Study of the role of different severity scores in respiratory ICU

SOFA and qSOFA usefulness for in-hospital death prediction of elderly patients admitted for suspected infection in internal medicine

PURPOSE

To reduce intensive care unit overcrowding and optimize resources, elderly patients affected by suspected infection with declining clinical conditions could be managed in internal medicine departments with stepdown beds. However, commonly used prognostic scores, as Sequential Organ Failure Assessment (SOFA) or quick SOFA (qSOFA) have never been studied in this specific setting. The aim of this study was to evaluate the role and the accuracy of SOFA and qSOFA as prognostic scores in a population of elderly patients with suspected infection admitted to stepdown beds of two internal medicine departments.

METHODS

Elderly patients admitted from the emergency department in the stepdown beds of two different internal medicine departments for suspected infection were assessed with SOFA and qSOFA scores at the admission. All patients were treated according to current guidelines. Age, sex, comorbidities, Charlson comorbidity index, SOFA and qSOFA were assessed. In-hospital death and length of hospital admission were also recorded.

RESULTS

390 subjects were enrolled. In-hospital death occurred in 144 (36.9%) patients; we observed that both SOFA (HR 1.189; 95% CI 1.128-1.253; p < 0.0001) and qSOFA (HR 1.803; 95% CI 1.503-2.164; p < 0.0001) scores were independently associated with an increased risk of in-hospital death. However, the accuracy of both SOFA (AUC: 0.686; 95% CI 0.637-0.732; p < 0.0001) and qSOFA (AUC: 0.680; 95% CI 0.641-0.735; p < 0.0001) in predicting in-hospital death was low in this population.

CONCLUSION

Elderly patients admitted to stepdown beds for suspected infection experience a high rate of in-hospital death; both SOFA and qSOFA scores can be useful to identify a group of patients who can benefit from admission to an intermediate care environment, however their accuracy is low.

Performance of critical care prognostic scoring systems in low and middle-income countries: a systematic review

Background

Prognostic models—used in critical care medicine for mortality predictions, for benchmarking and for illness stratification in clinical trials—have been validated predominantly in high-income countries. These results may not be reproducible in low or middle-income countries (LMICs), not only because of different case-mix characteristics but also because of missing predictor variables. The study objective was to systematically review literature on the use of critical care prognostic models in LMICs and assess their ability to discriminate between survivors and non-survivors at hospital discharge of those admitted to intensive care units (ICUs), their calibration, their accuracy, and the manner in which missing values were handled.

Methods

The PubMed database was searched in March 2017 to identify research articles reporting the use and performance of prognostic models in the evaluation of mortality in ICUs in LMICs. Studies carried out in ICUs in high-income countries or paediatric ICUs and studies that evaluated disease-specific scoring systems, were limited to a specific disease or single prognostic factor, were published only as abstracts, editorials, letters and systematic and narrative reviews or were not in English were excluded.

Results

Of the 2233 studies retrieved, 473 were searched and 50 articles reporting 119 models were included. Five articles described the development and evaluation of new models, whereas 114 articles externally validated Acute Physiology and Chronic Health Evaluation, the Simplified Acute Physiology Score and Mortality Probability Models or versions thereof. Missing values were only described in 34% of studies; exclusion and or imputation by normal values were used. Discrimination, calibration and accuracy were reported in 94.0%, 72.4% and 25% respectively. Good discrimination and calibration were reported in 88.9% and 58.3% respectively. However, only 10 evaluations that reported excellent discrimination also reported good calibration. Generalisability of the findings was limited by variability of inclusion and exclusion criteria, unavailability of post-ICU outcomes and missing value handling.

Conclusions

Robust interpretations regarding the applicability of prognostic models are currently hampered by poor adherence to reporting guidelines, especially when reporting missing value handling. Performance of mortality risk prediction models in LMIC ICUs is at best moderate, especially with limitations in calibration. This necessitates continued efforts to develop and validate LMIC models with readily available prognostic variables, perhaps aided by medical registries.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-017-1930-8) contains supplementary material, which is available to authorized users.