Assessing, accommodating, and interpreting the influences of heterogeneity

Perioperative increase in global blood flow to explicit defined goals and outcomes following surgery

BACKGROUND

Studies have suggested that increasing whole body blood flow and oxygen delivery around the time of surgery reduces mortality, morbidity and the expense of major operations.

OBJECTIVES

To describe the effects of increasing perioperative blood flow using fluids with or without inotropes or vasoactive drugs. Outcomes were mortality, morbidity, resource utilization and health status.

SEARCH METHODS

We searched CENTRAL (The Cochrane Library 2012, Issue 1), MEDLINE (1966 to March 2012) and EMBASE (1982 to March 2012). We manually searched the proceedings of major conferences and personal reference databases up to December 2011. We contacted experts in the field and pharmaceutical companies for published and unpublished data.

SELECTION CRITERIA

We included randomized controlled trials with or without blinding. We included studies involving adult patients (aged 16 years or older) undergoing surgery (patients having a procedure in an operating room). The intervention met the following criteria. 'Perioperative' was defined as starting up to 24 hours before surgery and stopping up to six hours after surgery. 'Targeted to increase global blood flow' was defined by explicit measured goals that were greater than in controls, specifically one or more of cardiac index, oxygen delivery, oxygen consumption, stroke volume (and the respective derived indices), mixed venous oxygen saturation (SVO(2)), oxygen extraction ratio (0(2)ER) or lactate.

DATA COLLECTION AND ANALYSIS

Two authors independently extracted the data. We contacted study authors for additional data. We used Review Manager software.

MAIN RESULTS

We included 31 studies of 5292 participants. There was no difference in mortality: 282/2615 (10.8%) died in the control group and 238/2677 (8.9%) in the treatment group, RR of 0.89 (95% CI 0.76 to 1.05, P = 0.18). However, the results were sensitive to analytical methods and the intervention was better than control when inverse variance or Mantel-Haenszel random-effects models were used, RR of 0.72 (95% CI 0.55 to 0.95, P = 0.02). The results were also sensitive to withdrawal of studies with methodological limitations. The rates of three morbidities were reduced by increasing global blood flow: renal failure, RR of 0.71 (95% CI 0.57 to 0.90); respiratory failure, RR of 0.51 (95% CI 0.28 to 0.93); and wound infections, RR of 0.65 (95% CI 0.51 to 0.84). There were no differences in the rates of nine other morbidities: arrhythmia, pneumonia, sepsis, abdominal infection, urinary tract infection, myocardial infarction, congestive cardiac failure or pulmonary oedema, or venous thrombosis. The number of patients with complications was reduced by the intervention, RR of 0.68 (95% CI 0.58 to 0.80). Hospital length of stay was reduced in the treatment group by a mean of 1.16 days (95% CI 0.43 to 1.89, P = 0.002). There was no difference in critical care length of stay. There were insufficient data to comment on quality of life and cost effectiveness.

AUTHORS' CONCLUSIONS

It remains uncertain whether increasing blood flow using fluids, with or without inotropes or vasoactive drugs, reduces mortality in adults undergoing surgery. The primary analysis in this review (mortality at longest follow-up) showed no difference between the intervention and control, but this result was sensitive to the method of analysis, the withdrawal of studies with methodological limitations, and is dominated by a single large RCT. Overall, for every 100 patients in whom blood flow is increased perioperatively to defined goals, one can expect 13 in 100 patients (from 40/100 to 27/100) to avoid a complication, 2/100 to avoid renal impairment (from 8/100 to 6/100), 5/100 to avoid respiratory failure (from 10/100 to 5/100), and 4/100 to avoid postoperative wound infection (from 10/100 to 6/100). On average, patients receiving the intervention stay in hospital one day less. It is unlikely that the intervention causes harm. The balance of current evidence does not support widespread implementation of this approach to reduce mortality but does suggest that complications and duration of hospital stay are reduced.

A Bayesian population PBPK model for multiroute chloroform exposure

A Bayesian hierarchical model was developed to estimate the parameters in a physiologically based pharmacokinetic (PBPK) model for chloroform using prior information and biomarker data from different exposure pathways. In particular, the model provides a quantitative description of the changes in physiological parameters associated with hot-water bath and showering scenarios. Through Bayesian inference, uncertainties in the PBPK parameters were reduced from the prior distributions. Prediction of biomarker data with the calibrated PBPK model was improved by the calibration. The posterior results indicate that blood flow rates varied under two different exposure scenarios, with a two-fold increase of the skin's blood flow rate predicted in the hot-bath scenario. This result highlights the importance of considering scenario-specific parameters in PBPK modeling. To demonstrate the application of a probability approach in toxicological assessment, results from the posterior distributions from this calibrated model were used to predict target tissue dose based on the rate of chloroform metabolized in liver. This study demonstrates the use of the Bayesian approach to optimize PBPK model parameters for typical household exposure scenarios.

The natural history of the use of healthcare information by women with breast cancer: a conceptual model

The overall goal of our research agenda is to contribute to improved quality of healthcare by identifying factors that foster or inhibit the use of healthcare information by patients to make informed healthcare decisions. We propose to study the natural history of the use of healthcare information by women with breast cancer to support decisions about health care. To do so in this paper we propose a conceptual model developed based on an extensive literature review and critique that describes patients' health information use over the disease course. It will guide our further investigation of the complex relationships among patients' personal circumstances, the progress of their medical treatment, and their satisfaction and empowerment as informed decision-makers. The model will help policy makers and health professionals identify the best means to provide patients with useful information, and help all stakeholders in health care acquire information needed to improve healthcare quality.

Statistical analysis of Clewell et al. PBPK model of trichloroethylene kinetics

A physiologically based pharmacokinetic model for trichloroethylene (TCE) in rodents and humans was calibrated with published toxicokinetic data sets. A Bayesian statistical framework was used to combine previous information about the model parameters with the data likelihood, to yield posterior parameter distributions. The use of the hierarchical statistical model yielded estimates of both variability between experimental groups and uncertainty in TCE toxicokinetics. After adjustment of the model by Markov chain Monte Carlo sampling, estimates of variability for the animal or human metabolic parameters ranged from a factor of 1.5-2 (geometric standard deviation [GSD]). Uncertainty was of the same order as variability for animals and higher than variability for humans. The model was used to make posterior predictions for several measures of cancer risk. These predictions were affected by both uncertainties and variability and exhibited GSDs ranging from 2 to 6 in mice and rats and from 2 to 10 for humans.