Validation of a predictive method for an accurate assessment of resting energy expenditure in medical mechanically ventilated patients

Objective: Use comparison with indirect calorimetry to confirm the ability of our previously described equation to predict resting energy expenditure in mechanically ventilated patients.Design: Prospective, validation study. Setting: Eighteen-bed, medical intensive care unit at a teaching hospital. Patients: All adult patients intubated >24 hrs were assessed for eligibility. Exclusion criteria were clinical situations that could contribute to erroneous calorimetric measurements. Interventions: Resting energy expenditure was calculated using the original Harris-Benedict equations and those corrected for usual stress factors, the Swinamer equation, the Fusco equation, the Ireton-Jones equation, and our equation: resting energy expenditure (kcal/day) = 8 × weight (kg) + 14 × height (cm) + 32 × minute ventilation (L/min) + 94 × temperature (°C) − 4834. Measurements and Main Results: Resting energy expenditure was measured by indirect calorimetry for the 45 included patients. Resting energy expenditure calculated with our predictive model correlated with the measured resting energy expenditure (r2 = .62, p < .0001), and Bland-Altman analysis showed a mean bias of −192 ± 277 kcal/day, with limits of agreement ranging from −735 to 351 kcal/day. Resting energy expenditure calculated with the Harris-Benedict equations was more weakly correlated with measured resting energy expenditure (r2 = .41, p < .0001), with Bland-Altman analysis showing a mean bias of 279 ± 346 kcal/day between them and the limits of agreement ranging from −399 to 957 kcal/day. Applying usual stress-correction factors to the Harris-Benedict equations generated wide variability, and the correlation with measured resting energy expenditure was poorer (r2 = .18, p < .0001), with Bland-Altman analysis showing a mean bias of −357 ± 750 kcal/day and limits of agreement ranging from −1827 to 1113 kcal/day. The use of the Swinamer, Fusco, or Ireton-Jones predictive methods yielded weaker correlation between calculated and measured resting energy expenditure (r2 = .41, p < .0001; r2 = .38, p < .0001; r2 = .39, p < .0001, respectively) than our equation, and Bland-Altman analysis showed no improvement in agreement and variability between methods. Conclusions: The Faisy equation, based on static (height), less stable (weight), and dynamic biometric variables (temperature and minute ventilation), provided precise and unbiased resting energy expenditure estimations in mechanically ventilated patients

Pharmacokinetics of epinephrine in patients with septic shock: modelization and interaction with endogenous neurohormonal status

Introduction In septic patients, an unpredictable response to epinephrine may be due to pharmacodynamic factors or to non-linear pharmacokinetics. The purpose of this study was to investigate the pharmacokinetics of epinephrine and its determinants in patients with septic shock. Methods Thirty-eight consecutive adult patients with septic shock were prospectively recruited immediately before epinephrine infusion. A baseline blood sample (C0) was taken to assess endogenous epinephrine, norepinephrine, renin, aldosterone, and plasma cortisol levels before epinephrine infusion. At a fixed cumulative epinephrine dose adjusted to body weight and under steady-state infusion, a second blood sample (C1) was taken to assess epinephrine and norepinephrine concentrations. Data were analyzed using the nonlinear mixed effect modeling software program NONMEM. Results Plasma epinephrine concentrations ranged from 4.4 to 540 nmol/L at steady-state infusion (range 0.1 to 7 mg/hr; 0.026 to 1.67 μg/kg/min). A one-compartment model adequately described the data. Only body weight (BW) and New Simplified Acute Physiologic Score (SAPSII) at intensive care unit admission significantly influenced epinephrine clearance: CL (L/hr) = 127 × (BW/70)0.60 × (SAPS II/50)-0.67. The corresponding half-life was 3.5 minutes. Endogenous norepinephrine plasma concentration significantly decreased during epinephrine infusion (median (range) 8.8 (1 – 56.7) at C0 vs. 4.5 (0.3 – 38.9) nmol/L at C1, P < 0.001). Conclusions Epinephrine pharmacokinetics is linear in septic shock patients, without any saturation at high doses. Basal neurohormonal status does not influence epinephrine pharmacokinetics. Exogenous epinephrine may alter the endogenous norepinephrine metabolism in septic patients

Impact of Morbidity and Mortality Conferences on Analysis of Mortality and Critical Events in Intensive Care Practice

Background Morbidity and mortality conferences are a tool for evaluating care management, but they lack a precise format for practice in intensive care units.Objectives To evaluate the feasibility and usefulness of regular morbidity and mortality conferences specific to intensive care units for improving quality of care and patient safety. Methods For 1 year, a prospective study was conducted in an 18-bed intensive care unit. Events analyzed included deaths in the unit and 4 adverse events (unexpected cardiac arrest, unplanned extubation, reintubation within 24–48 hours after planned extubation, and readmission to the unit within 48 hours after discharge) considered potentially preventable in optimal intensive care practice. During conferences, events were collectively analyzed with the help of an external auditor to determine their severity, causality, and preventability. Results During the study period, 260 deaths and 100 adverse events involving 300 patients were analyzed. The adverse events rate was 16.6 per 1000 patient-days. Adverse events occurred more often between noon and 4 pm (P = .001).The conference consensus was that 6.1% of deaths and 36% of adverse events were preventable. Preventable deaths were associated with iatrogenesis (P = .008), human errors (P < .001), and failure of unit management factors or communication (P = .003). Three major recommendations were made concerning standardization of care or prescription and organizational management, and no similar incidents have recurred. Conclusion In addition to their educational value, regular morbidity and mortality conferences formatted for intensive care units are useful for assessing quality of care and patient safety

ULtrasonographic diagnostic criterion for severe diaphragmatic dysfunction after cardiac surgery

Background: Severe diaphragmatic dysfunction can prolong mechanical ventilation after cardiac surgery. An ultrasonographic criterion for diagnosing severe diaphragmatic dysfunction defined by a reference technique such as transdiaphragmatic pressure measurements has never been determined.Methods: Twenty-eight patients requiring mechanical ventilation > 7 days postoperatively were studied. Esophageal and gastric pressures were measured to calculate transdiaphragmatic pressure during maximal inspiratory effort and the Gilbert index, which evaluates the diaphragm contribution to respiratory pressure swings during quiet ventilation. Ultrasonography allowed measuring right and left hemidiaphragmatic excursions during maximal inspiratory effort. Best E is the greatest positive value from either hemidiaphragm. Twenty cardiac surgery patients with uncomplicated postoperative course were also evaluated with ultrasonography preoperatively and postoperatively. Measurements were performed in semirecumbent position.Results: Transdiaphragmatic pressure during maximal inspiratory effort was below normal value in 27 of the 28 patients receiving prolonged mechanical ventilation (median, 39 cm H2O; interquartile range [IQR] 28 cm H2O). Eight patients had Gilbert indexes ≤ 0 indicating severe diaphragmatic dysfunction. Best E was lower in patients with Gilbert index ≤ 0 than > 0 (30 mm; IQR, 10 mm; vs 19 mm; IQR, 7 mm, respectively; p = 0.001). Best E < 25 mm had a positive likelihood ratio of 6.7 (95% confidence interval [CI], 2.4 to 19) and a negative likelihood ratio of 0 (95% CI, 0 to 1.1) for having a Gilbert index ≤ 0. None of the patients with uncomplicated course had Best E < 25 mm either preoperatively or postoperatively.Conclusions: Ultrasonographic-based determination of hemidiaphragm excursions in patients requiring prolonged mechanical ventilation after cardiac surgery may help identify those with and without severe diaphragmatic dysfunction as defined by the Gilbert index

Impact of energy deficit calculated by a predictive method on outcome in medical patients requiring prolonged acute mechanical ventilation

To assess energy balance in very sick medical patients requiring prolonged acute mechanical ventilation and its possible impact on outcome, we conducted an observational study of the first 14 d of intensive care unit (ICU) stay in thirty-eight consecutive adult patients intubated at least 7 d. Exclusive enteral nutrition (EN) was started within 24 h of ICU admission and progressively increased, in absence of gastrointestinal intolerance, to the recommended energy of 125·5 kJ/kg per d. Calculated energy balance was defined as energy delivered − resting energy expenditure estimated by a predictive method based on static and dynamic biometric parameters. Mean energy balance was − 5439 (sem 222) kJ per d. EN was interrupted 23 % of the time and situations limiting feeding administration reached 64 % of survey time. ICU mortality was 72 %. Non-survivors had higher mean energy deficit than ICU survivors (P = 0·004). Multivariate analysis identified mean energy deficit as independently associated with ICU death (P = 0·02). Higher ICU mortality was observed with higher energy deficit (P = 0·003 comparing quartiles). Using receiver operating characteristic curve analysis, the best deficit threshold for predicting ICU mortality was 5021 kJ per d. Kaplan–Meier analysis showed that patients with mean energy deficit ≧5021 kJ per d had a higher ICU mortality rate than patients with lower mean energy deficit after the 14th ICU day (P = 0·01). The study suggests that large negative energy balance seems to be an independent determinant of ICU mortality in a very sick medical population requiring prolonged acute mechanical ventilation, especially when energy deficit exceeds 5021 kJ per d

Bioelectrical impedance phase angle in clinical practice: implications for prognosis in stage IIIB and IV non-small cell lung cancer

<p>Abstract</p> <p>Background</p> <p>A frequent manifestation of advanced lung cancer is malnutrition, timely identification and treatment of which can lead to improved patient outcomes. Bioelectrical impedance analysis (BIA) is an easy-to-use and non-invasive technique to evaluate changes in body composition and nutritional status. We investigated the prognostic role of BIA-derived phase angle in advanced non-small cell lung cancer (NSCLC).</p> <p>Methods</p> <p>A case series of 165 stages IIIB and IV NSCLC patients treated at our center. The Kaplan Meier method was used to calculate survival. Cox proportional hazard models were constructed to evaluate the prognostic effect of phase angle, independent of stage at diagnosis and prior treatment history.</p> <p>Results</p> <p>93 were males and 72 females. 61 had stage IIIB disease at diagnosis while 104 had stage IV. The median phase angle was 5.3 degrees (range = 2.9 – 8). Patients with phase angle <= 5.3 had a median survival of 7.6 months (95% CI: 4.7 to 9.5; n = 81), while those with > 5.3 had 12.4 months (95% CI: 10.5 to 18.7; n = 84); (p = 0.02). After adjusting for age, stage at diagnosis and prior treatment history we found that every one degree increase in phase angle was associated with a relative risk of 0.79 (95% CI: 0.64 to 0.97, P = 0.02).</p> <p>Conclusion</p> <p>We found BIA-derived phase angle to be an independent prognostic indicator in patients with stage IIIB and IV NSCLC. Nutritional interventions targeted at improving phase angle could potentially lead to an improved survival in patients with advanced NSCLC.</p

Bioelectrical impedance phase angle as a prognostic indicator in breast cancer

<p>Abstract</p> <p>Background</p> <p>Bioelectrical impedance analysis (BIA) is an easy-to-use, non-invasive, and reproducible technique to evaluate changes in body composition and nutritional status. Phase angle, determined by bioelectrical impedance analysis (BIA), detects changes in tissue electrical properties and has been hypothesized to be a marker of malnutrition. Since malnutrition can be found in patients with breast cancer, we investigated the prognostic role of phase angle in breast cancer.</p> <p>Methods</p> <p>We evaluated a case series of 259 histologically confirmed breast cancer patients treated at Cancer Treatment Centers of America. Kaplan Meier method was used to calculate survival. Cox proportional hazard models were constructed to evaluate the prognostic effect of phase angle independent of stage at diagnosis and prior treatment history. Survival was calculated as the time interval between the date of first patient visit to the hospital and the date of death from any cause or date of last contact/last known to be alive.</p> <p>Results</p> <p>Of 259 patients, 81 were newly diagnosed at our hospital while 178 had received prior treatment elsewhere. 56 had stage I disease at diagnosis, 110 had stage II, 46 had stage III and 34 had stage IV. The median age at diagnosis was 49 years (range 25 – 74 years). The median phase angle score was 5.6 (range = 1.5 – 8.9). Patients with phase angle <= 5.6 had a median survival of 23.1 months (95% CI: 14.2 to 31.9; n = 129), while those > 5.6 had 49.9 months (95% CI: 35.6 to 77.8; n = 130); the difference being statistically significant (p = 0.031). Multivariate Cox modeling, after adjusting for stage at diagnosis and prior treatment history found that every one unit increase in phase angle score was associated with a relative risk of 0.82 (95% CI: 0.68 to 0.99, P = 0.041). Stage at diagnosis (p = 0.006) and prior treatment history (p = 0.001) were also predictive of survival independent of each other and phase angle.</p> <p>Conclusion</p> <p>This study demonstrates that BIA-derived phase angle is an independent prognostic indicator in patients with breast cancer. Nutritional interventions targeted at improving phase angle could potentially lead to an improved survival in patients with breast cancer.</p