Serum lactate as a predictor of mortality in patients with infection

Immunometabolites in viral infections: Action mechanism and function

The interplay between viral pathogens and host metabolism plays a pivotal role in determining the outcome of viral infections. Upon viral detection, the metabolic landscape of the host cell undergoes significant changes, shifting from oxidative respiration via the tricarboxylic acid (TCA) cycle to increased aerobic glycolysis. This metabolic shift is accompanied by elevated nutrient accessibility, which is vital for cell function, development, and proliferation. Furthermore, depositing metabolites derived from fatty acids, TCA intermediates, and amino acid catabolism accelerates the immunometabolic transition, facilitating pro-inflammatory and antimicrobial responses. Immunometabolites refer to small molecules involved in cellular metabolism regulating the immune response. These molecules include nutrients, such as glucose and amino acids, along with metabolic intermediates and signaling molecules adenosine, lactate, itaconate, succinate, kynurenine, and prostaglandins. Emerging evidence suggests that immunometabolites released by immune cells establish a complex interaction network within local niches, orchestrating and fine-tuning immune responses during viral diseases. However, our current understanding of the immense capacity of metabolites to convey essential cell signals from one cell to another or within cellular compartments remains incomplete. Unraveling these complexities would be crucial for harnessing the potential of immunometabolites in therapeutic interventions. In this review, we discuss specific immunometabolites and their mechanisms of action in viral infections, emphasizing recent findings and future directions in this rapidly evolving field.

Models predicting mortality risk of patients with burns to ≥ 50% of the total body surface

BACKGROUND

Several models predicting mortality risk of burn patients have been proposed. However, models that consider all such patients may not well predict the mortality of patients with extensive burns.

METHOD

This retrospective multicentre study recruited patients with extensive burns (≥ 50% of the total body surface area [TBSA]) treated in three hospitals of Eastern China from 1 January 2016 to 30 June 2022. The performances of six predictive models were assessed by drawing receiver operating characteristic (ROC) and calibration curves. Potential predictors were sought via "least absolute shrinkage and selection operator" regression. Multivariate logistic regression was employed to construct a predictive model for patients with burns to ≥ 50% of the TBSA. A nomogram was prepared and the performance thereof assessed by reference to the ROC, calibration, and decision curves.

RESULT

A total of 465 eligible patients with burns to ≥ 50% TBSA were included, of whom 139 (29.9%) died. The FLAMES model exhibited the largest area under the ROC curve (AUC) (0.875), followed by the models of Zhou et al. (0.853) and the ABSI model (0.802). The calibration curve of the Zhou et al. model fitted well; those of the other models significantly overestimated the mortality risk. The new nomogram includes four variables: age, the %TBSA burned, the area of full-thickness burns, and blood lactate. The AUCs (training set 0.889; internal validation set 0.934; external validation set 0.890) and calibration curves showed that the nomogram exhibited an excellent discriminative capacity and that the predictions were very accurate.

CONCLUSION

For patients with burns to ≥ 50％of the TBSA, the Zhou et al. and FLAMES models demonstrate relatively high predictive ability for mortality. The new nomogram is sensitive, specific, and accurate, and will aid rapid clinical decision-making.

Excess fermentation and lactic acidosis as detrimental functions of the gut microbes in treatment-naive TB patients

Introduction

The link between gut microbiota and host immunity motivated numerous studies of the gut microbiome in tuberculosis (TB) patients. However, these studies did not explore the metabolic capacity of the gut community, which is a key axis of impact on the host's immunity.

Methods

We used deep sequencing of fecal samples from 23 treatment-naive TB patients and 48 healthy donors to reconstruct the gut microbiome's metabolic capacity and strain/species-level content.

Results

We show that the systematic depletion of the commensal flora of the large intestine, Bacteroidetes, and an increase in Actinobacteria, Firmicutes, and Proteobacteria such as Streptococcaceae, Erysipelotrichaceae, Lachnospiraceae, and Enterobacteriaceae explains the strong taxonomic divergence of the gut community in TB patients. The cumulative expansion of diverse disease-associated pathobionts in patients reached 1/4 of the total gut microbiota, suggesting a heavy toll on host immunity along with MTB infection. Reconstruction of metabolic pathways showed that the microbial community in patients shifted toward rapid growth using glycolysis and excess fermentation to produce acetate and lactate. Higher glucose availability in the intestine likely drives fermentation to lactate and growth, causing acidosis and endotoxemia.

Discussion

Excessive fermentation and lactic acidosis likely characterize TB patients' disturbed gut microbiomes. Since lactic acidosis strongly suppresses the normal gut flora, directly interferes with macrophage function, and is linked to mortality in TB patients, our findings highlight gut lactate acidosis as a novel research focus. If confirmed, gut acidosis may be a novel potential host-directed treatment target to augment traditional TB treatment.

Hierarchical Capability in Distinguishing Severities of Sepsis via Serum Lactate: A Network Meta-Analysis

Background: Blood lactate is a potentially useful biomarker to predict the mortality and severity of sepsis. The purpose of this study is to systematically review the ability of lactate to predict hierarchical sepsis clinical outcomes and distinguish sepsis, severe sepsis and septic shock. Methods: We conducted an exhaustive search of the PubMed, Embase and Cochrane Library databases for studies published before 1 October 2022. Inclusion criteria mandated the presence of case-control, cohort studies and randomized controlled trials that established the association between before-treatment blood lactate levels and the mortality of individuals with sepsis, severe sepsis or septic shock. Data was analyzed using STATA Version 16.0. Results: A total of 127 studies, encompassing 107,445 patients, were ultimately incorporated into our analysis. Meta-analysis of blood lactate levels at varying thresholds revealed a statistically significant elevation in blood lactate levels predicting mortality (OR = 1.57, 95% CI 1.48-1.65, I2 = 92.8%, p < 0.00001). Blood lactate levels were significantly higher in non-survivors compared to survivors in sepsis patients (SMD = 0.77, 95% CI 0.74-0.79, I2 = 83.7%, p = 0.000). The prognostic utility of blood lactate in sepsis mortality was validated through hierarchical summary receiver operating characteristic curve (HSROC) analysis, yielding an area under the curve (AUC) of 0.72 (95% CI 0.68-0.76), accompanied by a summary sensitivity of 0.65 (95% CI 0.59-0.7) and a summary specificity of 0.7 (95% CI 0.64-0.75). Unfortunately, the network meta-analysis could not identify any significant differences in average blood lactate values' assessments among sepsis, severe sepsis and septic shock patients. Conclusions: This meta-analysis demonstrated that high-level blood lactate was associated with a higher risk of sepsis mortality. Lactate has a relatively accurate predictive ability for the mortality risk of sepsis. However, the network analysis found that the levels of blood lactate were not effective in distinguishing between patients with sepsis, severe sepsis and septic shock.

Reverse shock index multiplied by simplified motor score as a predictor of clinical outcomes for patients with COVID-19

BACKGROUND

The reverse shock index (rSI) combined with the Simplified Motor Score (sMS), that is, the rSI-sMS, is a novel and efficient prehospital triage scoring system for patients with COVID-19. In this study, we evaluated the predictive accuracy of the rSI-sMS for general ward and intensive care unit (ICU) admission among patients with COVID-19 and compared it with that of other measures, including the shock index (SI), modified SI (mSI), rSI combined with the Glasgow Coma Scale (rSI-GCS), and rSI combined with the GCS motor subscale (rSI-GCSM).

METHODS

All patients who visited the emergency department of Taipei Tzu Chi Hospital between January 2021 and June 2022 were included in this retrospective cohort. A diagnosis of COVID-19 was confirmed through a SARS-CoV-2 reverse-transcription polymerase chain reaction test or SARS-CoV-2 rapid test with oropharyngeal or nasopharyngeal swabs and was double confirmed by checking International Classification of Diseases, Tenth Revision, Clinical Modification codes in electronic medical records. In-hospital mortality was regarded as the primary outcome, and sepsis, general ward or ICU admission, endotracheal intubation, and total hospital length of stay (LOS) were regarded as secondary outcomes. Multivariate logistic regression was used to determine the relationship between the scoring systems and the three major outcomes of patients with COVID-19, including. The discriminant ability of the predictive scoring systems was investigated using the area under the receiver operating characteristic curve, and the most favorable cutoff value of the rSI-sMS for each major outcome was determined using Youden's index.

RESULTS

After 74,183 patients younger than 20 years (n = 11,572) and without COVID-19 (n = 62,611) were excluded, 9,282 patients with COVID-19 (median age: 45 years, interquartile range: 33-60 years, 46.1% men) were identified as eligible for inclusion in the study. The rate of in-hospital mortality was determined to be 0.75%. The rSI-sMS scores were significantly lower in the patient groups with sepsis, hyperlactatemia, admission to a general ward, admission to the ICU, total length of stay ≥ 14 days, and mortality. Compared with the SI, mSI, and rSI-GCSM, the rSI-sMS exhibited a significantly higher accuracy for predicting general ward admission, ICU admission, and mortality but a similar accuracy to that of the rSI-GCS. The optimal cutoff values of the rSI-sMS for predicting general ward admission, ICU admission, and mortality were calculated to be 3.17, 3.45, and 3.15, respectively, with a predictive accuracy of 86.83%, 81.94%%, and 90.96%, respectively.

CONCLUSIONS

Compared with the SI, mSI, and rSI-GCSM, the rSI-sMS has a higher predictive accuracy for general ward admission, ICU admission, and mortality among patients with COVID-19.

Unmeasured Organic Anions as Predictors of Clinical Outcomes in Lactic Acidosis due to Sepsis

Background and Objectives: In lactic acidosis, lactate can only explain 30% of the variance in the anion gap (AG), and the elevated AG not explained by lactate is due to unmeasured organic anions (UOAs). Some studies using less precise surrogates for UOA have suggested that UOA may predict clinical outcomes better than lactate. The aim of this study was to determine whether UOA predicts clinical outcomes better than lactate levels. Design, Setting, Participants, & Measurements: This was a retrospective cohort study of adult ICU patients with sepsis. Baseline AG and albumin measurements were obtained. An albumin-corrected delta AG was calculated. UOAs were estimated using the formula: Delta AG - serum lactate. A multivariate logistic regression model with its respective ROC curve was constructed to explore the relationship between in-hospital mortality, UOA, and lactate. Results: 526 patients were included. In the combined model examining both lactate and UOA, the odds ratio (OR) [95% CI] for predicting ICU length of stay (LOS) was 1.050 [1.029-1.072] and 1.022 [1.009-1.035], respectively; the OR [95% CI] for predicting in-hospital mortality was 1.224 [1.104-1.358] and 0.997 [0.943-1.054], respectively. The ROC curve for in-hospital mortality demonstrated that the Area Under the Curve (AUC) for lactate, UOA, and combined lactate and UOA was 0.7726, 0.7486, and 0.7732, respectively. The AUC for combined lactate and UOA were not statistically significantly higher than the AUC for lactate alone (P .9193). Conclusions: As expected, serum lactate predicted both ICU LOS and in-hospital mortality. UOA did predict ICU LOS, although the reason for this association is not known. UOA did not predict in-hospital mortality based on the OR and the ROC curve's AUC, contrary to some previous studies. However, our study used a more precise quantitative estimate of UOA, including the use of baseline albumin-corrected AG. Prior studies attempting to identify UOA have identified Krebs cycle intermediates including citrate and isocitrate, suggesting that in our study these anions associated with the Krebs cycle contributed to the UOA.

Modified Rapid Emergency Medicine Score-Lactate (mREMS-L) performance to screen non-anticipated 30-day-related-mortality in emergency department

BACKGROUND

The aim of this study was to compare the ability to predict 30-day in-hospital mortality of lactate versus the modified Rapid Emergency Medicine Score (mREMS) versus the arithmetic sum of the mREMS plus the numerical value of lactate (mREMS-L).

METHODS

A prospective, multicentric, emergency department delivery, pragmatic study was conducted. To determine the predictive capacity of the scales, lactate was measured and the mREMS and mREMS-L were calculated in adult patients (aged>18 years) transferred with high priority by ambulance to the emergency department in five hospitals of Castilla y Leon between 1 January 2020 and 31 December 2021. The area under the receiver operating characteristic (ROC) curve of each of the scales was calculated in terms of mortality for 30 days.

RESULTS

A total of 5371 participants were included, and the in-hospital mortality rate at 30 days was of 11.4% (615 cases). The best cut-off point determined in the mREMS was 7.0 points (sensitivity of 67% and specificity of 84%), and for lactate, the cut-off point was 1.4 mmol/L (sensitivity of 88% and specificity of 67%). Finally, the combined mREMS-L showed a cut-off point of 7.9 (sensitivity of 83% and a specificity of 83%). The area under the ROC curve of the mREMS, lactate and mREMS-L for 30-day mortality was 0.851, 0.853, and 0.903, respectively (p < 0.001 in all cases).

CONCLUSIONS

The new score generated, mREMS-L, obtained better statistical results than its components (mREMS and lactate) separately.

Serum lactate and the mortality of critically ill patients in the emergency department: A retrospective study

Serum lactate levels have been widely studied as a prognostic marker in critically ill patients, particularly those in the intensive care unit. However, it remains unknown whether the serum lactate levels affect the mortality rate of critically ill patients admitted to hospital. To investigate this hypothesis, the vital signs and blood gas analysis data of 1,393 critically ill patients who visited the Emergency Department of Affiliated Kunshan Hospital of Jiangsu University (Kunshan, China) between January and December 2021 were collected. Patients were divided into two groups, 30-day survival group and a 30-day death group, and logistic regression analysis was used to investigate the association between vital signs, laboratory results and mortality rates of critically ill patients. A total of 1,393 critically ill patients was enrolled in the present study, with a male-to-female ratio of 1.17:1.00, a mean age of 67.72±19.29 years and a mortality rate of 11.6%. The multivariate logistic regression analysis revealed that increased serum lactate levels were an independent risk factor for mortality rate of critically ill patients [Odds ratio (OR)=1.50, 95% confidence interval (95% CI): 1.40-1.62]. The critical cut-off value for the serum lactate levels was identified as 2.35 mmol/l. In addition, OR values of age, heart rate, systolic blood pressure, transcutaneous oxygen saturation (SpO₂) and hemoglobin were 1.02, 1.01, 0.99, 0.96 and 0.99, respectively (95% CI: 1.01-1.04, 1.00-1.02, 0.98-0.99, 0.94-0.98 and 0.98-1.00, respectively). The logistic regression model was found to be of value in terms of identifying the mortality rate of patients and the area under the receiver operating characteristic curve was 0.894 (95% CI: 0.863-0.925; P<0.001). In conclusion, the present study showed that high serum lactate levels in critically ill patients upon admission to hospital are associated with higher 30-day mortality rate.

Hyperlactatemia is associated with increased risks of long-term mortality and major adverse cardiovascular events in sepsis survivors

INTRODUCTION

Serum lactate is a potentially valuable biomarker for risk assessment for patients with sepsis, as hyperlactatemia is associated with elevated short-term mortality risks. However, the associations between hyperlactatemia and long-term clinical outcomes in sepsis survivors remain unknown. The objective of this study was to investigate whether hyperlactatemia at the time of hospitalisation for sepsis was associated with worse long-term clinical outcomes in sepsis survivors.

METHODS

In total, of 4983 sepsis survivors aged ≥ 20 years were enrolled in this study between January 1, 2012, and December 31, 2018. They were divided into low (≤18 mg/dL; n = 2698) and high (>18 mg/dL; n = 2285) lactate groups. The high lactate group was then matched 1:1 by propensity-score method to the low lactate group. The outcomes of interest were all-cause mortality, major adverse cardiac events (MACEs), ischaemic stroke, myocardial infarction, hospitalisation for heart failure, and end-stage renal disease.

RESULTS

After propensity score matching, the high lactate group had greater risks of all-cause mortality (hazard ratio [HR] 1.54, 95% confidence interval [CI] 1.41-1.67), MACEs (HR 1.53, 95% CI 1.29-1.81), ischaemic stroke (HR 1.47, 95% CI 1.19-1.81), myocardial infarction (HR 1.52, 95% CI 1.17-1.99), and end-stage renal disease (HR 1.42, 95% CI 1.16-1.72). Subgroup analyses stratified by baseline renal function revealed almost similarity across groups.

CONCLUSION

We found that hyperlactatemia is associated with long-term risks of mortality and MACEs in sepsis survivors. Physicians may consider more aggressive and prompter management of sepsis in patients who present with hyperlactatemia to improve long-term prognoses.

Implementing Pediatric Surviving Sepsis Campaign Guidelines: Improving Compliance With Lactate Measurement in the PICU

The 2020 pediatric Surviving Sepsis Campaign (pSSC) recommends measuring lactate during the first hour of resuscitation for severe sepsis/shock. We aimed to improve compliance with this recommendation for patients who develop severe sepsis/shock while admitted to the PICU.

DESIGN

Structured, quality improvement initiative.

SETTING

Single-center, 26-bed, quaternary-care PICU.

PATIENTS

All patients with PICU-onset severe sepsis/shock from December 2018 to December 2021.

INTERVENTIONS

Creation of a multidisciplinary local sepsis improvement team, education program targeting frontline providers (nurse practitioners, resident physicians), and peer-to-peer nursing education program with feedback to key stakeholders.

MEASUREMENTS AND MAIN RESULTS

The primary outcome measure was compliance with obtaining a lactate measurement within 60 minutes of the onset of severe sepsis/shock originating in our PICU using a local Improving Pediatric Sepsis Outcomes database and definitions. The process measure was time to first lactate measurement. Secondary outcomes included number of IV antibiotic days, number of vasoactive days, number of ICU days, and number of ventilator days. A total of 166 unique PICU-onset severe sepsis/shock events and 156 unique patients were included. One year after implementation of our first interventions with subsequent Plan-Do-Study-Act cycles, overall compliance increased from 38% to 47% (24% improvement) and time to first lactate decreased from 175 to 94 minutes (46% improvement). Using a statistical process control I chart, the preshift mean for time to first lactate measurement was noted to be 179 minutes and the postshift mean was noted to be 81 minutes demonstrating a 55% improvement.

CONCLUSIONS

This multidisciplinary approach led to improvement in time to first lactate measurement, an important step toward attaining our target of lactate measurement within 60 minutes of septic shock identification. Improving compliance is necessary for understanding implications of the 2020 pSSC guidelines on sepsis morbidity and mortality.

Serum Lactate-Albumin Ratio: Soothsayer for Outcome in Sepsis

AIM

The aim of this study is to assess the efficacy of the serum lactate/albumin (L/A) ratio as a prognostic marker of sepsis syndrome.

MATERIALS AND METHODS

This study was conducted in the Internal Medicine Department at Acharya Vinoba Bhave Rural Hospital with a sample size of 160 cases of sepsis. The serum L/A ratio was calculated on admission and correlated with deaths and morbidity. Statistical analysis was significant if the P-value was less than 0.05.

RESULTS

The mean age of patients was 52.83 ± 16.80 years with a male predominance (64.4% vs. 35.6%). The mean L/A ratio was 0.95 ± 0.46. The proportion of discharged subjects and mortality were 58.8% and 41.2%, respectively. The study found that a higher mean L/A ratio (1.1-1.44) was significantly linked to the various variables in the study. Furthermore, a significantly higher median L/A ratio of 1.23 was found in subjects with vasopressor use. The median L/A ratio in the Discharge group and Death group was 0.64 and 1.27, respectively. The area under the receiver operating characteristic (AUROC) curve indicated that accurate diagnostic performance was 0.976 in predicting Death versus Discharge for the L/A ratio.

CONCLUSION

This study found that, compared to lactate and albumin alone, the predictor value of the L/A ratio was outstanding in predicting death and hospital stay (discharge) among sepsis participants, with a sensitivity of 100% and a specificity of 88%.

Intensive care unit-acquired pneumonia caused by Klebsiella pneumoniae in China: Risk factors and prediction model of mortality

Intensive care unit (ICU)-acquired pneumonia (ICUAP) is a major concern owing to its associated high mortality rate. Few studies have focused on ICUAP caused by Klebsiella pneumoniae (KP). This study aimed to investigate the risk factors for ICUAP-associated death due to KP and to develop a mortality prediction model. Patients with KP-associated ICUAP at Renji Hospital were enrolled from January 2012 to December 2017. The patients were registered from the ICU units of the Surgery, Gynecology and Obstetrics, Neurosurgery, Emergency and Geriatric Departments, and were followed for 30 days. A multivariate analysis was performed to analyze the differences between 30-day survivors and nonsurvivors, and to determine the independent risk factors. Receiver operator characteristic (ROC) curves were also used to determine the predictive power of the model. Among the 285 patients with KP-associated ICUAP, the median age was 70.55 years, and 61.6% were men. Fifty patients died. The nonsurvivors had a lower Glasgow coma score (GCS), platelet count, and albumin concentrations, but higher lactate concentrations, than the survivors. The nonsurvivors were also more likely to be admitted to the ICU for respiratory failure and surgery, and they received less appropriate empirical antimicrobial therapy than the survivors. A lower GCS (odds ratio [OR] = 0.836, 95% confidence interval [CI]: 0.770-0.907), lower albumin concentrations (OR = 0.836, 95% CI: 0.770-0.907), higher lactate concentrations (OR = 1.167, 95% CI: 1.0013-1.344) and inappropriate empirical treatment (OR = 2.559, 95% CI: 1.080-6.065) were independent risk factors for mortality in patients with KP-associated ICUAP. ROC curve analysis showed that the risk of death was higher in patients with 2 or more independent risk factors. The predictive model was effective, with an area under the ROC curve of 0.823 (95% CI: 0.773-0.865). The number of independent risk factors is positively correlated with the risk of death. Our model shows excellent predictive performance.

[Sepsis during pregnancy: Key points in 2022]

Sepsis is a severe affection, that requires an urgent and specific treatment sequence. Physiological changes occurring during pregnancy make the diagnosis of sepsis more challenging in this setting, with possible delay in treatment initiation, that in turn is responsible for poorer maternal and fetal outcome. This review aims to summarize current knowledge on the diagnosis and treatment of maternal sepsis, as well as persistent knowledge gaps in the field.

Diagnostic and therapeutic value of biomarkers in urosepsis

Urosepsis is sepsis caused by urogenital tract infection and is one of the most common critical illnesses in urology. If urosepsis is not diagnosed early, it can rapidly progress and worsen, leading to increased mortality. In recent years, with the increase of urinary tract surgery, the incidence of urosepsis continues to rise, posing a serious threat to patients. Early diagnosis of urosepsis, timely and effective treatment can greatly reduce the mortality of patients. Biomarkers such as WBC, NLR, PCT, IL-6, CRP, lactate, and LncRNA all play specific roles in the early diagnosis or prognosis of urosepsis. In addition to the abnormal increase of WBC, we should be more alert to the rapid decline of WBC. NLR values were superior to WBC counts alone in predicting infection severity. Compared with several other biomarkers, PCT values can differentiate between bacterial and non-bacterial sepsis. IL-6 always has high sensitivity and specificity for the diagnosis of sepsis, and CRP also has high sensitivity and specificity for the diagnosis of urosepsis. Lactic acid is closely related to the prognosis of patients with urosepsis. LncRNAs may be potential biomarkers of urosepsis. This article summarizes the main biomarkers, hoping to provide a reference for the timely diagnosis and evaluation of urosepsis.

Hyperlactatemia is a predictor of mortality in patients undergoing continuous renal replacement therapy for acute kidney injury

BACKGROUND

Hyperlactatemia occurs frequently in critically ill patients, and this pathologic condition leads to worse outcomes in several disease subsets. Herein, we addressed whether hyperlactatemia is associated with the risk of mortality in patients undergoing continuous renal replacement therapy (CRRT) due to acute kidney injury.

METHODS

A total of 1,661 patients who underwent CRRT for severe acute kidney injury were retrospectively reviewed between 2010 and 2020. The patients were categorized according to their serum lactate levels, such as high (≥ 7.6 mmol/l), moderate (2.1-7.5 mmol/l) and low (≤ 2 mmol/l), at the time of CRRT initiation. The hazard ratios (HRs) for the risk of in-hospital mortality were calculated with adjustment of multiple variables. The increase in the area under the receiver operating characteristic curve (AUROC) for the mortality risk was evaluated after adding serum lactate levels to the Sequential Organ Failure Assessment (SOFA) and the Acute Physiology and Chronic Health Evaluation (APACHE) II score-based models.

RESULTS

A total of 802 (48.3%) and 542 (32.6%) patients had moderate and high lactate levels, respectively. The moderate and high lactate groups had a higher risk of mortality than the low lactate group, with HRs of 1.64 (1.22-2.20) and 4.18 (2.99-5.85), respectively. The lactate-enhanced models had higher AUROCs than the models without lactates (0.764 vs. 0.702 for SOFA score; 0.737 vs. 0.678 for APACHE II score).

CONCLUSIONS

Hyperlactatemia is associated with mortality outcomes in patients undergoing CRRT for acute kidney injury. Serum lactate levels may need to be monitored in this patient subset.

Evaluation of plasma lactate parameters for predicting mortality of septic patients

Objective

To compare the accuracy of serum lactate parameters, including lactate peak concentration (LACpeak), lactate time area (LACarea), and lactate clearance (LC) for predicting mortality of the septic patients, and to compare with the predictive accuracy of National Early Warning Score (NEWS) and Sequential Organ Failure Assessment (SOFA) scores.

Methods

This study retrospectively screened the septic patients admitted to the ICU in the Medical Information Mart for Intensive Care IV (MIMIC-IV) from 2008 to 2019. The baseline data and outcomes of patients were gathered. The subjects were divided into the non-survival group and the survival group. SOFA, NEWS, LACpeak, and LACarea were recorded. The LC was calculated 6 h after LACpeak. The above parameters were compared by the T-test and Mann-Whitney U test, and odds ratios were calculated adjusting for age and sex. The receiver operating characteristic curves (ROCs) of subjects were plotted according to SOFA, NEWS, LACpeak, and LACarea within 24h, and LC at 6h of ICU admission. The Areas under the ROC curve (AUCs), sensitivity, and specificity were compared with R version 4.1.1.

Results

1,169 septic patients were involved, and 366 (31.3%) patients died within 28 days. Compared to the survival group, the LACpeak of the non-survival group was higher [4.85 (3.2, 7.9) vs. 3.4 (2.6, 5.25) mmol/L, adjusted odds ratio 1.18, P < 0.001], and the LACarea of the non-survivals was higher than the survivals too [18.44 (10.36, 27.63) vs. 13.65 (9.01, 21.73), adjusted odds ratio 1.03, P < 0.001)]. The LC of the survivals at 6 h after LACpeak was significantly higher than that of the non-survivals [0.26 (0.14.0.42) vs. 0.19 (0.10, 0.33), adjusted odds ratio 0.06, P < 0.01]. Within 24h of ICU admission, the AUCs of mortality prediction in descending order were NEWS [0.73 (0.70, 0.76)], SOFA [0.69 (0.66, 0.73)], LACpeak [0.64 (0.61, 0.68)], and LACarea [0.60 (0.56, 0.63)]. There were 204 patients with 6-hour LC after LACpeak the AUCs of LACarea, LACpeak and LC were 0.73(0.65, 0.80), 0.71(0.62,0.78) and 0.65 (0.56, 0.73), respectively.

Conclusions

The predictive accuracy of LC was not superior to LACpeak and LACarea for the mortality of the septic patients and the predictive value of all the above lactate parameters for mortality maybe not better than SOFA and NEWS.

Can an End-to-End Telesepsis Solution Improve the Severe Sepsis and Septic Shock Management Bundle-1 Metrics for Sepsis Patients Admitted From the Emergency Department to the Hospital?

Early detection and treatment for sepsis patients are key components to improving sepsis care delivery and increased The Severe Sepsis and Septic Shock Management Bundle (SEP-1) compliance may correlate with improved outcomes.

OBJECTIVES

We assessed the impact of implementing a partially automated end-to-end sepsis solution including electronic medical record-linked automated monitoring, early detection, around-the-clock nurse navigators, and teleconsultation, on SEP-1 compliance in patients with primary sepsis, present at admission, admitted through the emergency department (ER).

DESIGN SETTING AND PARTICIPANTS

After a "surveillance only" training period between September 3, 2020, and October 5, 2020, the automated end-to-end sepsis solution intervention period occurred from October 6, 2020, to January 1, 2021 in five ERs in an academic health system. Patients who screened positive for greater than or equal to 3 sepsis screening criteria (systemic inflammatory response syndrome, quick Sequential Organ Failure Assessment, pulse oximetry), had evidence of infection and acute organ dysfunction, and were receiving treatment consistent with infection or sepsis were included.

MAIN OUTCOMES AND MEASURES

SEP-1 compliance during the "surveillance only" period compared to the intervention period.

RESULTS

During the intervention period, 56,713 patients presented to the five ERs; 20,213 (35.6%) met electronic screening criteria for potential sepsis; 1,233 patients had a primary diagnosis of sepsis, present at admission, and were captured by the nurse navigators. Median age of the cohort was 68 years (interquartile range, 57-79 yr); 55.3% were male; 63.5% were White/Caucasian, 26.3% Black/African-American; was 16.7%, and 879 patients (71.3%) were presumed bacterial sepsis, nonviral etiology, and SEP-1 bundle eligible. Nurse navigator real-time classification of this group increased from 51.7% during the "surveillance only" period to 71.8% during the intervention period (p = 0.0002). Five hospital SEP-1 compliance for the period leading into the study period (July 1, 2020-August 31, 2020) was 62% (p < 0.0001), during the "surveillance only" period, it was 68.4% and during the intervention period it was 78.3% (p = 0.002).

CONCLUSIONS AND RELEVANCE

During an 11-week period of sepsis screening, monitoring, and teleconsultation in 5 EDs, SEP-1 compliance improved significantly compared with institutional SEP-1 reporting metrics and to a "surveillance only" training period.

Construction and efficacy evaluation of an early warning scoring system for septic shock in patients with digestive tract perforation: A retrospective cohort study

Objective

To establish an early warning scoring system for septic shock in patients with digestive tract perforation (DTP) and evaluate its diagnostic efficacy.

Methods

Patients with surgically confirmed or clinically diagnosed DTP admitted to the Department of Intensive Care Medicine of Fujian Provincial Hospital from June 2012 to October 2021 were retrospectively analyzed. General demographic characteristics, perforation-related information, vital signs, common laboratory indicators, and common ICU scores (Glasgow Coma Scale score, Acute Physiology and Chronic Health Evaluation-II score,Sequential Organ Failure Assessment score) were collected. The patients were divided into shock group and non-shock group according to whether the patients had septic shock during hospitalization. The risk factors of septic shock were screened by basic statistical analysis and multivariate Logistic regression analysis. The receiver operating characteristic curve was drawn to determine the cut-off value of the continuous indicators and discretized with reference to clinic, and the corresponding score was set according to the β regression coefficient of each variable.

Results

A total of 176 patients with DTP were included. The average age of the patients was 64.13 ± 14.67 years old, and 74.40% were males. The incidence of septic shock was 30.11% (53/176). Multivariate Logistic regression analysis showed that the highest heart rate≥105 beats/min, Glasgow Coma Scale score≤14 points, lactic acid≥5.75 mmol/L, procalcitonin≥41.47 ug/L, C-reactive protein≥222.5 mg/L were independent risk factors for septic shock in patients with DTP. The total score of clinical diagnostic scoring system of septic shock in patients with DTP was 6 points, including the highest heart rate≥105 beats/min (1 point), lactic acid≥5.75 mmol/L (two points), procalcitonin≥41.47 ug/L (one point), C-reactive protein≥222.5 mg/L (1 point), and Glasgow Coma Scale score≤14 points (1 point). The area under ROC curve (AUC) of this scoring system was 0.789 and the 95% confidence interval was 0.717–0.860 (P &lt; 0.001); when the optimal cut-off value was 2.5, the sensitivity and specificity were 54.70 and 87.80%, respectively.

Conclusion

This new score system has its certain clinical value and has important guiding significance for clinicians to judge the prognosis of patients with DTP in time.

Independent risk factors of mortality in patients with sepsis receiving single-dose etomidate as an induction agent during rapid sequence intubation in a large tertiary emergency department in Thailand

BACKGROUND

There is limited evidence regarding factors associated with mortality in septic patients receiving etomidate. This study aimed to determine independent pre-intubation factors predicting 28-day mortality in septic patients receiving single-dose etomidate as an induction agent during rapid sequence intubation (RSI).

METHODS

This single-center retrospective cohort study included intubated septic patients receiving etomidate as an induction agent during RSI in the emergency department of Siriraj hospital, Bangkok, Thailand, between January 1st, 2016 and June 30th, 2020. Pre-intubation characteristics were compared between survivors and non-survivors. Independent risk factors associated with 28-day mortality were identified using the Cox proportional hazards regression model. Association between etomidate dosage and mortality was also determined.

RESULTS

A total of 344 patients, 238 (69%) survivors and 106 (31%) non-survivors, were included in the analyses. The initial Cox hazards model identified a pre-intubation lactate level ≥ 4 mmol/L as an independent factor associated with mortality (adjusted Hazards ratio [aHR] 2.66, 95% confidence interval [CI] 1.55-4.56). After removing lactate level from the model due to limited lactate values in the data, cancer was also predictive of 28-day mortality (aHR 1.83, 95%CI 1.10-3.04), while patients with respiratory infections and underlying chronic lung disease were associated with lower mortality (aHR 0.54, 95%CI 0.37-0.80 and aHR 0.57, 0.33-0.96, respectively). Etomidate dosage was not associated with mortality in our study.

CONCLUSION

In septic patients who received a single dose of etomidate, a pre-intubation lactate level ≥ 4 mmol/L and cancer were associated with increased 28-day mortality, while respiratory infection and underlying chronic lung disease were associated with lower mortality. Physicians may take these factors into consideration when selecting induction agents for septic patients.

Apelin-13 Attenuates Lipopolysaccharide-Induced Inflammatory Responses and Acute Lung Injury by Regulating PFKFB3-Driven Glycolysis Induced by NOX4-Dependent ROS

Purpose

Acute lung injury (ALI) is a life-threatening condition with limited therapeutic options. Macrophage inflammation plays a key role in the development of ALI. Abnormal glycolysis of macrophages contributes to the inflammatory response. However, the role of macrophage glycolysis in ALI still requires investigation. Apelin-13 has been shown to protect against ALI, whereas the underlying mechanisms remain unclear. In this study, we explored the effect of apelin-13 on lipopolysaccharide (LPS)-induced inflammation and ALI via regulation of glycolysis by modulating redox homeostasis in macrophages.

Methods

Serums from 34 patients with sepsis and 13 healthy volunteers were analyzed. In vivo, the protective effect of apelin-13 against LPS-induced ALI was evaluated using a mouse model of LPS-induced ALI. In vitro, mouse bone marrow macrophages (BMDMs) were pretreated with the antioxidant, NADPH oxidase (NOX) 4 (NOX4) small-interfering RNA (siRNA), the 6-phosphofructo-2 -kinase/fructose- 2,6-biphosphatase 3 (PFKFB3) siRNA, or the PFKFB3 overexpression plasmid before exposure to LPS.

Results

Serum apelin-13 levels were significantly elevated in patients with sepsis and sepsis-associated acute respiratory distress syndrome (ARDS) (P<0.0001). In vivo, apelin-13 suppressed LPS-induced ALI and inflammatory cytokine production (P<0.05). Furthermore, apelin-13 reduced hydrogen peroxide (H₂O₂) content, NOX4 protein levels, and glycolysis. In vitro, LPS stimulation elevated NOX4 protein levels and reactive oxygen species (ROS) production (P<0.05). These changes resulted in the accumulation of glycolysis in BMDMs. Treatment with antioxidant or NOX4 siRNA inhibited LPS-induced glycolysis and inflammatory cytokine production (P<0.05). Moreover, in vitro experiments revealed that PFKFB3 regulates the release of pro-inflammatory cytokines by modulating glycolysis. In contrast, the action of apelin-13 opposed the effects of LPS.

Conclusion

In conclusion, apelin-13 protects against LPS-induced inflammatory responses and ALI by regulating PFKFB3-driven glycolysis induced by NOX4-dependent ROS.

Serum Lactate and Mortality during Pediatric Admissions: Is 2 Really the Magic Number?

The primary objective of this study was to determine if serum lactate level at the time of hospital admission can predict mortality in pediatric patients. A systematic review was conducted to identify studies that assessed the utility of serum lactate at the time of admission to predict mortality in pediatric patients. The areas under the curve from the receiver operator curve analyses were utilized to determine the pooled area under the curve. Additionally, standardized mean difference was compared between those who survived to discharge and those who did not. A total of 12 studies with 2,099 patients were included. Out of these, 357 (17%) experienced mortality. The pooled area under the curve for all patients was 0.74 (0.67-0.80, p  < 0.01). The pooled analyses for all admissions were higher in those who experienced mortality (6.5 vs. 3.3 mmol/L) with a standardized mean difference of 2.60 (1.74-3.51, p  < 0.01). The pooled area under the curve for cardiac surgery patients was 0.63 (0.53-0.72, p  < 0.01). The levels for cardiac surgery patients were higher in those who experienced mortality (5.5 vs. 4.1 mmol/L) with a standardized mean difference of 1.80 (0.05-3.56, p  = 0.04). Serum lactate at the time of admission can be valuable in identifying pediatric patients at greater risk for inpatient mortality. This remained the case when only cardiac surgery patients were included.

Improving sepsis care in Africa: an opportunity for change?

Sepsis is common and represents a major public health burden with significant associated morbidity and mortality. However, despite substantial advances in sepsis recognition and management in well-resourced health systems, there remains a distinct lack of research into sepsis in Africa. The lack of evidence affects all levels of healthcare delivery from individual patient management to strategic planning at health-system level. This is particular pertinent as African countries experience some of the highest global burden of sepsis. The 2017 World Health Assembly resolution on sepsis and the creation of the Africa Sepsis Alliance provided an opportunity for change. However, progress so far has been frustratingly slow. The recurrent Ebola virus disease outbreaks and the COVID-19 pandemic on the African continent further reinforce the need for urgent healthcare system strengthening. We recommend that African countries develop national action plans for sepsis which should address the needs of all critically ill patients.

The prognostic value of the lactate/albumin ratio for predicting mortality in septic patients presenting to the emergency department: a prospective study

OBJECTIVES

Lactate/albumin (L/A) ratio is a biomarker in sepsis that has been shown to outperform lactate. This prospective study aims to validate the superior prognostic value of the L/A ratio to lactate in sepsis and septic shock.

METHODS

Prospective cohort conducted from September 2018 till February 2021 on adult patients presenting to the Emergency Department (ED) at a tertiary care centre with sepsis or septic shock. The primary outcome was the prognostic value of the L/A ratio compared to lactate with regards to mortality.

RESULTS

A total of 939 septic patients were included throughout the study period. A total of 236 patients developed septic shock. The AUC value of the L/A ratio in septic patients was 0.65 (95% CI 0.61-0.70) and was higher than that of lactate alone 0.60 (95% CI 0.55-0.64) with a p < .0001. The optimal L/A ratio cut-off threshold that separated survivors from non-survivors was found to be 0.115 for all septic patients. The AUC of the L/A ratio was significantly higher for patients with a lactate ≥2 mmol/L: 0.69 (95% CI 0.64-0.74) versus 0.60 (95% CI 0.54-0.66) with a p < .0001 as well as for patients with an albumin level less than 30 g/L (AUC = 0.69 95% CI= 0.62-0.75 vs AUC= 0.66 95% CI= 0.59-0.73, p = .04). Among septic shock patients there was no statically significant difference in the AUC value of the L/A ratio compared to lactate (0.53 95% CI 0.45-0.61 vs 0.50 95% CI 0.43-0.58 respectively with a p-value = .11).

CONCLUSIONS

The L/A ratio is a better predictor of in-patient mortality than lactate in sepsis patients. This superiority was not found in the septic shock subgroup. Our results encourage the use of the ratio early in the ED as a superior prognostic tool in sepsis patients.Key messagesWe aimed to assess the prognostic usefulness of the Lactate/Albumin ratio compared to lactate alone in septic and septic shock patients.The L/A ratio proved to be a better predictor of in-patient mortality than lactate alone in sepsis patients. This pattern also applies across various subgroups in our study (malignancy, diabetics, age above 65, lactate level less than 2 mmol/L, albumin less than 30 g/L). Our results favour the use of the L/A ratio over lactate alone in patients with sepsis and the previously mentioned subgroups.Our results do not favour the use of the ratio instead of lactate in septic shock patients as there was no statistically significant difference between the AUCs of the ratio and lactate alone.

Influenza A induces lactate formation to inhibit type I IFN in primary human airway epithelium

Pathogenic viruses induce metabolic changes in host cells to secure the availability of biomolecules and energy to propagate. Influenza A virus (IAV) and severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) both infect the human airway epithelium and are important human pathogens. The metabolic changes induced by these viruses in a physiologically relevant human model and how this affects innate immune responses to limit viral propagation are not well known. Using an ex vivo model of pseudostratified primary human airway epithelium, we here demonstrate that infection with both IAV and SARS-CoV-2 resulted in distinct metabolic changes including increases in lactate dehydrogenase A (LDHA) expression and LDHA-mediated lactate formation. Interestingly, LDHA regulated both basal and induced mitochondrial anti-viral signaling protein (MAVS)-dependent type I interferon (IFN) responses to promote IAV, but not SARS-CoV-2, replication. Our data demonstrate that LDHA and lactate promote IAV but not SARS-CoV-2 replication by inhibiting MAVS-dependent induction of type I IFN in primary human airway epithelium.

Lactate Is a Metabolic Mediator That Shapes Immune Cell Fate and Function

Lactate and the associated H⁺ ions are still introduced in many biochemistry and general biology textbooks and courses as a metabolic by-product within fast or oxygen-independent glycolysis. However, the role of lactate as a fuel source has been well-appreciated in the field of physiology, and the role of lactate as a metabolic feedback regulator and distinct signaling molecule is beginning to gain traction in the field of immunology. We now know that while lactate and the associated H⁺ ions are generally immunosuppressive negative regulators, there are cell, receptor, mediator, and microenvironment-specific effects that augment T helper (Th)17, macrophage (M)2, tumor-associated macrophage, and neutrophil functions. Moreover, we are beginning to uncover how lactate and H⁺ utilize different transporters and signaling cascades in various immune cell types. These immunomodulatory effects may have a substantial impact in cancer, sepsis, autoimmunity, wound healing, and other immunomodulatory conditions with elevated lactate levels. In this article, we summarize the known effects of lactate and H⁺ on immune cells to hypothesize potential explanations for the divergent inflammatory vs. anti-inflammatory effects.

Machine Learning Consensus Clustering Approach for Patients with Lactic Acidosis in Intensive Care Units

BACKGROUND

Lactic acidosis is a heterogeneous condition with multiple underlying causes and associated outcomes. The use of multi-dimensional patient data to subtype lactic acidosis can personalize patient care. Machine learning consensus clustering may identify lactic acidosis subgroups with unique clinical profiles and outcomes.

METHODS

We used the Medical Information Mart for Intensive Care III database to abstract electronic medical record data from patients admitted to intensive care units (ICU) in a tertiary care hospital in the United States. We included patients who developed lactic acidosis (defined as serum lactate ≥ 4 mmol/L) within 48 h of ICU admission. We performed consensus clustering analysis based on patient characteristics, comorbidities, vital signs, organ supports, and laboratory data to identify clinically distinct lactic acidosis subgroups. We calculated standardized mean differences to show key subgroup features. We compared outcomes among subgroups.

RESULTS

We identified 1919 patients with lactic acidosis. The algorithm revealed three best unique lactic acidosis subgroups based on patient variables. Cluster 1 (n = 554) was characterized by old age, elective admission to cardiac surgery ICU, vasopressor use, mechanical ventilation use, and higher pH and serum bicarbonate. Cluster 2 (n = 815) was characterized by young age, admission to trauma/surgical ICU with higher blood pressure, lower comorbidity burden, lower severity index, and less vasopressor use. Cluster 3 (n = 550) was characterized by admission to medical ICU, history of liver disease and coagulopathy, acute kidney injury, lower blood pressure, higher comorbidity burden, higher severity index, higher serum lactate, and lower pH and serum bicarbonate. Cluster 3 had the worst outcomes, while cluster 1 had the most favorable outcomes in terms of persistent lactic acidosis and mortality.

CONCLUSIONS

Consensus clustering analysis synthesized the pattern of clinical and laboratory data to reveal clinically distinct lactic acidosis subgroups with different outcomes.

Machine Learning Prediction Models for Mortality in Intensive Care Unit Patients with Lactic Acidosis

Background: Lactic acidosis is the most common cause of anion gap metabolic acidosis in the intensive care unit (ICU), associated with poor outcomes including mortality. We sought to compare machine learning (ML) approaches versus logistic regression analysis for prediction of mortality in lactic acidosis patients admitted to the ICU. Methods: We used the Medical Information Mart for Intensive Care (MIMIC-III) database to identify ICU adult patients with lactic acidosis (serum lactate ≥4 mmol/L). The outcome of interest was hospital mortality. We developed prediction models using four ML approaches consisting of random forest (RF), decision tree (DT), extreme gradient boosting (XGBoost), artificial neural network (ANN), and statistical modeling with forward stepwise logistic regression using the testing dataset. We then assessed model performance using area under the receiver operating characteristic curve (AUROC), accuracy, precision, error rate, Matthews correlation coefficient (MCC), F1 score, and assessed model calibration using the Brier score, in the independent testing dataset. Results: Of 1919 lactic acidosis ICU patients, 1535 and 384 were included in the training and testing dataset, respectively. Hospital mortality was 30%. RF had the highest AUROC at 0.83, followed by logistic regression 0.81, XGBoost 0.81, ANN 0.79, and DT 0.71. In addition, RF also had the highest accuracy (0.79), MCC (0.45), F1 score (0.56), and lowest error rate (21.4%). The RF model was the most well-calibrated. The Brier score for RF, DT, XGBoost, ANN, and multivariable logistic regression was 0.15, 0.19, 0.18, 0.19, and 0.16, respectively. The RF model outperformed multivariable logistic regression model, SOFA score (AUROC 0.74), SAP II score (AUROC 0.77), and Charlson score (AUROC 0.69). Conclusion: The ML prediction model using RF algorithm provided the highest predictive performance for hospital mortality among ICU patient with lactic acidosis.

Lactate Alters Metabolism in Human Macrophages and Improves Their Ability to Kill Mycobacterium tuberculosis

In order to mount an appropriate immune response to infection, the macrophage must alter its metabolism by increasing aerobic glycolysis and concomitantly decreasing oxidative phosphorylation; a process known as the Warburg effect. Consequently, lactate, the end-product of glycolysis, accumulates in the extracellular environment. The subsequent effect of lactate on surrounding macrophages is poorly understood. Mycobacterium tuberculosis (Mtb), the causative organism of Tuberculosis (TB), is phagocytosed by macrophages in the airways. Mtb infected macrophages upregulate aerobic glycolysis and effector functions to try to kill the bacteria. Our lab has previously shown that human macrophages produce lactate in response to infection with Mtb. Although lactate has largely been considered a waste product of aerobic glycolysis, we hypothesised that the presence of extracellular lactate would impact subsequent immunometabolic responses and modulate macrophage function. We demonstrate that the presence of exogenous lactate has an immediate effect on the cellular metabolism of resting human macrophages; causing a decrease in extracellular acidification rate (ECAR; analogous to the rate of glycolysis) and an increase in the oxygen consumption rate (OCR; analogous to oxidative phosphorylation). When lactate-treated macrophages were stimulated with Mtb or LPS, glycolysis proceeds to increase immediately upon stimulation but oxidative phosphorylation remains stable compared with untreated cells that display a decrease in OCR. This resulted in a significantly reduced ECAR/OCR ratio early in response to stimulation. Since altered metabolism is intrinsically linked to macrophage function, we examined the effect of lactate on macrophage cytokine production and ability to kill Mtb. Lactate significantly reduced the concentrations of TNF and IL-1β produced by human macrophages in response to Mtb but did not alter IL-10 and IL-6 production. In addition, lactate significantly improved bacillary clearance in human macrophages infected with Mtb, through a mechanism that is, at least in part, mediated by promoting autophagy. These data indicate that lactate, the product of glycolysis, has a negative feedback effect on macrophages resulting in an attenuated glycolytic shift upon subsequent stimulation and reduced pro-inflammatory cytokine production. Interestingly, this pro-resolution effect of lactate is associated with increased capacity to kill Mtb.

Combination of Model for End-Stage Liver Disease and Lactate Predicts Death in Patients Treated With Salvage Transjugular Intrahepatic Portosystemic Shunt for Refractory Variceal Bleeding

BACKGROUND AND AIMS

Data about the prognosis of salvage transjugular intrahepatic portosystemic shunt (TIPS) using covered stents for refractory variceal bleeding caused by portal hypertension are scarce. We aimed to assess survival and to identify predictors of mortality in these patients.

APPROACH AND RESULTS

One hundred sixty-four patients with cirrhosis from five centers treated with salvage TIPS between 2007 and 2017 were retrospectively divided into a derivation cohort (83 patients) and a validation cohort (81 patients). Comparisons were performed using the Mann-Whitney and Fischer's exact test. Six-week overall survival (OS) was correlated with variables on the day of the TIPS using Kaplan-Meier curves with log-rank test and univariate/multivariate analyses using the Cox model. Eighty-three patients were included in the derivation cohort (male, 78%; age, 55 years, alcohol-associated cirrhosis, 88%; Model for End-Stage Liver Disease [MELD], 19 [15-27]; arterial lactate, 3.7 mmol/L [2.0-8.3]). Six-week OS rate was 58%. At multivariate analysis, the MELD score (OR, 1.064; 95% CI, 1.005-1.126; P = 0.028) and arterial lactate (OR, 1.063; 95% CI, 1.013-1.114; P = 0.032) were associated with 6-week OS. Six-week OS rates were 100% in patients with arterial lactate ≤2.5 mmol/L and MELD score ≤ 15 and 5% in patients with lactate ≥12 mmol/L and/or MELD score ≥ 30. The 81 patients of the validation cohort had similar MELD and arterial lactate level but lower creatinine level (94 vs 106 µmol/L, P = 0.008); 6-week OS was 67%. Six-week OS rates were 86% in patients with arterial lactate ≤2.5 mmol/L and MELD score ≤ 15 and 10% for patients with lactate ≥12 mmol/L and/or MELD score ≥ 30. In the overall cohort, rebleeding rate was 15.8% at 6 weeks, and the acute-on-chronic liver failure grade (OR, 1.699; 95% CI, 1.056-1.663; P = 0.040) was independently associated with rebleeding.

CONCLUSIONS

After salvage TIPS, 6-week mortality remains high and can be predicted by MELD score and lactate. Survival rate at 6 weeks was >85% in patients with arterial lactate ≤2.5 mmol/L and MELD score ≤ 15, while mortality was >90% for lactate ≥12 mmol/L and/or MELD score ≥ 30.

What Is the Utility of Measuring Lactate Levels in Patients with Sepsis and Septic Shock?

Elevations in blood lactate concentrations have been studied in sepsis and other disease states for decades and are well known to be associated with increased mortality. Many studies have also demonstrated the prognostic accuracy of serial lactate levels, and some have suggested that lactate clearance may be a useful therapeutic target for resuscitation. Lactate measurements have therefore gained an increasingly prominent role in sepsis definitions, screening protocols, management guidelines, and quality measures over the past two decades. The heavy emphasis on lactate monitoring, however, has also generated controversy and concerns. Lactate is not specific to infection and its frequent use for sepsis screening and diagnosis may therefore trigger unnecessary broad-spectrum antibiotic use in some patients. Because hyperlactatemia does not always reflect fluid-responsive hypoperfusion, titrating resuscitation to lactate clearance can also lead to unnecessary fluid and volume overload. More broadly, there is a lack of high-quality evidence demonstrating that initial and serial lactate monitoring leads to better patient-centered outcomes. Indeed, a recent randomized controlled trial comparing resuscitation strategies based on lactate clearance versus normalizing capillary refill time showed no benefit and potential harm with lactate-guided therapy. In this article, we review the basic pathobiology of lactate metabolism and delineate why the traditional paradigm that hyperlactatemia reflects tissue hypoxia is overly simplistic and incomplete. We then review the evidence behind the diagnostic, prognostic, and therapeutic uses of lactate monitoring and place this in the context of evolving sepsis diagnosis and management guidelines.

Retrospective evaluation of the prognostic utility of quick sequential organ failure assessment scores in dogs with surgically treated sepsis (2011-2018): 204 cases

OBJECTIVE

To assess the prognostic utility of admission quick Sequential Organ Failure Assessment (qSOFA) scores for in-hospital mortality in a population of dogs with surgically treated sepsis.

DESIGN

Retrospective cohort study of dogs from January 2011 to January 2018.

SETTING

University teaching hospital.

ANIMALS

One thousand three hundred nine cases were identified with a clinical diagnosis of sepsis requiring surgical source control. Two hundred and four dogs with surgically treated sepsis met inclusion criteria, defined as: meeting 2 or more systemic inflammatory response syndrome (SIRS) criteria with a documented source of infection. One hundred and forty-three cases of septic peritonitis, 26 cases of septic soft tissue infection, 20 cases of pyometra, and 15 cases of pyothorax were evaluated.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Overall in-hospital mortality was 63 of 204 (30.9%). Patients with a qSOFA ≥ 2 were more likely to die or be euthanized (odds ratio [OR] 7.1, 95% confidence interval [CI] 2.9-16.4; P < 0.0001). Survivor and nonsurvivor qSOFA scores were significantly different in all categories. Dogs with septic peritonitis and a qSOFA ≥ 2 had an increased risk of postoperative complications (OR 3.9; 95% CI 1.3-11.1; P = 0.02). qSOFA scores were correlated with length of hospitalization in survivors of all-cause surgical sepsis (r = 0.28, P = 0.0007), septic peritonitis (r = 0.33, P = 0.001), and septic soft tissue infection (r = 0.59, P = 0.004).

CONCLUSIONS

This was the first study to retrospectively evaluate the prognostic utility of qSOFA scores in dogs surgically treated for sepsis. Dogs diagnosed with septic peritonitis and other causes of surgically treated sepsis with a qSOFA ≥ 2 may have a higher risk of in-hospital mortality, although future prospective studies are necessary.

The utility of transcutaneous carbon dioxide measurements in the emergency department: A prospective cohort study

BACKGROUND

Rapid identification of patients with occult injury and illness in the emergency department can be difficult. Transcutaneous carbon dioxide (TCO2) and oxygen (TO2) measurements may be non-invasive surrogate markers for the identification of such patients.

OBJECTIVES

To determine if TCO2 or TO2 are useful adjuncts for identifying severe illness and the correlation between TCO2, lactate, and end tidal carbon dioxide (ETCO2).

METHODS

Prospective TCO2 and TO2 measurements at a tertiary level 1 trauma center were obtained using a transcutaneous sensor on 300 adult patients. Severe illness was defined as death, intensive care unit (ICU) admission, bilevel positive airway pressure, vasopressor use, or length of stay >2 days. TCO2 and TO2 were compared to illness severity using t tests and correlation coefficients.

RESULTS

Mean TO2 did not differ between severe illness (58.9, 95% CI 54.9-62.9) and non-severe illness (58.0, 95% CI 54.7-61.1). Mean TCO2 was similar between severe (34.6, 95% CI 33-36.2) vs non-severe illness (35.9, 95% CI 34.7-37.1). TCO2 was 28.7 (95% CI 24.0-33.4) for ICU vs. 35.9 (95% CI 34.9-36.9) for non-ICU patients. The mean TCO2 in those with lactate > 2.0 was 29.8 (95% CI 25.8-33.8) compared with 35.7 (95% CI 34.9-36.9) for lactate < 2.0. TCO2 was not correlated with ETCO2 (r = 0.32, 95% CI 0.22-0.42).

CONCLUSION

TCO2 could be a useful adjunct for identifying significant injury and illness and patient outcomes in an emergency department (ED) population. TO2 did not predict severe illness. TCO2 and ETCO2 are only moderately correlated, indicating that they are not equivalent and may be useful under different circumstances.

Endothelial metabolism in pulmonary vascular homeostasis and acute respiratory distress syndrome

Capillary endothelial cells possess a specialized metabolism necessary to adapt to the unique alveolar-capillary environment. Here, we highlight how endothelial metabolism preserves the integrity of the pulmonary circulation by controlling vascular permeability, defending against oxidative stress, facilitating rapid migration and angiogenesis in response to injury, and regulating the epigenetic landscape of endothelial cells. Recent reports on single-cell RNA-sequencing reveal subpopulations of pulmonary capillary endothelial cells with distinctive reparative capacities, which potentially offer new insight into their metabolic signature. Lastly, we discuss broad implications of pulmonary vascular metabolism on acute respiratory distress syndrome, touching on emerging findings of endotheliitis in coronavirus disease 2019 (COVID-19) lungs.

National Early Warning Score Does Not Accurately Predict Mortality for Patients With Infection Outside the Intensive Care Unit: A Systematic Review and Meta-Analysis

Background: The prognostic value of the national early warning score (NEWS) in patients with infections remains controversial. We aimed to evaluate the prognostic accuracy of NEWS for prediction of in-hospital mortality in patients with infections outside the intensive care unit (ICU). Methods: We searched PubMed, Embase, and Scopus for related articles from January 2012 to April 2021. Sensitivity, specificity, and likelihood ratios were pooled by using the bivariate random-effects model. Overall prognostic performance was summarized by using the area under the curve (AUC). We performed subgroup analyses to assess the prognostic accuracy of NEWS in selected populations. Results: A total of 21 studies with 107,008 participants were included. The pooled sensitivity and specificity of NEWS were 0.71 and 0.60. The pooled AUC of NEWS was 0.70, which was similar to quick sequential organ failure assessment (qSOFA, AUC: 0.70) and better than systemic inflammatory response syndrome (SIRS, AUC: 0.60). However, the sensitivity (0.55) and AUC (0.63) of NEWS were poor in elder patients. The NEWS of 5 was more sensitive, which was a better threshold for activating urgent assessment and treatment. Conclusions: The NEWS had good diagnostic accuracy for early prediction of mortality in patients with infections outside the ICU, and the sensitivity and specificity were more moderate when compared with qSOFA and SIRS. Insufficient sensitivity and poor performance in the elder population may have limitations as an early warning score for adverse outcomes. NEWS should be used for continuous monitoring rather than a single time point predictive tool.

Prediction of Impending Septic Shock in Children With Sepsis

Objectives

Sepsis and septic shock are leading causes of in-hospital mortality. Timely treatment is crucial in improving patient outcome, yet treatment delays remain common. Early prediction of those patients with sepsis who will progress to its most severe form, septic shock, can increase the actionable window for interventions. We aim to extend a time-evolving risk score, previously developed in adult patients, to predict pediatric sepsis patients who are likely to develop septic shock before its onset, and to determine whether or not these risk scores stratify into groups with distinct temporal evolution once this prediction is made.

Design

Retrospective cohort study.

Setting

Academic medical center from July 1, 2016, to December 11, 2020.

Patients

Six-thousand one-hundred sixty-one patients under 18 admitted to the Johns Hopkins Hospital PICU.

Interventions

None.

Measurements and Main Results

We trained risk models to predict impending transition into septic shock and compute time-evolving risk scores representative of a patient's probability of developing septic shock. We obtain early prediction performance of 0.90 area under the receiver operating curve, 43% overall positive predictive value, patient-specific positive predictive value as high as 62%, and an 8.9-hour median early warning time using Sepsis-3 labels based on age-adjusted Sequential Organ Failure Assessment score. Using spectral clustering, we stratified pediatric sepsis patients into two clusters differing in septic shock prevalence, mortality, and proportion of patients adequately fluid resuscitated.

CONCLUSIONS

We demonstrate the applicability of our methodology for early prediction and stratification for risk of septic shock in pediatric sepsis patients. Through analyses of risk score evolution over time, we corroborate our past finding of an abrupt transition preceding onset of septic shock in children and are able to stratify pediatric sepsis patients using their risk score trajectories into low and high-risk categories.

Perioperative Management of Complex Hepatectomy for Colorectal Liver Metastases: The Alliance between the Surgeon and the Anesthetist

Simple Summary

Major high-risk surgery (HRS) exposes patients to potential perioperative adverse events. Hepatic resection of colorectal metastases can surely be included into the HRS class of operations. Limiting such risks is the main target of the perioperative medicine. In this context the collaboration between the anesthetist and the surgeon and the sharing of management protocols is of utmost importance and represents the key issue for a successful outcome. In our institution, we have been adopting consolidated protocols for patients undergoing this type of surgery for decades; this made our mixed team (surgeons and anesthetists) capable of achieving a safe outcome for the majority of our surgical population. In this narrative review, we report the most recent state of the art of perioperative management of hepatic resection of colorectal metastases along with our experience in this field, trying to point out the main issues.

Abstract

Hepatic resection has been widely accepted as the first choice for the treatment of colorectal metastases. Liver surgery has been recognized as a major abdominal procedure; it exposes patients to a high risk of perioperative adverse events. Decision sharing and the multimodal approach to the patients’ management are the two key items for a safe outcome, even in such a high-risk surgery. This review aims at addressing the main perioperative issues (preoperative evaluation; general anesthesia and intraoperative fluid management and hemodynamic monitoring; intraoperative metabolism; administration policy for blood-derivative products; postoperative pain control; postoperative complications), in particular, from the anesthetist’s point of view; however, only an alliance with the surgery team may be successful in case of adverse events to accomplish a good final outcome.

The effect of midodrine on lactate clearance in patients with septic shock: a pilot study

Background: The effect of midodrine on lactate clearance has not been assessed in critically ill patients yet. Objective: The goal of this study was to assess the effect of adjunctive midodrine therapy on lactate clearance in patients with septic shock. Materials & methods: Patients with septic shock were assigned to receive either adjunctive midodrine 10 mg three-times a day for 5 days (midodrine group = 15 patients) or not (control group = 13 patients). Results: The lactate clearance was significantly faster in the midodrine group than the control group (p = 0.049) with a large effect size (ηp2 = 0.141). Conclusion: When midodrine was added to intravenous vasopressors, it significantly accelerated lactate clearance in patients with septic shock. Trial registration number: IRCT20100228003449N25 (Clinicaltrials.gov).

Lactate/albumin ratio is more effective than lactate or albumin alone in predicting clinical outcomes in intensive care patients with sepsis

This study aimed to compare the value of lactate, albumin, and lactate/albumin ratio for the prediction of mortality in sepsis patients. Patients admitted to the intensive care unit (ICU) due to sepsis between January 2016 and January 2019 were evaluated retrospectively. Lactate, albumin, and lactate/albumin ratio values were compared between surviving and non-surviving patients and their predictive value for mortality was evaluated. A total of 1136 sepsis patients admitted to the ICU were included in the study. The mortality rate was 42.7% (485/1136 patients). In ROC analysis for mortality prediction, the area under the curve and optimal cut-off values were 0.816 and >2.2 mmol/L for lactate, 0.812 and ≤26 g/L for albumin, and 0.869 and >0.71 for lactate/albumin ratio, respectively. Our analysis of lactate, albumin, and lactate/albumin ratio in the largest patient sample to date showed that lactate/albumin ratio was a stronger parameter than lactate or albumin alone in predicting mortality among sepsis patients in the ICU. Lactate/albumin ratio is an easily obtained parameter with potential value for critically ill patients.

Early Warning Factors of Death in COVID-19 Patients

The infectious coronavirus disease 2019 (COVID-19) has spread all over the world and been persistently evolving so far. The number of deaths in the whole world has been rising rapidly. However, the early warning factors for mortality have not been well ascertained. In this retrospective, single-centre cohort study, we included some adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Renmin Hospital of Wuhan University who had been discharged or had died by Apr. 8, 2020. Demographic, clinical and laboratory data at admission were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable analysis, Cox proportional hazard model analysis and receiver operating characteristic (ROC) curve to explore the early warning factors associated with in-hospital death. A total of 159 patients were included in this study, of whom 86 were discharged and 73 died in hospital. Hypertension (52.1% vs. 29.1%, P=0.003) and coronary heart disease (28.8% vs. 12.8%, P=0.012) were more frequent among non-survived patients than among survived patients. The proportions of patients with dyspnoea (67.1% vs. 25.6%, P<0.001), chest distress (58.9% vs. 26.7%, P<0.001) and fatigue (64.4% vs. 25.6%, P<0.001) were significantly higher in the non-survived group than in the survived group. Regression analysis with the Cox proportional hazards mode revealed that increasing odds of in-hospital death were associated with higher IL-6 (odds ratio 10.87, 95% CI 1.41-83.59; P=0.022), lactate (3.59, 1.71-7.54; P=0.001), older age (1.86, 1.03-3.38; P=0.041) and lower lymphopenia (5.44, 2.71-10.93; P<0.001) at admission. The areas under the ROC curve (AUCs) of IL-6, lymphocyte, age and lactate were 0.933, 0.928, 0.786 and 0.753 respectively. The AUC of IL-6 was significantly higher than that of age (z=3.332, P=0.0009) and lactate (z=4.441, P<0.0001) for outcome prediction. There was no significant difference between the AUCs of IL-6 and lymphocyte for outcome prediction (z=0.372, P=0.7101). It was concluded that the potential risk factors of higher IL-6, lactate, older age and lower lymphopenia at admission could help clinicians to identify patients with poor prognosis at an early stage.

Vibrational spectroscopic analysis of blood for diagnosis of infections and sepsis: a review of requirements for a rapid diagnostic test

Infections and sepsis represent a growing global burden. There is a widespread clinical need for a rapid, high-throughput and sensitive technique for the diagnosis of infections and detection of invading pathogens and the presence of sepsis. Current diagnostic methods primarily consist of laboratory-based haematology, biochemistry and microbiology that are time consuming, labour- and resource-intensive, and prone to both false positive and false negative results. Current methods are insufficient for the increasing demands on healthcare systems, causing delays in diagnosis and initiation of treatment, due to the intrinsic time delay in sample preparation, measurement, and analysis. Vibrational spectroscopic techniques can overcome these limitations by providing a rapid, label-free and low-cost method for blood analysis, with limited sample preparation required, potentially revolutionising clinical diagnostics by producing actionable results that enable early diagnosis, leading to improved patient outcomes. This review will discuss the challenges associated with the diagnosis of infections and sepsis, primarily within the UK healthcare system. We will consider the clinical potential of spectroscopic point-of-care technologies to enable blood analysis in the primary-care setting.

The sensitivity of qSOFA calculated at triage and during emergency department treatment to rapidly identify sepsis patients

The quick sequential organ failure assessment (qSOFA) score has been proposed as a means to rapidly identify adult patients with suspected infection, in pre-hospital, Emergency Department (ED), or general hospital ward locations, who are in a high-risk category with increased likelihood of "poor outcomes:" a greater than 10% chance of dying or an increased likelihood of spending 3 or more days in the ICU. This score is intended to replace the use of systemic inflammatory response syndrome (SIRS) criteria as a screening tool; however, its role in ED screening and identification has yet to be fully elucidated. In this retrospective observational study, we explored the performance of triage qSOFA (tqSOFA), maximum qSOFA, and first initial serum lactate (> 3 mmol/L) at predicting in-hospital mortality and compared these results to those for the initial SIRS criteria obtained in triage. A total of 2859 sepsis cases were included and the in-hospital mortality rate was 14.4%. The sensitivity of tqSOFA ≥ 2 and maximum qSOFA ≥ 2 to predict in-hospital mortality were 33% and 69%, respectively. For comparison, the triage SIRS criteria and the initial lactate > 3 mmol/L had sensitivities of 82% and 65%, respectively. These results demonstrate that in a large ED sepsis database the earliest measurement of end organ impairment, tqSOFA, performed poorly at identifying patients at increased risk of mortality and maximum qSOFA did not significantly outperform initial serum lactate levels.

Relative Hyperlactatemia in the Emergency Department

Objective: The clinical interpretation of lactate ≤ 2.00 mmol/L in emergency department (ED) patients is not well-characterized. This study aims to determine the optimal cutoff value for lactate within the reference range that predicts in-hospital mortality among ED patients.

Methods: This was a retrospective study of adult patients presenting to a tertiary ED with an initial serum lactate level of <2.00 mmol/L. The primary outcome was in-hospital mortality. Youden's index was utilized to determine the optimal threshold that predicts mortality. Patients above the threshold were labeled as having relative hyperlactatemia.

Results: During the study period, 1,638 patients were included. The mean age was 66.9 ± 18.6 years, 47.1% of the population were female, and the most prevalent comorbidity was hypertension (56.7%). The mean lactate level at presentation was 1.5 ± 0.3 mmol/L. In-hospital mortality was 3.8% in the overall population, and 16.2% were admitted to the ICU. A lactate level of 1.33 mmol/L was found to be the optimal cutoff that best discriminates between survivors and non-survivors. Relative hyperlactatemia was an independent predictor of in-hospital mortality (OR 1.78 C1.18–4.03; p = 0.02). Finally, relative hyperlactatemia was associated with increased mortality in patients without hypertension (4.7 vs. 1.1%; p = 0.008), as well as patients without diabetes or COPD.

Conclusion: The optimal cutoff of initial serum lactate that discriminates between survivors and non-survivors in the ED is 1.33 mmol/L. Relative hyperlactatemia is associated with increased mortality in emergency department patients, and this interaction seems to be more important in healthy patients.

Evaluation of an Anti-Thrombotic Continuous Lactate and Blood Pressure Monitoring Catheter in an In Vivo Piglet Model undergoing Open-Heart Surgery with Cardiopulmonary Bypass

Blood lactate and blood pressure measurements are important predictors of life-threatening complications after infant open-heart surgeries requiring cardiopulmonary bypass (CPB). We have developed an intravascular nitric oxide (NO)-releasing 5-Fr catheter that contains a lactate sensor for continuous in-blood lactate monitoring and a dedicated lumen for third-party pressure sensor attachment. This device has antimicrobial and antithrombotic properties and can be implanted intravascularly. The importance of this design is its ability to inhibit thrombosis, due to the slow release of NO through the surface of the catheter and around the electrochemical lactate sensors, to allow continuous data acquisition for more than 48 h. An in vivo study was performed using six piglets undergoing open-heart surgery with CPB and cardioplegic arrest, in order to mimic intra-operative conditions for infants undergoing cardiac surgery with CPB. In each study of 3 h, two 5-Fr NO-releasing lactate and blood-pressure monitoring catheters were implanted in the femoral vessels (arteries and veins) and the CPB circuitry to monitor changing lactate levels and blood pressures during and immediately after aortic cross-clamp removal and separation from CBP. Electrical signals continuously acquired through the sensors were processed and displayed on the device's display and via Bluetooth to a computer in real-time with the use of a two-point in vivo calibration against blood gas results. The study results show that lactate levels measured from those sensors implanted in the CPB circuit during CPB were comparable to those acquired by arterial blood gas measurements, whereas lactate levels measured from sensors implanted in the femoral artery were closely correlated with those acquired intermittently by blood gas prior to CPB initiation, but not during CPB. Blood pressure sensors attached to one lumen of the device displayed accurate blood pressure readings compared to those measured using an FDA approved pressure sensor already on the market. We recommend that the sensor be implanted in the CPB's circuit to continuously monitor lactate during CPB, and implanted in the femoral arteries or jugular veins to monitor lactate before and after CPB. Blood pressures dramatically drop during CPB due to lower blood flow into the lower body, and we suspect that the femoral arteries are likely collapsing or constricting on the implanted catheter and disrupting the sensor-to-blood contact. This study shows that the device is able to accurately and continuously monitor lactate levels during CPB and potentially prevent post-surgery complications in infants.

Age-adjusted and Expanded Lactate Thresholds as Predictors of All-Cause Mortality in the Emergency Department

INTRODUCTION

While numerous studies have found emergency department (ED) lactate levels to be associated with increased in-hospital mortality, little information is available on the role age plays in this association. This study investigates whether age is a necessary variable to consider when using lactate levels as a marker of prognosis and a guide for management decisions in the ED.

METHODS

This was a retrospective cohort study in an urban, tertiary-care teaching hospital. A total of 13,506 lactate levels were obtained over a 4.5-year period. All adult patients who had a lactate level obtained by the treating provider in the ED were screened for inclusion. The main outcome measure was in-hospital mortality using age-adjusted cohorts and expanded lactate thresholds with secondary outcomes comparing mortality based on the primary clinical impression.

RESULTS

Of the 8796 patients in this analysis, there were 474 (5.4%) deaths. Mortality rates increased with both increasing lactate levels and increasing age. For all ages, mortality rates increased from 2.8% in the less than 2.0 millimoles per liter (mmol/L) lactate level, to 5.6% in the 2.0-2.9 mmol/L lactate level, to 8.0% in the 3.0-3.9 mmol/L lactate level, to 13.9% in the 4.0-4.9 mmol/L lactate level, to 13.7% in the 5.0-5.9 mmol/L lactate level, and to 39.1% in the 6.0 mmol/L or greater lactate level (p <0.0001). Survivors, regardless of age, had a mean lactate level <2.0 whereas non-survivors had mean lactate levels of 6.5, 4.5, and 3.7 mmol/L for age cohorts 18-39, 40-64, and ≥ 65 years, respectively.

CONCLUSION

Our findings suggest that although lactate levels can be used as a prognostic tool to risk stratify ED patients, the traditional lactate level thresholds may need to be adjusted to account for varying risk based on age and clinical impressions.

Predicting Bacterial Versus Viral Infection, or None of the Above: Current and Future Prospects of Biomarkers

Sepsis and pneumonia cause significant morbidity and mortality worldwide. Despite improvements in diagnostic methodologies for organism identification, the early recognition and further risk stratification of these infections can be challenging. Although traditional clinical scoring systems are beneficial for the management of sepsis and pneumonia, biomarkers supporting the diagnosis and management of these infectious diseases are needed. Many biomarkers have been identified and there is no lack of studies and meta-analyses assessing the utility of biomarkers. Focusing primarily on sepsis and pneumonia, this article discusses the most commonly used biomarkers for which clinical laboratory testing methods are available.

Necrotizing Fasciitis Within 72 hours After Presentation with Skin and Skin Structure Infection

Introduction

A small percentage of patients with skin infections later develop necrotizing fasciitis (NF). Diagnostic testing is needed to identify patients with skin infections at low risk of NF who could be discharged from the emergency department (ED) after antibiotic initiation. Elevated lactate has been associated with NF; existing estimates of the frequency of NF are based on retrospective reviews, and cases often lack testing for lactate. We present the incidence of patients with skin infections who developed NF and their baseline lactates.

Methods

In four phase-3 trials, 2883 adults with complicated or acute bacterial skin and skin structure infections were randomized to dalbavancin or comparator, with early and late follow-up visits through Day 28. We prospectively collected baseline plasma lactates in one trial to assess an association with NF.

Results

NF was diagnosed in 3/2883 patients (0.1%); all three survived. In the study with prospectively collected baseline lactates (n = 622), 15/622 (2.4%) had a lactate ≥4 millimoles per liter (mmol/L), including 3/622 (0.5%) with a lactate ≥7 mmol/L. NF was not seen in patients with a lactate <4 mmol/L; NF was seen in 1/15 (6.7%) with a lactate ≥4 mmol/L, including 1/3 (33.3%) with lactate ≥7 mmol/L.

Conclusions

NF incidence within 72 hours of antibiotic initiation in patients with complicated or acute bacterial skin and skin structure infections was extremely low (0.1%) and occurred in 6.7% with a lactate ≥4 mmol/L. Lactate <4 mmol/L can be used to identify patients at low risk of NF who could be safely discharged from the ED after antibiotic initiation.

Maternal sepsis

Maternal sepsis is "a life-threatening condition defined as an organ dysfunction caused by an infection during pregnancy, delivery, puerperium, or after an abortion," with the potential to save millions of lives if a proper approximation is made. Undetected or poorly managed maternal infections can lead to sepsis, death, or disability for the mother, and an increased likelihood of early neonatal infection and other adverse outcomes. Physiological, immunologic, and mechanical changes that occur in pregnancy make pregnant women more susceptible to infections than nonpregnant women and may obscure signs and symptoms of infection and sepsis, resulting in a delay in the recognition and treatment of sepsis. Prioritization of the creation and validation of tools that allow the development of clear and standardized diagnostic criteria of maternal sepsis and septic shock, according to the changes inherent to pregnancy, correspond to highly effective strategies to reduce the impact of these conditions on maternal health worldwide. After an adequate diagnostic approach, the next goal is achieving stabilization, trying to stop the progression from sepsis to septic shock, and improving tissue perfusion to limit cell dysfunction. Management protocol implementation during the first hour of treatment will be the most important determinant for the reduction of maternal mortality associated with sepsis and septic shock.

Supervised machine learning for the prediction of infection on admission to hospital: a prospective observational cohort study

BACKGROUND

Infection diagnosis can be challenging, relying on clinical judgement and non-specific markers of infection. We evaluated a supervised machine learning (SML) algorithm for diagnosing bacterial infection using routinely available blood parameters on presentation to hospital.

METHODS

An SML algorithm was developed to classify cases into infection versus no infection using microbiology records and six available blood parameters (C-reactive protein, white cell count, bilirubin, creatinine, ALT and alkaline phosphatase) from 160203 individuals. A cohort of patients admitted to hospital over a 6 month period had their admission blood parameters prospectively inputted into the SML algorithm. They were prospectively followed up from admission to classify those who fulfilled clinical case criteria for a community-acquired bacterial infection within 72 h of admission using a pre-determined definition. Predictive ability was assessed using receiver operating characteristics (ROC) with cut-off values for optimal sensitivity and specificity explored.

RESULTS

One hundred and four individuals were included prospectively. The median (range) cohort age was 65 (21-98)  years. The majority were female (56/104; 54%). Thirty-six (35%) were diagnosed with infection in the first 72 h of admission. Overall, 44/104 (42%) individuals had microbiological investigations performed. Treatment was prescribed for 33/36 (92%) of infected individuals and 4/68 (6%) of those with no identifiable bacterial infection. Mean (SD) likelihood estimates for those with and without infection were significantly different. The infection group had a likelihood of 0.80 (0.09) and the non-infection group 0.50 (0.29) (P < 0.01; 95% CI: 0.20-0.40). ROC AUC was 0.84 (95% CI: 0.76-0.91).

CONCLUSIONS

An SML algorithm was able to diagnose infection in individuals presenting to hospital using routinely available blood parameters.