Current practice regarding invasive monitoring in intensive care units in Finland. A nationwide study of the uses of arterial, pulmonary artery and central venous catheters and their effect on outcome. The Finnish Intensive Care Study Group.

As part of a nationwide evaluation of intensive care, we examined patient- and hospital-related factors which could influence the patterns of utilization of arterial cannulae and central venous and pulmonary artery catheters. We also studied the possible impact of these interventions on the short-term outcome among 14,951 consecutive ICU admissions to 25 intensive care units (75% of all ICU beds) in Finland. There was considerable variation between individual units in the use of these devices even if the differences in severity of illness were taken into account. Arterial cannulation was used in 71.2%, PA catheterization in 10.6% and CVP monitoring in 49.3% of cases in teaching ICUs, excluding cardiac surgery, and in 38.5%, 2.6% and 33.1% of cases in non-teaching ICUs respectively. The factors predicting the use of invasive monitoring included extensive surgery causing a risk of cardiovascular instability, needs for mechanical ventilation, infusion of vasoactive drugs and complicated fluid therapy. Cardiovascular problems among non-operative patients increased the odds for PA catheterization but reduced them for arterial and CV cannulation. No clear-cut benefit could be found in the form of hospital mortality reduction from invasive haemodynamic monitoring, used as described in this study.

Contribution of non-neurologic disturbances in acute physiology to the prediction of intensive care outcome after head injury or non-traumatic intracranial haemorrhage.

OBJECTIVE: To study the additional contribution of non-neurologic disturbances in acute physiology and chronic health to the prediction of intensive care outcome in patients with head injury or non-traumatic intracranial haemorrhage. DESIGN: A nationwide study in Finland with prospectively collected data on all adult patients admitted to intensive care after head trauma or non-traumatic intracranial haemorrhage during a 14-month period. Two-thirds of the patients were randomly selected to derive predictive models, and the remaining one third constituted the validation sample. SETTING: A total of 25 medical and surgical ICUs in Finland (13 in tertiary referral centers). PATIENTS: 901 consecutive adult patients with head injury or non-traumatic intracranial haemorrhage. MEASUREMENTS AND RESULTS: Variables of the APACHE II including Glasgow Coma Score were collected at the time of ICU admission. Two predictive models were created to explain hospital mortality. The addition of variables describing acute physiology to a predictive model consisting of Glasgow Coma Score, age, diagnosis of head injury and the type of ICU admission did not increase its performance in discriminating between survivors and nonsurvivors, but the calibration accuracy of the predictive model especially at the high ranges of risk was improved. CONCLUSIONS: The non-neurologic disturbances in acute physiology have prognostic significance in the prediction of intensive care outcome in patients with head injury or non-traumatic intracerebral haemorrhage. The created predictive model may supplement clinical judgement of this patient group.

Prediction of outcome from intensive care after gastroenterologic emergency.

Prognostic factors determining the outcome from intensive care were studied in 952 patients admitted to 25 Finnish ICUs after gastroenterologic emergency. Logistic regression analysis was used to create predictive models based on the APACHE II-system. The models were constructed by using data from a random two-thirds of the study population and validated in the remaining independent one-third together with the original APACHE II-index. The Acute Physiology Score, age, and a pre-existing liver disease were the three most important determinants of outcome. The inclusion of the TISS score describing the intensity of treatment into a model did not enhance the accuracy of the prediction. Our models were better calibrated than the original APACHE II-equation when tested by the goodness-of-fit -statistics. These statistical models may help the clinicians to predict the outcome for an individual patient by providing them information about the relative impacts of predictive factors or about the probability of death. These probabilities should be interpreted cautiously, taking into account the limitations of statistical methods. This is especially important when assessing the highrisk patients. Their number in our study was too low for accurate outcome prediction.

Postoperative pain management and recovery after remifentanil-based anaesthesia with isoflurane or propofol for major abdominal surgery. Remifentanil Study Group.

We have assessed if recovery times after morphine or fentanyl, given before terminating remifentanil anaesthesia with isoflurane or propofol, are compromised. We studied patients undergoing elective, major abdominal surgery, allocated randomly to receive remifentanil and isoflurane (n = 277) or remifentanil and propofol (n = 274) anaesthesia. Twenty-five minutes before the end of surgery, patients received fentanyl 0.15 mg or morphine 15 mg in a randomized, double-blind manner followed by a second dose (fentanyl 0.05 mg, morphine 7 mg) for moderate or severe pain in recovery. Recovery was rapid and at an Aldrete score > or = 9 (median 12-15 min), 42-51% of patients reported none or mild pain. However, 26-35% of patients reported severe pain and > 90% required a second dose of opioid within 21-27 min after anaesthesia.

Acute physiology and chronic health evaluation (APACHE II) and Glasgow coma scores as predictors of outcome from intensive care after cardiac arrest.

OBJECTIVES: a) To examine the accuracy of the Acute Physiology and Chronic Health Evaluation (APACHE II) and the Glasgow Coma Scores as predictors of the outcome of patients following resuscitation from cardiac arrest; b) to study the impact of the components of APACHE II on the prediction. DESIGN: A nationwide study in Finland with prospectively collected data on all patients admitted to intensive care after cardiac arrest during a 14-month period. Two thirds of the cardiac arrest patients included in the study were randomly selected to derive predictive models, and the remaining one third constituted the validation sample. SETTING: A total of 25 medical and surgical ICUs in Finland (13 in tertiary referral centers). PATIENTS: Six-hundred nineteen consecutive cardiac arrest patients. Fifteen patients less than 16 yrs were excluded. MAIN OUTCOME MEASURES: Variables included in the APACHE II or Glasgow Coma Scores were collected at the time of ICU admission and then three times after admission, at 24-hr intervals. ICU- and hospital-mortality rates and a 6-month mortality rate after ICU admission were studied. RESULTS: Of 604 study patients, 370 (61.3%) patients died in the hospital. The most accurate prediction of hospital outcome was based on data collected after the first day of ICU care, not on the admission values. Twenty-one (21.9%) of 96 patients with a low APACHE II score (less than or equal to 9) died compared with 66 (84.6%) of 78 patients with a high APACHE II score (greater than or equal to 25) (p less than .001). Of 160 patients with a normal Glasgow Coma Score (14 to 15), 45 (28.1%) died, whereas there were 114 (81.4%) nonsurvivors among 140 patients with a low Glasgow Coma Score of 3 (p less than .001). The performance of predictive models, including age, the Chronic Health Evaluation, and either the Acute Physiology Score (Acute Physiology Score model) or the Glasgow Coma Score (Glasgow Coma Score model) were compared with the prediction according to the APACHE II in the validation sample. When using 80% probability of death as a decision rule, the Acute Physiology Score model determined 35 of 153 patients to have high risk of death, 29 of whom died (the positive predictive value being 82.9%). The Glasgow Coma Score model predicted 34 patients to die, 26 of whom died (positive predictive value 76.5%), and the APACHE II score predicted seven deaths, five of whom actually died (positive predictive value 71.4%). CONCLUSIONS: The APACHE II scoring system cannot be recommended as a prognostic tool to support clinical judgement in cardiac arrest patients, but by modifying it, a more accurate prediction of poor outcome could be achieved. The Glasgow Coma Score explained to a great extent the predictive power of the APACHE II.