Prognostic Accuracy of Screening Tools for Clinical Deterioration in Adults With Suspected Sepsis in Northeastern Thailand: A Cohort Validation Study.

Background: We sought to assess the performance of commonly used clinical scoring systems to predict imminent clinical deterioration in patients hospitalized with suspected infection in rural Thailand. Methods: Patients with suspected infection were prospectively enrolled within 24 hours of admission to a referral hospital in northeastern Thailand between 2013 and 2017. In patients not requiring intensive medical interventions, multiple enrollment scores were calculated including the National Early Warning Score (NEWS), the Modified Early Warning Score, Between the Flags, and the quick Sequential Organ Failure Assessment score. Scores were tested for predictive accuracy of clinical deterioration, defined as a new requirement of mechanical ventilation, vasoactive medications, intensive care unit admission, and/or death approximately 1 day after enrollment. The association of each score with clinical deterioration was evaluated by means of logistic regression, and discrimination was assessed by generating area under the receiver operating characteristic curve. Results: Of 4989 enrolled patients, 2680 met criteria for secondary analysis, and 100 of 2680 (4%) experienced clinical deterioration within 1 day after enrollment. NEWS had the highest discrimination for predicting clinical deterioration (area under the receiver operating characteristic curve, 0.78 [95% confidence interval, .74-.83]) compared with the Modified Early Warning Score (0.67 [.63-.73]; P < .001), quick Sequential Organ Failure Assessment (0.65 [.60-.70]; P < .001), and Between the Flags (0.69 [.64-.75]; P < .001). NEWS ≥5 yielded optimal sensitivity and specificity for clinical deterioration prediction. Conclusions: In patients hospitalized with suspected infection in a resource-limited setting in Southeast Asia, NEWS can identify patients at risk of imminent clinical deterioration with greater accuracy than other clinical scoring systems.

Protocol: identifying policy, system, and environment change interventions to enhance availability of blood for transfusion in Kenya, a mixed-methods study.

BACKGROUND: Safe blood is essential for the care of patients with life-threatening anemia and hemorrhage. Low blood donation rates, inefficient testing procedures, and other supply chain disruptions in blood administration affect patients in low-resource settings across Sub-Saharan countries, including Kenya. Most efforts to improve access to transfusion have been unidimensional, usually focusing on only point along the blood system continuum, and have excluded community stakeholders from early stages of intervention development. Context-appropriate interventions to improve the availability of safe blood at the point of use in low-resource settings are of paramount importance. Thus, this protocol proposes a multifaceted approach to characterize the Kenyan blood supply chain through quantitative and qualitative analyses as well as an industrial engineering approach. METHODS: This study will use a mixed-methods approach in addition to engineering process mapping, modeling and simulation of blood availability in Kenya. It will be guided by a multidimensional three-by-three-by-three matrix: three socioeconomic settings, three components of the blood system continuum, and three levels of urgency of blood transfusion. Qualitative data collection includes one-on-one interviews and focus group discussions with stakeholders across the continuum to characterize ground-level deficits and potential policy, systems, and environment (PSE) interventions. Prospectively-collected quantitative data will be used to estimate blood collection and transfusion of blood. We will create a process map of the blood system continuum to model the response to PSE changes proposed by stakeholders. Lastly, we will identify those PSE changes that may have the greatest impact on blood transfusion availability, accounting for differences across socioeconomic settings and levels of urgency. DISCUSSION: Identifying and prioritizing community-driven interventions to improve blood supply in low-resource settings are of utmost importance. Varied constraints in blood collection, processing, delivery, and use make each socioeconomic setting unique. Using a multifaceted approach to understand the Kenyan blood supply and model the response to stakeholder-proposed PSE changes may lead to identification of contextually appropriate intervention targets to meet the transfusion needs of the population.

Prevalence of Antimicrobial Resistance and Association with Patient Outcomes in a Rural Kenyan Hospital.

Data on antimicrobial resistance (AMR) and association with outcomes in resource-variable intensive care units (ICU) are lacking. Data currently available are limited to large, urban centers. We attempted to understand this locally through a dual-purpose, retrospective study. Cohort A consisted of adult and pediatric patients who had blood, urine, or cerebrospinal fluid cultures obtained from 2016 to 2020. A total of 3,013 isolates were used to create the Kijabe Hospital's first antibiogram. Gram-negative organisms were found to be less than 50% susceptible to third- and fourth-generation cephalosporins, 67% susceptible to piperacillin-tazobactam, 87% susceptible to amikacin, and 93% susceptible to meropenem. We then evaluated the association between AMR and clinical characteristics, management, and outcomes among ICU patients (Cohort B). Demographics, vital signs, laboratory results, management data, and outcomes were obtained. Antimicrobial resistance was defined as resistance to one or more antimicrobials. Seventy-six patients were admitted to the ICU with bacteremia during this time. Forty complete paper charts were found for review. Median age was 34 years (interquartile range, 9-51), 26 patients were male (65%), and 28 patients were older than 18 years (70%). Septic shock was the most common diagnosis (n = 22, 55%). Six patients had AMR bacteremia; Escherichia coli was most common (n = 3, 50%). There was not a difference in mortality between patients with AMR versus non-AMR infections (P = 0.54). This study found a prevalence of AMR. There was no association between AMR and outcomes among ICU patients. More studies are needed to understand the impact of AMR in resource-variable settings.

Association of clinical prediction scores with hospital mortality in an adult medical and surgical intensive care unit in Kenya.

Importance: Mortality prediction among critically ill patients in resource limited settings is difficult. Identifying the best mortality prediction tool is important for counseling patients and families, benchmarking quality improvement efforts, and defining severity of illness for clinical research studies. Objective: Compare predictive capacity of the Modified Early Warning Score (MEWS), Universal Vital Assessment (UVA), Tropical Intensive Care Score (TropICS), Rwanda Mortality Probability Model (R-MPM), and quick Sequential Organ Failure Assessment (qSOFA) for hospital mortality among adults admitted to a medical-surgical intensive care unit (ICU) in rural Kenya. We performed a pre-planned subgroup analysis among ICU patients with suspected infection. Design setting and participants: Prospective single-center cohort study at a tertiary care, academic hospital in Kenya. All adults 18 years and older admitted to the ICU January 2018-June 2019 were included. Main outcomes and measures: The primary outcome was association of clinical prediction tool score with hospital mortality, as defined by area under the receiver operating characteristic curve (AUROC). Demographic, physiologic, laboratory, therapeutic, and mortality data were collected. 338 patients were included, none were excluded. Median age was 42 years (IQR 33-62) and 61% (n = 207) were male. Fifty-nine percent (n = 199) required mechanical ventilation and 35% (n = 118) received vasopressors upon ICU admission. Overall hospital mortality was 31% (n = 104). 323 patients had all component variables recorded for R-MPM, 261 for MEWS, and 253 for UVA. The AUROC was highest for MEWS (0.76), followed by R-MPM (0.75), qSOFA (0.70), and UVA (0.69) (p < 0.001). Predictive capacity was similar among patients with suspected infection. Conclusion and relevance: All tools had acceptable predictive capacity for hospital mortality, with variable observed availability of the component data. R-MPM and MEWS had high rates of variable availability as well as good AUROC, suggesting these tools may prove useful in low resource ICUs.

An exploratory assessment of the management of pediatric traumatic brain injury in three centers in Africa.

Purpose: Traumatic brain injury (TBI) is a leading cause of morbidity and mortality in low- and middle-income countries (LMICs). Hospital care practices of pediatric TBI patients in LMICs are unknown. Our objective was to report on hospital management and outcomes of children with TBI in three centers in LMICs. Methods: We completed a secondary analysis of a prospective observational study in children (<18 years) over a 4-week period. Outcome was determined by Pediatric Cerebral Performance Category (PCPC) score; an unfavorable score was defined as PCPC > 2 or an increase of two points from baseline. Data were compared using Chi-square and Wilcoxon rank sum tests. Results: Fifty-six children presented with TBI (age 0-17 y), most commonly due to falls (43%, n = 24). Emergency department Glasgow Coma Scale scores were ≤ 8 in 21% (n = 12). Head computed tomography was performed in 79% (n = 44) of patients. Forty (71%) children were admitted to the hospital, 25 (63%) of whom were treated for suspected intracranial hypertension. Intracranial pressure monitoring was unavailable. Five (9%, n = 5) children died and 10 (28%, n = 36) inpatient survivors had a newly diagnosed unfavorable outcome on discharge. Conclusion: Inpatient management and monitoring capability of pediatric TBI patients in 3 LMIC-based tertiary hospitals was varied. Results support the need for prospective studies to inform development of evidence-based TBI management guidelines tailored to the unique needs and resources in LMICs.

A sepsis early warning system is associated with improved patient outcomes.

In a real-world implementation of a machine-learning (ML)-based sepsis early warning system (EWS), Adams et al.1,2 found that timely provider response to an alert was associated with improved mortality, highlighting the potential utility of these systems in patient care.

The BLOODSAFE program: Building the future of access to safe blood in Sub-Saharan Africa.

BACKGROUND: The supply of blood in many low- and middle-income nations in Sub-Saharan Africa (SSA) does not meet the patient care needs. Lack and delay of blood transfusion cause harm to patients and slow the rate of progress in other parts of the health system. Recognizing the power of implementation science, the BLOODSAFE Program was initiated which supports three SSA research study teams and one data coordinating center (DCC) with the goal to improve access to safe blood transfusion in SSA. STUDY DESIGN AND METHODS: The study team in Ghana is focusing on studying and decreasing iron deficiency in blood donors and evaluating social engagement of blood donors through different approaches. The study team in Kenya is building a "vein to vein" workflow model to elucidate and devise strategies to overcome barriers to blood donation and improve infrastructural components of blood product production and use. The Malawi team is studying the infectious disease ramifications of blood donation as well as blood donor retention strategies aimed at blood donors who commence their donation career in secondary schools. RESULTS AND DISCUSSION: Together the project teams and the DCC work as a consortium to support each other through a shared study protocol that will study donor motivations, outcomes, and adverse events across all three countries. The BLOODSAFE Program has the potential to lead to generalizable improvement approaches for increasing access to safe blood in SSA as well as mentoring and building the research capacity and careers of many investigators.

Critical Care Pandemic Preparation: Considerations and Lessons Learned from COVID-19.

Pandemics, increases in disease incidence that affect multiple regions of the world, present huge challenges to health care systems and in particular to policymakers, public health authorities, clinicians, and all health care workers (HCWs). The recent COVID-19 pandemic has resulted in millions of severely ill patients, many of whom who have required hospital and intensive care unit (ICU) admission. The discipline of critical care is a vital and integral component of pandemic preparedness. Safe and effective critical care has the potential to improve outcomes, motivate individuals to seek timely medical attention, and attenuate the devastating sequelae of a severe pandemic. To achieve this, suitable critical care planning and preparation are essential.

Enhanced bedside mortality prediction combining point-of-care lactate and the quick Sequential Organ Failure Assessment (qSOFA) score in patients hospitalised with suspected infection in southeast Asia: a cohort study.

BACKGROUND: Simple, bedside prediction of infection-related mortality in low-resource settings is crucial for triage and resource-utilisation decisions. We aimed to evaluate mortality prediction by combining point-of-care venous lactate with the quick Sequential Organ Failure Assessment (qSOFA) score in adult patients admitted to hospital with suspected infection in southeast Asia. METHODS: We performed a cohort study by prospectively enrolling patients aged 18 years or older who had been admitted to hospital within the previous 24 h for suspected infection (with at least three documented systemic manifestations of infection according to the 2012 Surviving Sepsis Campaign) at Sunpasitthiprasong Hospital in Ubon Ratchathani, Thailand (derivation cohort). Venous lactate concentration was determined by a point-of-care device and multiple scores were developed. We then evaluated candidate 28-day mortality prediction models combining qSOFA and the lactate scores. A final model was compared with the qSOFA score, a lactate score, and a modified Sequential Organ Failure Assessment (SOFA) score for mortality discrimination using the area under the receiver operating characteristic curve (AUROC). Mortality discrimination of the qSOFA-lactate score was then verified in an external, prospectively enrolled, multinational cohort in southeast Asia. FINDINGS: Between March 1, 2013, and Jan 26, 2017, 5001 patients were enrolled in the derivation cohort; 4980 had point-of-care lactate data available and were eligible for analysis, and 816 died within 28 days of enrolment. The discrimination for 28-day mortality prediction of a qSOFA-lactate score combining the qSOFA score and a lactate score was superior to that of the qSOFA score alone (AUROC 0·78 [95% CI 0·76-0·80] vs 0·68 [0·67-0·70]; p<0·0001) and similar to a modified SOFA score (0·77 [0·75-0·78]; p=0·088). A lactate score alone had superior discrimination compared with the qSOFA score (AUROC 0·76 [95% CI 0·74-0·78]; p<0·0001). 815 patients were enrolled in the external validation cohort and 792 had point-of-care lactate data and were included in the analysis; the qSOFA-lactate score (AUROC 0·77 [95% CI 0·73-0·82]) showed significantly improved 28-day mortality discrimination compared with the qSOFA score alone (0·69 [0·63-0·74]; p<0·0001). INTERPRETATION: In southeast Asia, rapid, bedside assessments based on point-of-care lactate concentration combined with the qSOFA score can identify patients at risk of sepsis-related mortality with greater accuracy than the qSOFA score alone, and with similar accuracy to a modified SOFA score. FUNDING: National Institutes of Health, Wellcome Trust.

Comparative clinical characteristics and outcomes of patients with community acquired bacteremia caused by Escherichia coli, Burkholderia pseudomallei and Staphylococcus aureus: A prospective observational study (Ubon-sepsis).

BACKGROUND: Community acquired bacteremia (CAB) is a common cause of sepsis in low and middle-income countries (LMICs). However, knowledge about factors associated with outcomes of CAB in LMICs is limited. METHODOLOGY/PRINCIPAL FINDINGS: A prospective observational study (Ubon-sepsis) of adults admitted to a referral hospital with community-acquired infection in Northeastern Thailand was conducted between March 1, 2013 and February 1, 2017. In the present analysis, patients with a blood culture collected within 24 hours of admission that was positive for one of the three most common pathogens were studied. Clinical features, management, and outcomes of patients with each cause of CAB were compared. Of 3,806 patients presenting with community-acquired sepsis, 155, 131 and 37 patients had a blood culture positive for Escherichia coli, Burkholderia pseudomallei and Staphylococcus aureus, respectively. Of these 323 CAB patients, 284 (89%) were transferred from other hospitals. 28-day mortality was highest in patients with B. pseudomallei bactaeremia (66%), followed by those with S. aureus bacteraemia (43%) and E. coli (19%) bacteraemia. In the multivariable Cox proportional hazards model adjusted for age, sex, transfer from another hospital, empirical antibiotics prior to or during the transfer, and presence of organ dysfunction on admission, B. pseudomallei (aHR 3.78; 95%CI 2.31-6.21) and S. aureus (aHR 2.72; 95%CI 1.40-5.28) bacteraemias were associated with higher mortality compared to E. coli bacteraemia. Receiving empirical antibiotics recommended for CAB caused by the etiologic organism prior to or during transfer was associated with survival (aHR 0.58; 95%CI 0.38-0.88). CONCLUSIONS/SIGNIFICANCE: Mortality of patients with CAB caused by B. pseudomallei was higher than those caused by S. aureus and E. coli, even after adjusting for presence of organ dysfunction on admission and effectiveness of empirical antibiotics received. Improving algorithms or rapid diagnostic tests to guide early empirical antibiotic may be key to improving CAB outcomes in LMICs.

Pragmatic Recommendations for the Prevention and Treatment of Acute Kidney Injury in Patients with COVID-19 in Low- and Middle-Income Countries.

Current recommendations for the management of patients with COVID-19 and acute kidney injury (AKI) are largely based on evidence from resource-rich settings, mostly located in high-income countries. It is often unpractical to apply these recommendations to resource-restricted settings. We report on a set of pragmatic recommendations for the prevention, diagnosis, and management of patients with COVID-19 and AKI in low- and middle-income countries (LMICs). For the prevention of AKI among patients with COVID-19 in LMICs, we recommend using isotonic crystalloid solutions for expansion of intravascular volume, avoiding nephrotoxic medications, and using a conservative fluid management strategy in patients with respiratory failure. For the diagnosis of AKI, we suggest that any patient with COVID-19 presenting with an elevated serum creatinine level without available historical values be considered as having AKI. If serum creatinine testing is not available, we suggest that patients with proteinuria should be considered to have possible AKI. We suggest expansion of the use of point-of-care serum creatinine and salivary urea nitrogen testing in community health settings, as funding and availability allow. For the management of patients with AKI and COVID-19 in LMICS, we recommend judicious use of intravenous fluid resuscitation. For patients requiring dialysis who do not have acute respiratory distress syndrome (ARDS), we suggest using peritoneal dialysis (PD) as first choice, where available and feasible. For patients requiring dialysis who do have ARDS, we suggest using hemodialysis, where available and feasible, to optimize fluid removal. We suggest using locally produced PD solutions when commercially produced solutions are unavailable or unaffordable.

Pragmatic Recommendations for Identification and Triage of Patients with COVID-19 in Low- and Middle-Income Countries.

Effective identification and prognostication of severe COVID-19 patients presenting to healthcare facilities are essential to reducing morbidity and mortality. Low- and middle-income country (LMIC) facilities often suffer from restrictions in availability of human resources, laboratory testing, medications, and imaging during routine functioning, and such shortages may worsen during times of surge. Low- and middle-income country healthcare providers will need contextually appropriate tools to identify and triage potential COVID-19 patients. We report on a series of LMIC-appropriate recommendations and suggestions for screening and triage of COVID-19 patients in LMICs, based on a pragmatic, experience-based appraisal of existing literature. We recommend that all patients be screened upon first contact with the healthcare system using a locally approved questionnaire to identify individuals who have suspected or confirmed COVID-19. We suggest that primary screening tools used to identify individuals who have suspected or confirmed COVID-19 include a broad range of signs and symptoms based on standard case definitions of COVID-19 disease. We recommend that screening include endemic febrile illness per routine protocols upon presentation to a healthcare facility. We recommend that, following screening and implementation of appropriate universal source control measures, suspected COVID-19 patients be triaged with a triage tool appropriate for the setting. We recommend a standardized severity score based on the WHO COVID-19 disease definitions be assigned to all suspected and confirmed COVID-19 patients before their disposition from the emergency unit. We suggest against using diagnostic imaging to improve triage of reverse transcriptase (RT)-PCR-confirmed COVID-19 patients, unless a patient has worsening respiratory status. We suggest against the use of point-of-care lung ultrasound to improve triage of RT-PCR-confirmed COVID-19 patients. We suggest the use of diagnostic imaging to improve sensitivity of appropriate triage in suspected COVID-19 patients who are RT-PCR negative but have moderate to severe symptoms and are suspected of a false-negative RT-PCR with high risk of disease progression. We suggest the use of diagnostic imaging to improve sensitivity of appropriate triage in suspected COVID-19 patients with moderate or severe clinical features who are without access to RT-PCR testing for SARS-CoV-2.

A 2-Biomarker Model Augments Clinical Prediction of Mortality in Melioidosis.

BACKGROUND: Melioidosis, infection caused by Burkholderia pseudomallei, is a common cause of sepsis with high associated mortality in Southeast Asia. Identification of patients at high likelihood of clinical deterioration is important for guiding decisions about resource allocation and management. We sought to develop a biomarker-based model for 28-day mortality prediction in melioidosis. METHODS: In a derivation set (N = 113) of prospectively enrolled, hospitalized Thai patients with melioidosis, we measured concentrations of interferon-γ, interleukin-1ß, interleukin-6, interleukin-8, interleukin-10, tumor necrosis factor-ɑ, granulocyte-colony stimulating factor, and interleukin-17A. We used least absolute shrinkage and selection operator (LASSO) regression to identify a subset of predictive biomarkers and performed logistic regression and receiver operating characteristic curve analysis to evaluate biomarker-based prediction of 28-day mortality compared with clinical variables. We repeated select analyses in an internal validation set (N = 78) and in a prospectively enrolled external validation set (N = 161) of hospitalized adults with melioidosis. RESULTS: All 8 cytokines were positively associated with 28-day mortality. Of these, interleukin-6 and interleukin-8 were selected by LASSO regression. A model consisting of interleukin-6, interleukin-8, and clinical variables significantly improved 28-day mortality prediction over a model of only clinical variables [AUC (95% confidence interval [CI]): 0.86 (.79-.92) vs 0.78 (.69-.87); P = .01]. In both the internal validation set (0.91 [0.84-0.97]) and the external validation set (0.81 [0.74-0.88]), the combined model including biomarkers significantly improved 28-day mortality prediction over a model limited to clinical variables. CONCLUSIONS: A 2-biomarker model augments clinical prediction of 28-day mortality in melioidosis.

Sepsis Epidemiology Across the International Classification of Diseases, 9th Edition, to International Classification of Diseases, 10th Edition, Chasm-A Direct Application of the Institute for Health Metrics and Evaluation Case Definition to Hospital Discharge Data.

OBJECTIVES: Describe the epidemiology of sepsis across the transition from the International Classification of Diseases, 9th Edition, and International Classification of Diseases, 10th Edition, coding systems, evaluating estimates of two previously published International Classification of Diseases, 10th Edition, coding strategies. DESIGN: Serial cross-sectional analysis. SETTING: Healthcare Utilization Project's annual Nationwide Inpatient Sample of U.S. hospital discharges, 2012-2017. PATIENTS: Discharges greater than or equal to 18 years old, which met one of the three case definitions for sepsis. For the records using International Classification of Diseases, 9th Edition, we used previously published modified Angus criteria, and for records using International Classification of Diseases, 10th Edition, we deployed a case definition used by the Centers for Medicare & Medicaid Services and a case definition developed by the Institute for Health Metrics and Evaluation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: During the study period, there were discontinuities in the sepsis incidence estimates using the modified Angus International Classification of Diseases, 9th Edition, criteria in 2014 and either Centers for Medicare & Medicaid Services or Institute for Health Metrics and Evaluation International Classification of Diseases, 10th Edition, criteria in 2016. In 2014, there were an estimated 1,009 cases (95% CI, 989-1,030) of modified Angus sepsis per 100,000 persons, whereas in 2016, there were 709 cases (95% CI, 694-724) of Centers for Medicare & Medicaid Services sepsis and 1,498 cases (95% CI, 1,471-1,092) of Institute for Health Metrics and Evaluation sepsis per 100,000 persons. Furthermore, the Institute for Health Metrics and Evaluation definition identified a sepsis cohort with similar hospital characteristics but a younger age distribution, higher proportion of women, lower severity of illness, and lower hospital mortality. CONCLUSIONS: The Institute for Health Metrics and Evaluation International Classification of Diseases, 10th Edition, coding strategy for identifying sepsis may capture a larger patient population within administrative datasets that are different from those identified with previously deployed International Classification of Diseases-based methods. Further work is required to determine the optimal International Classification of Diseases, 10th Edition, coding strategy for use in hospital discharge data.

sTREM-1 predicts mortality in hospitalized patients with infection in a tropical, middle-income country.

BACKGROUND: Few studies of biomarkers as predictors of outcome in infection have been performed in tropical, low- and middle-income countries where the burden of sepsis is highest. We evaluated whether selected biomarkers could predict 28-day mortality in infected patients in rural Thailand. METHODS: Four thousand nine hundred eighty-nine adult patients admitted with suspected infection to a referral hospital in northeast Thailand were prospectively enrolled within 24 h of admission. In a secondary analysis of 760 patients, interleukin-8 (IL-8), soluble tumor necrosis factor receptor 1 (sTNFR-1), angiopoietin-1 (Ang-1), angiopoietin-2 (Ang-2), and soluble triggering receptor expressed by myeloid cells 1 (sTREM-1) were measured in the plasma. Association with 28-day mortality was evaluated using regression; a parsimonious biomarker model was selected using the least absolute shrinkage and selection operator (LASSO) method. Discrimination of mortality was assessed by receiver operating characteristic curve analysis and verified by multiple methods. RESULTS: IL-8, sTNFR-1, Ang-2, and sTREM-1 concentrations were strongly associated with death. LASSO identified a three-biomarker model of sTREM-1, Ang-2, and IL-8, but sTREM-1 alone provided comparable mortality discrimination (p = 0.07). sTREM-1 alone was comparable to a model of clinical variables (area under receiver operating characteristic curve [AUC] 0.81, 95% confidence interval [CI] 0.77-0.85 vs AUC 0.79, 95% CI 0.74-0.84; p = 0.43). The combination of sTREM-1 and clinical variables yielded greater mortality discrimination than clinical variables alone (AUC 0.83, 95% CI 0.79-0.87; p = 0.004). CONCLUSIONS: sTREM-1 predicts mortality from infection in a tropical, middle-income country comparably to a model derived from clinical variables and, when combined with clinical variables, can further augment mortality prediction. TRIAL REGISTRATION: The Ubon-sepsis study was registered on ClinicalTrials.gov ( NCT02217592 ), 2014.