Efficacy of the APACHE II Score at ICU Discharge in Predicting Post-ICU Mortality and ICU Readmission in Critically Ill Surgical Patients

Lee, Hannah; Lim, Cheong; Hong, Hyunsook; Ju, Jae-Woo; Jeon, Young Tae; Hwang, Jung‐Won; Park, Hee Pyoung

doi:10.1177/0310057x1504300206

Cited by 91 publications

(82 citation statements)

References 26 publications

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“…Several pediatric intensive care units (PICU) have adopted the Pediatric Risk of Mortality (PRISM), [9,10] Pediatric Index of Mortality (PIM), [11,12] or Acute Physiology and Chronic Health Evaluation II score (APACHE II) [13] to assess the severity of sepsis in pediatric patients. However, these indices involve multiple systematic parameters and complex computation; this might not be ideal for the clinical use in pediatric sepsis patients, as their care typically requires quick clinical judgment.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a mortality risk model for pediatric sepsis

Chen

et al. 2017

Medicine

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Pediatric sepsis is a burdensome public health problem. Assessing the mortality risk of pediatric sepsis patients, offering effective treatment guidance, and improving prognosis to reduce mortality rates, are crucial.We extracted data derived from electronic medical records of pediatric sepsis patients that were collected during the first 24 hours after admission to the pediatric intensive care unit (PICU) of the Hunan Children's hospital from January 2012 to June 2014. A total of 788 children were randomly divided into a training (592, 75%) and validation group (196, 25%). The risk factors for mortality among these patients were identified by conducting multivariate logistic regression in the training group. Based on the established logistic regression equation, the logit probabilities for all patients (in both groups) were calculated to verify the model's internal and external validities.According to the training group, 6 variables (brain natriuretic peptide, albumin, total bilirubin, D-dimer, lactate levels, and mechanical ventilation in 24 hours) were included in the final logistic regression model. The areas under the curves of the model were 0.854 (0.826, 0.881) and 0.844 (0.816, 0.873) in the training and validation groups, respectively.The Mortality Risk Model for Pediatric Sepsis we established in this study showed acceptable accuracy to predict the mortality risk in pediatric sepsis patients.

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Section: Introductionmentioning

confidence: 99%

Development and validation of a mortality risk model for pediatric sepsis

Chen

et al. 2017

Medicine

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“…In a study by Angus et al (19), the APACHE II score was also predictive of 1-year mortality (AUC of 0.671) in patients undergoing liver transplants. In contrast, a study by Lee et al reported no relation between the scores calculated on admission and post-discharge mortality (40). Lower diagnostic accuracy in predicting long-term mortality could be due to various reasons.…”

Section: Discussionmentioning

confidence: 87%

“…The treatment implemented during ICU stay, eventual complications and the quality of the follow-up care and rehabilitation, in uence the patient's outcome and can change the results provided by the scoring systems. Lee et al found that the discharge APACHE II score was a good predictor of post-ICU mortality and readmission (40). Therefore, it would be more reasonable to focus on the scores calculated to estimate the long-term prediction of the patients on their discharge from the ICU.…”

Section: Discussionmentioning

confidence: 99%

Validation of APACHE II, APACHE III and SAPS II scores in short- and long-term mortality prediction in a mixed intensive care unit in Poland: a cohort study

Czajka

Ziębińska

Marczenko

et al. 2020

Preprint

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Background. There are several scores used for in-hospital mortality prediction in critical illness. Their application in a local scenario requires validation to ensure appropriate diagnostic accuracy. Moreover, their use in assessing post-discharge mortality in intensive care unit (ICU) survivors has not been extensively studied. We aimed to validate APACHE II, APACHE III and SAPS II scores in short- and long-term mortality prediction in a mixed adult ICU in Poland. APACHE II, APACHE III and SAPS II scores, with corresponding predicted mortality ratios, were calculated for 303 consecutive patients admitted to a 10-bed ICU in 2016. Short-term (in-hospital) and long-term (12-month post-discharge) mortality was assessed.Results. Median APACHE II, APACHE III and SAPS II scores were 19 (IQR 12-24), 67 (36.5-88) and 44 (27-56) points, with corresponding in-hospital mortality ratios of 25.8% (IQR 12.1-46.0), 18.5% (IQR 3.8-41.8) and 34.8% (IQR 7.9-59.8). Observed in-hospital mortality was 35.6%. Moreover, 12-month post-discharge mortality reached 17.4%. All the scores predicted in-hospital mortality (p<0.05): APACHE II (AUC=0.78; 95%CI 0.73-0.83), APACHE III (AUC=0.79; 95%CI 0.74-0.84) and SAPS II (AUC=0.79; 95%CI 0.74-0.84); as well as mortality after hospital discharge (p<0.05): APACHE II (AUC=0.71; 95%CI 0.64-0.78), APACHE III (AUC=0.72; 95%CI 0.65-0.78) and SAPS II (AUC=0.69; 95%CI 0.62-0.76), with no statistically significant difference between the scores (p>0.05). The calibration of the scores was good.Conclusions. All the scores are acceptable predictors of in-hospital mortality. In the case of post-discharge mortality, their diagnostic accuracy is lower and of borderline clinical relevance. Further studies are needed to create scores estimating the long-term prognosis of subjects successfully discharged from the ICU.

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“…Readmission to ICU is associated with higher mortality risk than the initial admission (35). Considering the funding for ICU services which consumes substantial amount of health resources, a decrease in the readmission to ICU rates can be used as a hospital performance indicator (36)(37)(38). The first step of reducing the rates of readmission to ICU process is to anticipate the patients who would be readmitted to ICU priorly and improve general wards healthcare quality (39-41).…”

Section: Resultsmentioning

confidence: 99%

Evaluation of Readmitted Patients After Intensive Care Unit Discharge (Retrospective Study)

Çayören¹,

Müslümanoğlu²,

Sevdi³

et al. 2019

BMB

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Nearly %10 of the discharged patients are readmitted to intensive care unit (ICU) at the same hospital stay. Reduction of readmission rates could be used as a hospital performance indicator. Our aim is to analyse the reasons and results of readmissions of patients who were discharged to a general ward from ICU in a two-year period. Method: Readmissions of the patients who had been treated in our ICU between the dates of 01.01.2015-31.12.2016 were analysed retrospectively. Demographic characteristics of patients, readmission rates, initial admission indications and comorbidities, distribution of readmission indications, timing of readmission after discharge, distribution of patients in terms of mechanical ventilation need, discharge time of readmitted patients at initial admission to ICU after weaning, readmission mortality rates, Glasgow Coma Scale (GCS), APACHE-II and SOFA scores of patients at initial admission and readmission were analysed and compared. Results: 59 patients (3.55%) are readmitted to ICU after discharge at the same hospital stay. When examining the departments where the readmitted patients came from, it is seen that 19 patients (32.2%) were readmitted to ICU from department of general surgery. 22 of readmissions (37.29%) occurred within first 48 hours after discharge. The most common reasons of readmissions are for postoperative monitoring after revisional surgery (44.07%) and acute respiratory failure (40.68%). Conclusion: The patients who are discharged from ICU are at a high risk of being readmitted to ICU (35). Readmission to ICU is associated with higher mortality risk than the initial admission. The first step of reducing Amaç: Taburcu edilen hastaların yaklaşık %10' u yatış süresi içerisinde yeniden yoğun bakım ünitesine (YBÜ) gitmektedir. YBÜ'ye yeniden yatış oranlarındaki azalma, hastane performansında bir kalite göstergesidir. Bu çalışmadaki amacımız, YBÜ'den hastane içine, iki yıllık süre içerisinde taburcu edilen hastaların yeniden yatışlarının nedenlerini ve sonuçlarını analiz etmektir. Yöntem: 01.01.2015-31.12.2016 tarihleri arasında hastanemiz YBÜ'de tedavi edilen hastaların tekrar yatışları geriye dönük olarak incelendi. Hastaların demografik özellikleri, tekrar yatış oranları, hastaların ilk yatış endikasyonları ve yandaş hastalıkları, tekrar yatışların endikasyonlarına göre dağılımı, tekrar yatışın taburculuk sonrası ne zaman gerçekleştiği, mekanik ventilasyon ihtiyacına göre hastaların dağılımı, tekrar yatışı olan hastaların birinci kabullerinde weaning sonrası taburcu olma zamanı, tekrar yatışlardaki mortalite oranları, hastaların YBÜ'ye ilk ve tekrar yatışındaki Glasgow Koma Skalası (GCS), APACHE-II ve SOFA skorları incelenerek kıyaslandı. Bulgular: YBÜ'den taburcu edilen ve hastaneden taburcu olmadan tekrar yatışı yapılan hasta sayısı 59 olarak bulundu (%3,55). Hastaların tekrar geldikleri bölümler incelendiğinde en fazla 19 (%32,2) hasta Genel Cerrahi Kliniği'ndendi. Tekrar kabul edilen hastaların 22'si (%37,29) taburcu edildikten sonraki ilk 48 saat içinde gerçekleşti. T...

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Efficacy of the APACHE II Score at ICU Discharge in Predicting Post-ICU Mortality and ICU Readmission in Critically Ill Surgical Patients

Cited by 91 publications

References 26 publications

Development and validation of a mortality risk model for pediatric sepsis

Development and validation of a mortality risk model for pediatric sepsis

Validation of APACHE II, APACHE III and SAPS II scores in short- and long-term mortality prediction in a mixed intensive care unit in Poland: a cohort study

Evaluation of Readmitted Patients After Intensive Care Unit Discharge (Retrospective Study)

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