Utility of an initial D-dimer assay in screening for traumatic or spontaneous intracranial hemorrhage.

OBJECTIVE: To evaluate the sensitivity of a D-dimer assay as a screening tool for possible traumatic or spontaneous intracranial hemorrhage. If adequately sensitive, the D-dimer assay may potentially permit omission of a more expensive computed tomography (CT) scan of the head when such hemorrhage is clinically suspected. METHODS: Prospective, consecutive, blinded study of patients (age > 16 years) requiring a CT scan of the head for suspected intracranial hemorrhage over a five-month period at a university, Level I trauma center. All study patients had a serum D-dimer assay obtained prior to their CT scans. Sensitivity and specificity, with 95% confidence intervals (95% CIs), of the enzyme-linked immunosorbent assay (ELISA) D-dimer assay for the detection of intracranial hemorrhage were calculated. RESULTS: Of the 319 patients entered in the study, 25 (7.8%) had a CT scan positive for intracranial hemorrhage. Patients with intracranial hemorrhage were more likely to have a positive D-dimer assay (chi-square = 13.075, p < 0.001). The D-dimer assay had 21 true-positive and four false-negative tests, resulting in a sensitivity of 84.0% (95% CI = 63.7% to 95.5%) and a specificity of 55.8% (95% CI = 55.5% to 55.9%). The four false-negative cases included one small intraparenchymal hemorrhage, one small subarachnoid hemorrhage, one moderate-sized intraparenchymal hemorrhage with mid-line shift, and one large subdural hematoma requiring emergent surgery. CONCLUSIONS: Due to the catastrophic nature of missing an intracranial hemorrhage in the emergency department, the D-dimer assay is not adequately sensitive or predictive to use as a screening tool to allow routine omission of head CT scanning.

Double-blind, randomized study of nalmefene and naloxone in emergency department patients with suspected narcotic overdose.

STUDY OBJECTIVES: To compare the efficacy, safety, and withdrawal symptoms in emergency department patients with suspected narcotic overdose treated with nalmefene, an opioid antagonist with a 4- to 10-hour duration of action, with those treated with naloxone. METHODS: Adults in 9 centers who would otherwise receive naloxone for altered consciousness levels were randomly assigned to receive intravenous study drug (1 mg nalmefene, or 2 mg nalmefene or 2 mg naloxone, double-blinded) every 5 minutes as needed for up to 4 doses in a 4-hour study. Outcomes were 20-minute and 4-hour posttreatment changes in respiratory rates, Neurobehavioral Assessment Scale scores, Opioid Withdrawal Scale scores, and incidences of adverse events. RESULTS: Opioid positivity was recorded for 30 of 63 (1-mg nalmefene), 23 of 55 (2-mg nalmefene), and 24 of 58 (naloxone) cases, 75% of whom also had nonopioid central nervous system depressants. Most patients received only 1 dose of study drug. Similar, clinically meaningful improvements in respiratory rates and Neurobehavioral Assessment Scale scores were seen with all treatments. No statistical differences in efficacy or withdrawal outcomes were seen between treatment groups, and no significant overall time-treatment interactions occurred, in either the entire patient group or among opioid-positive cases (P >.21, all comparisons). Adverse events occurred in 30.9% (2 mg nalmefene), 15.9% (1 mg nalmefene), and 15.5% (naloxone) of patients (P >.08); none were associated with morbidity. CONCLUSION: In this study of patients with varied potential causes of altered consciousness, nalmefene (1 mg and 2 mg) and naloxone (2 mg) appeared to be efficacious, safe, and to yield similar clinical outcomes.

Mock drug delivery to the proximal aorta during cardiopulmonary resuscitation: central vs peripheral intravenous infusion with varying flush volumes.

OBJECTIVE: To compare mock drug deliveries to the proximal aorta during CPR after peripheral vs central i.v. administration when the mock drug is followed by different postinfusion flush volumes. METHODS: Delivery of indocyanine green (ICG) dye to the proximal aorta of an instrumented 20-kg canine cardiac arrest model was examined. The ICG administration (2.5 mg) preceded either a 2-mL or a 10-mL saline flush, for either a central or a peripheral i.v. route of dye administration. Five dogs each underwent three sets of the four possible route/flush-volume combinations in a stratified randomized order. Real-time dye-absorbance-vs-time curves, as sampled from the proximal aorta, modeled central-circulation drug delivery. Systolic and diastolic blood pressures (BPs) were monitored, and the absorbance-vs-time curve upstroke phases were used to estimate cardiac output during arrest. RESULTS: Times (mean +/- SD) to onset of dye appearance did not differ significantly between peripheral/10 mL (126 +/- 35 sec) and central/10 mL (108 +/- 35 sec), or between central/2 mL (123 +/- 31 sec) and central/10 mL. Times to onset of dye appearance did differ between peripheral/2 mL (161 +/- 70 sec) and central/10 mL [analysis of variance (ANOVA) p = 0.032]. Times to peak dye concentration did not differ significantly between peripheral/10 mL (230 +/- 88 sec) and either central/10 mL (202 +/- 88 sec) or central/2 mL (215 +/- 83 sec), but differed between peripheral/2 mL (326 +/- 134 sec) and every other route/flush-volume combination (ANOVA p = 0.009). Peak dye concentrations and systolic/diastolic BPs (averaging 23/10 for all route/flush-volume combinations) did not differ significantly between any route/flush-volume combinations. CONCLUSION: An adequately sized postinfusion crystalloid flush (0.5 mL/kg) permits peripherally administered model drug to reach the central circulation as quickly and in equivalent concentration as centrally administered drug during CPR in a canine cardiac arrest model.

Non-normality of distribution of Glasgow Coma Scores and Revised Trauma Scores.

STUDY OBJECTIVE: Inferential and descriptive statistics continue to be used incorrectly when analyzing biomedical data. Glasgow Coma Score (GCS) and Revised Trauma Score (RTS) data have recently been described and analyzed using parametric statistical methods in several studies despite the ordinal nature of these data scales. The objective of this study was to determine whether GCS and RTS data are normally distributed, despite their ordinal nature. HYPOTHESIS: Neither GCS nor RTS data are normally distributed. DESIGN: A retrospective review of GCS and RTS data obtained at a medical school teaching and county hospital that is a Level I trauma center. PARTICIPANTS: Patients who met criteria for trauma team activation at the hospital. METHODS: GCS and RTS data distributions were compared to a standard normal distribution using the chi 2 goodness of fit test. RESULTS: GCS and RTS data distributions differed significantly from the normal distribution for all data sets examined. CONCLUSION: Parametric statistical descriptors and inferential methods are inappropriate for use with GCS and RTS data. Ordinal data should be tested for normality before statistical analysis with parametric statistical methods.

Naloxone-associated patient violence: an overlooked toxicity?

OBJECTIVE: To report two cases of a previously unreported adverse effect, violent patient behavior, after the reversal of sedation by intravenous naloxone. DESIGN: Case report. PATIENTS/INTERVENTIONS: Responses of two individuals who had reversal of sedation by intravenous naloxone are compared. RESULTS: Placement of patient restraints before the administration of intravenous naloxone to obtunded or unconscious patients can make an important contribution to the safety of patients, healthcare personnel, and public safety personnel, as illustrated by the violent reaction of one unrestrained patient after naloxone administration. CONCLUSIONS: Patient restraint should be considered before naloxone administration to protect the patient and healthcare workers. In the prehospital setting, limiting the use of naloxone to patients with decreased mental status and respiratory depression would decrease the likelihood of naloxone-induced violent behavior.

Effect of standing orders on paramedic scene time for trauma patients.

STUDY OBJECTIVE: To determine if a protocol change that allowed paramedics to perform certain procedures before base station contact (standing orders) would decrease scene time in trauma patients. DESIGN: Retrospective review of case series. SETTING: A single-tiered, all advanced life support emergency medical services system. INTERVENTION: Implementation with standing orders for invasive procedures. TYPE OF PARTICIPANTS: All physiologically unstable trauma patients transported to a Level I trauma center by ambulance. MEASUREMENTS AND MAIN RESULTS: One hundred ninety-seven patients met the inclusion criteria--87 before and 110 after the initiation of standing orders. Mean scene times for the control group (15.3 +/- 8.4 minutes) and for the standing orders group (15.1 +/- 7.6 minutes) were similar (P = .18). The power of the study to detect a two-minute difference in scene time was .92. Scene time was not influenced by mechanism of injury, and the number of procedures performed on patients was similar between the two groups. CONCLUSION: Standing orders did not decrease scene time in physiologically unstable trauma patients. Further study is necessary to delineate the factors that actually contribute to on-scene time and the factors that are important in determining whether standing orders or on-line medical contact should be used.

Introduction to biostatistics: Part 6, Correlation and regression.

Correlation and regression analysis are applied to data to define and quantify the relationship between two variables. Correlation analysis is used to estimate the strength of a relationship between two variables. The correlation coefficient r is a dimensionless number ranging from -1 to +1. A value of -1 signifies a perfect negative, or indirect (inverse) relationship. A value of +1 signifies a perfect positive, or direct relationship. The r can be calculated as the Pearson-product r, using normally distributed interval or ratio data, or as the Spearman rank r, using non-normally distributed data that are not interval or ratio in nature. Linear regression analysis results in the formation of an equation of a line (Y = mX + b), which mathematically describes the line of best fit for a data relationship between X and Y variables. This equation can then be used to predict additional dependent variable values (Y), based on the value or the independent variable X, the slope m, and the Y-intercept b. Interpretation of the correlation coefficient r involves use of r2, which implies the degree of variability of Y due to X. Tests of significance for linear regression are similar conceptually to significance testing using analysis of variance. Multiple correlation and regression, more complex analytical methods that define relationships between three or more variables, are not covered in this article. Closing comments for this final installment of this introduction to biostatistics series are presented.

Improved survival and reduced myocardial necrosis with cardiopulmonary bypass reperfusion in a canine model of coronary occlusion and cardiac arrest.

STUDY QUESTION: Does cardiopulmonary bypass (CPB) improve resuscitation rates and limit infarct size after cardiac arrest and acute myocardial infarction? DESIGN: Controlled randomized trial with all animals undergoing left anterior descending coronary artery occlusion and subsequent ventricular fibrillation and resuscitation. All animals were supported for four hours after resuscitation in an intensive care setting. INTERVENTION: Group 1 (eight) was resuscitated with standard external CPR and advanced life support. Group 2 (eight) was resuscitated with CPB. MEASUREMENTS AND MAIN RESULTS: Group hemodynamic, resuscitation variables, number resuscitated, and number of four-hour survivors were compared. Ischemic and necrotic myocardial weights were determined with histochemical staining techniques in four-hour survivors. Infarct size was measured as the ratio of necrotic weight to ischemic weight. Significantly fewer dogs were resuscitated in group 1 (four of eight) than in group 2 (eight of eight) (P less than .05). Group 2 survivors required significantly less epinephrine and lidocaine than group 1 survivors (P less than .05) and higher aortic diastolic and coronary perfusion pressures after CPB (P less than .001). The ratio of myocardial necrotic weight to ischemic weight at four hours was 0.82 +/- 0.25 in group 1 and 0.22 +/- 0.25 in group 2 (P less than .05). However, collateral blood flow was not measured in this study. CONCLUSION: This pilot study further substantiates the improvement in resuscitation rates obtainable with CPB. CPB may also limit infarct size during the postresuscitation period and requires further study.

Introduction to biostatistics: Part 5, Statistical inference techniques for hypothesis testing with nonparametric data.

Specific statistical tests are used when the null hypothesis (H0) is to be tested using nonparametric nominal or ordinal data. With nominal data, experimental results are expressed by proportions or frequencies. Chi-square or related tests (the Fisher's exact test or the rows by columns test) are appropriate for testing H0 with nominal data. Ordinal data permit arrangement of statistical results by rank. Rank-order tests used to test H0 with ordinal data include the Mann-Whitney U, Kolmogorov-Smirnov, Wilcoxon, Kruskal-Wallis, and Friedman tests. The Kruskal-Wallis and Friedman tests permit multiple intergroup comparisons. Other rank-order tests permit only single intergroup comparisons. Specific details to guide the researcher in the proper selection of these tests are presented.

Cardiopulmonary bypass in a model of acute myocardial infarction and cardiac arrest.

Cardiopulmonary bypass (CPB) reperfusion has demonstrated improved resuscitation rates in ventricular fibrillation cardiac arrest models. To investigate the effectiveness of CPB reperfusion in an ischemic cardiac arrest setting, simulating the clinical scenario of myocardial ischemia preceding sudden cardiac death, we developed a canine model of acute myocardial infarction followed by ventricular fibrillation. Sixteen dogs were randomly assigned to two groups. Group 1 (eight) had ventricular fibrillation induced without left anterior descending coronary artery occlusion. Group 2 (eight) had a thrombogenic copper coil placed in the left anterior descending artery and showed ECG evidence of acute myocardial infarction before induction of ventricular fibrillation. CPR commenced after eight minutes of ventricular fibrillation. Epinephrine 0.05 mg/kg and NaHCO3 1.0 mEq/kg were administered at ten minutes. CPB was begun at 12 minutes and continued for one hour. Myocardial ischemic and necrotic areas were determined in four-hour survivors by dual histochemical staining. All animals were resuscitated; all eight group 1 and six of eight group 2 animals survived to four hours. With the onset of CPB, coronary perfusion pressures increased significantly by 68.6 +/- 31.8 (SD) mm Hg in group 1 and 56.2 +/- 34.6 mm Hg in group 2 over those obtained with CPR (P less than .001).(ABSTRACT TRUNCATED AT 250 WORDS)

Introduction to biostatistics: Part 4, statistical inference techniques in hypothesis testing.

Statistical methods used to test the null hypothesis are termed tests of significance. Selection of an appropriate test of significance is dependent on the type of data to be analyzed and the number of groups to be compared. Parametric tests of significance are based on the parameters, mean, standard deviation, and variance, and thus are used appropriately when interval or ratio data are analyzed. The t-test and analysis of variance (ANOVA) are examples of parametric tests of significance. Assumptions regarding the data to be analyzed when using the t-test or ANOVA include normality of the populations from which the sample data are drawn, homogeneity of the variances of the populations from which the sample data are drawn, and independence of the data points within a sample group. The t-test is the appropriate test of significance to use if there are only two groups to compare. If there are three or more groups to compare, ANOVA is the appropriate test. ANOVA holds the preset alpha level constant. While ANOVA will imply a significant difference between the groups compared, a multiple comparison test will define which of the three or more groups differ significantly.

Introduction to biostatistics: Part 3, Sensitivity, specificity, predictive value, and hypothesis testing.

Diagnostic tests guide physicians in assessment of clinical disease states, just as statistical tests guide scientists in the testing of scientific hypotheses. Sensitivity and specificity are properties of diagnostic tests and are not predictive of disease in individual patients. Positive and negative predictive values are predictive of disease in patients and are dependent on both the diagnostic test used and the prevalence of disease in the population studied. These concepts are best illustrated by study of a two by two table of possible outcomes of testing, which shows that diagnostic tests may lead to correct or erroneous clinical conclusions. In a similar manner, hypothesis testing may or may not yield correct conclusions. A two by two table of possible outcomes shows that two types of errors in hypothesis testing are possible. One can falsely conclude that a significant difference exists between groups (type I error). The probability of a type I error is alpha. One can falsely conclude that no difference exists between groups (type II error). The probability of a type II error is beta. The consequence and probability of these errors depend on the nature of the research study. Statistical power indicates the ability of a research study to detect a significant difference between populations, when a significant difference truly exists. Power equals 1-beta. Because hypothesis testing yields "yes" or "no" answers, confidence intervals can be calculated to complement the results of hypothesis testing. Finally, just as some abnormal laboratory values can be ignored clinically, some statistical differences may not be relevant clinically.

Introduction to biostatistics: Part 2, Descriptive statistics.

Descriptive statistics include measures of central tendency and variability. Measures of central tendency include mean, median, and mode. The mean is the arithmetic average of data from interval or ratio scales. The median reflects the 50th percentile score. The mode is the most frequently occurring value of a data distribution. Measures of variability include range, interquartile range, standard deviation, and standard error of the mean. The range describes the spread between the extreme values of data. Interquartile range is data included between the 25th and 75th percentile of a distribution. Standard deviation describes variability of data about the sample mean, while standard error of the mean helps describe the distribution of several sample means about a true population mean. Finally, confidence intervals, which are derived from the standard error of the mean, define an interval likely to include a true population value, based on sample statistical values and probability charceristics of data distributions.

Introduction to biostatistics: Part 1, Basic concepts.

Statistical methods commonly used to analyze data presented in journal articles should be understood by both medical scientists and practicing clinicians. Inappropriate data analysis methods have been reported in 42% to 78% of original publications in critical reviews of selected medical journals. The only way to halt researchers' misuse of statistics and improve the clinician's knowledge of statistics is through education. This is the first of a six-part series of articles intended to provide the reader with a basic, yet fundamental knowledge of common biomedical statistical methods. The series will cover basic concepts of statistical analysis, descriptive statistics, statistical inference theory, comparison of means, chi 2, and correlational and regression techniques. A conceptual explanation will accompany discussion of the appropriate use of these techniques.

Acute yellow phosphorus poisoning from pesticide pastes.

Ten cases of ingestion of yellow phosphorus rat poison, including four cases that occurred during the past 3 years, are reported. Comparison of these cases with 82 others from the literature showed that ingestion of yellow phosphorus paste often results in clinical findings that are different from those described for acute yellow phosphorus poisoning in current toxicology texts. The time lag between swallowing of the poison and onset of symptoms varied from a few minutes to 24 h. Garlic odor, mucosal burns, and phosphorescent vomitus or feces occurred in only a small percentage of cases. Diarrhea was not a presenting complaint. Initial symptoms were referable to the gastrointestinal tract, central nervous system, or both. Mortality rates were 23% for patients who had early symptoms of vomiting or abdominal pain; 73% for those where the first manifestation of intoxication was restlessness, irritability, drowsiness, stupor, or coma; and 47% for patients who had a combination of these GI and CNS symptoms initially. Applying standard diagnostic criteria for yellow phosphorus poisoning to patients who have consumed yellow phosphorus pastes may result in serious diagnostic errors.