Cerebral oxygenation in mechanically ventilated early cardiac arrest survivors: The impact of hypercapnia

BACKGROUND : Optimal cerebral oxygenation is considered fundamental to cerebral protection in cardiac arrest (CA) patients. Hypercapnia increases cerebral blood flow and may also improve cerebral oxygenation. It is uncertain, however, whether this effect occurs in mechanically ventilated early survivors of CA. METHODS: We enrolled mechanically ventilated resuscitated patients within 36 h of their cardiac arrest. We performed a prospective double cross-over physiological study comparing the impact of normocapnia (PaCO2 35-45 mmHg) vs. mild hypercapnia (PaCO2 45-55 mmHg) on regional cerebral tissue oxygen saturation (SctO2) assessed by near infrared spectroscopy (NIRS).RESULTS: We studied seven adult CA patients with a median time to return of spontaneous circulation of 28 min at a median of 26 h and 30 min after CA. During normocapnia (median EtCO2 of 32 mmHg [30-41 mmHg] and PaCO2 of 37 mmHg [32-45 mmHg]) the median NIRS-derived left frontal SctO2 was 61% [52-65%] and the right frontal SctO2 was 61% [54-68%]. However, during mild hypercapnia (median EtCO2 of 49 mmHg [40-57 mmHg] and PaCO2 of 52 mmHg [43-55 mmHg) the median left frontal SctO2 increased to 69% [59-78%] and the right frontal SctO2 increased to 73% [61-76%])(p = 0.001, for all comparisons). CONCLUSION: During the early post-resuscitation period, in mechanically ventilated CA patients, mild hypercapnia increases cerebral oxygenation as assessed by NIRS. Further investigations of the effect of prolonged mild hypercapnia on cerebral oxygenation and patient outcomes appear justified.

The Scored Patient-Generated Subjective Global Assessment (PG-SGA) and its Association with Quality of Life in Ambulatory Patients Receiving Radiotherapy

OBJECTIVE: To evaluate the scored Patient-generated Subjective Global Assessment (PG-SGA) tool as an outcome measure in clinical nutrition practice and determine its association with quality of life (QoL). DESIGN: A prospective 4 week study assessing the nutritional status and QoL of ambulatory patients receiving radiation therapy to the head, neck, rectal or abdominal area. SETTING: Australian radiation oncology facilities. SUBJECTS: Sixty cancer patients aged 24-85 y. INTERVENTION: Scored PG-SGA questionnaire, subjective global assessment (SGA), QoL (EORTC QLQ-C30 version 3). RESULTS: According to SGA, 65.0% (39) of subjects were well-nourished, 28.3% (17) moderately or suspected of being malnourished and 6.7% (4) severely malnourished. PG-SGA score and global QoL were correlated (r=-0.66, P<0.001) at baseline. There was a decrease in nutritional status according to PG-SGA score (P<0.001) and SGA (P<0.001); and a decrease in global QoL (P<0.001) after 4 weeks of radiotherapy. There was a linear trend for change in PG-SGA score (P<0.001) and change in global QoL (P=0.003) between those patients who improved (5%) maintained (56.7%) or deteriorated (33.3%) in nutritional status according to SGA. There was a correlation between change in PG-SGA score and change in QoL after 4 weeks of radiotherapy (r=-0.55, P<0.001). Regression analysis determined that 26% of the variation of change in QoL was explained by change in PG-SGA (P=0.001). CONCLUSION: The scored PG-SGA is a nutrition assessment tool that identifies malnutrition in ambulatory oncology patients receiving radiotherapy and can be used to predict the magnitude of change in QoL.

Clinical Accuracy of the MedGem Indirect Calorimeter for Measuring Resting Energy Expenditure in Cancer Patients

OBJECTIVE: To compare, in patients with cancer and in healthy subjects, measured resting energy expenditure (REE) from traditional indirect calorimetry to a new portable device (MedGem) and predicted REE. DESIGN: Cross-sectional clinical validation study. SETTING: Private radiation oncology centre, Brisbane, Australia. SUBJECTS: Cancer patients (n = 18) and healthy subjects (n = 17) aged 37-86 y, with body mass indices ranging from 18 to 42 kg/m(2). INTERVENTIONS: Oxygen consumption (VO(2)) and REE were measured by VMax229 (VM) and MedGem (MG) indirect calorimeters in random order after a 12-h fast and 30-min rest. REE was also calculated from the MG without adjustment for nitrogen excretion (MGN) and estimated from Harris-Benedict prediction equations. Data were analysed using the Bland and Altman approach, based on a clinically acceptable difference between methods of 5%. RESULTS: The mean bias (MGN-VM) was 10% and limits of agreement were -42 to 21% for cancer patients; mean bias -5% with limits of -45 to 35% for healthy subjects. Less than half of the cancer patients (n = 7, 46.7%) and only a third (n = 5, 33.3%) of healthy subjects had measured REE by MGN within clinically acceptable limits of VM. Predicted REE showed a mean bias (HB-VM) of -5% for cancer patients and 4% for healthy subjects, with limits of agreement of -30 to 20% and -27 to 34%, respectively. CONCLUSIONS: Limits of agreement for the MG and Harris Benedict equations compared to traditional indirect calorimetry were similar but wide, indicating poor clinical accuracy for determining the REE of individual cancer patients and healthy subjects.

Correcting for bias when estimating the cost of hospital-acquired infection : an analysis of lower respiratory tract infections in non-surgical patients

Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).

Smoothing a Discrete Hazard Function for the Number of Patients Colonized with Methicillin-Resistance Staphylococcus Aureus in an Intensive Care Unit

A new method for estimating the time to colonization of Methicillin-resistant Staphylococcus Aureus (MRSA) patients is developed in this paper. The time to colonization of MRSA is modelled using a Bayesian smoothing approach for the hazard function. There are two prior models discussed in this paper: the first difference prior and the second difference prior. The second difference prior model gives smoother estimates of the hazard functions and, when applied to data from an intensive care unit (ICU), clearly shows increasing hazard up to day 13, then a decreasing hazard. The results clearly demonstrate that the hazard is not constant and provide a useful quantification of the effect of length of stay on the risk of MRSA colonization which provides useful insight.