Australian and New Zealand practice in intensive care (ANZPIC II): Predictors of physician confidence to diagnose pneumonia and determine illness severity in ventilated patients

The manner in which elements of clinical history, physical examination and investigations influence subjectively assessed illness severity and outcome prediction is poorly understood. This study investigates the relationship between clinician and objectively assessed illness severity and the factors influencing clinician's diagnostic confidence and illness severity rating for ventilated patients with suspected pneumonia in the intensive care unit (ICU). A prospective study of fourteen ICUs included all ventilated admissions with a clinical diagnosis of pneumonia. Data collection included pneumonia type - community-acquired (CAP), hospital-acquired (HAP) and ventilator-associated (VAP), clinician determined illness severity (CDIS), diagnostic methods, clinical diagnostic confidence (CDC), microbiological isolates and antibiotic use. For 476 episodes of pneumonia (48% CAP, 24% HAP, 28% VAP), CDC was greatest for CAP (64% CAP, 50% HAP and 49% VAP, P < 0.01) or when pneumonia was considered life-threatening (84% high CDC, 13% medium CDC and 3% low CDC, P < 0.001). Life-threatening pneumonia was predicted by worsening gas exchange (OR 4.8, CI 95% 2.3-10.2, P < 0.001), clinical signs of consolidation (OR 2.0, CI 95% 1.2-3.2, P < 0.01) and the Sepsis-Related Organ Failure Assessment (SOFA) Score (OR 1.1, CI 95% 1.1-1.2, P < 0.001). Diagnostic confidence increased with CDIS (OR 163, CI 95% 8.4-31.4, P < 0.001), definite pathogen isolation (OR 3.3, CI 95% 2.0-5.6) and clinical signs of consolidation (OR 2.1, CI 95% 1.3-3.3, P = 0.001). Although the CDIS, SOFA Score and the Simplified Acute Physiologic Score (SAPS II) were all associated with mortality, the SAPS II Score was the best predictor of mortality (P = 0.02). Diagnostic confidence for pneumonia is moderate but increases with more classical presentations. A small set of clinical parameters influence subjective assessment. Objective assessment using SAPS II Scoring is a better predictor of mortality.

Re-admission to intensive care: Identification of risk factors

Background and Purpose. The re-admission of patients to intensive care is associated with increased morbidity, mortality, loss of morale for patients and family, and increased health costs. The aim of the present study was to identify factors which place patients at a higher risk of re-admission to intensive care. Method. A prospective study of patients who were re-admitted to a 22-bed tertiary level intensive care facility within a 12-month period. Data were kept on every patient re-admitted to intensive care, including standard demographic data, initial admission diagnosis, co-morbidities, re-admission diagnosis, mobility on discharge, secretions, airway, chest X-ray, PaCO2, PaO2, PaO2/FiO2and time of discharge. Subjects included 74 patients who had been re-admitted to intensive care in a 12-month period and a comparison group of patients who were not re-admitted to intensive care. A cross-tabs procedure was initially used to estimate maximum likelihood. Significant factors with an value of 65 years (p

Disease risk and mortality prediction in intensive care patients with pneumonia. Australian and New Zealand practice in intensive care (ANZPIC II)

This study of ventilated patients investigated pneumonia risk factors and outcome predictors in 476 episodes of pneumonia (48% community-acquired pneumonia, 24% hospital-acquired pneumonia, 28% ventilator-associated pneumonia) using a prospective survey in 14 intensive care units within Australia and New Zealand. For community acquired pneumonia, mortality increased with immunosuppression (OR 5.32, CI 95% 1.58-17.99, P < 0. 01), clinical signs of consolidation (OR 2.43, CI 95% 1.09-5.44, P = 0. 03) and Sepsis-Related Organ Failure Assessment (SOFA) scores (OR 1.19, CI 95% 1.08-1.30, P < 0. 001) but improved if appropriate antibiotic changes were made within three days of intensive care unit admission (OR 0.42, CI 95% 0.20-0.86, P = 0.02). For hospital-acquired pneumonia, immunosuppression (OR 6.98, CI 95% 1.16-42.2, P = 0.03) and non-metastatic cancer (OR 3.78, CI 95% 1.20-11.93, P = 0.02) were the principal mortality predictors. Alcoholism (OR 7.80, CI 95% 1.20-1750, P < 0.001), high SOFA scores (OR 1.44, CI 95% 1.20-1.75, P = 0.001) and the isolation of high risk organisms including Pseudomonas aeruginosa, Acinetobacter spp, Stenotrophomonas spp and methicillin resistant Staphylococcus aureus (OR 4.79, CI 95% 1.43-16.03, P = 0.01), were associated with increased mortality in ventilator-associated pneumonia. The use of non-invasive ventilation was independently protective against mortality for patients with community-acquired and hospital-acquired pneumonia (OR 0.35, CI 95% 0.18-0.68, P = 0.002). Mortality was similar for patients requiting both invasive and non-invasive ventilation and non-invasive ventilation alone (21% compared with 20% respectively, P = 0.56). Pneumonia risks and mortality predictors in Australian and New Zealand ICUs vary with pneumonia type. A history of alcoholism is a major risk factor for mortality in ventilator-associated pneumonia, greater in magnitude than the mortality effect of immunosuppression in hospital-acquired pneumonia or community-acquired pneumonia. Non-invasive ventilation is associated with reduced ICU mortality. Clinical signs of consolidation worsen, while rationalising antibiotic therapy within three days of ICU admission improves mortality for community-acquired pneumonia patients.

Australian and New Zealand practice in intensive care (ANZPIC II: The spectrum of practice in the diagnosis and management of pneumonia in patients requiring mechanical ventilation

This study of ventilated patients investigated current clinical practice in 476 episodes of pneumonia (48% community-acquired pneumonia, 24% hospital-acquired pneumonia, 28% ventilator-associated pneumonia) using a prospective survey in 14 intensive care units (ICUs) within Australia and New Zealand. Diagnostic methods and confidence, disease severity, microbiology and antibiotic use were assessed. All pneumonia types had similar mortality (community-acquired pneumonia 33%, hospital-acquired pneumonia 37% and ventilator-associated pneumonia 24%, P = 0.15) with no inter-hospital differences (P = 0.08-0.91). Bronchoscopy was performed in 26%, its use predicted by admission hospital (one tertiary: OR 9.98, CI 95% 5.11-19.49, P < 0.001; one regional: OR 629, CI 95% 3.24-12.20, P < 0.001), clinical signs of consolidation (OR 3.72, CI 95% 2.09-662, P < 0.001) and diagnostic confidence (OR 2.19, CI 95% 1.29-3.72, P = 0.004). Bronchoscopy did not predict outcome (P = 0.11) or appropriate antibiotic selection (P = 0.69). Inappropriate antibiotic prescription was similar for all pneumonia types (11-13%, P = 0.12) and hospitals (0-16%, P = 0.25). Blood cultures were taken in 51% of cases. For community-acquired pneumonia, 70% received a third generation cephalosporin and 65% a macrolide. Third generation cephalosporins were less frequently used for mild infections (OR 0.38, CI 95% 0.16-0.90, P = 0.03), hospital-acquired pneumonia (OR 0.40, CI 95% 0.23-0.72, P < 0.01), ventilator-associated pneumonia (OR 0.04, CI 95% 0.02-0.13, P < 0.001), suspected aspiration (OR 0.20, CI 95% 0.04-0.92, P = 0.04), in one regional (OR 0.26, CI 95% 0.07-0.97, P = 0.05) and one tertiary hospital (OR 0.14, CI 95% 0.03-0.73, P = 0.02) but were more commonly used in older patients (OR 1.02, CI 95% 1.01-1.03, P = 0.01). There is practice variability in bronchoscopy and antibiotic use for pneumonia in Australian and New Zealand ICUs without significant impact on patient outcome, as the prevalence of inappropriate antibiotic prescription is low. There are opportunities for improving microbiological diagnostic work-up for isolation of aetiological pathogens.

The costs of caring for patients in a tertiary referral Australian intensive care unit

We determined the direct cost of an Intensive Care Unit (ICU) bed in a tertiary referral Australian ICU and the cost drivers thereof, by retrospectively analysing a number of prospectively designed Hospital- and Unit-specific electronic databases. The study period was a financial year, from 1 July 2002 to 30 June 2003. There were 1615 patients occupying 5692 fractional occupied bed days at a total cost of A$15,915,964, with an average length of stay of 3.69 days (range 0.5-77, median 1.06, interquartile range 2.33). The main cost driver not incorporated into this analysis was blood products (paid for centrally). The average costs of an ICU day and total stay per patient were A$2670 and A$9852 respectively. Staff-related charges were 68.76%, with consumables related expenditure making up 19.65%, clinical support services 9.55% and capital equipment 2.04%. Overtime charges and nursing agency staff were 19.4% of staff-related charges (2.9% for agency staff), 3.9% lower than expenditure associated with full-time employment charges, such as pension and leave. The emergency nature of ICU means it is difficult to accurately set a nursing establishment to cater for all admissions and therefore it is hard to decide what is an acceptable percentage difference between agency/overtime costs compared with the costs associated with full-time staff appointments. Consumable expenditure is likely to increase the most with new innovation and therapies. Using protocol driven practices may tighten and control costs incurred in ICU.

Antibiotic resistance in the intensive care unit: A primer in bacteriology

The clinical use of potent, well-tolerated, broad-spectrum antibiotics has been paralleled by the development of resistance in bacteria, and the prevalence of highly resistant bacteria in some intensive care units is despairingly commonplace. The intensive care community faces the realistic prospect of untreatable nosocomial infections and should be searching for new approaches to diagnose and manage resistant bacteria. In this review, we discuss some of the relevant underlying biology, with a particular focus on genetic transfer vehicles and the relationship of selection pressure to their movements. It is an attempt to demystify the relevant language and concepts for the anaesthetist and intensivist, to explain some of the reasons for the emergence of resistance in bacteria, and to provide a contextual basis for discussion of management approaches such as selective decontamination and antibiotic cycling.

Adoption of a sedation scoring system and sedation guideline in an intensive care unit

Aim. The paper presents a study assessing the rate of adoption of a sedation scoring system and sedation guideline. Background. Clinical practice guidelines including sedation guidelines have been shown to improve patient outcomes by standardizing care. In particular sedation guidelines have been shown to be beneficial for intensive care patients by reducing the duration of ventilation. Despite the acceptance that clinical practice guidelines are beneficial, adoption rates are rarely measured. Adoption data may reveal other factors which contribute to improved outcomes. Therefore, the usefulness of the guideline may be more appropriately assessed by collecting adoption data. Method. A quasi-experimental pre-intervention and postintervention quality improvement design was used. Adoption was operationalized as documentation of sedation score every 4 hours and use of the sedation and analgesic medications suggested in the guideline. Adoption data were collected from patients' charts on a random day of the month; all patients in the intensive care unit on that day were assigned an adoption category. Sedation scoring system adoption data were collected before implementation of a sedation guideline, which was implemented using an intensive information-giving strategy, and guideline adoption data were fed back to bedside nurses. After implementation of the guideline, adoption data were collected for both the sedation scoring system and the guideline. The data were collected in the years 2002-2004. Findings. The sedation scoring system was not used extensively in the pre-intervention phase of the study; however, this improved in the postintervention phase. The findings suggest that the sedation guideline was gradually adopted following implementation in the postintervention phase of the study. Field notes taken during the implementation of the sedation scoring system and the guideline reveal widespread acceptance of both. Conclusion. Measurement of adoption is a complex process. Appropriate operationalization contributes to greater accuracy. Further investigation is warranted to establish the intensity and extent of implementation required to positively affect patient outcomes.

The effect of an algorithm-based sedation guideline on the duration of mechanical ventilation in an Australian intensive care unit

To examine the effect of an algorithm-based sedation guideline developed in a North American intensive care unit (ICU) on the duration of mechanical ventilation of patients in an Australian ICU. The intervention was tested in a pre-intervention, post-intervention comparative investigation in a 14-bed adult intensive care unit. Adult mechanically ventilated patients were selected consecutively (n =322) The pre-intervention and post-intervention groups were similar except for a higher number of patients with a neurological diagnosis in the pre-intervention group. An algorithm-based sedation guideline including a sedation scale was introduced using a multifaceted implementation strategy. The median duration of ventilation was 5.6 days in the post-intervention group, compared with 4.8 days for the pre-intervention group (P = 0.99). The length of stay was 8.2 days in the post-intervention group versus 7.1 days in the pre-intervention group (P = 0.04). There were no statistically significant differences for the other secondary outcomes, including the score on the Experience of Treatment in ICU 7 item questionnaire, number of tracheostomies and number of self-extubations. Records of compliance to recording the sedation score during both phases revealed that patients were slightly more deeply sedated when the guideline was used. The use of the algorithm-based sedation guideline did not reduce duration of mechanical ventilation in the setting of this study.

Antibacterial dosing in intensive care: Pharmacokinetics, degree of disease and pharmacodynamics of sepsis

Treatment of sepsis remains a significant challenge with persisting high mortality and morbidity. Early and appropriate antibacterial therapy remains an important intervention for such patients. To optimise antibacterial therapy, the clinician must possess knowledge of the pharmacokinetic and pharmacodynamic properties of commonly used antibacterials and how these parameters may be affected by the constellation of pathophysiological changes occurring during sepsis. Sepsis, and the treatment thereof, increases renal preload and, via capillary permeability, leads to 'third-spacing', both resulting in higher antibacterial clearances. Alternatively, sepsis can induce multiple organ dysfunction, including renal and/or hepatic dysfunction, causing a decrease in antibacterial clearance. Aminoglycosides are concentration-dependent antibacterials and they display an increased volume of distribution (V-d) in sepsis, resulting in decreased peak serum concentrations. Reduced clearance from renal dysfunction would increase the likelihood of toxicity. Individualised dosing using extended interval dosing, which maximises the peak serum drug concentration (C-max)/minimum inhibitory concentration ratio is recommended. beta-Lactams and carbapenems are time-dependent antibacterials. An increase in Vd and renal clearance will require increased dosing or administration by continuous infusion. If renal impairment occurs a corresponding dose reduction may be required. Vancomycin displays predominantly time-dependent pharmacodynamic properties and probably requires higher than conventionally recommended doses because of an increased V-d and clearance during sepsis without organ dysfunction. However, optimal dosing regimens remain unresolved. The poor penetration of vancomycin into solid organs may require alternative therapies when sepsis involves solid organs (e.g. lung). Ciprofloxacin displays largely concentration-dependent kill characteristics, but also exerts some time-dependent effects. The V-d of ciprofloxacin is not altered with fluid shifts or over time, and thus no alterations of standard doses are required unless renal dysfunction occurs. In order to optimise antibacterial regimens in patients with sepsis, the pathophysiological effects of systemic inflammatory response syndrome need consideration, in conjunction with knowledge of the different kill characteristics of the various antibacterial classes. In conclusion, certain antibacterials can have a very high V-d, therefore leading to a low C-max and if a high peak is needed, then this would lead to underdosing. The Vd of certain antibacterials, namely aminoglycosides and vancomycin, changes over time, which means dosing may need to be altered over time. Some patients with serum creatinine values within the normal range can have very high drug clearances, thereby producing low serum drug levels and again leading to underdosing. Copyright © 2010 Elsevier Inc. All rights reserved.