Mortality Prediction Using SOFA Score in Critically Ill Surgical and Non-Surgical Patients: Which Parameter Is the Most Valuable?

Analyzing how the components of the SOFA score change over time in their contribution to mortality

OBJECTIVE

Determine how each organ component of the SOFA score differs in its contribution to mortality risk and how that contribution may change over time.

METHODS

We performed multivariate logistic regression analysis to assess the contribution of each organ component to mortality risk on Days 1 and 7 of an intensive care unit stay. We used data from two publicly available datasets, eICU Collaborative Research Database (eICU-CRD) (208 hospitals) and Medical Information Mart for Intensive Care IV (MIMIC-IV) (1 hospital). The odds ratio of each SOFA component that contributed to mortality was calculated. Mortality was defined as death either in the intensive care unit or within 72 hours of discharge from the intensive care unit.

RESULTS

A total of 7,871 intensive care unit stays from eICU-CRD and 4,926 intensive care unit stays from MIMIC-IV were included. Liver dysfunction was most predictive of mortality on Day 1 in both cohorts (OR 1.3; 95%CI 1.2 - 1.4; OR 1.3; 95%CI 1.2 - 1.4, respectively). In the eICU-CRD cohort, central nervous system dysfunction was most predictive of mortality on Day 7 (OR 1.4; 95%CI 1.4 - 1.5). In the MIMIC-IV cohort, respiratory dysfunction (OR 1.4; 95%CI 1.3 - 1.5) and cardiovascular dysfunction (OR 1.4; 95%CI 1.3 - 1.5) were most predictive of mortality on Day 7.

CONCLUSION

The SOFA score may be an oversimplification of how dysfunction of different organ systems contributes to mortality over time. Further research at a more granular timescale is needed to explore how the SOFA score can evolve and be ameliorated.

Outcomes of High-Dose Versus Low-Dose Vitamin D on Prognosis of Sepsis Requiring Mechanical Ventilation: A Randomized Controlled Trial

Background: Critically ill patients with sepsis have a high incidence of vitamin D deficiency. Vitamin D promotes the synthesis of human cathelicidin antimicrobial peptide, a precursor of LL-37, which is a part of the innate immune system. This study investigated the effectiveness and safety of the early administration of high-dose enteral vitamin D3 in comparison with low-dose vitamin D3 in patients with sepsis requiring mechanical ventilation (MV). Methods: Eighty adult patients with sepsis requiring MV with known vitamin D deficiency were randomly assigned to receive either an enteral 50 000 IU (Group I) or 5000 IU (Group II) vitamin D supplementation. Clinical and laboratory parameters were evaluated at baseline and on days 4 and 7 between the study groups. The change in serum procalcitonin (PCT) levels on day 7 was the primary outcome, while the change in serum LL-37 levels on day 7, changes in sequential organ failure assessment (SOFA) score, and clinical pulmonary infection score on day 7, MV duration, and hospital length of stay (LOS) were the secondary outcomes. Results: The (day 7-day 0) change in serum PCT and LL-37 levels and SOFA score were significantly different in Group I (P = .010, P < .001, and P < .001, respectively). The SOFA score was significantly different on days 4 and 7 in Group I (P < .001 and P < .001, respectively). The incidence of early ventilator-associated pneumonia was significantly different between both treatment groups (P = .025). The hospital LOS was shorter in Group I (P < .001). No 25-hydroxyvitamin-D toxicity was observed in either group. Conclusions: Early enteral administration of high-dose vitamin D3 in critically ill patients with sepsis requiring MV along with standard treatment for sepsis decreased serum procalcitonin levels, increased serum LL-37 levels, and ameliorated illness severity scores.

Development of a Simple Scoring System for Predicting Discharge Safety from the Medical ICU to Low-Acuity Wards: The Role of the Sequential Organ Failure Assessment Score, Albumin, and Red Blood Cell Distribution Width

Despite advancements in artificial intelligence-based decision-making, transitioning patients from intensive care units (ICUs) to low-acuity wards is challenging, especially in resource-limited settings. This study aimed to develop a simple scoring system to predict ICU discharge safety. We retrospectively analyzed patients admitted to a tertiary hospital's medical ICU (MICU) between July 2016 and December 2021. This period was divided into two phases for model development and validation. We identified risk factors associated with unexpected death within 14 days of MICU discharge and developed a predictive scoring system that incorporated these factors. We verified the system's performance using validation data. In the development cohort, 522 patients were discharged from the MICU, and 42 (8.04%) died unexpectedly. In multivariate analysis, the Sequential Organ Failure Assessment (SOFA) score (odds ratio [OR] 1.26, 95% confidence interval [CI] 1.13-1.41), red blood cell distribution width (RDW) (OR 1.20, 95% CI 1.07-1.36), and albumin (OR 0.37, 95% CI 0.16-0.84) were predictors of unexpected death. Each variable was assigned a weighted point in the scoring system, and the area under the curve (AUC) was 0.788 (95% CI 0.714-0.855). The scoring system was performed using an AUC of 0.738 (95% CI 0.653-0.822) in the validation cohort of 343 patients with 9.62% of unexpected deaths. When a cut-off of 0.032 was applied, a sensitivity and a specificity of 81.8% and 55.2%, respectively, were achieved. This simple bedside predictive score for ICU discharge uses the SOFA score, albumin level, and RDW to aid in timely decision-making and optimize critical care facility allocation in resource-limited settings.

Investigating the Utility of the SOFA Score and Creating a Modified SOFA Score for Predicting Mortality in the Intensive Care Units in a Tertiary Hospital in Jordan

Background

The utility of the Sequential Organ Failure Assessment (SOFA) score in predicting mortality in the intensive care unit (ICU) has been demonstrated before, but serial testing in various settings is required to validate and improve the score. This study examined the utility of the SOFA score in predicting mortality in Jordanian ICU patients and aimed to find a modified score that required fewer laboratory tests.

Methods

A prospective observational study was conducted at Jordan University Hospital (JUH). All adult patients admitted to JUH ICUs between June and December 2020 were included in the study. SOFA scores were measured daily during the whole ICU stay. A modified SOFA score (mSOFA) was constructed from the available laboratory, clinical, and demographic data. The performance of the SOFA, mSOFA, qSOFA, and SIRS in predicting ICU mortality was assessed using the area under the receiver operating characteristic curve (AUROC).

Results

194 patients were followed up. SOFA score (mean ± SD) at admission was significantly higher in non-survivors (7.5 ± 3.9) compared to survivors (2.4 ± 2.2) and performed the best in predicting ICU mortality (AUROC = 0.8756, 95% CI: 0.8117-0.9395) compared to qSOFA (AUROC = 0.746, 95% CI: 0.655-0.836) and SIRS (AUROC = 0.533, 95% CI: 0.425-0.641). The constructed mSOFA included points for the hepatic and CNS SOFA scores, in addition to one point each for the presence of chronic kidney disease or the use of breathing support; it performed as well as the SOFA score in this cohort or better than the SOFA score in a subgroup of patients with heart disease.

Conclusion

SOFA score was a good predictor of mortality in a Jordanian ICU population and better than qSOFA, while SIRS could not predict mortality. Furthermore, the proposed mSOFA score which employed fewer laboratory tests could be used after validation from larger studies.

Comparison of nasotracheal versus orotracheal intubation for sedation, assisted spontaneous breathing, mobilization, and outcome in critically ill patients: an exploratory retrospective analysis

Nasotracheal intubation (NTI) may be used for long term ventilation in critically ill patients. Although tracheostomy is often favored, NTI may exhibit potential benefits. Compared to orotracheal intubation (OTI), patients receiving NTI may require less sedation and thus be more alert and with less episodes of depression of respiratory drive. We aimed to study the association of NTI versus OTI with sedation, assisted breathing, mobilization, and outcome in an exploratory analysis. Retrospective data on patients intubated in the intensive care unit (ICU) and ventilated for > 48 h were retrieved from electronic records for up to ten days after intubation. Outcome measures were a Richmond Agitation and Sedation Scale (RASS) of 0 or - 1, sedatives, vasopressors, assisted breathing, mobilization on the ICU mobility scale (ICU-MS), and outcome. From January 2018 to December 2020, 988 patients received OTI and 221 NTI. On day 1-3, a RASS of 0 or - 1 was attained in OTI for 4.0 ± 6.1 h/d versus 9.4 ± 8.4 h/d in NTI, p < 0.001. Propofol, sufentanil, and norepinephrine were required less frequently in NTI and doses were lower. The NTI group showed a higher proportion of spontaneous breathing from day 1 to 7 (day 1-6: p < 0.001, day 7: p = 0.002). ICU-MS scores were higher in the NTI group (d1-d9: p < 0.001, d10: p = 0.012). OTI was an independent predictor for mortality (odds ratio 1.602, 95% confidence interval 1.132-2.268, p = 0.008). No difference in the rate of tracheostomy was found. NTI was associated with less sedation, more spontaneous breathing, and a higher degree of mobilization during physiotherapy. OTI was identified as an independent predictor for mortality. Due to these findings a new prospective evaluation of NTI versus OTI should be conducted to study risks and benefits in current critical care medicine.

Utility of the Modified Nutritional Risk in the Critically ill Score as an Outcome Predictor in All-Cause Acute Respiratory Distress Syndrome and Acute Febrile Illness-Induced Acute Respiratory Distress Syndrome

Introduction

Nutritional risk in the Critically Ill (NUTRIC) score is a predictor of adverse outcomes in the critically ill, and its utility in a specific population of critically ill has been recommended. We aimed to study the utility of modified NUTRIC (mNUTRIC) score as a mortality predictor in acute febrile illness (AFI)-induced acute respiratory distress syndrome (ARDS) and all-cause ARDS patients.

Methods

We recorded data from two prospective observational ARDS studies conducted at a single-center tertiary care hospital to evaluate the utility of the mNUTRIC score as an independent mortality predictor in all-cause ARDS and AFI-ARDS. A total of 216 all-cause ARDS patients were included, of which 73 were AFI-ARDS and 143 were non-AFI ARDS.

Results

Mortality of AFI-ARDS was 16/73 (21.9%) compared to 62/143 (43.35%) in non-AFI ARDS (P = 0.002). There were no significant differences in severity of ARDS in AFI-ARDS and non-AFI ARDS groups (P = 0.504). The mNUTRIC score was found to be an independent predictor of mortality in all-cause ARDS patients (n = 216) and AFI-ARDS patients (n = 73) after Cox regression multivariable analysis. In all-cause ARDS, the mNUTRIC score had an area under the curve (AUC) of 0.778, cutoff ≥4, 82.1% sensitivity, and 65.9% specificity as a predictor of mortality. In AFI-ARDS, the mNUTRIC score had an AUC of 0.769, cutoff ≥4, 81.3% sensitivity, 66.67% specificity, and P = 0.001 as a predictor of mortality.

Conclusion

The mNUTRIC score is an independent mortality predictor for all-cause ARDS and AFI-ARDS patients. AFI-ARDS has significantly lesser mortality than non-AFI ARDS.

Predictors of survival from Acinetobacter in Saudi Arabian intensive care units: A prospective, one-year, six-city, ten-center cohort study

BACKGROUND

Antibiotic-resistant Acinetobacter baumannii is a continuously-emerging worldwide health crisis, with mortality rates approaching 50% in intensive care unit (ICU) patients. The objective of this study was to evaluate regional, patient-related, and organism-related predictors of survival among critically-ill patients with confirmed Acinetobacter infection.

METHODS

This prospective cohort study was conducted within ten ICUs across six geographically- and climatologically-distinct cities across Saudi Arabia over 13 months.

RESULTS

Of 169 patients with confirmed Acinetobacter infection enrolled in the study, 80 (47.6%) died. Survivors were statistically younger, predominantly male, more likely to be admitted for trauma, less likely to have hypertension, diabetes, or have undergone hemodialysis, and more likely to have been treated with antibiotics prior to having a positive culture for Acinetobacter, but less likely to have received an aminoglycoside. Survivors also had lower baseline APACHE II and SOFA scores and were infected with stains of Acinetobacter that had less meropenem- or colistin-resistance. Multivariate analysis identified the following independent predictors of survival: younger age, lower ICU-day#1 APACHE-II and ICU-day#3 SOFA scores, being admitted for trauma, and having no history of hemodialysis.

CONCLUSIONS

Patient-related factors outweigh regional and hospital-related factors as predictors of survival among critically-ill patients with Acinetobacter infection.

Establishment of ICU Mortality Risk Prediction Models with Machine Learning Algorithm Using MIMIC-IV Database

Objective: The mortality rate of critically ill patients in ICUs is relatively high. In order to evaluate patients’ mortality risk, different scoring systems are used to help clinicians assess prognosis in ICUs, such as the Acute Physiology and Chronic Health Evaluation III (APACHE III) and the Logistic Organ Dysfunction Score (LODS). In this research, we aimed to establish and compare multiple machine learning models with physiology subscores of APACHE III—namely, the Acute Physiology Score III (APS III)—and LODS scoring systems in order to obtain better performance for ICU mortality prediction. Methods: A total number of 67,748 patients from the Medical Information Database for Intensive Care (MIMIC-IV) were enrolled, including 7055 deceased patients, and the same number of surviving patients were selected by the random downsampling technique, for a total of 14,110 patients included in the study. The enrolled patients were randomly divided into a training dataset (n = 9877) and a validation dataset (n = 4233). Fivefold cross-validation and grid search procedures were used to find and evaluate the best hyperparameters in different machine learning models. Taking the subscores of LODS and the physiology subscores that are part of the APACHE III scoring systems as input variables, four machine learning methods of XGBoost, logistic regression, support vector machine, and decision tree were used to establish ICU mortality prediction models, with AUCs as metrics. AUCs, specificity, sensitivity, positive predictive value, negative predictive value, and calibration curves were used to find the best model. Results: For the prediction of mortality risk in ICU patients, the AUC of the XGBoost model was 0.918 (95%CI, 0.915–0.922), and the AUCs of logistic regression, SVM, and decision tree were 0.872 (95%CI, 0.867–0.877), 0.872 (95%CI, 0.867–0.877), and 0.852 (95%CI, 0.847–0.857), respectively. The calibration curves of logistic regression and support vector machine performed better than the other two models in the ranges 0–40% and 70%–100%, respectively, while XGBoost performed better in the range of 40–70%. Conclusions: The mortality risk of ICU patients can be better predicted by the characteristics of the Acute Physiology Score III and the Logistic Organ Dysfunction Score with XGBoost in terms of ROC curve, sensitivity, and specificity. The XGBoost model could assist clinicians in judging in-hospital outcome of critically ill patients, especially in patients with a more uncertain survival outcome.

Brain natriuretic peptide and cardiac troponin I for prediction of the prognosis in cancer patients with sepsis

BACKGROUND

This article aimed to study the value of brain natriuretic peptide (BNP) and cardiac troponin I(cTnI) for predicting the prognosis in cancer patients with sepsis.

METHODS

A cohort of 233 cancer patients with sepsis admitted to our ICU from January 2017 to October 2020 was included in this retrospective study. The data of BNP and cTnI on the first day (d1) and the third day(d3) after entering ICU, blood lactate (Lac), procalcitonin (PCT), Leucocyte and Sequential Organ failure assessment (SOFA) scores within 24 hr of entering ICU, the incidence of septic shock, acute kidney injury(AKI), acute respiratory failure (ARF) or sepsis-induced myocardial dysfunction(SIMD) in ICU, fluid balance in 24 hr and 72 hr after entering ICU, time of mechanical ventilation(MV), length of stay, emergency surgery were collected. According to 28-day mortality, patients were divided into survival group (190 cases) and death group (43 cases). All the above variables were compared.

RESULTS

BNP was an independent predictor for the mortality in these patients (P < 0.05).While cTnI was not. BNP on d3 in 681.5 pg/ml predicted the mortality with a sensitivity of 91.5 % and a specificity of 88.7 %. All patients were divided into the new two groups following the cutoff value of BNP on d3(681.5pg/ml), and the survival curve showed a significant difference with Kaplan-Meier analysis (P < 0.05). BNP had statistical differences between four groups based on the comorbidities(septic shock, AKI, ARF or SIMD), but cTnI was not.

CONCLUSIONS

BNP was a great predictor for the prognosis of cancer patients with sepsis, while cTnI was not.

Haemogram-Derived Indices for Screening and Prognostication in Critically Ill Septic Shock Patients: A Case-Control Study

This study aimed (1) to assess the diagnostic accuracy of neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), monocyte-to-lymphocyte (MLR) and platelet count-to-mean platelet volume (PLT/MPV) ratios in predicting septic shock in patients on admission to the intensive care unit (ICU) and (2) to compare it with the role of C-reactive protein (CRP), procalcitonin (PCT) and lactate level. We also sought (3) to verify whether the indices could be useful in ICU mortality prediction and (4) to compare them with Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score II (SAPS II) and Sequential Organ Failure Assessment (SOFA) scores. This retrospective study covered 138 patients, including 61 subjects with multi-organ failure due to septic shock (study group) and 77 sex- and age-matched controls. Septic patients had significantly higher NLR (p < 0.01) and NLR predicted septic shock occurrence (area under the ROC curve, AUROC = 0.66; 95% CI 0.58-0.74). PLR, MLR and PLT/MPV were impractical in sepsis prediction. Combination of CRP with NLR improved septic shock prediction (AUROC = 0.88; 95% CI 0.81-0.93). All indices failed to predict ICU mortality. APACHE II and SAPS II predicted mortality with AUROC = 0.68; 95% CI 0.54-0.78 and AUROC = 0.7; 95% CI 0.57-0.81, respectively. High NLR may be useful to identify patients with multi-organ failure due to septic shock but should be interpreted along with CRP or PCT. The investigated indices are not related with mortality in this specific clinical setting.