SOFA is superior to MOD score for the determination of non-neurologic organ dysfunction in patients with severe traumatic brain injury: a cohort study

INTRODUCTION: The objective of the present study was to compare the discriminative ability of the Sequential Organ Failure Assessment (SOFA) and Multiple Organ Dysfunction (MOD) scoring systems with respect to hospital mortality and unfavorable neurologic outcome in patients with severe traumatic brain injury admitted to the intensive care unit. METHOD: We performed a prospective cohort study at Foothills Medical Centre, the sole adult tertiary care trauma center servicing southern Alberta (population about 1.3 million). All patients aged 16 years or older with severe traumatic brain injury and intensive care unit length of stay greater than 48 hours between 1 May 2000 and 31 April 2003 were included. Non-neurologic organ dysfunction was measured using the SOFA and MODS scoring systems. Determination of organ dysfunction for each non-neurologic organ system was compared between the two systems by calculating the proportion of patients with SOFA and MOD component score defined organ failure. Consistent with previous literature, organ system failure was defined as a component score of three or greater. RESULTS: The odds of death and unfavorable neurologic outcome in patients with SOFA defined cardiovascular failure were 14.7 times (95% confidence interval [CI] 5.9–36.3) and 7.6 times (95% CI 3.5–16.3) that of those without cardiovascular failure, respectively. The development of SOFA-defined cardiovascular failure was a reasonable discriminator of hospital mortality and unfavorable neurologic outcome (area under the receiver operating characteristic [ROC] curve 0.75 and 0.73, respectively). The odds of death and unfavorable neurologic outcome in patients with MOD-defined cardiovascular failure were 2.6 times (95% CI 1.24–5.26) and 4.1 times (95% CI 1.3–12.4) that of those without cardiovascular failure, respectively. The development of MOD-defined cardiovascular failure was a poor discriminator of hospital mortality and unfavorable neurologic outcome (area under the ROC curve 0.57 and 0.59, respectively). Neither SOFA-defined nor MOD-defined respiratory failure was significantly associated with hospital mortality. CONCLUSION: In patients with brain injury, the SOFA scoring system has superior discriminative ability and stronger association with outcome compared with the MOD scoring system with respect to hospital mortality and unfavorable neurologic outcome

Pro/con debate: In patients who are potential candidates for organ donation after cardiac death, starting medications and/or interventions for the sole purpose of making the organs more viable is an acceptable practice

Several hospitals have been developing programmes for organ donation after cardiac death. Such programmes offer options for organ donation to patients who do not meet brain-death criteria but wish to donate their organs after withdrawal of life-support. These programmes also increase the available organ pool at a time when demand exceeds supply. Given that potential donors are managed in intensive care units, intensivists will be key components of these programmes. Donation after cardiac death clearly carries a number of important ethical issues with it. In the present issue of Critical Care two established groups debate the ethical acceptability of using medications/interventions in potential organ donors for the sole purpose of making the organs more viable. Such debates will be an increasingly common component of intensivists' future practice

Coexpression analysis of large cancer datasets provides insight into the cellular phenotypes of the tumour microenvironment

Background: Biopsies taken from individual tumours exhibit extensive differences in their cellular composition due to the inherent heterogeneity of cancers and vagaries of sample collection. As a result genes expressed in specific cell types, or associated with certain biological processes are detected at widely variable levels across samples in transcriptomic analyses. This heterogeneity also means that the level of expression of genes expressed specifically in a given cell type or process, will vary in line with the number of those cells within samples or activity of the pathway, and will therefore be correlated in their expression.Results: Using a novel 3D network-based approach we have analysed six large human cancer microarray datasets derived from more than 1,000 individuals. Based upon this analysis, and without needing to isolate the individual cells, we have defined a broad spectrum of cell-type and pathway-specific gene signatures present in cancer expression data which were also found to be largely conserved in a number of independent datasets.Conclusions: The conserved signature of the tumour-associated macrophage is shown to be largely-independent of tumour cell type. All stromal cell signatures have some degree of correlation with each other, since they must all be inversely correlated with the tumour component. However, viewed in the context of established tumours, the interactions between stromal components appear to be multifactorial given the level of one component e.g. vasculature, does not correlate tightly with another, such as the macrophage

Prolonged refractory status epilepticus following acute traumatic brain injury: a case report of excellent neurological recovery

INTRODUCTION: Refractory status epilepticus (RSE) secondary to traumatic brain injury (TBI) may be under-recognized and is associated with significant morbidity and mortality. METHODS: This case report describes a 20 year old previously healthy woman who suffered a severe TBI as a result of a motor vehicle collision and subsequently developed RSE. Pharmacological coma, physiological support and continuous electroencephalography (cEEG) were undertaken. RESULTS: Following 25 days of pharmacological coma, electrographic and clinical seizures subsided and the patient has made an excellent cognitive recovery. CONCLUSION: With early identification, aggressive physiological support, appropriate monitoring, including cEEG, and an adequate length of treatment, young trauma patients with no previous seizure history and limited structural damage to the brain can have excellent neurological recovery from prolonged RSE

Mining Twitter data to #educate the public about #sepsis

Introduction Sepsis is not well known. Only 58% of Americans know the word sepsis, less than 1% can identify its symptoms and one-third wrongly believe the disease is contagious (1). What if social media educated users about sepsis? There are at least 500 million tweets worldwide per day on Twitter. Objectives and Approach Early detection of sepsis with early treatment is associated with a decrease in mortality (2). The current study aims to use Twitter to share sepsis patients’ experiences. The approach consisted of using text data mining techniques by randomly extracting tweets (N =150) with the hashtag #sepsissurvivor (3) using R software (4). The study retrieved and quantified sepsis patients’ tweets into word frequency distributions using documentation summarization and word cloud techniques (5) for visual representation of Twitter data. Sepsis patients used images symptoms cards (6) to raise awareness. The study used the R package "tesseract" to extract text from images (6). Results Patients sharing their experiences frequently used the word “sepsis.” Cardiorespiratory compromise (septic shock—the highest mortality risk) was illustrated in the words "my heart stops” or elevated "heart" rate or “low blood pressure.” Several studies have reported increased mortality associated with delays in antibiotic administration (7). Many sepsis survivors had antibiotics exposure, both in a timely manner or delayed in use. Sepsis patients experienced long stays in the hospital. Tweets mentioned "infection" 39 times (8), which supports patients’ diagnoses in addition to high rates of "fever." The clustering technique using word association indicated infection was highly correlated with sepsis (9). Sepsis survivors shared the "pain" they went through. Conclusion/Implications Twitter presents an opportunity for patients to disseminate information about sepsis raising awareness about important symptoms. The information tweeted explores the impact of this diagnosis, and the need for early treatment. The current study demonstrates the opportunity to raise awareness through the learned experiences of patients in a novel medium

Linking Emergency Medical Services and Health System Data: Optimal Strategy and Bias Mitigation

Introduction Emergency Medical Services (EMS) systems dispatch paramedics to emergencies in the community. For critically ill patients, paramedic interventions and transport destination decisions may impact outcomes. Research is needed to inform paramedic care, but linking EMS data to health system outcomes is a barrier. Limited research exists on EMS data linkage. Objectives and Approach To optimize linkage of EMS data (fiscal year 2016/17) to the National Ambulatory Care Reporting System/Sunrise Clinical Manager datasets and assess bias. A random sample of EMS records were deterministically linked on provincial health number (PHN), transport destination, and EMS/emergency department arrival/presentation times ≤2hrs. Linked data were manually verified using last name, sex, date of birth, and hospital file number. For patients that remained unlinked (based on the variables listed above), further linkage attempts were made using additional variables. The combination of variables that optimized sensitivity/positive predictive value/f-measure were used to link the fiscal year. Linked/unlinked groups were descriptively compared. Results While results are still pending (available April, 2018), we hypothesize that there may be inherent differences in the clinical and encounter characteristics of patients that were linked versus unlinked. Patient identifiers such as PHN and name are important for linkage, but are not always collected on EMS events that require immediate treatment and rapid transport, yet these patients may be the most critically ill. Conclusion/Implications As more EMS systems attempt to systematically link their data to health system outcome, these results will be important to mitigate potential bias

Prognosis for long-term survival and renal recovery in critically ill patients with severe acute renal failure: a population-based study

INTRODUCTION: Severe acute renal failure (sARF) is associated with considerable morbidity, mortality and use of healthcare resources; however, its precise epidemiology and long-term outcomes have not been well described in a non-specified population. METHODS: Population-based surveillance was conducted among all adult residents of the Calgary Health Region (population 1 million) admitted to multidisciplinary and cardiovascular surgical intensive care units between May 1 1999 and April 30 2002. Clinical records were reviewed and outcome at 1 year was assessed. RESULTS: sARF occurred in 240 patients (11.0 per 100,000 population/year). Rates were highest in males and older patients (≥65 years of age). Risk factors for development of sARF included previous heart disease, stroke, pulmonary disease, diabetes mellitus, cancer, connective tissue disease, chronic renal dysfunction, and alcoholism. The annual mortality rate was 7.3 per 100,000 population with rates highest in males and those ≥65 years. The 28-day, 90-day, and 1-year case-fatality rates were 51%, 60%, and 64%, respectively. Increased Charlson co-morbidity index, presence of liver disease, higher APACHE II score, septic shock, and need for continuous renal replacement therapy were independently associated with death at 1 year. Renal recovery occurred in 78% (68/87) of survivors at 1 year. CONCLUSION: sARF is common and males, older patients, and those with underlying medical conditions are at greatest risk. Although the majority of patients with sARF will die, most survivors will become independent from renal replacement therapy within a year

A comparison between the APACHE II and Charlson Index Score for predicting hospital mortality in critically ill patients

<p>Abstract</p> <p>Background</p> <p>Risk adjustment and mortality prediction in studies of critical care are usually performed using acuity of illness scores, such as Acute Physiology and Chronic Health Evaluation II (APACHE II), which emphasize physiological derangement. Common risk adjustment systems used in administrative datasets, like the Charlson index, are entirely based on the presence of co-morbid illnesses. The purpose of this study was to compare the discriminative ability of the Charlson index to the APACHE II in predicting hospital mortality in adult multisystem ICU patients.</p> <p>Methods</p> <p>This was a population-based cohort design. The study sample consisted of adult (>17 years of age) residents of the Calgary Health Region admitted to a multisystem ICU between April 2002 and March 2004. Clinical data were collected prospectively and linked to hospital outcome data. Multiple regression analyses were used to compare the performance of APACHE II and the Charlson index.</p> <p>Results</p> <p>The Charlson index was a poor predictor of mortality (C = 0.626). There was minimal difference between a baseline model containing age, sex and acute physiology score (C = 0.74) and models containing either chronic health points (C = 0.76) or Charlson index variations (C = 0.75, 0.76, 0.77). No important improvement in prediction occurred when the Charlson index was added to the full APACHE II model (C = 0.808 to C = 0.813).</p> <p>Conclusion</p> <p>The Charlson index does not perform as well as the APACHE II in predicting hospital mortality in ICU patients. However, when acuity of illness scores are unavailable or are not recorded in a standard way, the Charlson index might be considered as an alternative method of risk adjustment and therefore facilitate comparisons between intensive care units.</p

Outcomes of selective nonoperative management of civilian abdominal gunshot wounds: a systematic review and meta-analysis

Abstract Background Although mandatory laparotomy has been standard of care for patients with abdominal gunshot wounds (GSWs) for decades, this approach is associated with non-therapeutic operations, morbidity, and long hospital stays. This systematic review and meta-analysis sought to summarize outcomes of selective nonoperative management (SNOM) of civilian abdominal GSWs. Methods We searched electronic databases (March 1966–April 1, 2017) and reference lists of articles included in the systematic review for studies reporting outcomes of SNOM of civilian abdominal GSWs. We meta-analyzed the associated risks of SNOM-related failure (defined as laparotomy during hospital admission), mortality, and morbidity across included studies using DerSimonian and Laird random-effects models. Between-study heterogeneity was assessed by calculating I2 statistics and conducting tests of homogeneity. Results Of 7155 citations identified, we included 41 studies [n = 22,847 patients with abdominal GSWs, of whom 6777 (29.7%) underwent SNOM]. The pooled risk of failure of SNOM in hemodynamically stable patients without a reduced level of consciousness or signs of peritonitis was 7.0% [95% confidence interval (CI) = 3.9–10.1%; I2 = 92.6%, homogeneity p  0.99). In patients who failed SNOM, the pooled estimate of the risk of therapeutic laparotomy was 68.0% (95% CI = 58.3–77.7%; I2 = 91.5%; homogeneity p < 0.001). Risks of failure of SNOM were lowest in studies that evaluated patients with right thoracoabdomen (3.4%; 95% CI = 0–7.0%; I2 = 0%; homogeneity p = 0.45), flank (7.0%; 95% CI = 3.9–10.1%), and back (3.1%; 95% CI = 0–6.5%) GSWs and highest in those that evaluated patients with anterior abdomen (13.2%; 95% CI = 6.3–20.1%) GSWs. In patients who underwent mandatory abdominopelvic computed tomography (CT), the pooled risk of failure was 4.1% versus 8.3% in those who underwent selective CT (p = 0.08). The overall sample-size-weighted mean hospital length of stay among patients who underwent SNOM was 6 days versus 10 days if they failed SNOM or developed an in-hospital complication. Conclusions SNOM of abdominal GSWs is safe when conducted in hemodynamically stable patients without a reduced level of consciousness or signs of peritonitis. Failure of SNOM may be lower in patients with GSWs to the back, flank, or right thoracoabdomen and be decreased by mandatory use of abdominopelvic CT scans

Getting the invite list right : a discussion of sepsis severity scoring systems in severe complicated intra-abdominal sepsis and randomized trial inclusion criteria

Background: Severe complicated intra-abdominal sepsis (SCIAS) is a worldwide challenge with increasing incidence. Open abdomen management with enhanced clearance of fluid and biomediators from the peritoneum is a potential therapy requiring prospective evaluation. Given the complexity of powering multi-center trials, it is essential to recruit an inception cohort sick enough to benefit from the intervention; otherwise, no effect of a potentially beneficial therapy may be apparent An evaluation of abilities of recognized predictive systems to recognize SCIAS patients was conducted using an existing intra-abdominal sepsis (IAS) database. Methods: All consecutive adult patients with a diffuse secondary peritonitis between 2012 and 2013 were collected from a quaternary care hospital in Finland, excluding appendicitis/cholecystitis. From this retrospectively collected database, a target population (93) of those with either ICU admission or mortality were selected. The performance metrics of the Third Consensus Definitions for Sepsis and Septic Shock based on both SOFA and quick SOFA, the World Society of Emergency Surgery Sepsis Severity Score (WSESSSS), the APACHE II score, Manheim Peritonitis Index (MPI), and the Calgary Predisposition, Infection, Response, and Organ dysfunction (CPIRO) score were all tested for their discriminant ability to identify this subgroup with SCIAS and to predict mortality. Results: Predictive systems with an area under-the-receiving-operating characteristic (AUQ curve >= 0.8 included SOFA, Sepsis-3 definitions, APACHE II, WSESSSS, and CPIRO scores with the overall best for CPIRO. The highest identification rates were SOFA score >= 2 (78.4%), followed by the WSESSSS score >= 8 (73.1%), SOFA >= 3 (752%), and APACHE II >= 14 (68.8%) identification. Combining the Sepsis-3 septic-shock definition and WSESSS >= 8 increased detection to 80%. Including CPIRO score >= 3 increased this to 82.8% (Sensitivity-SN; 83% Specificity-SP; 74%. Comparatively, SOFA >= 4 and WSESSSS >= 8 with or without septic-shock had 83.9% detection (SN; 84%, SP; 75%, 25% mortality). Conclusions: No one scoring system behaves perfectly, and all are largely dominated by organ dysfunction. Utilizing combinations of SOFA, CPIRO, and WSESSSS scores in addition to the Sepsis-3 septic shock definition appears to offer the widest "inclusion-criteria" to recognize patients with a high chance of mortality and ICU admission.Peer reviewe