Performance assessment of Acute Physiology and Chronic Health Evaluation II and Simplified Acute Physiology Score II in a referral respiratory intensive care unit in Iran

Developing Iranian sub-national Primary Health Care Measurement Framework: a study protocol

BACKGROUND

Developing an effective system for measurement and improvement of primary health care (PHC) based on the conditions and characteristics of the countries' health systems is one of the World Health Organization (WHO) recommendations.

AIMS

This study will aim to develop a framework to assess the Iranian sub-national PHC system performance using the WHO measurement framework for PHC.

METHODS/DESIGNS

This is a mix-method study with a triangulation design. The Iranian sub-national PHC Measurement Framework (PHCMF) will be developed through a review of the WHO's PHC measurement conceptual framework (for selecting key performance indicators (KPIs)), literature review (academic database), PHC-related national documents, consultations with national experts, and the Delphi technique for finalizing the framework. The required data for calculating selected KPIs is expected to encompass qualitative and quantitative data. Discussion: Iranian PHC system performance is not measured based on the holistic and scientific framework and international standards. The information obtained from this project will guide managers and policymakers to be aware of the current situation and the success rate of the PHC system in achieving the desired goals, as well as identify strengths and weaknesses of the PHC system and provide the solution to better policy formulation.

Acute Physiology and Chronic Health Evaluation II score for the assessment of mortality prediction in the intensive care unit: a single-centre study from Iran

BACKGROUND

The Acute Physiology and Chronic Health Evaluation (APACHE) II is still commonly used as an index of illness severity in patients admitted to intensive care unit (ICU) and has been validated for many research and clinical audit purposes.

AIMS AND OBJECTIVES

To investigate the diagnostic value of the APACHE II score for predicting mortality rate of critically ill patients.

DESIGN

This was a single-centre, retrospective study of 200 Iranian patients admitted in the medical-surgical adult ICU from June 2012 to May 2013.

METHODS

Demographic data, pre-existing comorbidities and variables required for calculating the APACHE II score were recorded. Receiver operating characteristic (ROC) curves were constructed, and the area under the ROC curves was calculated to assess the predictive value of the APACHE II score.

RESULTS

Of the 200 patients with a mean age of 55·27 ± 21·59 years enrolled in the study, 112 (54%) were admitted in the medical ICU and 88 (46%) in the surgical ICU. Finally, 116 patients (58%) died, and 84 patients (42%) survived. The overall actual and predicted ICU mortality were 58% and 25·16%, respectively. The mean APACHE II score was 16·31 in total patients, 17·78 in medical ICU and 14·45 in surgical ICU patients (P = 0·003). Overall, the APACHE II score had the highest prognostic value for predicting the mortality rate of critically ill patients with an area under the cure of 0·88, and with a cut-off value of 15, the APACHE II score predicted mortality of patients with a sensitivity of 85·3%, a specificity of 77·4%, a positive predictive value of 83·9% and a negative predictive value of 73·9%.

CONCLUSION

This study shows that an APACHE II score of 15 provides the best diagnostic accuracy to predict mortality of critically ill patients. Our observed mortality rate was greater than the predicted death rate, in comparison to the other prestigious centres in the world. Therefore, it appears that we must improve our intensive care to reduce mortality.

RELEVANCE TO CLINICAL PRACTICE

There is a need to create a suitable scoring system to predict the mortality rate of critically ill patients in accordance with the advanced technological equipment and experienced physicians and nurses in that ICU.

ACUTE PHYSIOLOGY AND CHRONIC HEALTH EVALUATION (APACHE) II SCORE - THE CLINICAL PREDICTOR IN NEUROSURGICAL INTENSIVE CARE UNIT

The APACHE II scoring system is approved for its benchmarking and mortality predictions, but there are only a few articles published to demonstrate it in neurosurgical patients. Therefore, this study was performed to acknowledge this score and its predictive performance to hospital mortality in a tertiary referral neurosurgical intensive care unit (ICU). All patients admitted to the Neurosurgical ICU from February 1 to July 31, 2011 were recruited. The parameters indicated in APACHE II score were collected. The adjusted predicted risk of death was calculated and compared with the death rate observed. Descriptive statistics including the receiver operating characteristic curve (ROC) was performed. The results showed that 276 patients were admitted during the mentioned period. The APACHE II score was 16.56 (95% CI, 15.84-17.29) and 19.08 (95% CI, 15.40-22.76) in survivors and non-survivors, while the adjusted predicted death rates were 13.39% (95% CI, 11.83-14.95) and 17.49% (95% CI, 9.81-25.17), respectively. The observed mortality was only 4.35%. The area under the ROC of APACHE II score to the hospital mortality was 0.62 (95% CI, 0.44-0.79). In conclusion, not only the APACHE II score in neurosurgical patients indicated low severity, but its performance to predict hospital mortality was also inferior. Additional studies of predicting mortality among these critical patients should be undertaken.

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.

APACHE II score cannot predict successful weaning from prolonged mechanical ventilation

At least 5% of all intensive care unit patients require prolonged respiratory support. Multiple factors have been suggested as possible predictors of successful respiratory weaning so far. We sought to verify whether the Acute Physiology and Chronic Health Evaluation II (APACHE II) can predict freedom from prolonged mechanical ventilation (PMV) in patients treated in a regional weaning centre. The study group comprised 130 consecutive patients (age; median (interquartile range): 71 (62–77) years), hospitalized between 1 January 2012, and 31 December 2013. APACHE II score was assessed based on the worst values taken during the first 24 hours after admission. Glasgow coma scale was excluded from calculations due to the likely influence of sedative agents. The outcome was defined as freedom from mechanical ventilation, with or without tracheostomy on discharge. Among survivors (n = 115), 88.2% were successfully liberated from mechanical ventilation and 60.9% from tracheostomy. APACHE II failed to predict freedom from mechanical ventilation (area under the receiver–operating characteristic curve [AUROC] = 0.534; 95% confidence interval [CI]: 0.439–0.628; p = 0.65) and tracheostomy tube removal (AUROC = 0.527; 95% CI: 0.431–0.621; p = 0.63). Weaning outcome was unrelated to the aetiology of respiratory failure on admission (p = 0.41). APACHE II cannot predict weaning outcome in patients requiring PMV.

Determination of Factors Affecting Mortality of Patients with Sepsis in a Tertiary Intensive Care Unit

OBJECTIVES

Sepsis is a disease with high mortality that is frequently observed in intensive care units. This study aimed to determine the risk factors affecting mortality of patients with sepsis who were followed up in the intensive care unit (ICU). We aimed to contribute to literature by evaluating the relationship between mortality and pro-brain natriuretic peptide (pro-BNP9), C-reactive protein (CRP), thrombocyte count, Acute Physiology and Chronic Health Evaluation (APACHE) II score, Sequential Organ Failure Assessment (SOFA) score, duration of hospitalization in the intensive care unit, and the presence of multidrug-resistant microorganism.

MATERIAL AND METHODS

Patients hospitalized in ICU because of the diagnosis of sepsis and septic shock between December 2010 and June 2012 were included in this retrospective study.

RESULTS

A total of 141 patients, including 74 male (52.5%) and 67 female (47.5%) patients, were involved in the study, and the median age was 66.8±17.9 years. Sixty-nine patients (48.9%) were discharged from the ICU; however, 72 patients (51.1%) were exitus. Multidrug-resistant microorganism was detected in 34 patients (24.1%). The patients' median SOFA score was 9.16±3.16, median APACHE-II score was 24.9±7.83, and median duration of hospitalization in the ICU was 8.44±11.61 days. It was found that mortality rate significantly increased in patients with the APACHE-II score of 24.5 and over, SOFA score of 8.5 and over, pro BNP value of 7241 ng/L and over, and CRP value of 96.5 mg/dL and over. Mortality rate was detected to be higher in patients undergoing invasive mechanical ventilation than in patients undergoing non-invasive mechanical ventilation. When thrombocyte count and mortality were associated with each other, it was found that the median value was 86000 mg/dL in exitus patients, whereas it was 185000 mg/dL in patients discharged from the ICU.

CONCLUSION

It was revealed that increased APACHE-II score, increased SOFA score, increased pro BNP score, increased CRP, the presence of multidrug-resistant microorganism, and decreased thrombocyte count elevated the rate of mortality. However, no relationship was observed between the duration of hospitalization in the ICU and mortality.