinical practice

Integrative analysis of the colorectal cancer proteome : potential clinical impact

Peer reviewedPostprin

Metabolite changes in blood predict the onset of tuberculosis

Immunogenetics and cellular immunology of bacterial infectious disease

Can analyses of electronic patient records be independently and externally validated? The effect of statins on the mortality of patients with ischaemic heart disease: a cohort study with nested case-control analysis

Objective To conduct a fully independent and external validation of a research study based on one electronic health record database, using a different electronic database sampling the same population. Design Using the Clinical Practice Research Datalink (CPRD), we replicated a published investigation into the effects of statins in patients with ischaemic heart disease (IHD) by a different research team using QResearch. We replicated the original methods and analysed all-cause mortality using: (1) a cohort analysis and (2) a case-control analysis nested within the full cohort. Setting Electronic health record databases containing longitudinal patient consultation data from large numbers of general practices distributed throughout the UK. Participants CPRD data for 34 925 patients with IHD from 224 general practices, compared to previously published results from QResearch for 13 029 patients from 89 general practices. The study period was from January 1996 to December 2003. Results We successfully replicated the methods of the original study very closely. In a cohort analysis, risk of death was lower by 55% for patients on statins, compared with 53% for QResearch (adjusted HR 0.45, 95% CI 0.40 to 0.50; vs 0.47, 95% CI 0.41 to 0.53). In case-control analyses, patients on statins had a 31% lower odds of death, compared with 39% for QResearch (adjusted OR 0.69, 95% CI 0.63 to 0.75; vs OR 0.61, 95% CI 0.52 to 0.72). Results were also close for individual statins. Conclusions Database differences in population characteristics and in data definitions, recording, quality and completeness had a minimal impact on key statistical outputs. The results uphold the validity of research using CPRD and QResearch by providing independent evidence that both datasets produce very similar estimates of treatment effect, leading to the same clinical and policy decisions. Together with other non-independent replication studies, there is a nascent body of evidence for wider validity