Physicians' perceptions of intensive care patients' 1-year prognoses compared to realistic prognoses.

BACKGROUND: It is unknown whether physicians treating critically ill patients have realistic perceptions of their patients' prognoses. METHODS: We sent a survey by email to Finnish anesthesiologists to investigate their ability to estimate the probability of 1-year survival of intensive care unit (ICU) patients based on data available at the beginning of intensive care. We presented 12 fictional but real-life-based patient cases and asked the respondent to estimate the probability of 1-year survival in each case by choosing one of the alternatives 5%, 10%-90% in 10% intervals and 95%. We compared the physicians' estimates to registry data-based realistic prognoses of comparable patients treated in the ICU. Based on the difference between the estimate and the realistic prognosis, we categorized the estimates into three groups: (1) difference less than 10 percentage points, (2) difference between 10 and 20 percentage points, and (3) difference over 20 percentage points. RESULTS: We received 210 responses (totally 2520 estimates). Of the respondents, 43 (20.5%) were specialists working mainly in the ICU, 81 (38.6%) were specialists working occasionally in the ICU, 47 (22.4%) were specialists not working in the ICU, and 39 (18.6%) were doctors in training. The difference between the estimate and the realistic prognosis was less than 10 percentage points for 1083 (43.0%) estimates, between 10 and 20 percentage points for 645 (25.6%) estimates, and over 20 percentage points for 792 (31.4%) estimates, out of which 612 (24.3% of all estimates) underestimated and 180 (7.1%) overestimated the likelihood of survival. The median error (the median of the differences between the estimate and the realistic prognosis) for all estimates was -8.8 [interquartile range (IQR), -20.0 to -0.2], which means that the most typical response underestimated the likelihood of survival by 9 percentage points. Based on the 12 estimates, we calculated the median error for each respondent. The median (IQR) of these median errors was -8.6 (-12.6 to -5.0) for specialists working mainly in the ICU, -8.1 (-13.0 to -5.2) for specialists working occasionally in the ICU, -9.7 (-17.7 to -6.3) for specialists not working in the ICU, and -9.1 (-14.5 to -5.1) for doctors in training (p = .29). CONCLUSION: Finnish anesthesiologists commonly misestimate the long-term prognoses of ICU patients, more often underestimating than overestimating the likelihood of 1-year survival. More education about critically ill patients' prognoses and better prediction tools are needed.

A novel score for predicting 1-year mortality of intensive care patients.

BACKGROUND: We aimed to develop a simple scoring table for predicting probability of death within 1-year after admission to an intensive care unit. We analysed data on emergency admissions from the nationwide Finnish intensive care quality registry. METHODS: We included first admissions of adult patients with data available on 1-year vital status (dead or alive) and all five variables included in a premorbid functional status score, which is the number of activities the person can manage independently of the following five: get out of bed, move indoors, dress, climb stairs and walk 400 m. We analysed data on patient characteristics and admission-associated factors from 2012 to 2014 to find predictors of 1-year mortality and to develop a score for predicting probability of death. We tested the performance of this score in data from 2015. We assessed the 1-year functional status score of survivors with data available. RESULTS: Out of 25,261 patients, 20,628 (81.7%) patients were able to perform all five functional activities independently prior to the intensive care unit admission. At 1-year post admission, 19,625 (77.7%) patients were alive. 1-year functional status score was known for 11,011 patients and 8970 (81.5%) patients achieved functional status score 5, managing all five activities independently. The score based on age, sex, preceding functional status, type of intensive care unit admission, severity of acute illness and the most significant diagnoses predicted 1-year mortality with an area under the receiver operating characteristic curve 0.78 (95% CI, 0.76-0.79). The calibration of our prediction model was good, with calibration intercept -0.01 (-0.07 to 0.05) and calibration slope 0.96 (0.90 to 1.02). CONCLUSION: Our score based on data available at intensive care unit admission predicted 1-year mortality with fairly good discrimination. Most survivors achieved good functional recovery.

Premorbid functional status as an outcome predictor in intensive care patients aged over 85 years.

BACKGROUND: Poor premorbid functional status (PFS) is associated with mortality after intensive care unit (ICU) admission in patients aged 80 years or older. In the subgroup of very old ICU patients, the ability to recover from critical illness varies irrespective of age. To assess the predictive ability of PFS also among the patients aged 85 or older we set out the current study. METHODS: In this nationwide observational registry study based on the Finnish Intensive Care Consortium database, we analysed data of patients aged 85 years or over treated in ICUs between May 2012 and December 2015. We defined PFS as good for patients who had been independent in activities of daily living (ADL) and able to climb stairs and as poor for those who were dependent on help or unable to climb stairs. To assess patients' functional outcome one year after ICU admission, we created a functional status score (FSS) based on how many out of five physical activities (getting out of bed, moving indoors, dressing, climbing stairs, and walking 400 m) the patient could manage. We also assessed the patients' ability to return to their previous type of accommodation. RESULTS: Overall, 2037 (3.3% of all adult ICU patients) patients were 85 years old or older. The average age of the study population was 87 years. Data on PFS were available for 1446 (71.0%) patients (good for 48.8% and poor for 51.2%). The one-year mortalities of patients with good and those with poor PFS were 29.2% and 50.1%, respectively, p < 0.001. Poor PFS increased the probability of death within 12 months, adjusted odds ratio (OR), 2.15; 95% confidence interval (CI) 1.68-2.76, p < 0.001. For 69.5% of survivors, the FSS one year after ICU admission was unchanged or higher than their premorbid FSS and 84.2% of patients living at home before ICU admission still lived at home. CONCLUSIONS: Poor PFS doubled the odds of death within one year. For most survivors, functional status was comparable to the premorbid status.

Intensive care patient survival after limiting life-sustaining treatment-The FINNEOL* national cohort study.

BACKGROUND: Few studies have examined survival in intensive care unit (ICU) patients after the restriction of life-sustaining treatment (LST). We aimed to analyse independent factors associated with hospital and 12-month survival rates in ICU patients after treatment restrictions. METHODS: This retrospective observational study examined all patients treated in adult ICUs from 1 January 2016 until 31 December 2016 included in the Finnish ICU Registry. Multivariable logistic regression analysis was performed to explain the effect on survival. RESULTS: Decisions to limit LST were made for 2444 patients (13.7%; 95% CI 13.2-14.2). ICU, hospital, and 12-month survival rates were 71% (95% CI 69-73), 49% (95% CI 47-51), and 24% (95% CI 22-26), respectively. In patients for whom life support was withheld, increased 12-month survival rates were associated with admission from the operating theatre (OR 1.9, 95% CI 1.1-3.4), good pre-hospital physical fitness (OR 4.7, 95% Cl 1.2-16.8) and being housed at home (OR 2.0, 95% Cl 1.4-2.8). Decreased survival rates were associated with admission from a hospital ward (OR 0.67, 95% Cl 0.5-0.9), higher comorbidity (OR 0.6, 95% Cl 0.4-0.9), cancer (OR 0.4, 95%CI 0.2-0.9), greater illness severity (SAPS II; OR 0.98, 95% Cl 0.98-0.99), and higher care intensity (TISS-76; OR 0.93, 95% Cl 0.92-0.95). CONCLUSION: Survival among ICU patients with limited treatment was higher than expected. Advanced age was not associated with higher mortality, potentially because treatment restrictions may be set more easily for older patients.

Vasoactive-inotropic score and the prediction of morbidity and mortality after cardiac surgery.

BACKGROUND: The vasoactive-inotropic score (VIS) predicts mortality and morbidity after paediatric cardiac surgery. Here we examined whether VIS also predicted outcome in adults after cardiac surgery, and compared predictive capability between VIS and three widely used scoring systems. METHODS: This single-centre retrospective cohort study included 3213 cardiac surgery patients. Maximal VIS (VISmax) was calculated using the highest doses of vasoactive and inotropic medications administered during the first 24 h post-surgery. We established five VISmax categories: 0-5, >5-15, >15-30, >30-45, and >45 points. The predictive accuracy of VISmax was evaluated for a composite outcome, which included 30-day mortality, mediastinitis, stroke, acute kidney injury, and myocardial infarction. RESULTS: VISmax showed good prediction accuracy for the composite outcome [area under the curve (AUC), 0.72; 95% confidence interval (CI), 0.69-0.75]. The incidence of the composite outcome was 9.6% overall and 43% in the highest VISmax group (>45). VISmax predicted 30-day mortality (AUC, 0.76; 95% CI, 0.69-0.83) and 1-yr mortality (AUC, 0.70; 95% CI, 0.65-0.74). Prediction accuracy for unfavourable outcome was significantly better with VISmax than with Acute Physiology and Chronic Health Evaluation II (P=0.01) and Simplified Acute Physiological Score II (P=0.048), but not with the Sequential Organ Failure Assessment score (P=0.32). CONCLUSIONS: In adults after cardiac surgery, VISmax predicted a composite of unfavourable outcomes and predicted mortality up to 1 yr after surgery.

Premorbid functional status as a predictor of 1-year mortality and functional status in intensive care patients aged 80 years or older.

PURPOSE: We assessed the association between the premorbid functional status (PFS) and 1-year mortality and functional status of very old intensive care patients. METHODS: Using a nationwide quality registry, we retrieved data on patients treated in Finnish intensive care units (ICUs) during the period May 2012‒April 2013. Of 16,389 patients, 1827 (11.1%) were very old (aged 80 years or older). We defined a person with good functional status as someone independent in activities of daily living (ADL) and able to climb stairs without assistance; a person with poor functional status was defined as needing assistance for ADL or being unable to climb stairs. We adjusted for severity of illness and calculated the impact of PFS. RESULTS: Overall, hospital mortality was 21.3% and 1-year mortality was 38.2%. For emergency patients (73.5% of all), hospital mortality was 28% and 1-year mortality was 48%. The functional status at 1 year was comparable to the PFS in 78% of the survivors. PFS was poor for 43.3% of the patients. A poor PFS predicted an increased risk of in-hospital death, adjusted odds ratio (OR) 1.50 (95% confidence interval, 1.07-2.10), and of 1-year mortality, OR 2.18 (1.67-2.85). PFS data significantly improved the prediction of 1-year mortality. CONCLUSIONS: Of very old ICU patients, 62% were alive 1 year after ICU admission and 78% of the survivors had a functional status comparable to the premorbid situation. A poor PFS doubled the odds of death within a year. Knowledge of PFS improved the prediction of 1-year mortality.