Using patient admission characteristics alone to predict mortality of critically ill patients: A comparison of 3 prognostic scores

Severity indexes of blunt trauma victims in intensive therapy: prediction capacity for mortality

OBJECTIVE

To identify the predictive capacity for mortality of the indexes Revised Trauma Score, Rapid Emergency Medicine Score, modified Rapid Emergency Medicine Score, and Simplified Acute Physiology Score III in blunt trauma victims hospitalized in an intensive care unit and compare their performance.

METHOD

Retrospective cohort of patients with blunt trauma in an intensive care unit from medical records. Receiver Operating Characteristic and a 95% confidence interval of the area under the curve were analyzed to compare results.

RESULTS

Out of 165 analyzed patients, 66.7% have received surgical treatment. The mortality in the intensive care unit and in the hospital was 17.6% and 20.6%, respectively. For the mortality in the intensive care unit, the area under the curve varied from 0.672 to 0.738; however, better results have been observed in surgical patients (0.747 to 0.811). Similar results have been observed for in-hospital mortality. In all analyses, the areas under the curve of the indexes presented no significant difference.

CONCLUSION

The accuracy of the severity indexes was moderate, with an improved performance when applied to surgical patients. The four indexes presented a similar prediction for the analyzed outcomes.

Level of acuity, severity and intensity of care of adults and older adults admitted to the Intensive Care Unit

OBJECTIVE

To characterize the level of acuity, severity and intensity of care of adults and older adults admitted to Intensive Care Units and to identify the predictors of severity with their respective predictive capacity according to the age group.

METHOD

A retrospective cohort based on the analysis of medical records of individuals admitted to eight adult intensive care units in the city of São Paulo. The clinical characteristics at admission in relation to severity profile and intensity of care were analyzed through association and correlation tests. The predictors were identified by linear regression and the predictive capacity through the ROC curve.

RESULTS

Of the 781 cases (41.1% from older adults), 56.2% were males with a mean age of 54.1 ± 17.3 years. The burden of the disease, the organic dysfunction and the number of devices were the predictors associated with greater severity among adults and older adults, in which the organic dysfunction had the highest predictive capacity (80%) in both groups.

CONCLUSION

Adults and older adults presented a similar profile of severity and intensity of care in admission to the Intensive Care Unit. Organic dysfunction was the factor with the best ability to predict severity in adults and older adults.

Trends of loss of peripheral muscle thickness on ultrasonography and its relationship with outcomes among patients with sepsis

Background and aims

Data regarding trends of muscle loss on ultrasonography (USG) and its relationship with various outcomes among critically ill patients is limited. This study aimed to describe the trends of loss of muscle thickness of the arm and thigh (assessed using USG) and to determine the relationship between loss of muscle thickness and in-hospital and post-discharge outcomes.

Methods

Muscle thickness of 70 patients with sepsis was measured at the level of the mid-arm and mid-thigh using bedside USG on days 1, 3, 5, 7, 10 and 14 and then weekly till discharge or death. Patients were followed up for 90 days after discharge.

Results

The muscle thickness (mean ± SD) at the level of the mid-arm and mid-thigh on day 1 was 23.13 ± 4.83 mm and 31.21 ± 8.56 mm, respectively. The percentage muscle thickness [median (min, max)] decline at the mid-arm and mid-thigh was 7.61 (- 1.51, 32.05)% and 10.62 (- 1.48, 32.06)%, respectively on day 7 as compared to baseline (p < 0.001). The decline in muscle thickness at the mid-arm and mid-thigh were higher among non-survivors compared to survivors at all time points. Also, the decline in muscle thickness was significantly higher among patients with worse outcome at day 90. Patients with ICU-acquired weakness also had significantly higher decline in muscle thickness (p < 0.05). Early decline (from day 1 to day 3) in muscle thickness was associated with in-hospital mortality. The probability of death by day 14 was higher for patients who had early decline (from day 1 to day 3) in muscle thickness of ≥ 6.59% and ≥ 5.20% at the mid-arm [HR 7.3 (95% CI 1.5, 34.2)] and the mid-thigh [HR 8.1 (95% CI 1.7, 37.9)], respectively. Decline in thickness from day 1 to day 3 was a good predictor of in-hospital mortality with area under the curve (AUC) of 0.81 and 0.86 for arm and thigh muscles, respectively.

Conclusions

Critically ill patients with sepsis exhibit a gradual decline in muscle thickness of both the arm and thigh. Decline in muscle thickness was associated with in-hospital mortality. USG has a potential to identify patients at risk of worse in-hospital and post-discharge outcomes.

Performance of the Acute Physiology and Chronic Health Evaluation II (APACHE II) in the prediction of hospital mortality in a mixed ICU in Singapore

Background:

The Acute Physiology and Chronic Health Evaluation II (APACHE II) is used to quantify disease severity and hospital mortality risk in critically ill patients. It is widely used in intensive care units (ICUs) in Singapore, but its prognostic validity remains questionable as it has not been thoroughly assessed by established statistical methods.

Objectives:

This study aimed to: (a) evaluate the discrimination and calibration accuracy of the APACHE II in the prediction of hospital mortality in a mixed ICU, and (b) customise the APACHE II in an effort to maximise its prognostic performance.

Methods:

A prospective cohort study was conducted and all adult patients with >24 h of ICU admission in a tertiary care institution in Singapore were included. The outcome measure was hospital mortality, and all patients were followed-up until hospital discharge or death for up to one year after ICU admission.

Results:

There were 503 patients, and their mean (SD) age and APACHE II score were 61.2 (15.8) years and 24.5 (8.2), respectively. Hospital mortality was 31%, and no patients were lost to follow-up. The APACHE II has good discrimination (receiver operating characteristic: 0.76) but poor calibration (Hosmer–Lemeshow C test: <0.001). Customisation did not significantly improve calibration accuracy.

Conclusions:

The APACHE II and its customised version should not be used in the local setting as they both have poor calibration. There is an urgent need for larger studies to perform second-level customisation or to develop a new prognostic model tailored to the Singapore critical care setting.

Severity and workload related to adverse events in the ICU

Objective:

To analyze whether an increase in patient severity and nursing workload are correlated to a greater incidence of adverse events (AEs) in critical patients.

Method:

A prospective single cohort study was performed on a sample of 138 patients hospitalized in an intensive care unit (ICU).

Results:

A total of 166 AEs, occurred, affecting 50.7% of the patients. Increased patient severity presented a direct relationship to the probability of AEs occurring. However, nursing workload did not present a statistically significant relationship with the occurrence of AEs.

Conclusion:

The results cast light on the importance of using evaluation tools by the nursing personnel in order to optimize their daily activities and focus on patient safety.

Objetivo:

Analisar se o aumento da gravidade do paciente e a carga de trabalho de enfermagem está relacionado à maior incidência de Eventos Adversos (EAs) em pacientes críticos.

Método:

Estudo de coorte única, prospectivo, com amostra de 138 pacientes internados em uma Unidade de Terapia Intensiva (UTI).

Resultados:

Ao todo, foram evidenciados 166 EAs, que acometeram 50,7% dos pacientes. O aumento da gravidade do paciente apresentou relação direta com a chance de ocorrência de EAs. Entretanto, a carga de trabalho de enfermagem não apresentou relação estatisticamente significativa, na ocorrência de EAs.

Conclusão:

Os resultados permitem refletir acerca da importância da equipe de enfermagem, em utilizar instrumentos de avaliação, com o objetivo de melhorar e planejar suas ações diárias, com foco na segurança do paciente.

Predictors of death in an Intensive Care Unit: contribution to the palliative approach

OBJECTIVE

To identify predictors of death in the Intensive Care Unit and relate eligible patients to preferential palliative care.

METHOD

A prospective cohort study that evaluated patients hospitalized for more than 24 hours, subdivided into G1 (patients who died) and G2 (patients who were discharged from hospital). For identifying the predictors for death outcome, the intensivist physician was asked the "surprise question" and clinical-demographic data were collected from the patients. Data were analyzed by descriptive/inferential statistics (p<0.05 significance).

RESULTS

170 patients were evaluated. The negative response to the "surprise question" was related to death outcome. A greater possibility of death (p<0.05) was observed among older and more frail patients with less functionality, chronic cardiac and/or renal insufficiencies or acute non-traumatic neurological insult, with multiorgan failure for more than 5 days, and hospitalized for longer.

CONCLUSION

Predictors of death were related to a subjective evaluation by the physician, the clinical condition of the patient, underlying diseases, the severity of the acute disease and the evolution of the critical illness. It is suggested that patients with two or more predictive criteria receive preferential palliative care.

Effect of non-linearity of a predictor on the shape and magnitude of its receiver-operating-characteristic curve in predicting a binary outcome

Area under a receiver-operating-characteristic (AUROC) curve is widely used in medicine to summarize the ability of a continuous predictive marker to predict a binary outcome. This study illustrated how a U-shaped or inverted U-shaped continuous predictor would affect the shape and magnitude of its AUROC curve in predicting a binary outcome by comparing the ROC curves of the worst first 24-hour arterial pH values of 9549 consecutive critically ill patients in predicting hospital mortality before and after centering the predictor by its mean or median. A simulation dataset with an inverted U-shaped predictor was used to assess how this would affect the shape and magnitude of the AUROC curve. An asymmetrical U-shaped relationship between pH and hospital mortality, resulting in an inverse-sigmoidal ROC curve, was observed. The AUROC substantially increased after centering the predictor by its mean (0.611 vs 0.722, difference = 0.111, 95% confidence interval [CI] 0.087–0.135), and was further improved after centering by its median (0.611 vs 0.745, difference = 0.133, 95%CI 0.110–0.157). A sigmoidal-shaped ROC curve was observed for an inverted U-shaped predictor. In summary, a non-linear predictor can result in a biphasic-shaped ROC curve; and centering the predictor can reduce its bias towards null predictive ability.

The Ability of the Acute Physiology and Chronic Health Evaluation (APACHE) IV Score to Predict Mortality in a Single Tertiary Hospital

Background

The Acute Physiology and Chronic Health Evaluation (APACHE) II model has been widely used in Korea. However, there have been few studies on the APACHE IV model in Korean intensive care units (ICUs). The aim of this study was to compare the ability of APACHE IV and APACHE II in predicting hospital mortality, and to investigate the ability of APACHE IV as a critical care triage criterion.

Methods

The study was designed as a prospective cohort study. Measurements of discrimination and calibration were performed using the area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow goodness-of-fit test respectively. We also calculated the standardized mortality ratio (SMR).

Results

The APACHE IV score, the Charlson Comorbidity index (CCI) score, acute respiratory distress syndrome, and unplanned ICU admissions were independently associated with hospital mortality. The calibration, discrimination, and SMR of APACHE IV were good (H = 7.67, P = 0.465; C = 3.42, P = 0.905; AUROC = 0.759; SMR = 1.00). However, the explanatory power of an APACHE IV score >93 alone on hospital mortality was low at 44.1%. The explanatory power was increased to 53.8% when the hospital mortality was predicted using a model that considers APACHE IV >93 scores, medical admission, and risk factors for CCI >3 coincidentally. However, the discriminative ability of the prediction model was unsatisfactory (C index <0.70).

Conclusions

The APACHE IV presented good discrimination, calibration, and SMR for hospital mortality.

Combining quick Sequential Organ Failure Assessment with plasma lactate concentration is comparable to standard Sequential Organ Failure Assessment score in predicting mortality of patients with and without suspected infection

PURPOSE

We sought to determine whether quick Sequential Organ Failure Assessment (qSOFA) score can be used to predict mortality of patients without suspected infection.

MATERIALS AND METHODS

Using prospectively collected data within the first hour of intensive care unit admission, the predictive ability of qSOFA was compared with the Simplified Acute Physiology Score III, Admission Mortality Prediction Model III, Acute Physiology and Chronic Health Evaluation II model, and standard (full-version) SOFA score using area under the receiver operating characteristic (AUROC) curve and Brier score.

RESULTS

Of the 2322 patients included, 279 (12.0%) died after intensive care unit admission. The qSOFA score had a modest ability to predict mortality of all critically ill patients (AUROC, 0.672; 95% confidence interval [CI], 0.638-0.707; Brier score 0.099) including the noninfected patients (AUROC, 0.685; 95% CI, 0.637-0.732; Brier score 0.081). The overall predictive ability and calibration of the qSOFA was comparable to other prognostic scores. Combining qSOFA score with lactate concentrations further enhanced its predictive ability (AUROC, 0.730; 95% CI, 0.694-0.765; Brier score 0.097), comparable to the standard SOFA score.

CONCLUSIONS

The qSOFA score had a modest ability to predict mortality of both septic and nonseptic patients; combining qSOFA with plasma lactate had a predictive ability comparable to the standard SOFA score.

A comparison of prognostic significance of strong ion gap (SIG) with other acid-base markers in the critically ill: a cohort study

Background

This cohort study compared the prognostic significance of strong ion gap (SIG) with other acid-base markers in the critically ill.

Methods

The relationships between SIG, lactate, anion gap (AG), anion gap albumin-corrected (AG-corrected), base excess or strong ion difference-effective (SIDe), all obtained within the first hour of intensive care unit (ICU) admission, and the hospital mortality of 6878 patients were analysed. The prognostic significance of each acid-base marker, both alone and in combination with the Admission Mortality Prediction Model (MPM₀ III) predicted mortality, were assessed by the area under the receiver operating characteristic curve (AUROC).

Results

Of the 6878 patients included in the study, 924 patients (13.4 %) died after ICU admission. Except for plasma chloride concentrations, all acid-base markers were significantly different between the survivors and non-survivors. SIG (with lactate: AUROC 0.631, confidence interval [CI] 0.611–0.652; without lactate: AUROC 0.521, 95 % CI 0.500–0.542) only had a modest ability to predict hospital mortality, and this was no better than using lactate concentration alone (AUROC 0.701, 95 % 0.682–0.721). Adding AG-corrected or SIG to a combination of lactate and MPM₀ III predicted risks also did not substantially improve the latter’s ability to differentiate between survivors and non-survivors. Arterial lactate concentrations explained about 11 % of the variability in the observed mortality, and it was more important than SIG (0.6 %) and SIDe (0.9 %) in predicting hospital mortality after adjusting for MPM₀ III predicted risks. Lactate remained as the strongest predictor for mortality in a sensitivity multivariate analysis, allowing for non-linearity of all acid-base markers.

Conclusions

The prognostic significance of SIG was modest and inferior to arterial lactate concentration for the critically ill. Lactate concentration should always be considered regardless whether physiological, base excess or physical-chemical approach is used to interpret acid-base disturbances in critically ill patients.