Measuring Agreement Among Prehospital Providers and Physicians in Patient Capacity Determination.

OBJECTIVES: If a patient wishes to refuse treatment in the prehospital setting, prehospital providers and consulting emergency physicians must establish that the patient possesses the capacity to do so. The objective of this study is to assess agreement among prehospital providers and emergency physicians in performing patient capacity assessments. METHODS: This study involved 139 prehospital providers and 28 emergency medicine physicians. Study participants listened to 30 medical control calls pertaining to patient capacity and were asked to interpret whether the patients in the scenarios had the capacity to refuse treatment. Participants also reported their comfort level using modified Likert scales. Inter-rater reliability was calculated utilizing Fleiss' and Model B kappa statistics. Fisher's exact tests were used to calculate p-values comparing the proportion in each cohort that responded "no capacity." Primary outcomes included inter-rater reliability in the physician and prehospital provider cohorts. RESULTS: The inter-rater agreement between the physicians was low (Fleiss' kappa = 0.31, standard error [SE] =0.06; model-based kappa = 0.18, SE = 0.04). Agreement was similarly low for the 135 prehospital providers (Fleiss' kappa = 0.30, SE = 0.06; model-based kappa = 0.28, SE = 0.04). The difference between the proportion of physicians and prehospital providers who responded "no capacity" was statistically significant in five of 30 scenarios. Median prehospital provider and physician confidence, on a 1 to 4 scale, was 2.00 (Q1-Q3 = 1.00-3.00 for prehospital providers and Q1-Q3 =1.0-2.0 for physicians). CONCLUSIONS: There was poor inter-rater reliability in capacity determination between and among the prehospital provider and physician cohorts. This suggests that there is need for additional study and standardization of this task.

Caprini venous thromboembolism risk assessment permits selection for postdischarge prophylactic anticoagulation in patients with resectable lung cancer.

OBJECTIVE: Postoperative venous thromboembolism (VTE) creates an 8-fold increase in mortality after lung resection. About one third of postoperative VTEs occur after discharge. The Caprini risk assessment model has been used by other specialties to calculate the risk of a VTE. Patients deemed high risk by the model are candidates for prophylactic anticoagulation after discharge, reducing the VTE risk by 60%. Our primary aims were to determine the frequency of VTE events and evaluate whether the Caprini model could risk-stratify patients. METHODS: Patients undergoing lung cancer resections during 2005 to 2013 were evaluated. Exclusion criteria were preoperative filter and therapeutic anticoagulation. A total of 232 patients were reviewed and Caprini scores calculated. Subjects were risk stratified into groups of low risk (0-4), moderate risk (5-8), and high risk (≥ 9). Occurrence of VTE events (deep vein thrombosis; pulmonary embolism) were identified by imaging. RESULTS: The 60-day VTE incidence was 5.2% (12 of 232); 33.3% occurred postdischarge (n = 4). Half (6 of 12) were pulmonary emboli, 1 of which caused a death, in an inpatient with a score of 16. The VTE incidence increased with Caprini score. Scores in the low, moderate, and high risk groups were associated with a VTE incidence of 0%, 1.7%, and 10.3%, respectively. With a high risk score cutoff of 9, the sensitivity, specificity, and accuracy are 83.3%, 60.5%, and 61.6%, respectively. CONCLUSIONS: One third of VTE events occurred after discharge. Postoperative VTE incidence was correlated with increasing Caprini scores. Patients in the high risk group had an incidence of 10.3%. Elevated scores may warrant extended chemoprophylaxis for patients after discharge.

A Duty to Describe: Better the Devil You Know Than the Devil You Don't.

Although many researchers have discussed replication as a means to facilitate self-correcting science, in this article, we identify meta-analyses and evaluating the validity of correlational and causal inferences as additional processes crucial to self-correction. We argue that researchers have a duty to describe sampling decisions they make; without such descriptions, self-correction becomes difficult, if not impossible. We developed the Replicability and Meta-Analytic Suitability Inventory (RAMSI) to evaluate the descriptive adequacy of a sample of studies taken from current psychological literature. Authors described only about 30% of the sampling decisions necessary for self-correcting science. We suggest that a modified RAMSI can be used by authors to guide their written reports and by reviewers to inform editorial recommendations. Finally, we claim that when researchers do not describe their sampling decisions, both readers and reviewers may assume that those decisions do not matter to the outcome of the study, do not affect inferences made from the research findings, do not inhibit inclusion in meta-analyses, and do not inhibit replicability of the study. If these assumptions are in error, as they often are, and the neglected decisions are relevant, then the neglect may create a good deal of mischief in the field.