Reliability and accuracy of Sequential Organ Failure Assessment (SOFA) scoring

Population-specific genetic-risk scores enable improved prediction of mortality within 28 days of sepsis onset: a retrospective Taiwanese cohort study

BACKGROUND

Sepsis is characterized by organ dysfunction as a response to infection and is one of the leading causes of mortality and loss of health. The heterogeneous nature of sepsis, along with ethnic differences in susceptibility, challenges a thorough understanding of its etiology. This study aimed to propose prediction models by leveraging genetic-risk scores and clinical variables that can assist in risk stratification of patients.

METHODS

A total of 1,403 patients from Taiwan, diagnosed with sepsis, were utilized. Genome-wide survival analysis was conducted, with death within 28 days from sepsis onset, as the primary event to report significantly associated SNPs. A polygenic risk score (PRS-sepsis) was constructed via clumping and thresholding method which was added to clinical-only models to generate better performing prognostic models for identifying high-risk patients. Kaplan-Meier analysis was conducted using PRS-sepsis.

RESULTS

A total of five single-nucleotide-polymorphisms (SNPs) reached genome-wide significance (p < 5e-8), and 86 SNPs reached suggestive significance (p < 1e-5). The prognostic model using PRS-sepsis showed significantly improved performance with c-index [confidence interval (CI)] of 0.79 [0.62-0.96] and area under receiver operating characteristic curve (AUROC) [CI] of 0.78 [0.75-0.80], in comparison to clinical-only prognostic models (c-index [CI] = 0.63 [0.45- 0.81], AUROC [CI] = 0.61 [0.58-0.64]). The ethnic specificity was established for our proposed models by comparing it with models generated using significant SNPs from prior European studies (c-index [CI] = 0.63 [0.42-0.85], AUROC [CI] = 0.60 [0.58-0.63]). Kaplan-Meier plots showed that patient groups with higher PRSs have inferior survival probability compared to those with lower PRSs.

CONCLUSIONS

This study proposed genetic-risk models specific for Taiwanese populations that outperformed clinical-only models. Also it established a strong racial-effect on the underlying genetics of sepsis-related mortality. The model can potentially be used in real clinical setting for deciding precise treatment courses for patients at high-risk thereby reducing the possibility of worse outcomes.

Three-year mortality of ICU survivors with sepsis, an infection or an inflammatory illness: an individually matched cohort study of ICU patients in the Netherlands from 2007 to 2019

BACKGROUND

Sepsis is a frequent reason for ICU admission and a leading cause of death. Its incidence has been increasing over the past decades. While hospital mortality is decreasing, it is recognized that the sequelae of sepsis extend well beyond hospitalization and are associated with a high mortality rate that persists years after hospitalization. The aim of this study was to disentangle the relative contribution of sepsis (infection with multi-organ failure), of infection and of inflammation, as reasons for ICU admission to long-term survival. This was done as infection and inflammation are both cardinal features of sepsis. We assessed the 3-year mortality of ICU patients admitted with sepsis, with individually matched ICU patients with an infection but not sepsis, and with an inflammatory illness not caused by infection, discharged alive from hospital.

METHODS

A multicenter cohort study of adult ICU survivors admitted between January 1st 2007 and January 1st 2019, with sepsis, an infection or an inflammatory illness. Patients were classified within the first 24 h of ICU admission according to APACHE IV admission diagnoses. Dutch ICUs (n = 78) prospectively recorded demographic and clinical data of all admissions in the NICE registry. These data were linked to a health care insurance claims database to obtain 3-year mortality data. To better understand and distinct the sepsis cohort from the non-sepsis infection and inflammatory condition cohorts, we performed several sensitivity analyses with varying definitions of the infection and inflammatory illness cohort.

RESULTS

Three-year mortality after discharge was 32.7% in the sepsis (N = 10,000), 33.6% in the infectious (N = 10,000), and 23.8% in the inflammatory illness cohort (N = 9997). Compared with sepsis patients, the adjusted HR for death within 3 years after hospital discharge was 1.00 (95% CI 0.95-1.05) for patients with an infection and 0.88 (95% CI 0.83-0.94) for patients with an inflammatory illness.

CONCLUSIONS

Both sepsis and non-sepsis infection patients had a significantly increased hazard rate of death in the 3 years after hospital discharge compared with patients with an inflammatory illness. Among sepsis and infection patients, one third died in the next 3 years, approximately 10% more than patients with an inflammatory illness. The fact that we did not find a difference between patients with sepsis or an infection suggests that the necessity for an ICU admission with an infection increases the risk of long-term mortality. This result emphasizes the need for greater attention to the post-ICU management of sepsis, infection, and severe inflammatory illness survivors.

Association between serum calcium and in-hospital mortality in critically ill atrial fibrillation patients from the MIMIC IV database

Thongprayoon et al. found in a study of 12,599 non-dialysis adult hospitalized patients that serum calcium (SC) disturbances affected more than half of the patients and were associated with increased in-hospital mortality. Similar impacts of SC disturbances on in-hospital mortality have been observed in patients with acute myocardial infarction and the general hospitalized population. Atrial fibrillation (AF), the most common arrhythmia in the intensive care unit (ICU), affects around 6% of critically ill patients. However, the significance of the relationship between SC levels and in-hospital mortality in these patients remains unclear. This study aimed to explore the correlation between SC levels and in-hospital mortality in ICU patients diagnosed with AF. Data from the MIMIC-IV database included 11,621 AF patients (average age 75.59 ± 11.74 years; 42.56% male), with an in-hospital mortality rate of 8.90%. A nonlinear relationship between SC levels and in-hospital mortality was observed. Effect sizes on either side of the inflection point were 0.79 (HR: 0.79, 95% CI 0.67-0.94, P = 0.006) and 1.12 (HR: 1.12, 95% CI 1.01-1.25, P = 0.029). Sensitivity analyses confirmed these results. SC levels around 8.56 mg/dL were associated with the lowest risk of in-hospital mortality, with risks increasing as SC levels deviated from this point. SC levels below this inflection point were linked to more pronounced clinical impacts. This finding has significant clinical implications for clinicians. Therefore, in the treatment of ICU patients with AF, clinicians should closely monitor SC levels, with a focus on maintaining them around 8.56 mg/dL.

Data-derived subtypes of delirium during critical illness

BACKGROUND

To understand delirium heterogeneity, prior work relied on psychomotor symptoms or risk factors to identify subtypes. Data-driven approaches have used machine learning to identify biologically plausible, treatment-responsive subtypes of other acute illnesses but have not been used to examine delirium.

METHODS

We conducted a secondary analysis of a large, multicenter prospective cohort study involving adults in medical or surgical ICUs with respiratory failure or shock who experienced delirium per the Confusion Assessment Method for the ICU. We used data collected before delirium diagnosis in an unsupervised latent class model to identify delirium subtypes and then compared demographics, clinical characteristics, and outcomes between subtypes in the final model.

FINDINGS

The 731 patients who developed delirium during critical illness had a median age of 63 [IQR, 54-72] years, a median Sequential Organ Failure Assessment score of 8.0 [6.0-11.0] and 613 [83.4%] were mechanically ventilated at delirium identification. A four-class model best fit the data with 50% of patients in subtype (ST) 1, 18% in subtype 2, 17% in subtype 3, and 14% in subtype 4. Subtype 2-which had more shock and kidney impairment-had the highest mortality (33% [ST2] vs. 17% [ST1], 25% [ST3], and 17% [ST4], p = 0.003). Subtype 4-which received more benzodiazepines and opioids-had the longest duration of delirium (6 days [ST4] vs. 3 [ST1], 4 [ST2], and 3 days [ST3], p < 0.001) and coma (4 days [ST4] vs. 2 [ST1], 1 [ST2], and 2 days [ST3], p < 0.001). Each of the four data-derived delirium subtypes was observed within previously identified psychomotor and risk factor-based delirium subtypes. Clinically significant cognitive impairment affected all subtypes at follow-up, but its severity did not differ by subtype (3-month, p = 0.26; 12-month, p = 0.80).

INTERPRETATION

The four data-derived delirium subtypes identified in this study should now be validated in independent cohorts, examined for differential treatment effects in trials, and inform mechanistic work evaluating treatment targets.

FUNDING

National Institutes of Health (T32HL007820, R01AG027472).

Palliative Care Utilization in Patients Requiring Extracorporeal Membrane Oxygenation: An Observational Study

Palliative care (PC) is a model of care centered around improving the quality of life for individuals with life-limiting illnesses. Few studies have examined its impact in patients on extracorporeal membrane oxygenation (ECMO). We aimed to describe demographics, clinical characteristics, and complications associated with PC consultation in adult patients requiring ECMO support. We analyzed data from an ECMO registry, including patients aged 18 years and older who have received either venoarterial (VA)- or venovenous (VV)-ECMO support between July 2016 and September 2021. We used analysis of variance and Fisher exact tests to identify factors associated with PC consultation. Of 256, 177 patients (69.1%) received VA-ECMO support and 79 (30.9%) received VV-ECMO support. Overall, 115 patients (44.9%) received PC consultation while on ECMO. Patients receiving PC consultation were more likely to be non-white (47% vs. 53%, p = 0.016), have an attending physician from a medical versus surgical specialty (65.3% vs. 39.6%), have VV-ECMO (77.2% vs. 30.5%, p < 0.001), and have longer ECMO duration (6.2 vs. 23.0, p < 0.001). Patients were seen by the PC team on an average of 7.6 times (range, 1-35), with those who died having significantly more visits (11.2 vs. 5.6, p < 0.001) despite the shorter hospital stay. The average time from cannulation to the first PC visit was 5.3 ± 5 days. Congestive heart failure in VA-ECMO, coronavirus disease 2019 infection in VV-ECMO, and non-white race and longer ECMO duration for all patients were associated with PC consultation. We found that despite the benefits of PC, it is underused in this population.

Glomerular hyperfiltration in patients with severe trauma

BACKGROUND AND OBJECTIVE

Augmented renal clearance or glomerular hyperfiltration (GHF) can significantly affect the clinical outcomes of renally eliminated drugs by promoting subtherapeutic drug exposure. The aggression suffered in patients who suffer severe trauma is a predisposition to manifest GHF and the identification of these patients remains a clinical challenge. The main objective of this study was to describe the prevalence of GHF in a cohort of critically ill trauma patients.

MATERIALS AND METHODS

Prospective observational study of a cohort of adult patients admitted after suffering severe trauma or polytrauma in the Anesthesiology ICU of the University Hospital of Albacete (Spain). Creatinine clearance (ClCr) was calculated in a 4-h urine collection sample at 24, 72 and 168 h after admission applying the formula; CrCl: [Diuresis in ml (urine/4 h) × Creatinine in urine (mg/dl)] ÷ [240 (minutes) × Creatinine in plasma (mg/dl)]. A CrCl above 130 mL/min was considered GHF. The analyses were performed with the statistical software R version 4.0.4.

RESULTS

85 patients were included. The median age of the patients was 51 years (IQR 26), 78.82% male. 68 patients were male (78.82%). 75.29% of the patients were polytraumatized. 61 patients (71.76%) presented GHF at some point in the CrCl determination. At 24 h of admission, 56.34% of the patients presented GHF with a mean CrCl of 195.8 ml/min, 61.11% of the patients presented it at 72 h with a mean CrCl of /min and 56.52% presented GHF at 168 h of admission with a mean CrCl of 207 ml/min. A significant positive relationship (p = 0.07) was found between GHF manifested at 72 h and at 168 h. We observed a statistically significant relationship between this phenomenon with younger ages, lower ISS scores and lower plasma creatinines.

CONCLUSIONS

GHF are a common condition in critically ill patients admitted for severe trauma. We recommend the use of CrCl to assess renal function and make dosage adjustments. Studies are required to understand the clinical impact of these phenomena on drug elimination and to be able to establish the ideal dosage in those cases.

Explainable machine learning using perioperative serial laboratory results to predict postoperative mortality in patients with peritonitis-induced sepsis

Purpose

Sepsis is one of the most common causes of death after surgery. Several conventional scoring systems have been developed to predict the outcome of sepsis; however, their predictive power is insufficient. The present study applies explainable machine-learning algorithms to improve the accuracy of predicting postoperative mortality in patients with sepsis caused by peritonitis.

Methods

We performed a retrospective analysis of data from demographic, clinical, and laboratory analyses, including the delta neutrophil index (DNI), WBC and neutrophil counts, and CRP level. Laboratory data were measured before surgery, 12-36 hours after surgery, and 60-84 hours after surgery. The primary study output was the probability of mortality. The areas under the receiver operating characteristic curves (AUCs) of several machine-learning algorithms using the Sequential Organ Failure Assessment (SOFA) and Simplified Acute Physiology Score (SAPS) 3 models were compared. 'SHapley Additive exPlanations' values were used to indicate the direction of the relationship between a variable and mortality.

Results

The CatBoost model yielded the highest AUC (0.933) for mortality compared to SAPS3 and SOFA (0.860 and 0.867, respectively). Increased DNI on day 3, septic shock, use of norepinephrine therapy, and increased international normalized ratio on day 3 had the greatest impact on the model's prediction of mortality.

Conclusion

Machine-learning algorithms increase the accuracy of predicting postoperative mortality in patients with sepsis caused by peritonitis.

Cannulate, extubate, ambulate approach for extracorporeal membrane oxygenation for COVID-19

OBJECTIVE

We compared outcomes in patients with severe COVID-19 versus non-COVID-19-related acute respiratory distress syndrome (ARDS) managed using a dynamic, goal-driven approach to venovenous extracorporeal membrane oxygenation (ECMO).

METHODS

We performed a retrospective, single-center analysis of our institutional ECMO registry using data from 2017 to 2021. We used Kaplan-Meier plots, Cox proportional hazard models, and propensity score analyses to evaluate the association of COVID-19 status (COVID-19-related ARDS vs non-COVID-19 ARDS) and survival to decannulation, discharge, tracheostomy, and extubation. We also conducted subgroup analyses to compare outcomes with the use of extracorporeal cytoreductive techniques (CytoSorb [CytoSorbents Corp] and plasmapheresis).

RESULTS

The sample comprised 128 patients, 50 with COVID-19 and 78 with non-COVID-19 ARDS. Advancing age was associated with decreased probability of survival to decannulation (P = .04). Compared with the non-COVID-19 ARDS group, patients with COVID-19 had a greater probability of survival to extubation (P < .01) and comparable survival to discharge (P = .14).

CONCLUSIONS

Patients with COVID-19 managed with ECMO had comparable outcomes as patients with non-COVID ARDS. A strategy of early extubation and ambulation might be a safe and effective strategy to improve outcomes and survival, even for patients with severe COVID-19.

Concordance between glomerular filtration rate estimation equations and 4-hour urinary creatinine clearance in critically ill patients with severe trauma

BACKGROUND AND OBJECTIVE

There is a growing body of evidence that the equations used to estimate the glomerular filtration rate (GFR) are not suitable in critically ill patients, a population whose GFR fluctuates continuously. Glomerular filtration is usually estimated by measuring urine creatinine clearance (CrCl) at various time points. The aim of our study was to evaluate the performance of the most widely used GFR calculators in the subpopulation of critically ill patients admitted for severe trauma, and to compare the results against determinations of CrCl in urine collected over a 4-h period (4h-CrCl).

MATERIAL AND METHODS

Observational study in patients hospitalized for severe trauma. We measured the 4h-CrCl and estimated GFR using the Cockcroft-Gault, modified Jelliffe, MDRD, t-MDRD, and CKD-EPI equations, adjusting the results for body surface area (BSA) (ml/min/1.73m2). Data were analysed using R version 4.0.4.

RESULTS

A total of 85 patients were included. Median age was 51 years, and 68 were men (78.82%). The mean BSA-adjusted 4h-CrCl (4h-ClCr/1.73m2) was 84.5 ml/min/1.73m2. We found that GFR estimated using the t-MDRD equation correlated significantly with 4h-CrCl/1.73m2. The Cockcroft-Gault equation correlated significantly with 4h-CrCl/1.73m2 when GFR was greater than 130ml/min/m2.

CONCLUSIONS

In ICU patients, glomerular filtration can be reliably estimated by determining urine CrCl, but GFR calculators are not accurate in this population.

End-tidal carbon dioxide's change to fluid challenge versus internal jugular vein dispensability index for predicting fluid responsiveness in septic patients: A prospective, observational study

Background and Aims

The prediction of fluid responsiveness is crucial for the fluid management of septic shock patients. This prospective, observational study was conducted to compare end-tidal carbon dioxide (ETCO2) change due to fluid challenge (FC-induced ΔETCO2) versus internal jugular vein distensibility index (IJVDI) as predictors of fluid responsiveness in such patients.

Methods

Septic hypoperfused mechanically ventilated patients were classified as fluid responders (Rs) and non-responders (NRs) according to the improvement of left ventricular outflow tract-velocity time integral (ΔLVOT-VTI) after fluid challenge (FC). The receiver operating characteristic (ROC) curves of FC-induced ΔETCO2, pre-(FC) IJVDI and their combination for prediction of fluid responsiveness were compared to that of ΔLVOT-VTI% as a gold standard.

Results

Of 140 patients who completed the study, 51 (36.4%) patients were classified as Rs and 89 (63.6%) patients as NRs. With regard to the prediction of fluid responsiveness, no significant difference (P. 0. 384) was found between the diagnostic accuracy of FC-induced ΔETCO2 >2 mmHg (area under the ROC curve [AUC] 0.908, P < 0.001) and that of pre-(FC) IJVDI >18% (AUC 0.938, P < 0.001), but a prediction model combining both markers, ΔETCO2 ≥3 mmHg and IJVDI ≥16%, achieved significantly higher accuracy (AUC 0.982, P < 0.001) than each independent one (P < 0.05).

Conclusion

Under stable ventilatory and metabolic conditions, the predictivity of FC-induced ΔETCO2 >2 mmHg can be comparable to that of pre-(FC) IJVDI >18%. A predictive model combining both FC-induced ΔETCO2 ≥3 mmHg and IJVDI ≥16% can provide higher accuracy than that recorded for each one independently.

Application Prospect of the SOFA Score and Related Modification Research Progress in Sepsis

In 2016, the SOFA score was proposed as the main evaluation system for diagnosis in the definition of sepsis 3.0, and the SOFA score has become a new research focus in sepsis. Some people are skeptical about diagnosing sepsis using the SOFA score. Experts and scholars from different regions have proposed different, modified versions of SOFA score to make up for the related problems with the use of the SOFA score in the diagnosis of sepsis. While synthesizing the different improved versions of SOFA proposed by experts and scholars in various regions, this paper also summarizes the relevant definitions of sepsis put forward in recent years to build a clear, improved application framework of SOFA score. In addition, the comparison between machine learning and SOFA scores related to sepsis is described and discussed in the article. Taken together, by summarizing the application of the improved SOFA score proposed in recent years in the related definition of sepsis, we believe that the SOFA score is still an effective means of diagnosing sepsis, but in the process of the continuous refinement and development of sepsis in the future, the SOFA score needs to be further refined and improved to provide more accurate coping strategies for different patient populations or application directions regarding sepsis. Against the big data background, machine learning has immeasurable value and significance, but its future applications should add more humanistic references and assistance.

Incidence, characteristics and risk factors of delirium in the intensive care unit: An observational study

AIMS AND OBJECTIVE

To investigate the incidence, characteristics and risk factors of delirium in the ICU.

BACKGROUND

Identifying the risk factors of delirium is important for early detection and to prevent adverse consequences.

DESIGN

An observational cohort study conducted according to STROBE Guidelines.

METHOD

The study was conducted with patients who stayed in ICU ≥24 h and were older than 18 years. Patients were assessed twice daily using the RASS and CAM-ICU until either discharge or death. Cumulative incidence was calculated. Demographic/clinical characteristics, length of stay and mortality were compared between patients with and without delirium. A logistic regression model was used to investigate risk factors.

RESULTS

The incidence of delirium was 31.8% and hypoactive type was the most frequent (41.5%). The median onset of delirium was 3 days (IQR = 2) with a mean duration of 5.27 ± 2.32 days. Patients with delirium were significantly older, had higher APACHE-II, SOFA and CPOT scores, higher blood urea levels, higher requirements for mechanical ventilation, sedation and physical restraints, longer stays in the ICU and higher mortality than those without delirium. The logistic regression analysis results revealed that a CPOT score ≥3 points (OR = 4.70, 95% CI: 1.05-20.93; p = .042), physical restraint (OR = 10.40, 95% CI: 2.75-39.27; p = .001) and ICU stay ≥7 days (OR = 7.26, 95% CI: 1.60-32.84; p = .010) were independent risk factors of delirium.

CONCLUSIONS

In this study, the incidence of delirium was high and associated with several factors. It is critical that delirium is considered by all members of the healthcare team, especially nurses, and that protocols are established for improvements.

RELEVANCE TO THE CLINICAL PRACTICE

Based on the results of this study, delirium could be decreased by preventing the presence of pain, prudent use of physical restraints and shortening the ICU stay.

Feeding intolerance in critically ill patients with COVID-19

BACKGROUND & AIMS

Early reports suggest significant difficulty with enteral feeding in critically ill COVID-19 patients. This study aimed to characterize the prevalence, clinical manifestations, and outcomes of feeding intolerance in critically ill patients with COVID-19.

METHODS

We examined 323 adult patients with COVID-19 admitted to the intensive care units (ICUs) of Massachusetts General Hospital between March 11 and June 28, 2020 who received enteral nutrition. Systematic chart review determined prevalence, clinical characteristics, and hospital outcomes (ICU complications, length of stay, and mortality) of feeding intolerance.

RESULTS

Feeding intolerance developed in 56% of the patients and most commonly manifested as large gastric residual volumes (83.9%), abdominal distension (67.2%), and vomiting (63.9%). Length of intubation (OR 1.05, 95% CI 1.03-1.08), ≥1 GI symptom on presentation (OR 0.76, 95% CI 0.59-0.97), and severe obesity (OR 0.29, 95% CI 0.13-0.66) were independently associated with development of feeding intolerance. Compared to feed-tolerant patients, patients with incident feeding intolerance were significantly more likely to suffer cardiac, renal, hepatic, and hematologic complications during their hospitalization. Feeding intolerance was similarly associated with poor outcomes including longer ICU stay (median [IQR] 21.5 [14-30] vs. 15 [9-22] days, P < 0.001), overall hospitalization time (median [IQR] 30.5 [19-42] vs. 24 [15-35], P < 0.001) and in-hospital mortality (33.9% vs. 16.1%, P < 0.001). Feeding intolerance was independently associated with an increased risk of death (HR 3.32; 95% CI 1.97-5.6).

CONCLUSIONS

Feeding intolerance is a frequently encountered complication in critically ill COVID-19 patients in a large tertiary care experience and is associated with poor outcomes.

Predictors of sedation period for critical illness patients focusing on early rehabilitation on the bed

There are various interventions of rehabilitation on the bed, but these are time-consuming and cannot be performed for all patients. The purpose of this study was to identify the patients who require early mobilization based on the level of sedation. We retrospectively evaluated the data of patients who underwent physical therapy, ICU admission of > 48 h, and were discharged alive. Sedation was defined as using sedative drugs and a Richmond Agitation-Sedation Scale score of < - 2. Multiple regression analysis was performed using sedation period as the objective variable, and receiver operating characteristic (ROC) curve and Spearman's rank correlation coefficient were performed. Of 462 patients admitted to the ICU, the data of 138 patients were analyzed. The Sequential Organ Failure Assessment (SOFA) score and non-surgery and emergency surgery cases were extracted as significant factors. The ROC curve with a positive sedation period of more than 3 days revealed the SOFA cutoff score was 10. A significant positive correlation was found between sedation period and the initial day on early mobilization. High SOFA scores, non-surgery and emergency surgery cases may be indicators of early mobilization on the bed in the ICU.

Domain Adaptation Using Convolutional Autoencoder and Gradient Boosting for Adverse Events Prediction in the Intensive Care Unit

More than 5 million patients have admitted annually to intensive care units (ICUs) in the United States. The leading causes of mortality are cardiovascular failures, multi-organ failures, and sepsis. Data-driven techniques have been used in the analysis of patient data to predict adverse events, such as ICU mortality and ICU readmission. These models often make use of temporal or static features from a single ICU database to make predictions on subsequent adverse events. To explore the potential of domain adaptation, we propose a method of data analysis using gradient boosting and convolutional autoencoder (CAE) to predict significant adverse events in the ICU, such as ICU mortality and ICU readmission. We demonstrate our results from a retrospective data analysis using patient records from a publicly available database called Multi-parameter Intelligent Monitoring in Intensive Care-II (MIMIC-II) and a local database from Children's Healthcare of Atlanta (CHOA). We demonstrate that after adopting novel data imputation on patient ICU data, gradient boosting is effective in both the mortality prediction task and the ICU readmission prediction task. In addition, we use gradient boosting to identify top-ranking temporal and non-temporal features in both prediction tasks. We discuss the relationship between these features and the specific prediction task. Lastly, we indicate that CAE might not be effective in feature extraction on one dataset, but domain adaptation with CAE feature extraction across two datasets shows promising results.

Survey of Glasgow Coma Scale and PaO 2 / FIO 2 ratio assessment methods for the Sequential Organ Failure Assessment score in Japanese intensive care units

Aim

Accurately calculating the Sequential Organ Failure Assessment (SOFA) score is essential for medical resource allocation and decision‐making. This study surveyed Japanese intensive care units regarding their assessment of the Glasgow Coma Scale (GCS) and PaO₂/FIO₂ ratio, components of the SOFA score.

Methods

A cross‐sectional, web‐based survey was conducted among healthcare workers. The survey consisted of questions about the intensive care units where they work and questions for respondents. It was distributed to healthcare workers by e‐mail through the Japanese Society of Intensive Care Medicine mailing list and social networking service.

Results

Among 414 responses, we obtained 211 valid responses and 175 survey results from unique intensive care units. When assessing GCS in patients under the influence of sedatives, 45.1% (95% confidence interval, 37.6–52.8) of intensive care units assessed GCS assuming that the sedatives had no influence. For the PaO₂/FIO₂ ratio in the SOFA score, calculation based on the Japanese Intensive Care Patient Database definition document and mechanical ventilator settings were the most common methods in patients with oxygen masks and on extracorporeal membrane oxygenation, respectively. Approximately 60% of respondents indicated that it was difficult to assess GCS assuming that sedatives had no influence.

Conclusion

In patients under the influence of sedatives, approximately half of the intensive care units assessed assumed GCS. There was variation in the methods used to assess the PaO₂/FIO₂ ratio. Standardized assessment methods for GCS and the PaO₂/FIO₂ ratio are needed to obtain valid SOFA score.

Performance of Sequential Organ Failure Assessment and Simplified Acute Physiology Score II for Post-Cardiac Surgery Patients in Intensive Care Unit

Background: The aim of this study is to assess the performance of Sequential Organ Failure Assessment (SOFA) score and Simplified Acute Physiology Score (SAPS II) on outcomes of patients with cardiac surgery and identify the cutoff values to provide a reference for early intervention.

Methods: All data were extracted from MIMIC-III (Medical Information Mart for Intensive Care-III) database. Cutoff values were calculated by the receiver-operating characteristic curve and Youden indexes. Patients were grouped, respectively, according to the cutoff values of SOFA and SAPS II. A non-adjusted model and adjusted model were established to evaluate the prediction of risk. Comparison of clinical efficacy between two scoring systems was made by decision curve analysis (DCA). The primary outcomes of this study were in-hospital mortality, 28-day mortality, 90-day mortality, and 1-year mortality after cardiac surgery. The secondary outcomes included length of hospital stay and intensive care unit (ICU) stay and the incidence of acute kidney injury (AKI) within 7 days after ICU admission.

Results: A total of 6,122 patients were collected and divided into the H-SOFA group (SOFA ≥ 7) and L-SOFA group (SOFA < 7) or H-SAPS II group (SAPS II ≥ 43) and L-SAPS II group (SAPS II < 43). In-hospital mortality, 28-day mortality, 90-day mortality, and 1-year mortality were higher, the length of hospital and ICU stay were longer in the H-SOFA group than in the L-SOFA group (p < 0.05), while the incidence of AKI was not significantly different. In-hospital mortality, 28-day mortality, 90-day mortality, 1-year mortality, and the incidence of AKI were all significantly higher in the H-SAPS II group than in the L-SAPS II group (p < 0.05). Hospital stay and ICU stay were longer in the H-SAPS II group than in the L-SAPS II group (p < 0.05). According to DCA, the SAPS II scoring system had more net benefits on assessing the long-term mortality compared with the SOFA scoring system.

Conclusion: Exceeding the cutoff values of SOFA and SAPS II scores could lead to increased mortality and extended length of ICU and hospital stay. The SAPS II scoring system had a better discriminative performance of 90-day mortality and 1-year mortality in post-cardiac surgery patients than the SOFA scoring system. Emphasizing the critical value of the scoring system is of significance for timely treatment.

GDF-15 Predicts In-Hospital Mortality of Critically Ill Patients with Acute Kidney Injury Requiring Continuous Renal Replacement Therapy: A Multicenter Prospective Study

Growth differentiation factor-15 (GDF-15) is a stress-responsive cytokine. This study evaluated the association between GDF-15 and in-hospital mortality among patients with severe acute kidney injury (AKI) requiring continuous renal replacement therapy (CRRT). Among the multicenter prospective CRRT cohort between 2017 and 2019, 66 patients whose blood sample was available were analyzed. Patients were divided into three groups according to the GDF-15 concentrations. The median GDF-15 level was 7865.5 pg/mL (496.9 pg/mL in the healthy control patients). Baseline characteristics were not different among tertile groups except the severity scores and serum lactate level, which were higher in the third tertile. After adjusting for confounding factors, the patients with higher GDF-15 had significantly increased risk of mortality (second tertile: adjusted hazards ratio [aHR], 3.67; 95% confidence interval [CI], 1.05-12.76; p = 0.041; third tertile: aHR, 6.81; 95% CI, 1.98-23.44; p = 0.002). Furthermore, GDF-15 predicted in-hospital mortality (area under the curve, 0.710; 95% CI, 0.585-0.815) better than APACHE II and SOFA scores. Serum GDF-15 concentration was elevated in AKI patients requiring CRRT, higher in more severe patients. GDF-15 is a better independent predictor for in-hospital mortality of critically ill AKI patients than the traditional risk scoring system such as APACHE II and SOFA scores.

In-hospital mortality associated factors in elderly patients with invasive mechanical ventilation in the emergency department

AIMS

To identify factors associated with in-hospital mortality, to estimate the intubation rate and to describe in-hospital mortality in patients over 65 years old with invasive mechanical ventilation (IMV) in the emergency department (ED).

METHODS

Retrospective cohort study of patients over 65 years old, who were intubated in an ED of a high complexity hospital between 2016 and 2018. Demographic data, comorbidities, and severity scores on admission were described. Bivariate and multivariate analyses were performed with logistic regression according to mortality and possible confounders.

RESULTS

A total of 285 patients with a mean age of 80 years required IMV in the emergency department, for a median of 3 days, and with a mean APACHE II score of 20 points of severity. The IMV rate was .48% (95% CI .43-.54), and 55.44% (158) died. Mortality-associated factors after age and sex adjustment were stroke (OR 2.13; 95% CI 1.21-3.76), chronic kidney failure, (OR 4.,38; 95% CI 1.91-10.04), Charlson index (OR 1.19; 95% CI 1.02-1.38), APACHE II score (OR 1.07; 95% CI 1.02-1.12), and SOFA score (OR 1.14; 95% CI 1.03-1.27).

DISCUSSION

Our IMV rate was lower than that stated by Johnson et al. in the United States in 2018 (.59%). In-hospital mortality in our study exceeded that predicted by the APACHE II score (40%) and SOFA (33%). However it was consistent with that reported by Lieberman et al. in Israel and Esteban et al. in the United States.

CONCLUSIONS

Although the IMV rate was low in the ED, more than half the patients died during hospitalization. Pre-existing cerebrovascular and renal diseases and high results in the comorbidities index and severity scores on admission were independent factors associated with in-hospital mortality.

Intensive Care Unit Scoring Systems

BACKGROUND

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.

OBJECTIVE

To describe the characteristics and applications of the scoring systems most frequently applied to critically ill patients.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Systemic immune-inflammation index as a promising predictor of mortality in patients with acute coronary syndrome: a real-world study

Objective

Prognostic indicators in acute coronary syndrome (ACS) would aid in decision-making and identifying high-risk patients. The systemic immune-inflammation index (SII) has good prognostic value in many diseases; however, its use has not been reported for ACS. We aimed to determine the associations between the SII and outcomes in patients with ACS, with adjustment for confounders.

Methods

In this retrospective cohort study, we used the MIMIC-III (Multiparameter Intelligent Monitoring in Intensive Care) database and the eICU Collaborative Research Database. The primary outcome was 30-day mortality. Cox regression analysis was performed to determine the relationship between the SII and patient outcomes, and we conducted subgroup analysis and smooth curve fitting.

Results

We identified 4699 patients with ACS: 1741 women and 2949 men, mean age 82.8±29.7 years, and mean SII 72.58±12.9. For 30-day all-cause mortality, the unadjusted hazard ratio (HR) (95% confidence interval [CI]) of SII <69.4 and SII >88.8 were 1.25 (1.04, 1.50) and 1.38 (1.15, 1.65), respectively. With SII >88.8, this association remained significant after adjustment for numerous potential confounders: HR 1.27 (1.06, 1.52). A similar relationship was observed for 90-day and 1-year all-cause mortality.

Conclusions

SII is a promising prognostic indicator for unselected patients with ACS. This finding needs to be confirmed in prospective studies.

German version of the Chelsea Critical Care Physical Assessment Tool (CPAx-GE): translation, cross-cultural adaptation, validity, and reliability

PURPOSE

To translate and cross-culturally adapt the Chelsea Critical Care Physical Assessment tool from English to German (CPAx-GE) and to examine its validity and reliability.

MATERIALS AND METHODS

Following a forward-backward translation including an expert round table discussion, the measurement properties of the CPAx-GE were explored in critically ill, mechanically ventilated adults. We investigated construct, cross-sectional, and cross-cultural validity of the CPAx-GE with other measurement instruments at pre-specified timepoints, analysed relative reliability with intraclass correlation coefficients (ICCs) and determined absolute agreement with the Bland-Altman plots.

RESULTS

Consensus for the translated CPAx-GE was reached. Validity was excellent with >80% of the pre-specified hypotheses accepted at baseline, critical care, and hospital discharge. Interrater reliability was high (ICCs > 0.8) across all visits. Limit of agreement ranged from -2 to 2 points. Error of measurement was small, floor, and ceiling effects limited.

CONCLUSIONS

The CPAx-GE demonstrated excellent construct, cross-sectional, and cross-cultural validity as well as high interrater reliability in critically ill adults with prolonged mechanical ventilation at baseline, critical care, and hospital discharge. Consequently, the CPAx-GE can be assumed equal to the original and recommended in the German-speaking area to assess physical function and activity of critically ill adults across the critical care and hospital stay. Trial registration: German Clinical Trials Register (DRKS) identification number: DRKS00012983 (https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00012983), registered on 20 September 2017, first patient enrolled on 21 November 2017.Implications for rehabilitationEarly rehabilitation of critically ill patients is recommended to prevent and treat the subsequent functional disability, but a suitable measurement instrument for the German-speaking area is lacking.The translated, cross-culturally adapted German CPAx demonstrated excellent validity and reliability in assessing physical function and activity in critically ill adults.Cross-sectional validity of the CPAx has been newly established and allows the use of this tool at clinically relevant time-points in the course of a critical illness.The CPAx-GE can therefore be used in clinical practice by German-speaking therapists to assess physical function and activity during early rehabilitation in the ICU and hospital.

Current Utility of Sequential Organ Failure Assessment Score: A Literature Review and Future Directions

The Sequential Organ Failure Assessment (SOFA) score is commonly used in the Intensive Care Unit (ICU) to evaluate, prognosticate and assess patients. Since its validation, the SOFA score has served in various settings, including medical, trauma, surgical, cardiac, and neurological ICUs. It has been a strong mortality predictor and literature over the years has documented the ability of the SOFA score to accurately distinguish survivors from non-survivors on admission. Over the years, multiple variations have been proposed to the SOFA score, which have led to the evolution of alternate validated scoring models replacing one or more components of the SOFA scoring system. Various SOFA based models have been used to evaluate specific clinical populations, such as patients with cardiac dysfunction, hepatic failure, renal failure, different races and public health illnesses, etc. This study is aimed to conduct a review of modifications in SOFA score in the past several years. We review the literature evaluating various modifications to the SOFA score such as modified SOFA, Modified SOFA, modified Cardiovascular SOFA, Extra-renal SOFA, Chronic Liver Failure SOFA, Mexican SOFA, quick SOFA, Lactic acid quick SOFA (LqSOFA), SOFA in hematological malignancies, SOFA with Richmond Agitation-Sedation scale and Pediatric SOFA. Various organ systems, their relevant scoring and the proposed modifications in each of these systems are presented in detail. There is a need to incorporate the most recent literature into the SOFA scoring system to make it more relevant and accurate in this rapidly evolving critical care environment. For future directions, we plan to put together most if not all updates in SOFA score and probably validate it in a large database a single institution and validate it in multisite data base.

SARS-CoV-2 infection: molecular mechanisms of severe outcomes to suggest therapeutics

Introduction:The year 2020 was defined by the 29,903 base pairs of RNA that codes for the SARS-CoV-2 genome. SARS-CoV-2 infects humans to cause COVID-19, spreading from patient-to-patient yet impacts patients very divergently.Areas covered: Within this review, we address the known molecular mechanisms and supporting data for COVID-19 clinical course and pathology, clinical risk factors and molecular signatures, therapeutics of severe COVID-19, and reinfection/vaccination. Literature and published datasets were reviewed using PubMed, Google Scholar, and NCBI SRA tools. The combination of exaggerated cytokine signaling, pneumonia, NETosis, pyroptosis, thrombocytopathy, endotheliopathy, multiple organ dysfunction syndrome (MODS), and acute respiratory distress syndrome (ARDS) create a positive feedback loop of severe damage in patients with COVID-19 that impacts the entire body and may persist for months following infection. Understanding the molecular pathways of severe COVID-19 opens the door for novel therapeutic design. We summarize the current insights into pathology, risk factors, secondary infections, genetics, omics, and drugs being tested to treat severe COVID-19.Expert opinion: A growing level of support suggests the need for stronger integration of biomarkers and precision medicine to guide treatment strategies of severe COVID-19, where each patient has unique outcomes and thus require guided treatment.

How ICU Patient Severity Affects Communicative Interactions Between Healthcare Professionals: A Study Utilizing Wearable Sociometric Badges

Numerous factors affecting the interactions between healthcare professionals in the workplace demand a comprehensive understanding if the quality of patient healthcare is to be improved. Our previous cross-sectional analysis showed that patient severity scores [i.e., Acute Physiology and Chronic Health Evaluation (APACHE) II] in the 24 h following admission positively correlated with the length of the face-to-face interactions among ICU healthcare professionals. The present study aims to address how the relationships between patient severity and interaction lengths can change over a period of time during both admission and treatment in the ICU. We retrospectively analyzed data prospectively collected between 19 February to 17 March 2016 from an open ICU in a University Hospital in Japan. We used wearable sensors to collect a spatiotemporal distribution dataset documenting the face-to-face interactions between ICU healthcare professionals, which involved 76 ICU staff members, each of whom worked for 160 h, on average, during the 4-week period of data collection. We studied the longitudinal relationships among these interactions, which occurred at the patient bedside, vis-à-vis the severity of the patient's condition [i.e., the Sequential Organ Failure Assessment (SOFA) score] assessed every 24 h. On Day 1, during which a total of 117 patients stayed in the ICU, we found statistically significant positive associations between the interaction lengths and their SOFA scores, as shown by the Spearman's correlation coefficient value (R) of 0.447 (p < 0.01). During the course of our observation from Day 1 to Day 10, the number of patients (N) who stayed in the ICU gradually decreased (N = 117, Day1; N = 10, Day 10), as they either were discharged or died. The statistically significant positive associations of the interaction lengths with the SOFA scores disappeared from Days 2 to 6, but re-emerged on Day 7 (R = 0.620, p < 0.05) and Day 8 (R = 0.625, p < 0.05), then disappearing again on Days 9 and 10. Whereas all 6 SOFA sub-scores correlated well with the interaction lengths on Day 1, only a few of the sub-scores (coagulation, cardiovascular, and central nervous system scores) did so; specifically, those on Days 7 and 8. The results suggest that patient severity may play an important role in affecting the interactions between ICU healthcare professionals in a time-related manner on ICU Day 1 and on Days 7/8.

A machine learning approach for mortality prediction only using non-invasive parameters

At present, the traditional scoring methods generally utilize laboratory measurements to predict mortality. It results in difficulties of early mortality prediction in the rural areas lack of professional laboratorians and medical laboratory equipment. To improve the efficiency, accuracy, and applicability of mortality prediction in the remote areas, a novel mortality prediction method based on machine learning algorithms is proposed, which only uses non-invasive parameters readily available from ordinary monitors and manual measurement. A new feature selection method based on the Bayes error rate is developed to select valuable features. Based on non-invasive parameters, four machine learning models were trained for early mortality prediction. The subjects contained in this study suffered from general critical diseases including but not limited to cancer, bone fracture, and diarrhea. Comparison tests among five traditional scoring methods and these four machine learning models with and without laboratory measurement variables are performed. Only using the non-invasive parameters, the LightGBM algorithms have an excellent performance with the largest accuracy of 0.797 and AUC of 0.879. There is no apparent difference between the mortality prediction performance with and without laboratory measurement variables for the four machine learning methods. After reducing the number of feature variables to no more than 50, the machine learning models still outperform the traditional scoring systems, with AUC higher than 0.83. The machine learning approaches only using non-invasive parameters achieved an excellent mortality prediction performance and can equal those using extra laboratory measurements, which can be applied in rural areas and remote battlefield for mortality risk evaluation. Graphical abstract.

Age is not a risk factor in survival of severely ill patients with co-morbidities in a medical intensive care unit

BACKGROUND

The individuals over 65 years old constitute an important patient population of medical intensive care units (ICUs).

AIM

To evaluate the risk factors for mortality in a medical ICU consisting a group of patients with a large number of co-morbidities.

METHODS

This is a retrospective study involving patients who were followed for more than 48 h. The cohort was divided into two groups according to age: (1) young, < 65 years old, and (2) elderly, ≥ 65 years old.

RESULTS

A total of 693 patients (303 F, 390 M) were included. The median age was 68 years (18-97). There were 279 (40.3%) young and 414 (59.7%) elderly patients. There was no difference between the groups in gender and mortality (p = 0.436, p = 0.932, respectively). Most of the co-morbid diseases were more common in the elderly except solid malignancies which were more common in young patients (p = 0.033). Long ICU stay, long hospital stay before ICU, high APACHE II and Charlson co-morbidity index scores, pneumonia, acute hepatic failure/coma, malignancy, acute hemodialysis, need for vasopressors, and invasive mechanical ventilation were independent predictors of ICU mortality.

CONCLUSION

Age and gender were not found to be predictors of mortality. There was no survival advantage between young and elderly patients. Co-morbid diseases, apart from malignancy, had no effect on mortality. In developing countries, where patients with terminal illness and multiple co-morbid diseases are treated in the ICU, age should not be a determining factor in patient selection for ICU or in the treatment decisions to be applied to patients.

Comparison of the Automated Pediatric Logistic Organ Dysfunction-2 Versus Manual Pediatric Logistic Organ Dysfunction-2 Score for Critically Ill Children

OBJECTIVES

The Pediatric Logistic Organ Dysfunction-2 is a validated score that quantifies organ dysfunction severity and requires complex data collection that is time-consuming and subject to errors. We hypothesized that a computer algorithm that automatically collects and calculates the Pediatric Logistic Organ Dysfunction-2 (aPELOD-2) score would be valid, fast and at least as accurate as a manual approach (mPELOD-2).

DESIGN

Retrospective cohort study.

SETTING

Single center tertiary medical and surgical pediatric critical care unit (Sainte-Justine Hospital, Montreal, Canada).

PATIENTS

Critically ill children participating in four clinical studies between January 2013 and August 2018, a period during which mPELOD-2 data were manually collected.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The aPELOD-2 was calculated for all consecutive admissions between 2013 and 2018 (n = 5,279) and had a good survival discrimination with an area under the receiver operating characteristic curve of 0.84 (95% CI, 0.81-0.88). We also collected data from four single-center studies in which mPELOD-2 was calculated (n = 796, 57% medical, 43% surgical) and compared these measurements to those of the aPELOD-2. For those patients, median age was 15 months (interquartile range, 3-73 mo), median ICU stay was 5 days (interquartile range, 3-9 d), mortality was 3.9% (n = 28). The intraclass correlation coefficient between mPELOD-2 and aPELOD-2 was 0.75 (95% CI, 0.73-0.77). The Bland-Altman showed a bias of 1.9 (95% CI, 1.7-2) and limits of agreement of -3.1 (95% CI, -3.4 to -2.8) to 6.8 (95% CI, 6.5-7.2). The highest agreement (Cohen's Kappa) of the Pediatric Logistic Organ Dysfunction-2 components was noted for lactate level (0.88), invasive ventilation (0.86), and creatinine level (0.82) and the lowest for the Glasgow Coma Scale (0.52). The proportion of patients with multiple organ dysfunction syndrome was higher for aPELOD-2 (78%) than mPELOD-2 (72%; p = 0.002). The aPELOD-2 had a better survival discrimination (area under the receiver operating characteristic curve, 0.81; 95% CI, 0.72-0.90) over mPELOD-2 (area under the receiver operating characteristic curve, 0.70; 95% CI, 0.59-0.82; p = 0.01).

CONCLUSIONS

We successfully created a freely available automatic algorithm to calculate the Pediatric Logistic Organ Dysfunction-2 score that is less labor intensive and has better survival discrimination than the manual calculation. Use of an automated system could greatly facilitate integration of the Pediatric Logistic Organ Dysfunction-2 score at the bedside and within clinical decision support systems.

Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy

Background

Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment (SOFA) scoring systems do not adequately predict mortality of patients undergoing continuous renal replacement therapy (CRRT) for severe acute kidney injury. Accordingly, the present study applies machine learning algorithms to improve prediction accuracy for this patient subset.

Methods

We randomly divided a total of 1571 adult patients who started CRRT for acute kidney injury into training (70%, n = 1094) and test (30%, n = 477) sets. The primary output consisted of the probability of mortality during admission to the intensive care unit (ICU) or hospital. We compared the area under the receiver operating characteristic curves (AUCs) of several machine learning algorithms with that of the APACHE II, SOFA, and the new abbreviated mortality scoring system for acute kidney injury with CRRT (MOSAIC model) results.

Results

For the ICU mortality, the random forest model showed the highest AUC (0.784 [0.744–0.825]), and the artificial neural network and extreme gradient boost models demonstrated the next best results (0.776 [0.735–0.818]). The AUC of the random forest model was higher than 0.611 (0.583–0.640), 0.677 (0.651–0.703), and 0.722 (0.677–0.767), as achieved by APACHE II, SOFA, and MOSAIC, respectively. The machine learning models also predicted in-hospital mortality better than APACHE II, SOFA, and MOSAIC.

Conclusion

Machine learning algorithms increase the accuracy of mortality prediction for patients undergoing CRRT for acute kidney injury compared with previous scoring models.

Antibacterial effect of fosfomycin tromethamine on the bacteria inside urinary infection stones

OBJECTIVE

This study sought to evaluate the antibacterial effect of fosfomycin tromethamine (FT) on the bacteria inside urinary infection stones.

METHODS

The internal structures of urinary stones were observed via scanning electron microscopy to verify the presence of internal bacteria. We randomly assigned equal numbers of patients with kidney stones who met the inclusion criteria into two groups in a prospective study and treated them with different perioperative antibiotics. One group (experimental group) was treated with FT, and the other (control group) was treated with cefuroxime sodium. All stone specimens were collected via percutaneous nephrolithotomy (PCNL). The primary infection stones were screened via a stone component analysis, 30 cases in the experimental group and 31 cases in the control group. High-performance liquid chromatography (HPLC)-mass spectrometry was used to measure the drug concentration inside the stones, the bacterial count was calculated via stone culture, and the clinical infection index were monitored for between-group comparisons.

RESULTS

Compared with the control group, the experimental group had a higher internal drug concentration, a higher drug sensitivity against various pathogenic bacteria, a lower bacterial colony count in the stone culture, and a lower incidence of postoperative clinical infection.

CONCLUSIONS

FT is more effective than cefuroxime, which is commonly used during the perioperative period of urinary stones, and exerts a high antibacterial effect on these internal bacteria, and effectively reduces the probability of infection and sepsis after urinary stone surgery. FT can be used as an antibiotic during the perioperative period of urinary stones.

The SOFA score-development, utility and challenges of accurate assessment in clinical trials

The Sequential Organ Failure Assessment or SOFA score was developed to assess the acute morbidity of critical illness at a population level and has been widely validated as a tool for this purpose across a range of healthcare settings and environments.In recent years, the SOFA score has become extensively used in a range of other applications. A change in the SOFA score of 2 or more is now a defining characteristic of the sepsis syndrome, and the European Medicines Agency has accepted that a change in the SOFA score is an acceptable surrogate marker of efficacy in exploratory trials of novel therapeutic agents in sepsis. The requirement to detect modest serial changes in a patients' SOFA score therefore means that increased clarity on how the score should be assessed in different circumstances is required.This review explores the development of the SOFA score, its applications and the challenges associated with measurement. In addition, it proposes guidance designed to facilitate the consistent and valid assessment of the score in multicentre sepsis trials involving novel therapeutic agents or interventions.ConclusionThe SOFA score is an increasingly important tool in defining both the clinical condition of the individual patient and the response to therapies in the context of clinical trials. Standardisation between different assessors in widespread centres is key to detecting response to treatment if the SOFA score is to be used as an outcome in sepsis clinical trials.

Investigate predictive capacity of in-hospital mortality of four severity score systems on critically ill patients with acute kidney injury

Although significant improvements have been achieved in the renal replacement therapy of acute kidney injury (AKI), the mortality of patients with AKI remains high. The aim of this study is to prospectively investigate the capacity of Acute Physiology and Chronic Health Evaluation version II (APACHE II), Simplified Acute Physiology Score version II (SAPS II), Sepsis-related Organ Failure Assessment (SOFA) and Acute Tubular Necrosis Individual Severity Index (ATN-ISI) to predict in-hospital mortality of critically ill patients with AKI. A prospective observational study was conducted in a university teaching hospital. 189 consecutive critically ill patients with AKI were selected according Risk, Injury, Failure, Loss, or End-stage kidney disease criteria. APACHE II, SAPS II, SOFA and ATN-ISI counts were obtained within the first 24 hours following admission. Receiver operating characteristic analyses (ROCs) were applied. Area under the ROC curve (AUC) was calculated. Sensitivity and specificity of in-hospital mortality prediction were calculated. In this study, the in-hospital mortality of critically ill patients with AKI was 37.04% (70/189). AUC of APACHE II, SAPS II, SOFA and ATN-ISI was 0.903 (95% CI 0.856 to 0.950), 0.893 (95% CI 0.847 to 0.940), 0.908 (95% CI 0.866 to 0.950) and 0.889 (95% CI 0.841 to 0.937) and sensitivity was 90.76%, 89.92%, 90.76% and 89.08% and specificity was 77.14%, 70.00%, 71.43% and 71.43%, respectively. In this study, it was found APACHE II, SAPS II, SOFA and ATN-ISI are reliable in-hospital mortality predictors of critically ill patients with AKI. Trial registration number: NCT00953992.

Application of pulse index continuous cardiac output system in elderly patients with acute myocardial infarction complicated by cardiogenic shock: A prospective randomized study

BACKGROUND

Cardiogenic shock (CS) secondary to acute myocardial infarction (AMI) complicates management of the condition, and often leads to poor prognosis. Prompt and accurate monitoring of cardiovascular and accompanying hemodynamic changes is crucial in achieving adequate management of the condition. Advances in technology has availed procedures such as pulse index continuous cardiac output (PiCCO), which can offer precise monitoring of cardiovascular functions and hemodynamic parameters. In this study, PiCCO is evaluated for its potential utility in improving management and clinical outcomes among elderly patients with AMI complicated by CS.

AIM

To assess whether use of the PiCCO system can improve clinical outcomes in elderly patients with AMI complicated by CS.

METHODS

Patients from emergency intensive care units (EICU) or coronary care units (CCU) were randomized to receive PiCCO monitoring or not. The APACHE II score, SOFA score, hs-TnI, NT-proBNP, PaO₂/FiO₂ ratio and lactate levels on day 1, 3 and 7 after treatment were compared. The infusion and urine volume at 0-24 h, 24-48 h and 48-72 h were recorded, as were the cardiac index (CI), extravascular lung water index (EVLWI), intrathoracic blood volume index (ITBVI) and global end diastolic volume index (GEDVI) at similar time intervals.

RESULTS

Sixty patients with AMI complicated by CS were included in the study. The PiCCO group had a significantly lower APACHE II score, SOFA score, hs-TnI and NT-proBNP levels on day 1, 3 and 7 after treatment. The infusion and urine volume during 0-24 h in the PiCCO group were significantly greater, and this group also showed significantly higher ADL scores. Furthermore, the PiCCO group spent lesser days on vasoactive agents, mechanical ventilation, and had a reduced length of stay in EICU/CCU. Additionally, the CI was significantly higher at 48 h and 72 h in the PiCCO group compared with that at 24 h, and the EVLWI, ITBVI and GEDVI were significantly decreased at 48 h and 72 h.

CONCLUSION

Applying the PiCCO system could improve the clinical outcomes of elderly patients with AMI complicated by CS.

Factors Influencing How Intensive Care Unit Nurses Allocate Their Time

Spending time with the patient is essential for intensive care unit (ICU) nurses to detect clinical change. This article reports on an examination of factors influencing nurses’ activity time allocation. Data were analyzed from a prospective time and motion study of medical ICU nurses. Nurse demographic data and observation, electronic locator technology, and electronic medical record log data were collected over 12 days from 11 registered nurses. Charlson Co-Morbidity Index and Sequential Organ Failure Assessment scores were calculated for patient assignments. Nurses averaged 78.04 ( SD = 47.85) min per patient on activities in the patient room. Years of ICU nursing experience and the patient’s Charlson Co-Morbidity Index was significantly associated with time spent in the patient’s room. Neither nursing education nor specialty certification was found to influence time spent in a patient’s room. Using technology can advance understanding of nurses’ time allocation leading to interventions optimizing time spent with the patient.

Vacuum-Assisted Wound Closure and Permanent Onlay Mesh-Mediated Fascial Traction: A Novel Technique for the Prevention of Incisional Hernia after Open Abdomen Therapy Including Results From a Retrospective Case Series

BACKGROUND AND AIMS

Incisional hernia development is a frequent long-term sequel after open abdomen treatment. This report describes a novel technique, the vacuum-assisted wound closure and permanent onlay mesh-mediated fascial traction for temporary and final closure of the open abdomen, with the intention to decrease incisional hernia rates. Primary aim was to evaluate incisional hernia development and secondary aims to describe short-term complications and patient-reported outcome.

MATERIALS AND METHODS

The basics of the technique is an onlay mesh, applied early during open abdomen treatment by suturing to the fascia in two rows with a 3- to 4-cm overlap from the midline incision, used for traction and kept for reinforced permanent closure. A retrospective case series, including chart review, evaluation of computed tomography/ultrasound images, and an out-patient clinical examination were performed. The patients were asked to answer a modified version of the ventral hernia pain questionnaire.

RESULTS

A total of 11 patients were treated with vacuum-assisted wound closure and permanent onlay mesh-mediated fascial traction with median follow-up of 467 days. Fascial closure rate was 100% and 30 day mortality 0%. Two of nine patients, eligible for incisional hernia follow-up, developed a hernia. Neither of the hernias were symptomatic nor clinically detectable. Six of 10 patients eligible for short-term follow-up had a prolonged wound-healing time exceeding 3 weeks. One of seven patients eligible for patient-reported outcome have had pain during the last week.

CONCLUSION

The vacuum-assisted wound closure and permanent onlay mesh-mediated fascial traction is a promising new technique for open abdomen treatment and reinforced fascial closure. The results of the first 11 patients treated with this technique show a low incisional hernia rate with manageable short-term wound complications and few patient-reported disadvantages.

Impact of the Chelsea critical care physical assessment (CPAx) tool on clinical outcomes of surgical and trauma patients in an intensive care unit: An experimental study

Background

Critically ill patients following traumatic injury or major surgery are at risk of loss of skeletal muscle mass, which leads to decreased physical function. Early rehabilitation in an intensive care unit (ICU) is thought to preserve or restore physical functioning. The Chelsea critical care physical assessment (CPAx) is a measurement tool used to assess physical function in the ICU.

Objectives

To determine whether the use of the CPAx tool as part of physiotherapy patient assessment, in two adult trauma and surgical ICU settings where early patient mobilisation forms part of standard physiotherapy practice, had an impact on ICU and hospital length of stay (LOS) through delivery of problem-oriented treatment plans.

Method

A single-centred pre–post quasi-experimental study was conducted. The population was a consecutive sample of surgical and trauma ICU patients. Participants’ functional ability was assessed with the CPAx tool on alternative days during their ICU stay, and rehabilitation goals were modified according to their CPAx score. Intensive care unit and hospital LOS data were collected and compared to data of a matched historical control group. Descriptive and inferential statistics were used.

Results

A total of 26 ICU patients were included in the intervention group (n = 26). They received CPAx-guided therapy, and outcomes were matched with ICU patients in the historical control group (n = 26). The median sequential organ failure assessment (SOFA) score was significantly higher in the control group (p = 0.005) (3.5 [IQR 2–6.3]) versus (2 [IQR 1.8–2.5]) for the intervention group. The median admission CPAx score for the intervention group was 33.5 (IQR 16.1–44), and the median ICU discharge score was 38 (IQR 28.5–43.8). No significant differences were found in ICU days (control 2.7 [IQR 1.1–5.2]; intervention 3.7 [IQR 2.3–5.4]; p = 0.27) or hospital LOS (control 13.5 [IQR 9.3–18.3]; intervention 11.4 [IQR 8.4–20.3], p = 0.42). Chelsea critical care physical assessment scores on ICU admission had a moderate negative correlation with hospital LOS (r = −0.58, p = 0.00, n = 23). Chelsea critical care physical assessment scores at ICU discharge had strong positive correlation with discharge SOFA scores (r = 0.7; p = 0.025; n = 10).

Conclusion

Problem-oriented patient rehabilitation informed by the CPAx tool resulted in improvement of physical function but did not reduce ICU or hospital LOS.

Clinical implications

A higher level of physical function at ICU admission, measured with CPAx, was associated with shorter hospital LOS.

Ceftolozane/tazobactam for the treatment of multidrug resistant Pseudomonas aeruginosa: experience from the Balearic Islands

A prospective, descriptive observational study of consecutive patients treated with ceftolozane/tazobactam in the reference hospital of the Balearic Islands (Spain), between May 2016 and September 2017, was performed. Demographic, clinical, and microbiological variables were recorded. The later included resistance profile, molecular typing, and whole genome sequencing of isolates showing resistance development. Fifty-eight patients were treated with ceftolozane/tazobactam. Thirty-five (60.3%) showed respiratory tract infections, 21 (36.2%) received monotherapy, and 37 (63.8%) combined therapy for ≥ 72 h, mainly with colistin (45.9%). In 46.6% of the patients, a dose of 1/0.5 g/8 h was used, whereas 2/1 g/8 h was used in 41.4%. In 56 of the cases (96.6%), the initial Pseudomonas aeruginosa isolates recovered showed a multidrug resistant (MDR) phenotype, and 50 of them (86.2%) additionally met the extensively drug resistant (XDR) criteria and were only susceptible colistin and/or aminoglycosides (mostly amikacin). The epidemic high-risk clone ST175 was detected in 50% of the patients. Clinical cure was documented in 37 patients (63.8%) and resistance development in 8 (13.8%). Clinical failure was associated with disease severity (SOFA), ventilator-dependent respiratory failure, XDR profile, high-risk clone ST175, negative control culture, and resistance development. In 6 of the 8 cases, resistance development was caused by structural mutations in AmpC, including some mutations described for the first time in vivo, whereas in the other 2, by mutations in OXA-10 leading to the extended spectrum OXA-14. Although further clinical experience is still needed, our results suggest that ceftolozane/tazobactam is an attractive option for the treatment of MDR/XDR P. aeruginosa infections.

Sequential Measurements of Pentraxin 3 Serum Levels in Patients with Ventilator-Associated Pneumonia: A Nested Case-Control Study

Purpose

The main purpose of this study was to investigate the dynamics of pentraxin 3 (PTX3) compared with procalcitonin (PCT) and C-reactive protein (CRP) in patients with suspicion of ventilator-associated pneumonia (VAP).

Materials and Methods

We designed a nested case-control study. This study was performed in the Surgical Intensive Care Unit of a tertiary care academic university and teaching hospital. Ninety-one adults who were mechanically ventilated for >48 hours were enrolled in the study. VAP diagnosis was established among 28 patients following the 2005 ATS/IDSA guidelines.

Results

The median PTX3 plasma level was 2.66 ng/mL in VAP adults compared to 0.25 ng/mL in non-VAP adults (p < 0.05). Procalcitonin and CRP levels did not significantly differ. Pentraxin 3, with a 2.56 ng/mL breakpoint, had 85% sensitivity, 86% specificity, 75% positive predictive value, and 92.9% negative predictive value for VAP diagnosis (AUC = 0.78).

Conclusions

With the suspicion of VAP, a pentraxin 3 plasma breakpoint of 2.56 ng/mL could contribute to the decision of whether to start antibiotics.

Inclusion and definition of acute renal dysfunction in critically ill patients in randomized controlled trials: a systematic review

BACKGROUND

In evidence-based medicine, multicenter, prospective, randomized controlled trials (RCTs) are the gold standard for evaluating treatment benefits and ensuring the effectiveness of interventions. Patient-centered outcomes, such as mortality, are most often the preferred evaluated outcomes. While there is currently agreement on how to classify renal dysfunction in critically ill patients , the application frequency of this new classification system in RCTs has not previously been evaluated. In this study, we aim to assess the definition of renal dysfunction in multicenter RCTs involving critically ill patients that included mortality as a primary endpoint.

METHODS

A comprehensive search was conducted for publications reporting multicenter randomized controlled trials (RCTs) involving adult patients in intensive care units (ICUs) that included mortality as a primary outcome. MEDLINE and PUBMED were queried for relevant articles in core clinical journals published between May 2004 and December 2017.

RESULTS

Of 418 articles reviewed, 46 multicenter RCTs with a primary endpoint related to mortality were included. Thirty-six (78.3%) of the trial reports provided information on renal function in the participants. Only seven articles (15.2%) included mean or median serum creatinine levels, mean creatinine clearance or estimated glomerular filtration rates. Sequential organ failure assessment (SOFA) score was the most commonly used definition of renal dysfunction (20 studies; 43.5%). Risk, Injury, Failure, Loss, End-stage renal disease (RIFLE), Acute Kidney Injury Network (AKIN) and Kidney Disease Improving Global Outcomes (KDIGO) criteria were used in five (10.9%) trials. In thirteen trials (28.3%), no renal dysfunction criteria were reported. Only one trial excluded patients with renal dysfunction, and it used urinary output or need for renal replacement therapy (RRT) as criteria for this diagnosis.

CONCLUSION

The presence of renal dysfunction was included as a baseline patient characteristic in most RCTs. The RIFLE, AKIN and KDIGO classification systems were infrequently used; renal dysfunction was generally defined using the SOFA score.

The validity and reliability of the Arabic version of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU): A prospective cohort study

BACKGROUND

Accurate diagnosis for Arabic speaking critically ill patients suffering from delirium is limited by the need for a valid/reliable translation of a standardized delirium instrument such as the Confusion Assessment Method for the ICU (CAM-ICU).

OBJECTIVE

To determine the validity and reliability of the Arabic version of the CAM-ICU.

DESIGN

A prospective cohort study design was used to conduct the current study.

SETTINGS

Data collection took place in Geriatric, Emergency and Surgical intensive care units.

PARTICIPANTS

Fifty-eight adult patients met the inclusion criteria and participated in the study. Among the participants 22(38%) patients were on mechanical ventilation.

METHODS

After translating the CAM-ICU into Arabic language, the Arabic CAM-ICU was administered by two well-trained critical care nurses and compared with reference standard assessments by delirium experts using the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM -IV-TR), along with assessment of severity of illness using Sequential Organ Failure Assessment (SOFA). Concurrent validity was assessed by calculating sensitivity, specificity and positive and negative predictive value (PPV and NPV) for the two Arabic CAM-ICU raters, where calculations were based on considering the DSM-IV-TR criterion as the reference standard. The convergent validity of the Arabic CAM-ICU was explored by comparing the Arabic CAM-ICU ratings and the total score of SOFA (severity of illness) and MMSE (cognitive impairment).

RESULTS

A total of 58 ICU patients were included, of whom 27 (47%) were diagnosed with delirium during their ICU stay via DSM-IV criteria. Interrater reliability for the Arabic CAM-ICU, overall and for mechanically ventilated patients assessed using Cohen's kappa (κ) were 0.82 and 1, respectively, p < 0.001. The sensitivities (95% CI) for the two critical care nurses when using the Arabic CAM-ICU compared with the reference standard were 81% (60%-93%) and 85% (65%-95%), respectively, whereas specificity (95% CI) was 81%(62%-92%) for both nurses. High sensitivity and specificity measures were also observed across subgroups; 100% for mechanically ventilated patients, 88% (60%-98%) and 79% (49%-94%) for those aged 65 years or older and 82% (56%-95%) and 75% (43%-93%) for those with SOFA scores at or above the median value.

CONCLUSIONS

The Arabic CAM-ICU appeared to be valid and reliable tool for diagnosing delirium. Future investigations may lead to a better understanding of the prevalence, predictors, and consequences of delirium among critically ill Arabic speaking patients.

Prospective Observational Study on Heart Rate Variability in Emergency Department Patients with Sepsis

Objective

To study the predictive value of heart rate variability in septic patients presented to the emergency department.

Design

Cross sectional study.

Setting

Emergency department.

Methods

Septic patients in the emergency department were recruited according to criteria. Heart rate variability data on time domain and frequency domain were generated from Holter records. Sequential Organ Failure Assessment, clinical progress and laboratory values were used to access the outcomes.

Results

Spectral power of total power (TP), low frequency (LF), very low frequency (VLF) and normalised low frequency (nLF) are shown to be significantly reduced in patients with sepsis who deteriorated (p=0.0070, 0.0032, 0.0005 and 0.0109 respectively). Cut off value 172.5 of VLF can identify all septic patients with potential deterioration.

Conclusions

Application of heart rate variability recording in emergency department is feasible and helpful in early identification of potentially deteriorating septic patients.

Quantifying the Mortality Impact of Do-Not-Resuscitate Orders in the ICU

OBJECTIVES

We quantified the 28-day mortality effect of preexisting do-not-resuscitate orders in ICUs.

DESIGN

Longitudinal, retrospective study of patients admitted to five ICUs at a tertiary university medical center (Beth Israel Deaconess Medical Center, BIDMC, Boston, MA) between 2001 and 2008.

INTERVENTION

None.

PATIENTS

Two cohorts were defined: patients with do not resuscitate advance directives on day 1 of ICU admission and a control group comprising patients with no limitations of level of care on ICU day 1 (full code).

MEASUREMENTS AND MAIN RESULTS

The primary outcome was mortality at 28 days after ICU admission. Of 19,007 ICU patients, 1,239 patients (6.5%) had a do-not-resuscitate order on the first day of ICU admission and survived 48 hours in the ICU. We matched those do-not-resuscitate patients with 2,402 patients with full-code status. Twenty-eight day and 1-year mortality were both significantly higher in the do-not-resuscitate group (33.9% vs 18.4% and 60.7% vs 40.2%; p < 0.001, respectively).

CONCLUSION

Do-not-resuscitate status is an independent risk factor for ICU mortality. This may reflect severity of illness not captured by other clinical factors, but the perceptions of the treating team related to do-not-resuscitate status could also be causally responsible for increased mortality in patients with do-not-resuscitate status.

SOFA and mortality endpoints in randomized controlled trials: a systematic review and meta-regression analysis

BACKGROUND

The sequential organ failure assessment score (SOFA) is increasingly used as an endpoint in intensive care randomized controlled trials (RCTs). Although serially measured SOFA is independently associated with mortality in observational cohorts, the association between treatment effects on SOFA vs. effects on mortality has not yet been quantified in RCTs. The aim of this study was to quantify the relationship between SOFA and mortality in RCTs and to identify which SOFA derivative best reflects between-group mortality differences.

METHODS

The review protocol was prospectively registered (Prospero CRD42016034014). We performed a literature search (up to May 1, 2016) for RCTs reporting both SOFA and mortality, and analyzed between-group differences in these outcomes. Treatment effects on SOFA and mortality were calculated as the between-group SOFA standardized difference and log odds ratio (OR), respectively. We used random-effects meta-regression to (1) quantify the linear relationship between RCT treatment effects on mortality (logOR) and SOFA (i.e. responsiveness) and (2) quantify residual heterogeneity (i.e. consistency, expressed as I ²).

RESULTS

Of 110 eligible RCTs, 87 qualified for analysis. Using all RCTs, SOFA was significantly associated with mortality (slope = 0.49 (95% CI 0.17; 0.82), p = 0.006, I ² = 5%); the overall mortality effect explained by SOFA score (R ²) was 9%. Fifty-eight RCTs used Fixed-day SOFA as an endpoint (i.e. the score on a fixed day after randomization), 25 studies used Delta SOFA as an endpoint (i.e. the trajectory from baseline score) and 15 studies used other SOFA derivatives as an endpoint. Fixed-day SOFA was not significantly associated with mortality (slope = 0.35 (95% CI -0.04; 0.75), p = 0.08, I ² = 12%) and explained 3% of the overall mortality effect (R ²). Delta SOFA was significantly associated with mortality (slope = 0.70 (95% CI 0.26; 1.14), p = 0.004, I ² = 0%) and explained 32% of the overall mortality effect (R ²).

CONCLUSIONS

Treatment effects on Delta SOFA appear to be reliably and consistently associated with mortality in RCTs. Fixed-day SOFA was the most frequently reported outcome among the reviewed RCTs, but was not significantly associated with mortality. Based on this study, we recommend using Delta SOFA rather than Fixed-day SOFA as an endpoint in future RCTs.