Mean platelet volume during coagulase-negative staphylococcal sepsis in neonates.

Coagulase-negative staphylococci are the most common cause of late-onset septicemia in neonates in intensive care nurseries. Clinical and laboratory diagnosis of infection with coagulase-negative staphylococci can be difficult. The authors reviewed serial mean platelet volumes of 18 infants in whom coagulase-negative staphylococci sepsis developed and found a significant increase in the mean platelet volume at the time of diagnosis and a return to baseline after resolution of the infection. The increase in mean platelet volume occurred although thrombocytopenia developed in only two of the infants and no difference was found in the mean platelet counts before and at the time of diagnosis of the infection. This finding may be a useful adjunct to the current laboratory tests used to diagnose coagulase-negative staphylococci sepsis in neonates.

Statistical methodology: IV. Analysis of variance, analysis of covariance, and multivariate analysis of variance.

Medical research frequently involves the statistical comparison of >2 groups, often using data obtained through the application of complex experimental designs. Fortunately, inferential statistical methodologies exist to address these situations. Analysis of variance (ANOVA) in its many forms is used to simultaneously test the equality of all groups in a study. One-way (with 1 independent variable), 2-way (with 2 independent variables), and repeated-measures (patients serve as their own controls) ANOVAs are forms of this technique. Each form has been developed to analyze data from a specific experimental design. Analysis of covariance (ANCOVA) allows the researcher to control for confounding variables that may influence the response of the dependent variable. Finally, multivariate analysis of variance (MANOVA) evaluates the simultaneous responses of multiple dependent variables to > or = 1 independent variable. Whereas ANOVA is the correct alternative to statistically inappropriate multiple t-tests, MANOVA is the correct alternative to statistically inappropriate multiple univariate ANOVA calculations. Use of each of these statistical methods requires an appropriate experimental design and data meeting a number of assumptions. When used properly, each of these methods provides a powerful statistical analysis technique.

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.

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 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.

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.

Autoregulation of cardiac output by passive elastic characteristics of the vascular capacitance system.

After a change in cardiac output, the magnitude of potential blood volume redistribution was investigated in 10 dogs anesthetized with chloralose. All of the venous return was pumped into a reservoir, using servocontrolled pumps to maintain fixed superior and inferior vena cava pressures. The cardiac output was set at various levels by pumping from the reservoir into the right atrium. Changes in reservoir volume were assumed to reflect the changes in vascular blood volume. After measuring the control responses, cardiovascular reflexes were blocked with hexamethonium. Reducing the cardiac output, for example, from 110 to 80 ml/(min.kg) with reflexes intact, caused a 9.2-ml/kg transfer of blood from the dog to the reservoir. With reflexes blocked, the same change in cardiac output caused 6.8 ml/kg of the blood to be transferred. Under the control conditions, throughout the range of 50-140 ml/(min.kg), an increase or decrease of cardiac output of 1 ml/(min.kg) elicited a 0.304 +/- 0.086 (mean +/- SD) ml/kg change in dog blood volume; with reflexes blocked, the flow sensitivity was 0.239 +/- 0.062 ml/kg. Thus, only 21% of the total blood volume redistribution was attributable to active reflex responses. Deterioration of the preparation may have attenuated the magnitude of active reflex activity. Neither the systemic vascular compliance of 1.80 +/- 0.35 ml/mm Hg.kg nor the fraction of venous return from the superior vena cava of 26.5 +/- 4.6% was significantly changed by reflex blockade.(ABSTRACT TRUNCATED AT 250 WORDS)

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.

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.

Vascular capacitance responses to hypercapnia of the vascularly isolated head.

Hypercapnic stimulation of the brain may account for some of the decrease in vascular capacitance (venoconstriction) seen with whole-body hypercapnia. Six mongrel dogs were anesthetized with alpha-chloralose and paralyzed with pancuronium bromide. The vagi were cut and the carotid bodies and sinuses were denervated. The head circulation was isolated and perfused with normoxic [arterial partial pressure of O2 (Pao2) = 112 mmHg], normocapnic (PaCO2 = 40 mmHg) blood, or one of three levels of normoxic, hypercapnic (PaCO2 = 56, 68, or 84 mmHg) blood. A membrane oxygenator was used to change gas tensions in the perfusate blood. The systemic circulation received normoxic, normocapnic blood (Pao2 = 107 mmHg; PaCO2 = 32 mmHg). Systemic arterial pressure increased from 111 to 134 mmHg, and heart rate decreased from 174 to 150 beats/min with a head blood PaCO2 of 84 mmHg. Central blood volume was not affected by head hypercapnia. Cardiac output significantly decreased only with a head blood PaCO2 of 84 mmHg. Mean circulatory filling pressure increased by 0.014 mmHg/1 mmHg increase in head PaCO2. The sensitivity of the total peripheral resistance to cephalic blood hypercapnia was 0.88%/mmHg, whereas that for the mean circulatory filling pressure was only 0.19%/mmHg. We conclude that stimulation of the brain, via perfusion of the head with hypercapnic blood, causes a small but significant increase in mean circulatory filling pressure, due to systemic venoconstriction.

Mean circulatory filling pressure: potential problems with measurement.

Three experimental series using 22 acutely splenectomized mongrel dogs were completed to 1) compare fibrillation (Fib) and acetylcholine (ACh) injection as methods to stop the heart for the mean circulatory filling pressure (Pmcf) maneuver, and 2) test whether Pmcf equals portal venous pressure 7 s after heart stoppage (Pportal7s). Blood volume changes of -10, -20, +10, or +20 ml/kg were imposed and Pmcf and Pportal measurements were obtained. Pportal7s and Pmcf were significantly different with volume depletion but were similar under control conditions. Pmcf with ACh and Pmcf with Fib were significantly different only after a volume change of -20 ml/kg. However, severe pulmonary congestion and atelectasis were detected in animals where Ach was used to stop the heart. In some cases (with injection directly into the pulmonary artery) the damage was severe enough to cause irreversible arterial hypoxia. Thus we conclude that the repeated use of ACh may exert a detrimental influence on pulmonary function, changing the physiological status of the experimental animal. Also, the central venous pressure at 7 s of heart stoppage (Pcv7s) is not a fully accurate estimate of the true mean circulatory filling pressure during the Pmcf maneuver, because Pcv7s did not equal the Pportal7s under all experimental conditions.

Vascular capacitance responses to severe systemic hypercapnia and hypoxia in dogs.

The magnitude of vascular capacitance change induced by hypercapnia, hypoxia, or hypoxic hypercapnia was estimated during the administration of experimental gas mixtures to anesthetized dogs for 25 min. Mean circulatory filling pressure (Pcf) was determined by fibrillating the heart and equilibrating arterial and venous pressures with a pump. We assumed that the total blood volume remained constant and that the magnitude of change in peripheral venous volume equaled the sum of the changes in blood volume in the cardiopulmonary and arterial beds. We further assumed that active (reflex) peripheral venoconstriction occurred if the cardiopulmonary and arterial bed blood volumes, as well as the Pcf, increased. Within 3 min, severe hypercapnia and hypoxic hypercapnia induced a 5.2 and 7.3 ml/kg reduction in systemic vascular capacity, and, by 19 min of experimental gas presentation, increased Pcf by 5.5 and 7.0 mmHg, respectively. Severe hypoxia had less effect (0.7 ml/ kg and 2.5 mmHg, respectively) at 19 min. Severe hypercapnia also increased the central venous, systemic arterial, and pulmonary arterial pressures and decreased heart rate. Hypoxic hypercapnia additionally increased cardiac output. We conclude that severe systemic hypercapnia, whether alone or in combination with hypoxia, causes a significant active reduction in vascular capacitance, but severe hypoxia is less effective.

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.