Relationship between low hemoglobin levels and mortality in patients with septic shock

Relationship between the magnitude of haemoglobin changes and long-term mortality in patients with sepsis: a retrospective cohort study

BACKGROUND

Sepsis is a common and severe disease with a high mortality rate in intensive care unit (ICU). The hemoglobin (HGB) level is a key parameter for oxygen supply in sepsis. Although HGB is associated with the progression of inflammation in sepsis patients, its role as a marker following sepsis treatment remains unclear. Here, we studied the correlation between early temporal changes in HGB levels and long-term mortality rates in septic patients.

METHOD

In this retrospective study of data on patients with sepsis from the Medical Information Mart for Intensive Care (MIMIC) IV database, the outcome was long-term mortality. Patients were divided based on the cut-off of the HGB percentage for receiver operating characteristic (ROC) curve calculation. Kaplan-Meier (KM) survival curves and Cox proportional hazards regression models were used to analyse the associations between groups and outcomes. Propensity score matching (PSM) was used to verify the results.

RESULTS

In this study, 2042 patients with sepsis and changes in HGB levels at day 4 after admission compared to day 1 were enrolled and divided into two groups: group 1 (n = 1147) for those with reduction of HGB < 7% and group 2 (n = 895) for those with dropping ≥ 7%. The long-term survival chances of sepsis with less than a 7% reduction in the proportion of HGB at day four were significantly higher than those of patients in the group with a reduction of 7% or more. After adjusting for covariates in the Cox model, the hazard ratios (HRs) with 95% confidence intervals (CIs) for long-term all-cause mortality in the group with a reduction of 7% or more were as follows: 180 days [HR = 1.41, 95% CI (1.22 to 1.63), P < 0.001]; 360 days [HR = 1.37, 95% CI (1.21 to 1.56), P < 0.001]; 540 days [HR = 1.35, 95% CI (1.20 to 1.53), P < 0.001]; 720 days [HR = 1.45, 95% CI (1.29 to 1.64), P < 0.001]. Additionally, the long-term survival rates, using Kaplan-Meier analysis, for the group with a reduction of 7% or more were lower compared to the group with less than 7% reduction at 180 days (54.3% vs. 65.3%, P < 0.001), 360 days (42.3% vs. 50.9%, P < 0.001), 540 days (40.2% vs. 48.6%, P < 0.001), and 720 days (35.5% vs. 46.1%, P < 0.001). The same trend was obtained after using PSM.

CONCLUSION

A ≥ 7% decrease in HGB levels on Day 4 after admission was associated with worse long-term prognosis in sepsis patients admitted to the ICU.

Postoperative pneumonia after femoral fracture surgery: an in-depth retrospective analysis

BACKGROUND

Femoral fractures significantly contribute to disability, predominantly in the elderly. Despite this, data on postoperative pneumonia following femoral fracture surgeries remains sparse. Our study sought to explore the incidence and impact of postoperative pneumonia on outcomes following such surgeries.

METHODS

A retrospective study analyzed femoral fracture patients hospitalized from 2016 to 2022. We scrutinized postoperative outcomes, including pneumonia, hospital stay duration, intensive care unit (ICU) admissions, and in-hospital mortality. We established stringent diagnostic criteria for postoperative pneumonia, incorporating both clinical signs and radiological evidence, excluding patients with prior infections or those discharged within 24 h post-surgery. Statistical analyses involved Chi-square and t-tests, linear regression, and logestic regression using SPSS.

RESULTS

Out of 636 patients, 10.8% were diagnosed with postoperative pneumonia. The average age was 79.55 ± 8.57 years, with a male prevalence of 47.8%. Common comorbidities were hypertension (78.3%), diabetes (60.9%), and cardiovascular diseases (40.6%). Surgical interventions were categorized as intramedullary nailing (40.6%), partial hip replacement (37.7%), and dynamic hip screw (21.7%). Postoperative pneumonia was associated with older age (AOR = 1.053, 95% CI 1.020 to 1.087, p = 0.002), ICU admission (AOR = 2.283, 95% CI 1.256 to 4.148, p = 0.007), and longer length of hospital stay (AOR = 1.079, 95% CI 1.030 to 1.130, p = 0.001). The presence of pneumonia was associated with a 2.621-day increase in hospitalization after adjusting for other variables (p < 0.001, 95% CI: 1.454 to 3.789).

CONCLUSION

This study accentuates the clinical significance of postoperative pneumonia in femoral fracture patients, with a noted incidence of 10.8%. A notable association with older age, prolonged hospital stays, and ICU admissions was observed, underscoring the necessity of addressing this complication to improve patient outcomes and healthcare resource allocation.

Acute blood loss anemia in hospitalized patients is associated with adverse outcomes: An analysis of the Nationwide Inpatient Sample

BACKGROUND

Acute blood loss anemia is the most common form of anemia and often results from traumatic injuries or gastrointestinal bleeding. There are limited studies analyzing outcomes associated with acute blood loss anemia in hospitalized patients.

METHODS

The Nationwide Inpatient Sample (NIS) was analyzed from 2010 to 2014 (n = 133,809). The impact of acute blood loss anemia on in-hospital mortality, length of stay (LOS), healthcare cost, and disposition was determined using regression modeling adjusted for age, gender, race, and comorbidities.

RESULTS

Hospitalized patients with acute blood loss anemia had significantly higher healthcare cost (adj OR 1.04; 95% CI: 1.04-1.05), greater lengths of stay (adj OR 1.18; 95% CI: 1.17-1.18), and were less likely to be discharged home compared to the general medical population (adj OR 0.27; 95% CI: 0.26-0.28). Acute blood loss anemia was associated with increased risk for mortality in unadjusted models (unadj 1.16; 95% CI: 1.12-1.20) but not in adjusted models (adj OR 0.91; 95% CI: 0.88-0.94). When analyzing comorbidities, a "muscle loss phenotype" had the strongest association with mortality in patients with acute blood loss anemia (adj OR 4.48; 95% CI: 4.35-4.61). The top five primary diagnostic codes associated with acute blood loss anemia were long bone fractures, GI bleeds, cardiac repair, sepsis, and OB/Gyn related causes. Sepsis had the highest association with mortality (18%, adj OR 2.59; 95% CI: 2.34-2.86) in those with acute blood loss anemia.

CONCLUSIONS

Acute blood loss anemia is associated with adverse outcomes in hospitalized patients.

Ceftriaxone-induced severe hemolytic anemia, renal calculi, and cholecystolithiasis in a 3-year-old child: a case report and literature review

Ceftriaxone is widely used in pediatric outpatient care for its efficacy against respiratory and digestive system infections, yet its increasing association with severe immune hemolytic reactions requires heightened vigilance from pediatricians. This report details a rare and severe case of ceftriaxone-induced severe immune hemolytic anemia (IHA), hemolytic crisis, myocardial injury, liver injury, renal calculi, and cholecystolithiasis in a previously healthy 3-year-old child. The child, treated for bronchitis, experienced sudden pallor, limb stiffness, and altered consciousness following the fifth day of ceftriaxone infusion, with hemoglobin (Hb) levels precipitously dropping to 21 g/L. Immediate cessation of ceftriaxone and the administration of oxygen therapy, blood transfusion, intravenous immunoglobulin (IVIG), and corticosteroids led to a gradual recovery. Despite initial improvements, the patient's condition necessitated extensive hospital care due to complications including myocardial injury, liver injury, renal calculi, and cholecystolithiasis. After a 12-day hospital stay and a 3-month follow-up, the child showed complete normalization of Hb and liver function and resolution of calculi. In children, ceftriaxone infusion may trigger severe, potentially fatal, hemolytic reactions. Pediatricians must promptly recognize symptoms such as pallor, limb stiffness, and unresponsiveness, indicative of ceftriaxone-induced severe IHA, and immediately discontinue the drug. Effective management includes timely blood transfusion, respiratory support, IVIG administration, and corticosteroids when necessary, along with rigorous vital signs monitoring. Continued vigilance is imperative, even after cessation of ceftriaxone, to promptly address any residual adverse effects.

Prognostic value of hemoglobin in patients with sepsis: A systematic review and meta-analysis

BACKGROUND

Sepsis patients have a high mortality rate and are frequently anemic. The importance of early detection and blood transfusion treatment cannot be overstated.

OBJECTIVE

A systematic review and meta-analysis of published literature was conducted to evaluate the association between hemoglobin and the prognosis of patients with sepsis.

METHODS

The PubMed, Embase, Cochrane Library and Chinese Biomedical Literature (CBM) databases were searched from inception to May 21, 2023. Pediatric patients were excluded, and there were no language restrictions. A random effects model was used to calculate pooled odds ratios to assess the relationship between hemoglobin and prognosis in sepsis.

RESULTS

There were 110,004 patients included in 9 studies, of which 51,568 had a poor prognosis. The results of univariate and multivariate analyzes showed that hemoglobin was associated with the prognosis of patients with sepsis (univariate OR: 1.35, 95 % confidence interval (CI): 1.16-1.58; multivariate OR: 1.26, 95 % CI: 1.13-1.40). Dose-response meta-analysis showed that there was a nonlinear relationship between hemoglobin level and prognosis in patients with sepsis.

CONCLUSION

The level of hemoglobin at admission is related to the prognosis of patients with sepsis, and decreases in hemoglobin level are associated with an increase in the mortality rate of patients with sepsis. Therefore, early transfusion of red blood cells should be performed in patients with sepsis, and early attention should be given to anemia in patients with sepsis. However, more robust studies are needed to further determine the level of early hemoglobin maintenance in patients with sepsis.

Applying artificial neural network in predicting sepsis mortality in the emergency department based on clinical features and complete blood count parameters

A complete blood count (CBC) is routinely ordered for emergency department (ED) patients with infections. Certain parameters, such as the neutrophil-to-lymphocyte ratio (NLR), might have prognostic value. We aimed to evaluate the prognostic value of the presenting CBC parameters combined with clinical variables in predicting 30-day mortality in adult ED patients with infections using an artificial neural network (ANN). We conducted a retrospective study of ED patients with infections between 17 December 2021 and 16 February 2022. Clinical variables and CBC parameters were collected from patient records, with NLR, monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) calculated. We determined the discriminatory performance using the area under the receiver operating characteristic curve (AUROC) and performed a 70/30 random data split and supervised ANN machine learning. We analyzed 558 patients, of whom 144 (25.8%) had sepsis and 60 (10.8%) died at 30 days. The AUROCs of NLR, MLR, PLR, and their sum were 0.644 (95% CI 0.573-0.716), 0.555 (95% CI 0.482-0.628), 0.606 (95% CI 0.529-0.682), and 0.610 (95% CI 0.534-0.686), respectively. The ANN model based on twelve variables including clinical variables, hemoglobin, red cell distribution width, NLR, and PLR achieved an AUROC of 0.811 in the testing dataset.

Predictive Rule for Mortality of Inpatients With Escherichia coli Bacteremia: Chi-Square Automatic Interaction Detector Decision Tree Analysis Model

AIM

A predictive rule for risk factors for mortality due to Escherichia coli (E. coli)bacteremia has not been defined, especially using the chi-square automatic interaction detector (CHAID) decision tree analysis. Here we aimed to create the predictive rule for risk factors for in-hospital mortality due to E. coli bacteremia.

METHODS

The outcome of this retrospective cross-sectional survey was death in the hospital due to E. coli bacteremia. Factors potentially predictive of death in the hospital due to E. coli bacteremia were analyzed using the CHAID decision tree analysis.

RESULTS

A total of 420 patients (male:female=196:224; mean±standard deviation [SD] age, 75.81±13.13 years) were included in this study. 56 patients (13.3%) died in the hospital. The CHAID decision tree analysis revealed that patients with total protein level ≤5.10 g/dL (incidence, 46.2%), total protein level ≤5.90 g/dL with disturbance of consciousness (incidence, 39.4%), and total protein level >5.90 g/dL with hemoglobin level ≤11.10 g/dL and lactate dehydrogenase level ≥312.0 IU/L (incidence, 42.3%) were included in the high-risk group.

CONCLUSIONS

Appropriate preventative therapy should be facilitated in patients with E. coliat a high risk of mortality.

A Predictive Rule for COVID-19 Pneumonia Among COVID-19 Patients: A Classification and Regression Tree (CART) Analysis Model

BACKGROUND

In this study, we aimed to identify predictive factors for coronavirus disease 2019 (COVID-19) patients with complicated pneumonia and determine which COVID-19 patients should undergo computed tomography (CT) using classification and regression tree (CART) analysis.

METHODS

This retrospective cross-sectional survey was conducted at a university hospital. We recruited patients diagnosed with COVID-19 between January 1 and December 31, 2020. We extracted clinical information (e.g., vital signs, symptoms, laboratory results, and CT findings) from patient records. Factors potentially predicting COVID-19 pneumonia were analyzed using Student's t-test, the chi-square test, and a CART analysis model.

RESULTS

Among 221 patients (119 men (53.8%); mean age, 54.59±18.61 years), 160 (72.4%) had pneumonia. The CART analysis revealed that patients were at high risk of pneumonia if they had C-reactive protein (CRP) levels of >1.60 mg/dL (incidence of pneumonia: 95.7%); CRP levels of ≤1.60 mg/dL + age >35.5 years + lactate dehydrogenase (LDH)>225.5 IU/L (incidence of pneumonia: 95.5%); and CRP levels of ≤1.60 mg/dL + age >35.5 years + LDH≤225.5 IU/L + hemoglobin ≤14.65 g/dL (incidence of pneumonia: 69.6%). The area of the curve of the receiver operating characteristic of the model was 0.860 (95% CI: 0.804-0.915), indicating sufficient explanatory power.

CONCLUSIONS

The present results are useful for deciding whether to perform CT in COVID-19 patients. High-risk patients such as those mentioned above should undergo CT.

Potential therapeutic effect of Carica papaya leaves extract on immune response, biochemical and hematological mechanisms on cecal ligation and puncture model of sepsis in rats: an in vivo study

Antibiotics and immunotherapies possess unavoidable adverse effects that hinder sepsis management. Herbal drugs have demonstrated potential immunomodulatory properties vital for sepsis treatment. We hypothesized in the present study that the use of Carica papaya leaves extract had the potential to improve survival and modulate immune cytokine release during sepsis. Animals were subjected to cecal ligation and puncture (CLP) to induce sepsis. Septic rats divided into 10 groups received ethanol extract of C. papaya leaves (50 and 100 mg/kg), imipenem (120 mg/kg) and cyclophosphamide (CP, 10 mg/kg). To investigate the immunomodulatory potentials of EE, cytokine levels like interleukin (IL-6), tumor necrosis factor (TNF-α), and IL-10 along with hematological and biochemical parameters were analyzed. Our results exhibited improved survival rates concerning ethanol extract treatment alone and in combination with imipenem and CP (100%) as compared to the CLP group (33.3%) on day 7 post-surgery. The combination treatment of ethanol extract with imipenem and CP significantly (P < 0.001) ameliorated cytokine levels and hematological and biochemical parameters in septic rats. A histopathological examination suggested improved liver and kidney tissue condition after combination treatment as compared to the CLP group. Therefore, it was concluded that combination therapy of extract with imipenem and CP improved survival rates and marked immunomodulatory potential in septic rats compared to monotherapy. The findings suggested the use of a mixture of these drugs in clinical settings to treat sepsis.

Blood count derangements after sepsis and association with post-hospital outcomes

Rationale

Predicting long-term outcomes in sepsis survivors remains a difficult task. Persistent inflammation post-sepsis is associated with increased risk for rehospitalization and death. As surrogate markers of inflammation, complete blood count parameters measured at hospital discharge may have prognostic value for sepsis survivors.

Objective

To determine the incremental value of complete blood count parameters over clinical characteristics for predicting 90-day outcomes in sepsis survivors.

Methods

Electronic health record data was used to identify sepsis hospitalizations at United States Veterans Affairs hospitals with live discharge and relevant laboratory data (2013 to 2018). We measured the association of eight complete blood count parameters with 90-day outcomes (mortality, rehospitalization, cause-specific rehospitalizations) using multivariable logistic regression models.

Measurements and main results

We identified 155,988 eligible hospitalizations for sepsis. Anemia (93.6%, N=142,162) and lymphopenia (28.1%, N=29,365) were the most common blood count abnormalities at discharge. In multivariable models, all parameters were associated with the primary outcome of 90-day mortality or rehospitalization and improved model discrimination above clinical characteristics alone (likelihood ratio test, p<0.02 for all). A model including all eight parameters significantly improved discrimination (AUROC, 0.6929 v. 0.6756) and reduced calibration error for the primary outcome. Hemoglobin had the greatest prognostic separation with a 1.5 fold increased incidence of the primary outcome in the lowest quintile (7.2-8.9 g/dL) versus highest quintile (12.70-15.80 g/dL). Hemoglobin and neutrophil lymphocyte ratio provided the most added value in predicting the primary outcome and 90-day mortality alone, respectively. Absolute lymphocyte count added little value in predicting 90-day outcomes.

Conclusions

The incorporation of discharge complete blood count parameters into prognostic scoring systems could improve prediction of 90-day outcomes. Hemoglobin had the greatest prognostic value for the primary composite outcome of 90-day rehospitalization or mortality. Absolute lymphocyte count provided little added value in multivariable model comparisons, including for infection- or sepsis-related rehospitalization.

Exploring a global interpretation mechanism for deep learning networks when predicting sepsis

The purpose of this study is to identify additional clinical features for sepsis detection through the use of a novel mechanism for interpreting black-box machine learning models trained and to provide a suitable evaluation for the mechanism. We use the publicly available dataset from the 2019 PhysioNet Challenge. It has around 40,000 Intensive Care Unit (ICU) patients with 40 physiological variables. Using Long Short-Term Memory (LSTM) as the representative black-box machine learning model, we adapted the Multi-set Classifier to globally interpret the black-box model for concepts it learned about sepsis. To identify relevant features, the result is compared against: (i) features used by a computational sepsis expert, (ii) clinical features from clinical collaborators, (iii) academic features from literature, and (iv) significant features from statistical hypothesis testing. Random Forest was found to be the computational sepsis expert because it had high accuracies for solving both the detection and early detection, and a high degree of overlap with clinical and literature features. Using the proposed interpretation mechanism and the dataset, we identified 17 features that the LSTM used for sepsis classification, 11 of which overlaps with the top 20 features from the Random Forest model, 10 with academic features and 5 with clinical features. Clinical opinion suggests, 3 LSTM features have strong correlation with some clinical features that were not identified by the mechanism. We also found that age, chloride ion concentration, pH and oxygen saturation should be investigated further for connection with developing sepsis. Interpretation mechanisms can bolster the incorporation of state-of-the-art machine learning models into clinical decision support systems, and might help clinicians to address the issue of early sepsis detection. The promising results from this study warrants further investigation into creation of new and improvement of existing interpretation mechanisms for black-box models, and into clinical features that are currently not used in clinical assessment of sepsis.

Clinical assessment of neutrophil gelatinase-associated lipocalin as a potential diagnostic marker for neonatal sepsis: a prospective cohort study

Sepsis is a life-threatening condition associated with high morbidity and mortality rates among neonates. Clinical diagnosis is limited due to the neonates' unspecific signs and symptoms as well as the long time required to obtain the blood culture results. Consequently, there is an urgent need for new biomarkers to early diagnose neonatal sepsis. We aimed to evaluate Neutrophil Gelatinase-Associated Lipocalin (NGAL) diagnostic performance to detect neonatal sepsis. We enrolled 30 neonates with sepsis admitted to the neonatal intensive care units and 30 age- and sex-matched healthy neonates recruited from the neonatal outpatient clinic during their routine follow-up visits. We measured NGAL levels by sandwich enzyme-linked immunosorbent assay, the C-reactive protein (CRP) with nephelometry technique using BN II nephelometer, and the complete blood count by Mindray BC-6800 analysers. NGAL, CRP, TLC, haemoglobin, and platelet levels showed significant differences between cases and control (all p < .001). Of the 30 neonates with sepsis, 17 neonates (56.7%) survived. At 0 h, the NGAL level showed no statistically significant difference between the non-survivors and survivors' groups; however, after 96 h, NGAL was significantly higher in the non-survivors group (p ˂ .001). Our diagnostic analysis showed that NGAL levels have strong discrimination power to early differentiate neonates with sepsis; at the 475.00 pg/ml cut-off value, NGAL showed both sensitivity and specificity of 100% with an area under curve of 100%. Conclusion: Our study suggests that NGAL could be a promising biomarker for neonatal sepsis detection. Further studies with larger sample sizes and survival analysis are warranted to confirm this finding and to clarify the efficacy of NGAL in survival prediction. Key findingsNGAL level was high in neonates with sepsisNGAL level was high in non-survived neonatesNGAL could be a promising diagnostic marker for sepsis.

A Decrease in Hb and Hypoproteinemia: Possible Predictors of Complications in Neonates with Late-Onset Sepsis in a Developing Country

Objective

The main purpose of our study was to determine the predictors of complications in neonates with late-onset sepsis (LOS).

Materials and methods

This was a retrospective cohort study conducted in a neonatal intensive care unit between June 2016 and February 2020. Neonates with LOS were enrolled in this study. According to whether complications were merged after LOS, neonates were divided into a complicated group and a noncomplicated group. The demographic data, perinatal conditions, blood cell count analysis, blood cultures, hypoproteinemia within 1 week after the onset of sepsis and treatment measures were compared between the groups.

Results

A total of 87 neonates with LOS were enrolled in this study. Significant differences were observed between the complicated and noncomplicated groups with regard to hemoglobin (Hb), a decrease in Hb, hypoproteinemia and red blood cell transfusions (P < 0.05). Further comparison found that neonates with LOS who had moderate or severe anemia at the time of sepsis onset were more likely to have complications than those with mild or no anemia. The results of binomial stepwise logistic regression suggested that a decrease in Hb (OR=0.045, P=0.025 < 0.05) and hypoproteinemia (OR=0.266, P=0.007 < 0.05) were independent predictors of complications in neonates with LOS. A receiver operating characteristic analysis showed that the area under the curve was 0.807 for a decrease in Hb.

Conclusion

A decrease in Hb and hypoproteinemia were independent predictors of complications and may help to predict the occurrence of complications in neonates with LOS in the early stage.

The Effect of Haematocrit on Measurement of the Mid-Infrared Refractive Index of Plasma in Whole Blood

Recent advances suggest that miniaturised mid-infrared (MIR) devices could replace more time-consuming, laboratory-based techniques for clinical diagnostics. This work uses Fourier transform infrared spectroscopy to show that the MIR complex refractive index of whole blood varies across a range of haematocrit. This indicates that the use of an evanescent measurement is not sufficient to optically exclude the cellular content of blood in the MIR, as previously assumed. Here, spectral refractive index data is presented in two ways. First, it is given as whole blood with varying haematocrit. Second, it is given as the percentage error that haematocrit introduces to plasma. The maximum error in the effective plasma refractive index due to the haematocrit of healthy adults was 0.25% for the real part n and 11% for the imaginary part k. This implies that calibration measurements of haematocrit can be used to account for errors introduced by the cellular content, enabling plasma spectra and analyte concentrations to be indirectly calculated from a whole blood sample. This methodological advance is of clinical importance as plasma concentration of analytes such as drugs can be determined using MIR without the preprocessing of whole blood.

Preexisting Clinical Frailty Is Associated With Worse Clinical Outcomes in Patients With Sepsis

OBJECTIVES

Frailty is a multidimensional syndrome or state of increased vulnerability to poor resolution of homoeostasis following a stressor event. Frailty is common in patients with sepsis. Sepsis and frailty are both associated with older age and chronic medical conditions. However, there is limited evidence about the direct association between frailty and sepsis. The aim of this study is to determine the association between preexisting clinical frailty and clinical outcomes in patients with sepsis.

DESIGN

A nationwide propensity score-matched cohort study analyzing data prospectively collected between September 2019 and February 2020.

SETTING

Nineteen tertiary or university-affiliated hospitals in South Korea.

PATIENTS

Adult patients who were diagnosed with sepsis.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Frailty status was assessed using the Clinical Frailty Scale. All patients were classified as "frail" (Clinical Frailty Scale score, 5-9) or "nonfrail" (Clinical Frailty Scale score, 1-4). Propensity score matching identified comparable nonfrail patients. The primary outcome was inhospital mortality. Multivariable logistic regression analysis was used to evaluate the association between frailty and inhospital mortality. The propensity score-matched cohort comprised 468 nonfrail patients and 468 frail patients; all covariate imbalances were alleviated. In the matched cohort (mean age, 69 ± 14 yr), 27.2% had septic shock at presentation. Inhospital mortality was 34.2% in the frail group and 26.9% in the nonfrail group (p = 0.019). The adjusted odds ratio for inhospital mortality in the frail group compared with the nonfrail group was 2.00 (95% CI, 1.39-2.89; p < 0.001). Among the patients who survived to discharge, the frail group was less likely to be discharged home compared with the nonfrail group, 64.0% versus 81.3%, respectively (p < 0.001).

CONCLUSIONS

In patients with sepsis, preexisting clinical frailty is associated with worse clinical outcomes than that in nonfrail patients, including inhospital mortality and discharge to home.

Impact of 1-Hour Bundle Achievement in Septic Shock

This study aimed to address the impact of 1-hr bundle achievement on outcomes in septic shock patients. Secondary analysis of multicenter prospectively collected data on septic shock patients who had undergone protocolized resuscitation bundle therapy at emergency departments was conducted. In-hospital mortality according to 1-h bundle achievement was compared using multivariable logistic regression analysis. Patients were also divided into 3 groups according to the time of bundle achievement and outcomes were compared to examine the difference in outcome for each group over time: group 1 (≤1 h reference), group 2 (1–3 h) and group 3 (3–6 h). In total, 1612 patients with septic shock were included. The 1-h bundle was achieved in 461 (28.6%) patients. The group that achieved the 1-h bundle did not show a significant difference in in-hospital mortality compared to the group that did not achieve the 1-h bundle on multivariable logistic regression analysis (<1 vs. >1 h) (odds ratio = 0.74, p = 0.091). However, 3- and 6- h bundle achievements showed significantly lower odds ratios of in-hospital mortality compared to the group that did not achieve the bundle (<3 vs. >3 h, <6 vs. >6 h, odds ratio = 0.604 and 0.458, respectively). There was no significant difference in in-hospital mortality over time for group 2 and 3 compared to that of group 1. One-hour bundle achievement was not associated with improved outcomes in septic shock patients. These data suggest that further investigation into the clinical implications of 1-h bundle achievement in patients with septic shock is warranted.