Logistic Organ Dysfunction System Research Articles

Predictive Value of Multiple Scoring Systems in the Prognosis of Septic Patients with Different Infection Sites: Analysis of the Medical Information Mart for the Intensive Care IV Database.

The heterogeneity nature of sepsis is significantly impacted by the site of infection. This study aims to explore the predictive value of multiple scoring systems in assessing the prognosis of septic patients across different infection sites. Data for this retrospective cohort study were extracted from the Medical Information Mart for Intensive Care IV database (MIMIC-IV) (v2.2). Adult patients meeting the criteria for sepsis 3.0 and admitted to the intensive care unit (ICU) were enrolled. Infection sites included were pneumonia, urinary tract infection (UTI), cellulitis, abdominal infection, and bacteremia. The primary outcome assessed was 28-day mortality. The sequential Organ Failure Assessment (SOFA) score, Oxford Acute Severity of Illness Score (OASIS), and Logistic Organ Dysfunction System (LODS) score were compared. Binomial logistic regression analysis was conducted to evaluate the association between these variables and mortality. Additionally, differences in the area under the curve (AUC) of receiver operating characteristic (ROC) among the scoring systems were analyzed. A total of 4721 patients were included in the analysis. The average 28-day mortality rate was 9.4%. Significant differences were observed in LODS, OASIS, and SOFA scores between the 28-day survival and non-survival groups across different infection sites (p < 0.01). In the pneumonia group and abdominal infection group, both the LODS and OASIS scoring systems emerged as independent risk factors for mortality in septic patients (odds ratio [OR]: 1.165, 95% confidence interval [CI]: 1.109-1.224, p < 0.001; OR: 1.047, 95% CI: 1.028-1.065, p < 0.001) (OR: 1.200, 95% CI: 1.091-1.319, p < 0.001; OR: 1.060, 95% CI: 1.025-1.095, p < 0.001). For patients with UTI, the LODS, OASIS, and SOFA scoring systems were identified as independent risk factors for mortality (OR: 1.142, 95% CI: 1.068-1.220, p < 0.001; OR: 1.062, 95% CI: 1.037-1.087, p < 0.001; OR: 1.146, 95% CI: 1.046-1.255, p = 0.004), with the AUC of LODS score and OASIS significantly higher than that of the SOFA score (p = 0.006). Among patients with cellulitis, the OASIS and SOFA scoring systems were identified as independent risk factors for mortality (OR: 1.055, 95% CI: 1.007-1.106, p = 0.025; OR: 1.187, 95% CI: 1.005-1.403, p = 0.044), with no significant difference in prognosis prediction observed (p = 0.243). In the bacteremia group, the LODS scoring system was identified as an independent risk factor for mortality (OR: 1.165, 95% CI: 1.109-1.224, p < 0.001). The findings suggest that LODS scores offer better prognostic accuracy for predicting the mortality risk in septic patients with pneumonia, abdominal infections, bacteremia, and UTI compared to SOFA scores.

Sequential respiratory support in septic patients undergoing continuous renal replacement therapy: A study based on MIMIC-III database

ObjectiveOxygen and hemodynamic management are important for providing a sufficient adequate oxygen-containing blood to the organs for septic patients. In present study, we aimed to explore the application of sequential respiratory support (SRS) and the association of SRS with the outcome of septic patients who needed continuous renal replacement therapy (CRRT). MethodsWe extracted the medical information of septic patients who received CRRT within 24 h of intensive care unit (ICU) admission from the MIMIC-III v1.4. SRS was defined as receiving firstly oxygen therapy followed by mechanical ventilation (MV) within 24 h of admission to ICU. The propensity score matching (PSM) was performed to compare the differences in clinical characteristics and outcomes of patients with or without SRS. Finally, we developed logistic regression models to analyze the effects of SRS on hospital mortality. ResultsA total of 181 patients entered in this study, and there were 80 patients undergoing MV including SRS group (n = 61) and non-SRS group (n = 19). In the multivariate logistic regression, the value of SRS was associated with the lower risk of hospital mortality adjusted by minimum systolic BP (SBP), maximum lactate, vasopressor use, and sequential organ failure assessment (SOFA) score or Logistic Organ Dysfunction System (LODS) scores within the first 24 h of ICU stay. After PSM adjusted by SBP, maximum lactate, vasopressor use, SOFA, and LODS, there were 31 patients in SRS group with a and 18 cases in non-SRS group, displaying a significantly lower hospital mortality in SRS group than that in patients without SRS (19.4 % vs. 83.3 %, P < 0.001). In addition, age, qSOFA, necessitating the administration of vasopressor, and duration of vasopressor were significantly correlated with the hospital mortality in septic patients undergoing CRRT and SRS. ConclusionsReceiving SRS within the first 24 h upon admission to the ICU was independently associated with the hospital mortality in patient with sepsis undergoing CRRT, and patients who were directly received MV had a high risk of death.

Accuracy of different scoring systems in cardiogenic shock patients treated with micro-axial percutaneous left ventricular assist device

Abstract Background Cardiogenic shock (CS) is the most severe form of acute heart failure characterized by high mortality. Micro-axial percutaneous left ventricular assist devices (pLVAD) might improve outcome. The utilization of these devices increased lately but is associated with high material and personnel costs and unknown impact on prognosis. Therefore, a precise assessment of prognosis is of immanent interest to determine upfront, who might benefit from the device. For this purpose, different scoring systems were developed. Purpose In the current study, we investigated accuracy of 9 different scoring systems predicting all-cause mortality at 30 days. Methods Data were collected from our ongoing Impella registry including more than 740 patients treated for different indications since 2014. Among them, 434 patients received a micro-axial pLVAD in CS. Acute Physiology and Chronic Health Evaluation (APACHE) II score (APA), Simplified Acute Physiology Score II (SAPS), Multiple Organ Dysfunction Score (MODS), Sequential Organ Failure Assessment (SOFA), Logistic Organ Dysfunction System (LODS) score, Organ Dysfunctions or Infection score (ODIN), ENCOURAGE score, CardShock score, and IABP-SHOCK II risk score were calculated. All-cause mortality was characterized with the use of Kaplan-Meier plots. A receiver operating characteristic (ROC) curve was generated, and the area under the curve (AUC) was estimated to determine the predictive value of the different scores for 30-day-mortality. Subgroup analyses were performed for CS caused by acute myocardial infarction (AMI), CS caused not by AMI, and cardiopulmonary resuscitation (CPR). Results Patients were 68±1 years old with predominance of male gender (73.5% [n=319]). CS was mainly caused by AMI (55.8% [n=242]). A CPR before pLVAD was performed in 49.5% [n=215] with a mean duration of 36±3 minutes. Initial serum lactate was 7.5±0.3 mmol/l. Further baseline characteristics are shown in Table 1. All-cause mortality at 30 days was 65.0±2.3% (Figure 1A). Survivors’ mean stay at hospital was 18±3 days. ROC analyses revealed a positive prediction of 30-day-mortality of all scores (Figure 1B). The SAPS showed the best, ODIN and IABP-SHOCK II risk score the lowest accuracies (ROC AUC [95% CI] SAPS 0.757 [0.704-0.810; p&amp;lt;0.001], ODIN 0.647 [0.585-0.708; p&amp;lt;0.001], IABP SHOCK II 0.649 [0.588-0.709; p&amp;lt;0.001]). In the subgroup analyses, comparable results were reached except for patients receiving a CPR. Among those patients, only SAPS, LODS and ENCOURAGE score significantly predicted 30-day-mortality, but accuracies were low (Figure 1C). Conclusion In CS patients treated with pLVAD, the examined scoring systems significantly predicted 30-day-mortality with relevant differences in accuracy. The best prediction was revealed by SAPS. None of the scores showed an acceptable prediction in patients receiving a CPR indicating a specific patient cohort in need for better prognostic tools.Table 1Figure 1

Development of a nomogram for predicting 90-day mortality in patients with sepsis-associated liver injury

The high mortality rate in sepsis patients is related to sepsis-associated liver injury (SALI). We sought to develop an accurate forecasting nomogram to estimate individual 90-day mortality in SALI patients. Data from 34,329 patients were extracted from the public Medical Information Mart for Intensive Care (MIMIC-IV) database. SALI was defined by total bilirubin (TBIL) > 2 mg/dL and the occurrence of an international normalized ratio (INR) > 1.5 in the presence of sepsis. Logistic regression analysis was performed to establish a prediction model called the nomogram based on the training set (n = 727), which was subsequently subjected to internal validation. Multivariate logistic regression analysis showed that SALI was an independent risk factor for mortality in patients with sepsis. The Kaplan‒Meier curves for 90-day survival were different between the SALI and non-SALI groups after propensity score matching (PSM) (log rank: P < 0.001 versus P = 0.038), regardless of PSM balance. The nomogram demonstrated better discrimination than the sequential organ failure assessment (SOFA) score, logistic organ dysfunction system (LODS) score, simplified acute physiology II (SAPS II) score, and Albumin–Bilirubin (ALBI) score in the training and validation sets, with areas under the receiver operating characteristic curve (AUROC) of 0.778 (95% CI 0.730–0.799, P < 0.001) and 0.804 (95% CI 0.713–0.820, P < 0.001), respectively. The calibration plot showed that the nomogram was sufficiently successful to predict the probability of 90-day mortality in both groups. The DCA of the nomogram demonstrated a higher net benefit regarding clinical usefulness than SOFA, LODS, SAPSII, and ALBI scores in the two groups. The nomogram performs exceptionally well in predicting the 90-day mortality rate in SALI patients, which can be used to assess the prognosis of patients with SALI and may assist in guiding clinical practice to enhance patient outcomes.

Decreased urine output is associated with increased in-hospital mortality from sepsis-associated acute respiratory distress syndrome

The relationship between urine output (UO) and in-hospital mortality in patients with sepsis-associated acute respiratory distress syndrome (ARDS) has not been elucidated. The demographic and clinical characteristics of patients from the intensive care unit with sepsis-associated ARDS in the Medical Information Mart for Intensive Care-IV database were collected, and binomial logistic regression was performed to determine whether UO was an independent risk factor for in-hospital death. Using the Logistic Organ Dysfunction System (LODS) and Sequential Organ Failure Assessment (SOFA) as a reference, receiver operating characteristic (ROC) curves were drawn to analyze the efficacy of UO in predicting in-hospital mortality, and the Kaplan-Meier curve was drawn with the optimal cut-off value of the ROC curve. Decision curve analysis (DCA) was performed to assess the clinical net benefit of UO in predicting in-hospital mortality. UO was an independent risk factor for in-hospital mortality in patients with sepsis-associated ARDS. The area under the ROC (AUC) for UO in predicting in-hospital mortality was 0.712, which was comparable to LODS and SOFA. The patients were grouped by the optimal UO cut-off value (1515 mL/day) identified by the ROC curve. The results showed that the median in-hospital survival time for the low-UO group was 20.565 days, and that of the high-UO group was 84.670 days. The risk of in-hospital death of the low-UO group was 3.0792 times that of the high-UO group. DCA showed that when using UO to predict in-hospital mortality, the clinical net benefit was higher than LODS or SOFA at almost all available threshold probabilities, particularly when the threshold probability was between 0.2 and 0.4. As a result, UO showed moderate efficacy in predicting in-hospital mortality, and when used to predict the in-hospital mortality of patients with sepsis-related ARDS, its clinical net benefit was higher than that of LODS or SOFA.

Simplified acute physiology score III is excellent for predicting in-hospital mortality in coronary care unit patients with acute myocardial infarction: A retrospective study.

Coronary care unit (CCU) patients with acute myocardial infarction (AMI) lack effective predictors of in-hospital mortality. This study aimed to investigate the performance of four scoring systems in predicting in-hospital mortality in CCU patients with AMI. The baseline data, the logistic organ dysfunction system (LODS), the Oxford acute severity of illness score (OASIS), the simplified acute physiology score II (SAPS II), and the simplified acute physiology score III (SAPS III) scores of the patients were extracted from the fourth edition of the Medical Information Mart for Critical Care (MIMIC-IV) database. Independent risk factors for in-hospital mortality were identified by regression analysis. We performed receiver operating characteristic (ROC) curves and compared the area under the curve (AUC) to clarify the predictive value of the four scoring systems. Meanwhile, Kaplan-Meier curves and decision curve analysis (DCA) were performed to determine the optimal scoring system for predicting in-hospital mortality. A total of 1,098 patients were included. The SAPS III was an independent risk factor for predicting in-hospital mortality in CCU patients with AMI before and after the propensity score matching (PSM) analysis. The discrimination of in-hospital mortality by SAPS III was superior to that of LODS, OASIS, and SAPS II. The AUC of the SAPS III scoring system was the highest among the four scoring systems, at 0.901 (before PSM) and 0.736 (after PSM). Survival analysis showed that significantly more in-hospital mortality occurred in the high-score SAPS III group compared to the low-score SAPS III group before PSM (HR 7.636, P < 0.001) and after PSM (HR 2.077, P = 0.005). The DCA curve of SAPS III had the greatest benefit score across the largest threshold range compared to the other three scoring systems. The SAPS III was an independent risk factor for predicting in-hospital mortality in CCU patients with AMI. The predictive value for in-hospital mortality with SAPS III is superior to that of LODS, OASIS, and SAPS II. The results of the DCA analysis suggest that SAPS III may provide a better clinical benefit for patients. We demonstrated that SAPS III is an excellent scoring system for predicting in-hospital mortality for CCU patients with AMI.

SAPS III is superior to SOFA for predicting 28-day mortality in sepsis patients based on Sepsis 3.0 criteria

IntroductionThe discrimination and calibration accuracy of prediction models tends to become poor over time. The performance of predictive models should be reevaluated periodically. The aim of this study was to reassess the discrimination of the six commonly used models for predicting 28-day mortality in patients with sepsis based on the Sepsis 3.0 criteria. MethodsPatient data were extracted from the fourth edition of the Medical Information Mart for Critical Care (MIMIC IV) database. The systemic inflammatory response syndrome (SIRS), Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS), Logistic Organ Dysfunction System (LODS), and Simplified Acute Physiology Score II (SAPS II) and III (SAPS III) scores were calculated and collected. The area under the receiver operating characteristic curve (AUROC) was used to compare the discrimination abilities of the models using non-parametric Wilcoxon statistics. The Delong method was used to perform pairwise comparisons of the AUROCs of the models. Multiple subgroup analyses for age, body mass index, and sex were performed with regard to the 28-day mortality prediction of the models. ResultsA total of 12 691 patients were included. The mean age of the patients was 65.97 ± 15.77 years; 7673 patients (60.50%) were male. The mean SIRS, SOFA, OASIS, SAPS II, LODS, and SAPS III scores were higher in the non-survivor group than in the survivor group. The discrimination for 28-day mortality with the SAPS III (AUROC 0.812, 95% confidence interval (CI) 0.802–0.822) and LODS (AUROC 0.804, 95% CI 0.743–0.765) models was superior to that of the SIRS (AUROC 0.575, 95% CI 0.562–0.589), SOFA (AUROC 0.612, 95% CI 0.598–0.626), OASIS (AUROC 0.753, 95% CI 0.742–0.764), and SAPS II (AUROC 0.754, 95% CI 0.743–0.765) models. The Youden index of the SAPS III model was 0.484, which was the highest among the models. Subgroup analyses showed similar results to the overall results. ConclusionsThe discrimination for 28-day mortality with the SAPS III and LODS models was superior to that of the SIRS, SOFA, OASIS, and SAPS II models. The SAPS III model showed the best discrimination capacity for 28-day mortality compared with the other models.

Intensive Care Unit Scoring Systems.

Illness severity scoring systems are commonly used in critical care. When applied to the populations for whom they were developed and validated, these tools can facilitate mortality prediction and risk stratification, optimize resource use, and improve patient outcomes. To describe the characteristics and applications of the scoring systems most frequently applied to critically ill patients. A literature search was performed using MEDLINE to identify original articles on intensive care unit scoring systems published in the English language from 1980 to 2020. Search terms associated with critical care scoring systems were used alone or in combination to find relevant publications. Two types of scoring systems are most frequently applied to critically ill patients: those that predict risk of in-hospital mortality at the time of intensive care unit admission (Acute Physiology and Chronic Health Evaluation, Simplified Acute Physiology Score, and Mortality Probability Models) and those that assess and characterize current degree of organ dysfunction (Multiple Organ Dysfunction Score, Sequential Organ Failure Assessment, and Logistic Organ Dysfunction System). This article details these systems' differing features and timing of use, score calculation, patient populations, and comparative performance data. Critical care nurses must be aware of the strengths, limitations, and specific characteristics of severity scoring systems commonly used in intensive care unit patients to effectively employ these tools in clinical practice and critically appraise research findings based on their use.

Value of procalcitonin and critical illness score in etiological diagnosis and prognosis of sepsis caused by intra-abdominal infections

To compare the early and late predictive values of critical illness score (CIS) and procalcitonin (PCT) in septic patients with blood stream infection (BSI) induced by intra-abdominal infection (IAI), and to identify the value of PCT in etiological diagnosis. The clinical data of patients with at least one positive blood culture within 24 hours admission to the emergency department of China-Japan Friendship Hospital from January 2014 to December 2019 and with final diagnosis of IAI induced sepsis were enrolled. Sequential organ failure assessment (SOFA), mortality in emergency department sepsis (MEDS), Logistic organ dysfunction system (LODS), and acute physiology and chronic health evaluation II (APACHE II) scores were calculated based on the parameters on the day of admission. Differences in various indicators among different Gram-stained bacterial infections and among patients with different prognosis at 28 days or 60 days were compared. Receiver operator characteristic curve (ROC curve) was used to analyze the value of PCT in differential etiological diagnosis of IAI induced sepsis caused by single bacterial infection, and the predictive value of CIS and PCT on 28-day and 60-day death of septic patients with BSI induced by IAI. A total of 221 septic patients with IAI caused by single bacterial infection were enrolled. The 28-day mortality was 19.9% (44/221), and the 60-day mortality was 25.8% (57/221). Mortality caused by Gram-positive (G+) bacterial infection of patients was significantly higher than that caused by Gram-negative (G-) bacterial infection (28 days: 34.6% vs. 11.4%, 60 days: 42.0% vs. 16.4%, both P < 0.01). Compared with patients with G+ bacterial infection, the PCT value of patients with G- bacterial infection was higher [μg/L: 4.31 (0.71, 25.71) vs. 1.29 (0.32, 10.83), P < 0.05]. Compared with survival group, the values of CIS and PCT in death group were higher, either in 28 days or in 60 days [death group vs. survival group in 28 days: SOFA score was 6.0 (4.0, 10.0) vs. 3.0 (2.0, 5.0), MEDS score: 11 (9, 14) vs. 6 (6, 9), LODS score: 4.0 (2.0, 6.0) vs. 1.0 (0, 2.0), APACHE II score: 17.0 (15.0, 24.0) vs. 12.0 (8.0, 15.0), PCT (μg/L): 3.48 (1.01, 26.70) vs. 2.45 (0.32, 15.65); death group vs. survival group in 60 days: SOFA score: 6.0 (4.0, 10.0) vs. 3.0 (2.0, 5.0), MEDS score: 9 (6, 14) vs. 6 (6, 9), LODS score: 4.0 (1.0, 5.0) vs. 1.0 (0, 2.0), APACHE II score: 16.5 (12.0, 20.0) vs. 12.0 (8.0, 15.0), PCT (μg/L): 2.67 (0.98, 17.73) vs. 2.22 (0.31, 16.75); all P < 0.05]. ROC curve showed that: (1) the area under ROC curve (AUC) of PCT in the diagnosis of IAI induced sepsis with single bacterial infection was 0.740 [95% confidence interval (95%CI) was 0.648-0.833]. When the optimal cut-off value of PCT was 1.82 μg/L, the sensitivity of diagnosis of G- bacterial infection was 74.0%, and the specificity was 68.2%. When PCT value was higher than 10.92 μg/L, the specificity of diagnosis of G- bacterial infection could reach 81.8%. (2) In the prediction of 28-day and 60-day mortality for septic patients with BSI induced by IAI, the APACHE II score achieved the highest AUC [28 days: 0.791 (95%CI was 0.680-0.902), 60 days: 0.748 (95%CI was 0.645-0.851)]. APACHE II score higher than 14.5 could help to predict 28-day and 60-day mortality for IAI patients with negative predictive values of 94.9% and 88.5%. However, the predictive value of PCT for septic patients with BSI induced by IAI was relatively lower [28-day AUC: 0.610 (95%CI was 0.495-0.725), 60-day AUC: 0.558 (95%CI was 0.450-0.667)]. PCT is more reliable in the identification of pathogen type among IAI induced sepsis with BSI, while APACHE II score may perform better in predicting early and late mortality.

Retrospective Evaluation Of The Accuracy Of Five Different Severity Scores To Predict The Mortality In Burns Patients.

Patients with great clinical impairment, due to extensive burns, need to be admitted to intensive care units, in these treatment sites, indices are used to classify the severity of patients. The aim of the study was to compare the accuracy of the FLAMES score in relation to the Acute Physiologic and Chronic Health Evaluation II (APACHE II), the Simplified Acute Physiologic Score II (SAPS II), the Logistic Organ Dysfunction System (LODS) and the Abbreviated Burn Severity Index (ABSI) applied to the severe burn patient facing mortality in an ICU of a reference center for burns in Brazil. A retrospective study conducted in ICU comparing the accuracy the APACHE II, SAPS II, LODS, ABSI and FLAMES instruments were applied to all the selected medical records. To evaluate the accuracy of the SIs, the Receiver Operating Characteristic curve was calculated and the area under the curve (AUC). Among the 574 patients included in the study, male individuals (70.13%), with an average age of 44.01 ± 28.64 prevailed and the majority of the burns were caused by accidents (76.53%). The outcome accounted for 35.29% of deaths. It was observed that the FLAMES and ABSI presented the two largest areas under the ROC curves and the highest sensitivities (96% and 89%, respectively). The APACHE II, SAPS II and LODS presented sensitivities equal to or greater than 80%. It has been demonstrated that indices specifically developed for burn patients, specifically the FLAMES and ABSI indices, presented better accuracies and prediction performances.

Development of a nomogram to predict 30-day mortality of patients with sepsis-associated encephalopathy: a retrospective cohort study

BackgroundSepsis-associated encephalopathy (SAE) is related to increased short-term mortality in patients with sepsis. We aim to establish a user-friendly nomogram for individual prediction of 30-day risk of mortality in patients with SAE.MethodsData were retrospectively retrieved from the Medical Information Mart for Intensive Care (MIMIC III) open source clinical database. SAE was defined by Glasgow Coma Score (GCS) < 15 or delirium at the presence of sepsis. Prediction model with a nomogram was constructed in the training set by logistic regression analysis and then undergone internal validation and sensitivity analysis.ResultsSAE accounted for about 50% in patients with sepsis and was independently associated with the 30-day mortality of sepsis. Variables eligible for the nomogram included patient’s age and clinical parameters on the first day of ICU admission including the GCS score, lactate, bilirubin, red blood cell distribution width (RDW), mean value of respiratory rate and temperature, and the use of vasopressor. Compared with Sequential Organ Failure Assessment (SOFA) and Logistic Organ Dysfunction System (LODS), the nomogram exhibited better discrimination with an area under the receiver operating characteristic curve (AUROC) of 0.763 (95%CI 0.736–0.791, p < 0.001) and 0.753 (95%CI 0.713–0.794, p < 0.001) in the training and validation sets, respectively. The calibration plot revealed an adequate fit of the nomogram for predicting the risk of 30-day mortality in both sets. Regarding to clinical usefulness, the DCA of the nomogram exhibited greater net benefit than SOFA and LODS in both of the training and validation sets. Besides, the nomogram exhibited acceptable discrimination, calibration, and clinical usefulness in sensitivity analysis.ConclusionsSAE is related to increased 30-day mortality of patients with sepsis. The nomogram presents excellent performance in predicting 30-day risk of mortality in SAE patients, which can be used to evaluate the prognosis of patients with SAE and may be more beneficial once specific treatments towards SAE are developed.

Diagnostic and predictive value of critical illness scores and biomarkers in bloodstream infection-associated pneumonia

To compare the early and late predictive value of several critical illness scores (CISs) and biomarkers in patients with bloodstream infection (BSI)-associated pneumonia, and to identify the value of procalcitonin (PCT) in etiological diagnosis. Patients with at least one positive blood culture within 24 hours admission to department of emergency of China-Japan Friendship Hospital from January 2014 to December 2018 and with final diagnosis of pneumonia were enrolled. Sequential organ failure assessment (SOFA), mortality in emergency department sepsis (MEDS), Logistic organ dysfunction system (LODS), and acute physiology and chronic health evaluation II (APACHE II) scores were calculated based on the first parameters on the day of admission. Differences of various indicators among different Gram-stained bacterial infections and among patients with different prognosis at 28-day or 60-day were compared. Receiver operating characteristic (ROC) curve was used to analyze the value of biomarkers in differential diagnosis of pneumonia caused by single bacterial infection, and the predictive value of several CISs and biomarkers on 28-day and 60-day death of patients with pneumonia. Among 540 patients with pneumonia caused by single bacterial infection, 256 (47.4%) patients with Gram-positive bacteria (GPB) infection and 284 (52.6%) with Gram-negative bacteria (GNB) infection. The 28-day mortality was 29.4% (159/540) and the 60-day mortality was 36.3% (196/540). PCT level was significantly higher in patients with GNB infection than that in GPB infected patients [μg/L: 1.99 (0.32, 13.19) vs. 0.45 (0.13, 3.53), P < 0.01]. There were significant differences of CISs and biomarkers between death group and survival group in predicting 28-day and 60-day mortality in BSI-associated pneumonia. ROC curve analysis showed that: (1) the optimal cut-off value of PCT in the diagnosis of single bacterial infection was 0.48 μg/L, with the area under ROC curve (AUC) was 0.739 [95% confidence interval (95%CI) was 0.686-0.793]. When PCT value was greater than 4.49 μg/L, the specificity of diagnostic of GNB infection could reach 81.8%, and the positive predictive value (PPV) was 75.0%. When PCT value was greater than 10.16 μg/L, the diagnostic specificity could reach 91.2%. (2) In the prediction of 28-day and 60-day mortality, the SOFA score showed highest AUC [28-day: 0.818 (95%CI was 0.768-0.867), 60-day: 0.800 (95%CI was 0.751-0.849)]. SOFA score greater than 8.5 points could help to predict 28-day and 60-day mortality for pneumonia patients with specificity of 90.5% and 91.6%, respectively. AUC of PCT for predicting 28-day and 60-day mortality in patients with BSI associated with pneumonia was 0.637 (95%CI was 0.575-0.700) and 0.628 (95%CI was 0.569-0.688), respectively. When PCT value was greater than 8.15 μg/L, the specificity and negative predictive value (NPV) were 80.2% and 75.1% respectively, and they could reach 80.2% and 68.7% when PCT value was greater than 7.46 μg/L. PCT is more reliable in the identification of pathogen type in BSI-associated pneumonia, while CISs may be more advantageous in the assessment of early and late prognosis.

Value of predicting prognosis of patients with heat stroke by three scoring methods

Objective: To explore the predictive value of different scoring methods for the prognosis of patients with hyperthermia. Methods: In September 2019, the clinical data of 49 patients with heat radiation disease in the second people's Hospital of Hefei were collected retrospectively. According to the prognosis of patients, they were divided into survival group (32 cases) and death group (17 cases) . The rapid emergency medicine score (REMS) , modified early warning score (modified early warning score) were calculated respectively Score (mews) , logistic organ dysfunction system (LODs) and the differences between the two groups were compared. ROC curve was used to evaluate the accuracy of various scores in the prognosis of patients with heat radiation disease. Results: the fatality of heat stroke was 34.69%, there were significant differences of REMS, MEWS and LODS between the two groups (P<0.05) , the area under ROC curve (AUC) of REMS, MEWS and LODS to predicting prognosis of heat stroke was (0.696±0.076, 95%CI: 0.548 to 0.844, P<0.05, 0.692±0.079, 95%CI: 0.536 to 0.848, P<0.05, 0.787±0.063, 95%CI: 0.663 to 0.911, P<0.05) respectively. Conclusion: There are valuable for predicting prognosis of patients with heat stroke by REMS, MEWS and LODS, especially the LODS, the REMS and MEWS are simple and easy.

Prognostic values of SOFA score, qSOFA score, and LODS score for patients with sepsis.

Sepsis continues to carry a high rate of mortality, which makes effective and simple evaluation methods for predicting the prognosis of septic patients especially important. In this study, we retrospectively analyzed the relationships between three scoring systems including Sequential Organ Failure Assessment (SOFA) score, Quick SOFA (qSOFA) score, and Logistic Organ Dysfunction System (LODS) score and the prognoses of septic patients. The baseline data, SOFA score, qSOFA score, LODS score, 28-day prognosis, and 90-day prognosis of patients who met the diagnostic criteria of sepsis were retrieved from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Receiver operating characteristic (ROC) curves were drawn for various indicators, and comparisons were drawn between the areas under the ROC curves (AUC) of the different scoring systems. The 28-day AUC was 0.661 (0.652, 0.670) for SOFA, 0.558 (0.548, 0.568) for qSOFA, and 0.668 (0.658, 0.677) for LODS; AUC-qSOFA vs. AUC-LODS was 0.103 (0.087, 0.120) (P<0.001), and AUC-qSOFA vs. AUC-LODS was 0.110 (0.094, 0.125) (P<0.001). The 90-day AUC was 0.630 (0.621, 0.640) for SOFA, 0.551 (0.541, 0.560) for qSOFA, and 0.644 (0.635, 0.653) for LODS; AUC-SOFA vs. AUC-qSOFA was 0.079 (0.065, 0.094) (P<0.001), and AUC-qSOFA vs. AUC-LODS was 0.093 (0.079, 0.107) (P<0.001). SOFA score, qSOFA score, and LODS score can all be used to predict the prognosis of septic patients. LODS score and SOFA score have higher accuracy than qSOFA score; however, qSOFA is simpler to use, making it a more suitable tool in an emergency setting.

Survival, Outcomes, and Use of Acuity Scoring Systems Following Tracheotomy in Veteran Patients.

To determine whether established prognosis tools used in the general population of critically ill patients will accurately predict tracheotomy-related outcomes and survival outcomes in critically ill patients undergoing tracheotomy. Retrospective chart review of 94 consecutive critically ill patients undergoing isolated tracheotomy. Logistic Organ Dysfunction System (LODS) and sepsis-related organ failure assessment (SOFA) scores, 2 validated measures of acuity in critically ill patients, were calculated for all patients. The only tracheotomy-related outcome of significance was the finding that patients with an LODS score ≤6 were more likely to become ventilator independent (P < .015). Higher LODS or SOFA scores were associated with in-house death (LODS, P = .001, SOFA, P = .008) and death within 90 days (LODS, P = .009, SOFA, P = .031), while death within 180 days was associated only with a higher LODS score (LODS, P = .018). When controlling for age, there was an association between both LODS (P = .015) and SOFA (P = .019) scores and death within 90 days of tracheotomy. The survival outcome for critically ill patients undergoing tracheotomy seems accurately predicted based on scoring systems designed for use in the general population of critically ill patients. Logistic Organ Dysfunction System may also be useful to predict the likelihood of the tracheotomy-related outcome of ventilator independence. This suggests that LODS scores may be helpful to palliative care clinicians as part of a shared decision-making aid in critically ill, ventilated patients for whom tracheotomy is being considered.

Type of admission and nursing workload ofcritical patients: a cross-sectional study.

According to the perception of nurses in the intensive care unit (ICU), surgical patients need more nursing care, thus requiring higher nursing workloads for these patients than those admitted as clinical patients. However, some study results on the relationship between the type of admission and the nursing workload are considered contradictory. To identify if the type of admission (clinical, emergency surgery or elective surgery) is a predictive factor of the nursing workload required by patients on the first day or throughout their stay in the ICU. This was a quantitative cross-sectional study comprised of a retrospective analysis of clinical records of critical patients. Data were collected from 1 May 2015 to 30 September 2015 in a hospital located in São Paulo, Brazil. Nursing workload was measured using the Nursing Activities Score. The type of admission and the demographic and clinical variables of the patients were investigated. Multiple linear regression was used to identify nursing workload predictive factors, with 5% significance level. In the analysed sample (n = 211; mean age of 60·3 ± 18·7years), there was a prevalence of male gender (56·9%). A statistically significant difference (p = 0·025) was found between the type of admission and the nursing workload required for patients on the first ICU day. The Simplified Acute Physiologic Score (p = 0·009) was a predictor of nursing workload on the first day in the ICU, and the Logistic Organ Dysfunction System (p = 0·026) and mortality (p < 0·001) were predictors throughout the ICU stay. The type of admission was not a predictive factor of the nursing workload required by critical patients. Identifying the predictive factors of nursing workload favours the appropriate staffing of the critical unit by nurses. However, nurses should not consider the type of admission in predicting the nursing workload required by patients in the ICU.

The logistic organ dysfunction system score predicts the prognosis of patients with alcoholic ketoacidosis

Alcoholic ketoacidosis (AKA) is occasionally associated with multiple complications leading to death. However, no study has yet evaluated prognostic factors in patients with AKA. It is known that the logistic organ dysfunction system (LODS) score is an objective and useful index to predict the prognosis. We used LODS score to predict prognosis of AKA. We retrospectively reviewed the medical records of 46 patients who were diagnosed as AKA in our hospital. The mean LODS score was 6.3. The probability of mortality based on the LODS score was 36.6%, and 16 patients (34.5%) did, in fact, die. The total LODS score and lactate dehydrogenase (LDH) were significantly higher in the non-survival group. Prothrombin activity, serum platelet number, and the serum albumin levels were significantly higher in the survival group. We found significant correlations between the LODS score and arterial pH, the albumin level, and the LDH concentration. Multivariate analysis showed that the serum albumin and LDH levels were independently associated with survival in AKA patients. AKA patients suffered high-level mortality and the LODS score was an accurate predictor of prognosis. Clinicians may use the LODS score to this end.

Development of a novel score for the prediction of hospital mortality in patients with severe sepsis: the use of electronic healthcare records with LASSO regression.

Background and objectiveThere are several disease severity scores being used for the prediction of mortality in critically ill patients. However, none of them was developed and validated specifically for patients with severe sepsis. The present study aimed to develop a novel prediction score for severe sepsis.ResultsA total of 3206 patients with severe sepsis were enrolled, including 1054 non-survivors and 2152 survivors. The LASSO score showed the best discrimination (area under curve: 0.772; 95% confidence interval: 0.735-0.810) in the validation cohort as compared with other scores such as simplified acute physiology score II, acute physiological score III, Logistic organ dysfunction system, sequential organ failure assessment score, and Oxford Acute Severity of Illness Score. The calibration slope was 0.889 and Brier value was 0.173.Materials and MethodsThe study employed a single center database called Medical Information Mart for Intensive Care-III) MIMIC-III for analysis. Severe sepsis was defined as infection and acute organ dysfunction. Clinical and laboratory variables used in clinical routines were included for screening. Subjects without missing values were included, and the whole dataset was split into training and validation cohorts. The score was coined LASSO score because variable selection was performed using the least absolute shrinkage and selection operator (LASSO) technique. Finally, the LASSO score was evaluated for its discrimination and calibration in the validation cohort.ConclusionsThe study developed the LASSO score for mortality prediction in patients with severe sepsis. Although the score had good discrimination and calibration in a randomly selected subsample, external validations are still required.

Correlation factor analysis on constipation in long-term ventilated patients in intensive care unit: a prospective observational cohort study

To explore the factors associated with delayed defecation in long-term ventilated patients in intensive care unit (ICU) and their potential effect on prognosis. A prospective observational cohort study was conducted. The patients admitted to general ICU of the Affiliated Hospital of Qingdao University from October 1st in 2013 to September 30th in 2015 who underwent mechanical ventilation (MV) for ≥6 days were enrolled, and they were divided into early defecation group (< 6 days) and late defecation group (≥6 days). At admission, clinical nutritional support were given as usual, and gender, age, acute physiology and chronic health evaluation II (APACHEII) score, admission reasons, MV reasons, the usage of morphine and epinephrine/norepinephrine, the highest positive end-expiratory pressure (PEEP), the lowest oxygenation index (PaO2/FiO2) and the lowest systolic blood pressure were collected. Logistic regression analysis was used to analyze the influencing factors of the first defecation time. ICU mortality, the length of ICU stay, central venous catheter (CVC) indwelling time, duration of MV, ICU acquired bacterial infection rate, and the incidence of ventilator associated pneumonia (VAP) were compared between early defecation group and late defecation group. Logistic organ dysfunction system (LOD) scores and gastric residual volume per day were recorded at the different time of MV. Totally 189 patients were enrolled, 39 patients did not satisfied the inclusion criteria and 13 patients gave up treatment or referrals were excluded. Finally 137 patients were enrolled in the analysis, 83 patients in late defecation group and 54 in early defecation group. There were no significant differences in the baseline characteristics such as gender, age, APACHE II score, LOD score at 1 day of MV, admission reasons, MV reasons, disgorging and gastric residual volume per day during the first 5 days of MV, enteral nutrition, lactulose treatment in patients with hepatic encephalopathy during the first 5 days of MV, and blood purification treatment between the two groups (all P > 0.05). Compared with the early defecation group, late defecation group had less patients with loose stools or watery stool at first time [15.7% (13/83) vs. 33.3% (18/54)], more patients using morphine and the usage of epinephrine/norepinephrine more than 24 hours [48.2% (40/83) vs. 40.7% (22/54), 42.2%(35/83) vs. 29.6% (16/54)], higher the maximum PEEP level [cmH2O (1 cmH2O = 0.098 kPa): 7.9±3.7 vs. 6.7±3.5], lower the minimal systolic blood pressure [mmHg (1 mmHg = 0.133 kPa): 74.8±28.1 vs. 88.9±30.2] and more severe of hypoxemia [PaO2/FiO2 < 150 mmHg, 54.2% (5/83) vs. 44.4% (24/53)], all of which had significant differences (all P < 0.05). Factors found statistical significances by single factor analysis were enrolled in the multiple regression analysis, which showed that PaO<inf>2</inf>/FiO<inf>2</inf> < 150 mmHg and systolic blood pressure < 90 mmHg were independently associated with a delay in defecation in patients undergoing long-term MV [PaO2/FiO2 < 150 mmHg: adjusted hazard rate: 1.415, 95% confidence interval (95%CI) = 1.061-1.590, P = 0.026; systolic blood pressure 70-89 mmHg: HR = 1.461, 95%CI = 1.164-1.788, P = 0.002; systolic blood pressure ≤ 69 mmHg: adjusted hazard rate = 1.273, 95%CI = 1.010-1.587, P = 0.034). ICU mortality, the length of ICU stay, CVC indwelling time, duration of MV, ICU acquired bacterial infection rate, and the incidence of VAP at 7 days of MV in late defecation group were significantly higher than those of early defecation group [ICU mortality rate: 15.7% (13/83) vs. 7.4% (4/54), the length of ICU stay (day): 17.0 (14.0, 23.0) vs. 15.0 (13.8, 20.0), CVC indwelling time (days): 12.0 (10.0, 14.0) vs. 10.0 (9.0, 11.3), duration of MV (days): 14.0 (10.0, 20.0) vs. 11.0 (9.8, 15.3), ICU acquired bacterial infections rate: 60.2% (50/83) vs. 14.8% (8/54), the incidence of VAP: 32.5% (27/83) vs. 14.8% (8/54); all P < 0.05]. There was no significant difference in LOD score between both groups. The LOD scores at 4 days and 9 days of MV in late defecation group were significantly higher than those of early defecation group (6.41±4.37 vs. 5.21±3.12, 4.33±2.20 vs. 3.50±2.90, both P < 0.01). PaO2/FiO2 < 150 mmHg and systolic blood pressure < 90 mmHg during the first 5 days of MV were independently associated with a delay in defecation in patients undergoing long-term MV. The results suggest that constipation is associated with adverse outcomes in long-term ventilated patients.

Risk factors for the mortality of trauma victims in the intensive care unit

To identify the risk factors associated with mortality of trauma victims during hospitalisation in the intensive care unit (ICU). Prospective cohort. Brazilian ICU specialising in the care of trauma victims. The subjects were divided into two groups: survivors and non-survivors. The variables used to compare the groups included demographic and clinical characteristics and illness/injury severity (Acute Physiology and Chronic Health Evaluation [APACHE II], Simplified Acute Physiology Score [SAPS II], Logistic Organ Dysfunction System [LODS], Injury Severity Score [ISS] and New Injury Severity Score [NISS]). The data were analysed using descriptive and inferential statistics and multiple logistic regression analysis. The sample consisted of 200 patients (164 males) with a mean age of 40.7 years. The predominant causes of injury were traffic accidents (57.5%) followed by falls (31.0%). The ICU mortality was 19.0%. Logistic regression analysis revealed that one point on the NISS and SAPS II scores increased the risk of death by 6% and 7%, respectively. In contrast, the risk of dying decreased 4% for each day of ICU hospitalisation. Professionals must use the SAPS II and NISS for the early identification of trauma victims at high risk for death especially during the first days of ICU hospitalisation.