Predicting six-month mortality of patients with traumatic brain injury: usefulness of common intensive care severity scores

Introduction

The aim of this study was to evaluate the usefulness of the APACHE II (Acute Physiology and Chronic Health Evaluation II), SAPS II (Simplified Acute Physiology Score II) and SOFA (Sequential Organ Failure Assessment) scores compared to simpler models based on age and Glasgow Coma Scale (GCS) in predicting long-term outcome of patients with moderate-to-severe traumatic brain injury (TBI) treated in the intensive care unit (ICU).

Methods

A national ICU database was screened for eligible TBI patients (age over 15 years, GCS 3–13) admitted in 2003–2012. Logistic regression was used for customization of APACHE II, SAPS II and SOFA score-based models for six-month mortality prediction. These models were compared to an adjusted SOFA-based model (including age) and a reference model (age and GCS). Internal validation was performed by a randomized split-sample technique. Prognostic performance was determined by assessing discrimination, calibration and precision.

Results

In total, 1,625 patients were included. The overall six-month mortality was 33%. The APACHE II and SAPS II-based models showed good discrimination (area under the curve (AUC) 0.79, 95% confidence interval (CI) 0.75 to 0.82; and 0.80, 95% CI 0.77 to 0.83, respectively), calibration (P > 0.05) and precision (Brier score 0.166 to 0.167). The SOFA-based model showed poor discrimination (AUC 0.68, 95% CI 0.64 to 0.72) and precision (Brier score 0.201) but good calibration (P > 0.05). The AUC of the SOFA-based model was significantly improved after the insertion of age and GCS (∆AUC +0.11, P < 0.001). The performance of the reference model was comparable to the APACHE II and SAPS II in terms of discrimination (AUC 0.77; compared to APACHE II, ΔAUC −0.02, P = 0.425; compared to SAPS II, ΔAUC −0.03, P = 0.218), calibration (P > 0.05) and precision (Brier score 0.181).

Conclusions

A simple prognostic model, based only on age and GCS, displayed a fairly good prognostic performance in predicting six-month mortality of ICU-treated patients with TBI. The use of the more complex scoring systems APACHE II, SAPS II and SOFA added little to the prognostic performance.     

Prognostic value of glucose‐to‐lymphocyte ratio in critically ill patients with acute respiratory distress syndrome: A retrospective cohort study

BackgroundThere is need to identify biomarkers for prognosis of acute respiratory distress syndrome (ADRS). This may allow early and accurate identification of patients with high‐risk ARDS to guide adjustment of clinical treatment and nursing intervention, which would ultimately improve prognosis of patients with ARDS. Biomarkers based on a combination of fasting glucose and lymphocyte counts to predict prognosis in critically ill patients with ARDS remain undefined. In this study, we investigated the association between glucose‐to‐lymphocyte ratio (GLR) and in‐hospital mortality.MethodsThe study obtained data from Medical Information Mart for Intensive Care‐IV (MIMIC‐IV Version 1.0) database. We defined the GLR as fasting glucose/lymphocyte count and the patient in‐hospital mortality was considered as the outcome. In addition, we employed linear and logistic regression models for analysis.ResultsIn total, 1,085 patients with ARDS were included in this study. The eligible participants included 498 female and 587 males, with a mean age of 64.2 ± 17.5 years. Logistic regression analysis demonstrated that higher GLR was an independent risk factor for all‐cause mortality (OR =1.67, 95% CI: 1.26–2.22) after adjusting for age, sex, anion gap, white blood cell count, congestive heart failure, sequential organ failure assessment (SOFA), SBP, DBP, and respiratory rate in both the dichotomized group and subgroups. We also analyzed the in‐hospital mortality to ROC curves by comparing the value between SOFA + GLR and SOFA. The area under the curve (AUC) was 0.6991 for the SOFA + GLR (95% CI: 0.6634–0.7348), and 0.6613 for the SOFA (95% CI: 0.6238–0.6988).ConclusionOur data showed that the GLR was an independent predictor of in‐hospital mortality for patients with ARDS. The GLR is an integrated, readily available clinical biomarker for mortality in patients with ARDS.     

Association of platelet count with all‐cause mortality from acute respiratory distress syndrome: A cohort study

BackgroundThe purpose of this study was to investigate whether platelet count was associated with mortality in acute respiratory distress syndrome (ARDS) patients.MethodsWe analyzed patients with ARDS from Multi‐parameter Intelligent Monitoring in Intensive Care Database III (MIMIC‐III). Platelet count was measured at the time of intensive care unit (ICU) admission. The cox proportional hazard model and subgroup analysis were used to determine the relationship between the platelet count and mortality of ARDS, as well as the consistency of its association. The primary outcome of this study was 365‐day mortality from the date of ICU admission.ResultThis study enrolled a total of 395 critically ill patients with ARDS. After adjustment for age, gender and ethnicity, the multivariate cox regression model showed that the hazard ratios (HRs) (95% confidence intervals [CIs]) of platelet count <192 × 10⁹/L and >296 × 10⁹/L were 2.08 (1.43, 3.04) and 1.35 (0.91, 2.01), respectively, compared with the reference (192–296 ×10⁹/L). After adjusting for confounding factors, lower platelet count (<192 × 10⁹/L) was associated with increased mortality (adjusted HR, 1.71; 95% CI 1.06–2.76, p = 0.0284). However, there was no similar trend in the 30‐day (adjusted HR,1.02; 95% CI 0.54–1.94) or 90‐day (adjusted HR, 1.65; 95% CI 0.94–2.89) mortality. In the subgroup analysis, lower platelet count showed significant interactions with specific populations (p interaction = 0.0413), especially in patients with atrial fibrillation.ConclusionTaken together, our analysis showed that platelet count is an independent predictor of mortality in critically ill patients with ARDS.     

Low serum level of apolipoprotein A1 may predict the severity of COVID‐19: A retrospective study

BackgroundDyslipidemia has been observed in patients with coronavirus disease 2019 (COVID‐19). This study aimed to investigate blood lipid profiles in patients with COVID‐19 and to explore their predictive values for COVID‐19 severity.MethodsA total of 142 consecutive patients with COVID‐19 were included in this single‐center retrospective study. Blood lipid profile characteristics were investigated in patients with COVID‐19 in comparison with 77 age‐ and gender‐matched healthy subjects, their predictive values for COVID‐19 severity were analyzed by using multivariable logistic regression analysis, and their prediction efficiencies were evaluated by using receiver operator characteristic (ROC) curves.ResultsThere were 125 and 17 cases in the non‐severe and severe groups, respectively. Total cholesterol (TC), high‐density lipoprotein cholesterol (HDL‐C), low‐density lipoprotein cholesterol (LDL‐C), and apolipoprotein A1 (ApoA1) gradually decreased across the groups in the following order: healthy controls, non‐severe group, and severe group. ApoA1 was identified as an independent risk factor for COVID‐19 severity (adjusted odds ratio [OR]: 0.865, 95% confidence interval [CI]: 0.800–0.935, p < 0.001), along with interleukin‐6 (IL‐6) (adjusted OR: 1.097, 95% CI: 1.034–1.165, p = 0.002). ApoA1 exhibited the highest area under the ROC curve (AUC) among all single markers (AUC: 0.896, 95% CI: 0.834–0.941); moreover, the risk model established using ApoA1 and IL‐6 enhanced prediction efficiency (AUC: 0.977, 95% CI: 0.932–0.995).ConclusionBlood lipid profiles in patients with COVID‐19 are quite abnormal compared with those in healthy subjects, especially in severe cases. Serum ApoA1 may represent a good indicator for predicting the severity of COVID‐19.     

Performance assessment of the Simplified Acute Physiology Score II,the Acute Physiology and Chronic Health Evaluation II score,and the Sequential Organ Failure Assessment score in predicting the outcomes of adult patients with hepatic portal venous gas in the ED

ObjectiveThis study aims to evaluate the performance of Simplified Acute Physiology Score II (SAPS II), the Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and the Sequential Organ Failure Assessment (SOFA) score for predicting illness severity and the mortality of adult hepatic portal venous gas (HPVG) patients presenting to the emergency department (ED). This will assist emergency physicians in risk stratification.MethodsData for 48 adult HPVG patients who visited our ED between December 2009 and December 2013 were analyzed. The SAPS II, APACHE II score, and SOFA score were calculated based on the worst laboratory values in the ED. The probability of death was calculated for each patient based on these scores. The ability of the SAPS II, APACHE II score, and SOFA score to predict group mortality was assessed by using receiver operating characteristic curve analysis and calibration analysis.ResultsThe sensitivity, specificity, and accuracy were 92.6%,71.4%, and 83.3%, respectively, for the SAPS II method; 77.8%, 81%, and 79.2%, respectively, for the APACHE II scoring system, and 77.8%, 76.2%, and 79.2%, respectively, for the SOFA score. In the receiver operating characteristic curve analysis, the areas under the curve for the SAPS II, APACHE II scoring system, and SOFA score were 0.910, 0.878, and 0.809, respectively.ConclusionThis is one of the largest series performed in a population of adult HPVG patients in the ED. The results from the present study showed that SAPS II is easier and more quickly calculated than the APACHE II and more superior in predicting the mortality of ED adult HPVG patients than the SOFA. We recommend that the SAPS II be used for outcome prediction and risk stratification in adult HPVG patients in the ED.     

Cautions on the laboratory indicators of COVID‐19 patients on and during admission

BackgroundDifferent disease severities of COVID‐19 patients could be reflected on clinical laboratory findings.MethodsIn this single‐centered retrospective study, demographic, clinical, and laboratory indicators on and during admission were compared among 74 participants with mild, moderate, critical severe, or severe classification. Risk factors associated with disease severity were analyzed by multivariate analyses. The AUC and 95% CI of the ROC curve were calculated.ResultsThe most common manifestations of these patients were fever and cough. Critical severe or severe group owned the longest length of stay (23 (19,31), p < 0.001). After multivariate logistic regression, independent influence factors on admission for severity of disease were CK‐MB (OR 0.674; 95% CI 0.489–0.928; p = 0.016), LDH (OR 1.111 or 1.107; 95% CI 1.026–1.204 or 1.022–1.199; p = 0.009 or 0.013), normal T‐BIL (OR 4.58 × 10⁻⁸; 95% CI 3.05 × 10⁻⁹–6.88 × 10⁻⁷; p < 0.001), LYM% (OR 0.008; 95% CI 0–0.602; p = 0.029), and normal ESR (OR 0.016; 95% CI 0–0.498; p = 0.019). Factors during hospitalization were normal T‐BIL (OR 8.56 × 10⁻⁹; 95% CI 8.30 × 10⁻¹⁰–8.83 × 10⁻⁸; p < 0.001), LYM (OR 0.068; 95% CI 0.005–0.934; p = 0.044), albumin (OR 0.565; 95% CI 0.327–0.977; p = 0.041), and normal NEU% (OR 0.013; 95% CI 0.000–0.967; p = 0.048). Combined indicators of AUC were 0.860 (LYM, LDH, and normal ESR on admission, p < 0.001) and 0.750 (CK‐MB, LDH, and normal T‐BIL during hospitalization, p = 0.020) when predicting for severe or critical severe patients.ConclusionTo pay close attention to the progression of COVID‐19 and take measures promptly, we should be cautious of the laboratory indicators when patients on admission especially CK‐MB, LDH, LYM%, T‐BIL as well as ESR; and T‐BIL, LYM, albumin, NEU% with the process of disease.     

The influence of missing components of the Acute Physiology Score of APACHE III on the measurement of ICU performance

Objective To determine the impact of missing Acute Physiology Score (APS) values on risk-adjusted mortality.Design Retrospective review of prospectively collected Acute Physiology and Chronic Health Evaluation (APACHE) III database.Setting The intensive care units (ICUs) of an academic medical center.Patients 38,411 patients admitted to ICU between October 1994 and December 2003.Measurements and results Data were collected on ICU type, missing first ICU day APS values, predicted and observed hospital mortality, standardized mortality ratio (SMR), 95% confidence interval (CI), odds ratio (OR). The overall observed and predicted hospital mortality rates were 8.7% and 10.8%, respectively, with SMR of 0.806 (95% CI 0.779–0.834). Complete data were available in 829 (2.2%). Vital signs were missing in almost none and serum albumin and bilirubin in over 80% of the patients. The number of missing variables was higher in less sick and surgical ICU patients. Logistic regression analysis showed that the risk of dying in the hospital was significantly associated with the number of missing APS variables (OR 1.058, 95% CI 1.027–1.090) when adjusted for the severity of illness. The risk of death was also associated with the type of missing variables.Conclusions Since missing APS values may lead to underestimation of the predicted mortality rates, the number and type of missing variables should be taken into consideration when assessing the performance of an ICU. Unless data collection is standardized, future prognostic models should use variables that are routinely measured in most critically ill patients without sacrificing statistical precision.This article refers to the editorial:     

Is C-reactive protein a good prognostic marker in septic patients?

Rationale  Several studies have shown that C-reactive protein (CRP) is a marker of infection. The aim of this study was to evaluate CRP as marker of prognosis outcome in septic patients and to assess the correlation of CRP with severity of sepsis. Methods  During a 14-month period, we prospectively included all patients with sepsis admitted to an intensive care unit (ICU). Patients were categorized into sepsis, severe sepsis and septic shock. Acute Physiology and Chronic Health Evaluation (APACHE) II score, Simplified Acute Physiology Score (SAPS) II, Sequential Organ Failure Assessment (SOFA) score, CRP, body temperature and white cell count (WCC) of the day of sepsis diagnosis were collected. Results  One hundred and fifty-eight consecutive septic patients (mean age 59 years, 98 men, ICU mortality 34%) were studied. The area under the receiver operating characteristics curves of APACHE II, SAPS II, SOFA, CRP, body temperature and WCC as prognostic markers of sepsis were 0.75 [95% confidence interval (CI) 0.67–0.83], 0.82 (95% CI 0.75–0.89), 0.8 (95% CI 0.72–0.88), 0.55 (95% CI 0.45–0.65), 0.48 (95% CI 0.38–0.58) and 0.46 (95% CI 0.35–0.56), respectively. In the subgroup of patients with documented sepsis we obtained similar results. The ICU mortality rate of septic patients with CRP < 10, 10–20, 20–30, 30–40 and >40 mg/dL was 20, 34, 30.8, 42.3 and 39.1%, respectively (P = 0.7). No correlation was found between CRP concentrations and severity of sepsis. Conclusions  In septic patients, CRP of the day of sepsis diagnosis is not a good marker of prognosis.     

Association Between Red Cell Distribution Width and Hospital Mortality in Patients with Sepsis

ObjectiveSepsis is the leading cause of death in patients admitted to adult intensive care units (ICUs). We aimed to determine the predictive value of red blood cell distribution width (RDW) in patients with sepsis in a large cohort.MethodsThis retrospective observational study used data from the eICU Collaborative Research Database. The prognostic value of RDW was investigated using the receiver operating characteristic (ROC) curve, multiple logistic regression model, integrated discriminatory index (IDI), and net reclassification index (NRI).ResultsIn total, 9743 patients were included. The area under the ROC curve of the RDW for predicting hospital mortality was 0.631 (95% confidence interval [CI]: 0.616–0.645). Based on the multiple logistic regression model, an RDW of ≥14.5% was correlated with hospital mortality, regardless of Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation IV (APACHE IV) scores (odds ratio [OR]: 1.838, 95% CI: 1.598–2.119). Using SOFA and APACHE IV scores as reference, the IDI and continuous NRI of RDW for hospital mortality was about 0.3 and 0.014, respectively.ConclusionsThe RDW may be useful in predicting hospital mortality in patients with sepsis, offering extra prognostic value beyond SOFA and APACHE IV scores.     

In‐hospital mortality in SARS‐CoV‐2 stratified by gamma‐glutamyl transferase levels

BackgroundThis study investigates in‐hospital mortality amongst patients with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and its relation to serum levels of gamma‐glutamyl transferase (GGT).MethodsPatients were stratified according to serum levels of gamma‐glutamyl transferase (GGT) (GGT<50 IU/L or GGT≥50 IU/L).ResultsA total of 802 participants were considered, amongst whom 486 had GGT<50 IU/L and a mean age of 48.1 (16.5) years, whilst 316 had GGT≥50 IU/L and a mean age of 53.8 (14.7) years. The chief sources of SARS‐CoV‐2 transmission were contact (366, 45.7%) and community (320, 40%). Most patients with GGT≥50 IU/L had either pneumonia (247, 78.2%) or acute respiratory distress syndrome (ARDS) (85, 26.9%), whilst those with GGT<50 IU/L had hypertension (141, 29%) or diabetes mellitus (DM) (147, 30.2%). Mortality was higher amongst patients with GGT≥50 IU/L (54, 17.1%) than amongst those with GGT<50 IU/L (29, 5.9%). More patients with GGT≥50 required high (83, 27.6%) or low (104, 34.6%) levels of oxygen, whereas most of those with GGT<50 had no requirement of oxygen (306, 71.2%). Multivariable logistic regression analysis indicated that GGT≥50 IU/L (odds ratio [OR]: 2.02, 95% confidence interval [CI]: 1.20–3.45, p=0.009), age (OR: 1.05, 95% CI: 1.03–1.07, p<0.001), hypertension (OR: 2.06, 95% CI: 1.19–3.63, p=0.011), methylprednisolone (OR: 2.96, 95% CI: 1.74–5.01, p<0.001) and fever (OR: 2.03, 95% CI: 1.15–3.68, p=0.016) were significant predictors of all‐cause cumulative mortality. A Cox proportional hazards regression model (B = −0.68, SE =0.24, HR =0.51, p = 0.004) showed that patients with GGT<50 IU/L had a 0.51‐times lower risk of all‐cause cumulative mortality than patients with GGT≥50 IU/L.ConclusionHigher levels of serum GGT were found to be an independent predictor of in‐hospital mortality.     

Comparison of two simplified severity scores (SAPS and APACHE II) for patients with acute myocardial infarction

The Simplified Acute Physiology Score (SAPS), the Acute Physiology and Chronic Health Evaluation II (APACHE II), the Acute Physiology Score (APS), and the Coronary Prognostic Index (CPI), calculated within the first 24 h of ICU admission, were compared in 76 patients with acute myocardial infarction (AMI). Sixteen (21%) patients subsequently died in the ICU. The nonsurvivors had significantly higher SAPS, APACHE II, and CPI scores than the survivors. ROC curves drawn for each severity index were in a discriminating position. There were no significant differences either between the areas under the ROC curves drawn for SAPS, APACHE II, and CPI, or between the overall accuracies of these indices. APS provided less homogeneous information. We conclude that SAPS and APACHE II, two severity indices which are easy to use, assess accurately the short-term prognosis, i.e., the ICU outcome, of patients with AMI.     

The predictive performance of the SAPS II and SAPS 3 scoring systems: A retrospective analysis

PurposeThe purpose was to analyze and compare the performance of Simplified Acute Physiology Score (SAPS) II and SAPS 3 (North Europe Logit) in an intensive care unit (ICU) for internal disorders at a German university hospital.Materials and methodsThis retrospective study was conducted at a single-center 12-bed ICU sector for Internal Medicine in Essen, Germany, within an 18-month period. Data for adult ICU patients (N = 548) were evaluated. SAPS II and SAPS 3 scores were assessed along with the predicted mortality rates. Discrimination was evaluated by calculating the area under the receiver operating characteristic curve, and calibration was evaluated using the Hosmer-Lemeshow goodness-of-fit C-test. The ratios of observed-to-expected deaths (standardized mortality ratio, SMR) were calculated along with the 95% confidence intervals (95% CIs).ResultsThe in-hospital mortality rate was 22.6%, which provided an SMR of 0.91 (95% CI, 0.77-0.99) for SAPS II and 0.62 (95% CI, 0.52-0.71) for SAPS 3. Both SAPS II and SAPS 3 exhibited acceptable discrimination, with an area under the receiver operating characteristic curve of 0.84 (95% CI, 0.79-0.89) and 0.73 (95% CI, 0.67-0.79), respectively. However, SAPS II demonstrated superior SMR-based discrimination, which was closer to the observed mortality rate, compared with SAPS 3. Calibration curves exhibited similar performance based on the Hosmer-Lemeshow goodness-of-fit C-test results: χ² = 7.10 with P = .525 for SAPS II and χ² = 3.10 with P = .876 for SAPS 3. Interestingly, both scores overpredicted mortality.ConclusionsIn this study, SAPS 3 overestimated mortality and therefore appears less suitable for risk evaluation in comparison to SAPS II.     

Early sedation and clinical outcomes of mechanically ventilated patients: a prospective multicenter cohort study

Introduction

Sedation overuse is frequent and possibly associated with poor outcomes in the intensive care unit (ICU) patients. However, the association of early oversedation with clinical outcomes has not been thoroughly evaluated. The aim of this study was to assess the association of early sedation strategies with outcomes of critically ill adult patients under mechanical ventilation (MV).

Methods

A secondary analysis of a multicenter prospective cohort conducted in 45 Brazilian ICUs, including adult patients requiring ventilatory support and sedation in the first 48 hours of ICU admissions, was performed. Sedation depth was evaluated after 48 hours of MV. Multivariate analysis was used to identify variables associated with hospital mortality.

Results

A total of 322 patients were evaluated. Overall, ICU and hospital mortality rates were 30.4% and 38.8%, respectively. Deep sedation was observed in 113 patients (35.1%). Longer duration of ventilatory support was observed (7 (4 to 10) versus 5 (3 to 9) days, P = 0.041) and more tracheostomies were performed in the deep sedation group (38.9% versus 22%, P = 0.001) despite similar PaO₂/FiO₂ ratios and acute respiratory distress syndrome (ARDS) severity. In a multivariate analysis, age (Odds Ratio (OR) 1.02; 95% confidence interval (CI) 1.00 to 1.03), Charlson Comorbidity Index >2 (OR 2.06; 95% CI, 1.44 to 2.94), Simplified Acute Physiology Score 3 (SAPS 3) score (OR 1.02; CI 95%, 1.00 to 1.04), severe ARDS (OR 1.44; CI 95%, 1.09 to 1.91) and deep sedation (OR 2.36; CI 95%, 1.31 to 4.25) were independently associated with increased hospital mortality.

Conclusions

Early deep sedation is associated with adverse outcomes and constitutes an independent predictor of hospital mortality in mechanically ventilated patients.     

Prognostic value of inflammation‐immunity‐nutrition score in patients with hepatocellular carcinoma treated with anti‐PD‐1 therapy

BackgroundThere are no validated biomarkers that can predict the clinical benefit of immune checkpoint blockers against the programmed cell death protein 1 (PD‐1) treatments in hepatocellular carcinoma (HCC). This study aimed to investigate the prognostic value of inflammation‐immunity‐nutrition score (IINS) in patients with HCC treated with anti‐PD‐1 therapy.MethodsA consecutive series of 101 HCC patients treated with PD‐1 inhibitors in Sichuan Provincial People''s Hospital between January 2018 and August 2020 were enrolled in the retrospective study. IINS (0–6) was constructed based on pretreatment high‐sensitivity C‐reactive protein (hsCRP), lymphocyte (LYM), and albumin (ALB). The patients were divided into high and low IINS groups according to IINS values. Prognostic values of each variable were evaluated with univariate and multivariate time‐dependent Cox regression analyses. Survival curves were calculated and compared using the Kaplan–Meier method and log‐rank test. The prognostic performance of IINS was further compared with that of other traditional prognostic indicators by receiver operating characteristic (ROC) curve and the areas under the ROC curve.ResultsPatients with low IINS had longer overall survival (OS) (HR: 4.711, 95% CI: 1.80–12.37, p = .001) and progression‐free survival (HR: 3.411, 95% CI: 1.79–6.51, p < .0001) than those with high IINS. The multivariate analysis identified IINS (HR: 3.746, 95% CI: 1.05–13.38, p = .042) and tumor number (HR: 5.111, 95% CI: 1.075–24.299, p = .04) as independent prognostic factors. According to ROC analysis, IINS (AUC =0.729, 95% CI: 0.597–0.861, p = .002) presented better prognostic performance than other traditional prognostic indicators. The area of the IINS‐CA19‐9 under the ROC curve (AUC) was higher than that of the IINS or CA19‐9 levels for the prediction of OS.ConclusionThe results suggest that IINS may be an independent prognostic indicator for HCC patients treated with anti‐PD‐1 therapy. IINS‐CA19‐9 classification may be more effective in predicting clinical benefit of anti‐PD‐1 therapy in HCC patients.     

Red blood cell distribution width‐to‐albumin ratio is associated with all‐cause mortality in cancer patients

BackgroundCancer causes a serious health burden on patients worldwide. Chronic low‐level inflammation plays a key role in tumorigenesis and prognosis. However, the role of the red blood cell distribution width (RDW)‐to‐albumin (RA) ratio in cancer mortality remains unclear.MethodsIn this retrospective cohort study, we collected clinical information from cancer patients from the Medical Information Mart for Intensive Care III (MIMIC‐III) version 1.4 database and then calculated RA by dividing RDW by albumin concentration. The primary outcome was 30 days mortality, while secondary outcomes were 90 days and 1 year mortality. Next, we adopted Cox regression models to calculate hazard ratios (HR) together with 95% confidence intervals (CI) for all‐cause mortalities associated with the RA ratio.ResultsFor 30 days mortality, the HR (95% CI) for the high RA ratio (≥5.51) was 2.17 [95CI% (1.87–2.51); p = <0.0001], compared with the low RA ratio (<5.51). In Model 2, we adjusted sex and age and obtained HR (95% CI) of 2.17 [95CI% (1.87–2.52); p = <0.0001] for the high RA ratio (≥5.51) group, compared to that in the low RA ratio (<5.51). In Model 3, adjusting for age, sex, anion gap, hematocrit, white blood cell count, congestive heart failure, SOFA, liver disease, and renal failure resulted in HR (95% CI) of 1.74 [95CI% (1.48–2.04); p = <0.0001] for the high RA ratio (≥5.51) relative to the low RA ratio (<5.51). We also analyzed common diseases in cancer patients but found no significant association.ConclusionTo the best of our knowledge, this is the first study demonstrating that increased RA ratio is independently associated with increased all‐cause mortality in cancer patients.     

Influencing factors of depressive symptoms in patients with malignant tumour

ObjectiveTo assess the influencing factors of depressive symptoms in malignant tumour patients.MethodsParticipants were 2079 inpatients with malignant tumour (1291: depressive symptoms; 788 no depressive symptoms). Univariable and multivariable logistic regression were used to evaluate sociodemographic and clinical factors influencing depressive symptoms.ResultsRisk factors were family income ≤5000 yuan (odds ratio [OR]: 4.966, 95% confidence interval [CI]: 2.938–8.395) and 5001–10,000 yuan (OR: 3.111, 95% CI: 1.840–5.260); Karnofsky Performance Status of 70 (OR: 2.783, 95% CI: 1.281–6.042) and 80 (OR: 1.834, 95% CI: 1.139–2.953); disease course ≤1 year; palliative treatment (OR: 2.288, 95% CI: 1.292–4.055); progressive disease (OR: 1.876, 95% CI: 1.284–2.739); pain (OR: 1.973, 95% CI: 1.555–2.505); cancer type: lung (OR: 3.199, 95% CI: 1.938–5.279), oesophagus (OR: 3.288, 95% CI: 1.673–6.464), cervix (OR: 1.542, 95% CI: 1.056–2.253) and partial knowledge of disease condition (OR: 2.366, 95% CI: 1.653–3.385). Return to work (OR: 0.503, 95% CI: 0.348–0.727) and physical exercise (OR: 0.437, 95% CI: 0.347–0.551) were protective against depressive symptoms.ConclusionsSeveral factors affected depressive symptoms in malignant tumour patients, including income, disease type and course, palliative treatment, return to work and physical exercise.     

Lymphocyte‐to‐monocyte ratio combined with CA19‐9 for predicting postoperative recurrence of colorectal cancer in patients with diabetes

ObjectiveTo investigate the significance of lymphocyte‐to‐monocyte ratio (LMR) combined with carbohydrate antigen (CA) 19‐9 for predicting postoperative recurrence of colorectal cancer (CRC) in patients with type II diabetes.MethodsWe conducted a retrospective analysis of 106 postoperative patients with stage II–III CRC and with type II diabetes. Their clinical indexes such as LMR and CA19‐9 were collected, and the patients were followed up for 5 years.ResultsThe CA19‐9 level was 119.7 U/ml at baseline in the relapsed group, while this was 24.81 U/ml in non‐relapsed group (p = 0.001). On the contrary, the LMR level was 5.10 and 2.57 for non‐relapsed and relapsed group (p < 0.001), respectively. Kaplan‐Meier survival curves stratified by CA19‐9 and LMR suggested that patients with lower CA19‐9 had higher survival probability (p < 0.001), while patients with high LMR level had higher survival probability (p < 0.001). The multivariable Cox proportional hazard regression analysis with CA19‐9 and LMR indicated that although the baseline CA19‐9 is significantly associated with increasing risk of disease recurrence, the HR (HR = 1.0, 95% CI 1.00–1.01) was small and close to 1, whereas the high baseline LMR (HR = 0.44, 95% CI 0.32–0.61) was associated with decrease in disease recurrence. Model with continuous CA19‐9 and LMR was able to better predict (AUC 73.17%) the disease recurrence.ConclusionLMR combined with CA19‐9 may become a new index for predicting postoperative recurrence of CRC in patients with diabetes.     

Benefit profile of recombinant human soluble thrombomodulin in sepsis-induced disseminated intravascular coagulation: a multicenter propensity score analysis

IntroductionThe safety and efficacy of recombinant human soluble thrombomodulin (rhTM) have been demonstrated, with promising evidence suggestive of efficacy for patients with severe sepsis involving coagulopathy in a phase IIb randomized controlled trial. However, the benefit profiles of rhTM have not been elucidated. The purpose of this study was to explore whether patients with greater disease severity, determined according to the Acute Physiology and Chronic Health Evaluation (APACHE) II and Sequential Organ Failure Assessment (SOFA) scores, would experience treatment benefit from rhTM administration.MethodsThis was a post hoc, subgroup analysis of a multicenter retrospective cohort study conducted in three Japanese tertiary referral hospitals. Patients with sepsis-induced disseminated intravascular coagulation (DIC) who required ventilator management were included. We stratified patients into several strata according to disease severity, determined by APACHE II and SOFA scores, using classification and regression trees for survival data. Intervention effects, expressed as hazard ratios (HR), were analyzed using Cox regression analysis adjusted for a propensity model to detect subgroup heterogeneity of the effects of rhTM on in-hospital mortality.ResultsParticipants were 162 patients with sepsis-induced DIC; 68 of these patients received rhTM and 94 did not. After adjusting for imbalances, rhTM administration was significantly associated with reduced mortality in high-risk patients (APACHE II: 24 to 29; HR: 0.281; 95% confidence interval (CI): 0.093 to 0.850; P = 0.025). A similar nonsignificant tendency was observed in the very high-risk subset (APACHE II: ≥30; HR: 0.529; 95% CI: 0.202 to 1.387; P = 0.195) but was not evident in the moderate-risk subset of patients (APACHE II: <24; HR: 0.814; 95% CI: 0.351 to 1.884; P = 0.630). A similar tendency was observed in analysis of SOFA scores (moderate-risk subset (SOFA: <11), P = 0.368; high-risk subset (SOFA: ≥11), P = 0.042).ConclusionsSurvival benefit was observed with rhTM treatment in sepsis-induced DIC and high risk of death according to baseline APACHE II and SOFA scores.     

NIH Grant Awards as a Metric of Clinical and Translational Research Training Effectiveness

The number of clinical research training programs has increased over the past 5–10 years, but few studies have quantitatively evaluated the effectiveness of these programs. The goal of this study was to evaluate the clinical and translational research training program at the University of Cincinnati by comparing the number of National Institutes of Health grants awarded to pediatric fellows who graduated from the MS degree program between 1995 and 2013 versus fellows who did not pursue an MS degree. Among 394 pediatric fellows, 16 of 81 (20%) MS alumni were awarded at least one NIH grant, as compared with 28 of 313 (9%) fellows who did not obtain an MS degree (p < 0.02). In multivariable analysis, MS alumni were more than three times as likely to have received at least one grant than were non‐MS fellows (OR = 3.5, 95% CI [1.7–7.2]; C‐statistic = 0.71) and MS alumni were more likely to obtain at least one K‐series (OR = 4.1, 95% CI [1.6–10.2]; C‐statistic = 0.74), M‐series (OR = 11.8, 95% CI [3.4–41.4]; C‐statistic = 0.81), or R‐series (OR = 10.1, 95% CI [2.4–42.8]; C‐statistic = 0.74) grant than were non‐MS fellows. These findings suggest that graduate training in clinical and translational research prepares graduates for the highly competitive field of clinical and translational research.