Performance of Simplified Acute Physiology Score 3 In Predicting Hospital Mortality In Emergency Intensive Care Unit

A simple mortality prediction model for sepsis patients in intensive care

Background

Sepsis is common in the intensive care unit (ICU). Two of the ICU's most widely used mortality prediction models are the Simplified Acute Physiology Score 3 (SAPS-3) and the Sequential Organ Failure Assessment (SOFA) score. We aimed to assess the mortality prediction performance of SAPS-3 and SOFA upon ICU admission for sepsis and find a simpler mortality prediction model for these patients to be used in clinical practice and when conducting studies.

Methods

A retrospective study of adult patients fulfilling the Sepsis-3 criteria admitted to four general ICUs was performed. A simple prognostic model was created using backward stepwise multivariate logistic regression. The area under the curve (AUC) of SAPS-3, SOFA and the simple model was assessed.

Results

One thousand nine hundred eighty four admissions were included. A simple six-parameter model consisting of age, immunosuppression, Glasgow Coma Scale, body temperature, C-reactive protein and bilirubin had an AUC of 0.72 (95% confidence interval (CI) 0.69-0.75) for 30-day mortality, which was non-inferior to SAPS-3 (AUC 0.75, 95% CI 0.72-0.77) (p = 0.071). SOFA had an AUC of 0.67 (95% CI 0.64-0.70) and was inferior to SAPS-3 (p < 0.001) and our simple model (p = 0.0019).

Conclusion

SAPS-3 has a lower prognostic value in sepsis than in the general ICU population. SOFA performs less well than SAPS-3. Our simple six-parameter model predicts mortality just as well as SAPS-3 upon ICU admission for sepsis, allowing the design of simple studies and performance monitoring.

Association of thyroid hormones and thyroid-stimulating hormone with mortality in adults admitted to the intensive care unit: A systematic review and meta-analysis

BACKGROUND

Thyroid hormones (THs) and thyroid-stimulating hormone (TSH) seem to show high potential in predicting the clinical death outcome of patients admitted to the intensive care unit (ICU). However, diverse studies on this topic are conflicting.

METHODS

A search was conducted by two investigators involved in this research in the PubMed, Embase, and Cochrane databases (all last launched on July 12, 2021). The quality of the included studies was evaluated using the Newcastle-Ottawa Quality Assessment Scale (NOS). Subgroup analyses were performed to determine the sources of heterogeneity. Sensitivity and publication bias analyses were also assessed.

RESULTS

A total of 27 studies (4970 participants) were included based on the eligibility criteria. Compared with survivors, nonsurvivors were found to have lower levels of THs (T3, T4, fT3, and fT4), whereas no significant difference was found in TSH levels (13 studies for T3: standardized mean differences [SMD], -0.78; 95% CI, -1.36 to -0.20; I2 = 96%; p = 0.008; 11 studies for T4: SMD = -0.79; 95% CI, -1.31 to -0.28; I2 =95%; p = 0.0002; 14 studies for fT3: SMD = -0.76; 95% CI, -1.21 to -0.32; I2 = 95%; p = 0.0008; 17 studies for fT4: SMD = -0.60; 95% CI, -0.99 to -0.22; I2 = 95%; p = 0.002; 20 studies for TSH: SMD = 0.00; 93% CI, -0.29 to 0.29; I2 = 93%; p = 0.98).

CONCLUSION

Nonsurvivors were associated with lower levels of THs (T3, T4, fT3, and fT4) than survivors. THs show great application potential in predicting ICU patients' death outcomes and improving already widely used prognostic scores in the ICU (ie, Acute Physiological and Chronic Health Evaluation [APACHE] II and Therapeutic Intervention Scoring System).

Equine simplified acute physiology score: Personalised medicine for the equine emergency patient

BACKGROUND

Scoring models are useful tools that guide the attending clinician in gauging the severity of disease evolution and in evaluating the efficacy of treatment. There are few tools available with this purpose for the non-human patient, including horses. We aimed (i) to adapt the simplified acute physiology score 3 (SAPS-3) model for the equine species, reaching a margin of accuracy greater than 75% in the calculation of the probability of survival/death and (ii) to build a decision tree that helps the attending veterinarian in assessment of the clinical evolution of the equine patient.

METHODS

From an initial pool of 5568 medical records from University-based Veterinary Hospitals, a final cohort of 1000 was further mined manually for data extraction. A set of 19 variables were evaluated and tested by five machine learning data mining algorithms.

RESULTS

The final scoring model, named EqSAPS for equine simplified acute physiology score, reached 91.83% of correct estimates (post hoc) for probability of death within 24 hours upon hospitalization. The area under receiver operating characteristic curve for outcome 'death' was 0.742, while for 'survival' was 0.652. The final decision tree was able to refine prognosis of patients whose EqSAPS score suggested 'death'.

CONCLUSION

EqSAPS is a useful tool to gauge the severity of the clinical presentation of the equine patient.

Predictive value of serum albumin levels on noradrenaline and fluid requirements in the first 24 h after admission to the Intensive Care Unit - A prospective observational study

PURPOSE

To determine the predictive value of serum albumin (SA) at admission to the intensive care unit (ICU) on the cumulative dose of noradrenaline, the fluids administered, the lactate level, and mortality during the first 24 h of ICU admission.

METHODS

A total of 100 ICU patients were included. The association between SA and the cumulative dose of noradrenaline was analyzed using logistic regression. For the total amount of fluids administered linear regression, for the lactate level and for 24 h mortality logistic regression was used. Age, gender, patient category, type of surgery, severe sepsis, lactate level, estimated glomerular filtration rate, c-reactive protein level, and the target mean arterial pressure were considered effect modifiers.

RESULTS

SA was significantly associated with the dose of noradrenaline (OR 0.92, 95% CI 0.84–0.99, p = 0.028), lower lactate levels (OR 1.14, 95% CI 1.00–1.30, p = 0.049), and with the amount of fluids administered (B -0.02, 95% CI −0.03/−0.00, p = 0.016), but not with mortality (OR 0.95, 95% CI 0.85–1.07, p = 0.41).

CONCLUSIONS

SA significantly predicts noradrenaline and fluid requirements as well as the change in lactate level during the first 24 h of ICU admission. Our observations have to be validated in another large cohort.