Cutoff of the reverse shock index multiplied by the Glasgow coma scale for predicting in-hospital mortality in adult patients with trauma: a retrospective cohort study.

BACKGROUND: Early identification of patients at risk of potential death and timely transfer to appropriate healthcare facilities are critical for reducing the number of preventable trauma deaths. This study aimed to establish a cutoff value to predict in-hospital mortality using the reverse shock index multiplied by the Glasgow Coma Scale (rSIG). METHODS: This multicenter retrospective cohort study used data from 23 emergency departments in South Korea between January 2011 and December 2020. The outcome variable was the in-hospital mortality. The relationship between rSIG and in-hospital mortality was plotted using the shape-restricted regression spline method. To set a cutoff for rSIG, we found the point on the curve where mortality started to increase and the point where the slope of the mortality curve changed the most. We also calculated the cutoff value for rSIG using Youden's index. RESULTS: A total of 318,506 adult patients with trauma were included. The shape-restricted regression spline curve showed that in-hospital mortality began to increase when the rSIG value was less than 18.86, and the slope of the graph increased the most at 12.57. The cutoff of 16.5, calculated using Youden's index, was closest to the target under-triage and over-triage rates, as suggested by the American College of Surgeons, when applied to patients with an rSIG of 20 or less. In addition, in patients with traumatic brain injury, when the rSIG value was over 25, in-hospital mortality tended to increase as the rSIG value increased. CONCLUSIONS: We propose an rSIG cutoff value of 16.5 as a predictor of in-hospital mortality in adult patients with trauma. However, in patients with traumatic brain injury, a high rSIG is also associated with in-hospital mortality. Appropriate cutoffs should be established for this group in the future.

Predictors of clinical outcomes in patients with sepsis: A retrospective study from a tertiary care hospital in Pakistan.

OBJECTIVE: To assess associations between various clinic-demographic factors and clinical outcomes among patients treated for sepsis. METHODS: The retrospective study was conducted at the Aga Khan University Hospital, Karachi, and comprised data of all patients aged >18 years diagnosed with sepsis from January to December 2019. Multivariable logistic regression was used to evaluate independent associations between predictors and outcomes. Data was analysed using R packages. RESULTS: Of the 1,136 patients, 621(54.6%) were male and 515(45.3%) were female. The overall mean age was 59.05±16.91 years. Female gender (odds ratio: 1.029; 95% confidence interval: 1.03-1.64) was found to be an independent predictor of septic shock, while hypertension (odds ratio0.75; 95% confidence interval: 0.59-0.95) emerged as a protective factor. Chronic kidney disease (odds ratio: 1.539; 95% confidence interval: 1.14-2.07) was an independent predictor of prolonged length of stay, while older age appeared to be protective (odds ratio: 0.98; 95% confidence interval: 0.98-0.99). Mortality was associated with a significantly lower odds of Escherichia coli on culture (odds ratio: 0.26; 95% confidence interval: 0.12-0.54). CONCLUSIONS: Independent associations were found between specific patient characteristics and adverse clinical outcomes.

Short- and Long-term survival prediction in patients with acute type A aortic dissection undergoing open surgery.

BACKGROUND: Acute Type A aortic dissection (ATAAD) is a life-threatening cardiovascular disease associated with high mortality rates, where surgical intervention remains the primary life-saving treatment. However, the mortality rate for ATAAD operations continues to be alarmingly high. To address this critical issue, our study aimed to assess the correlation between preoperative laboratory examination, clinical imaging data, and postoperative mortality in ATAAD patients. Additionally, we sought to establish a reliable prediction model for evaluating the risk of postoperative death. METHODS: In this study, a total of 384 patients with acute type A aortic dissection (ATAAD) who were admitted to the emergency department for surgical treatment were included. Based on preoperative laboratory examination and clinical imaging data of ATAAD patients, logistic analysis was used to obtain independent risk factors for postoperative in-hospital death. The survival prediction model was based on cox regression analysis and displayed as a nomogram. RESULTS: Logistic analysis identified several independent risk factors for postoperative in-hospital death, including Marfan syndrome, previous cardiac surgery history, previous renal dialysis history, direct bilirubin, serum phosphorus, D-dimer, white blood cell, multiple aortic ruptures and age. A survival prediction model based on cox regression analysis was established and presented as a nomogram. The model exhibited good discrimination and significantly improved the prediction of death risk in ATAAD patients. CONCLUSIONS: In this study, we developed a novel survival prediction model for acute type A aortic dissection based on preoperative clinical features. The model demonstrated good discriminatory power and improved accuracy in predicting the risk of death in ATAAD patients undergoing open surgery.

Baseline Characteristics of a Patient Cohort and Predictors of In-hospital MORtality in CORonary Care Units (MORCOR-TURK) Trial in Türkiye.

OBJECTIVE: The MORtality in CORonary Care Units in Türkiye (MORCOR-TURK) trial is a national registry evaluating predictors and rates of in-hospital mortality in coronary care unit (CCU) patients in Türkiye. This report describes the baseline demographic characteristics of patients recruited for the MORCOR-TURK trial. METHODS: The study is a multicenter, cross-sectional, prospective national registry that included 50 centers capable of 24-hour CCU service, selected from all seven geographic regions of Türkiye. All consecutive patients admitted to CCUs with cardiovascular emergencies between September 1-30, 2022, were prospectively enrolled. Baseline demographic characteristics, admission diagnoses, laboratory data, and cardiovascular risk factors were recorded. RESULTS: A total of 3,157 patients with a mean age of 65 years (range: 56-73) and 2,087 (66.1%) males were included in the analysis. Patients with arterial hypertension [1,864 patients (59%)], diabetes mellitus (DM) [1,184 (37.5%)], hyperlipidemia [1,120 (35.5%)], and smoking [1,093 (34.6%)] were noted. Non-ST elevation myocardial infarction (NSTEMI) was the leading cause of admission [1,187 patients (37.6%)], followed by ST elevation myocardial infarction (STEMI) in 742 patients (23.5%). Other frequent diagnoses included decompensated heart failure (HF) [339 patients (10.7%)] and arrhythmia [272 patients (8.6%)], respectively. Atrial fibrillation (AF) was the most common pathological rhythm [442 patients (14%)], and chest pain was the most common primary complaint [2,173 patients (68.8%)]. CONCLUSION: The most common admission diagnosis was acute coronary syndrome (ACS), particularly NSTEMI. Hypertension and DM were found to be the two leading risk factors, and AF was the most commonly seen pathological rhythm in all hospitalized patients. These findings may be useful in understanding the characteristics of patients admitted to CCUs and thus in taking precautions to decrease CCU admissions.

Severity of Respiratory Syncytial Virus vs COVID-19 and Influenza Among Hospitalized US Adults.

Importance: On June 21, 2023, the Centers for Disease Control and Prevention recommended the first respiratory syncytial virus (RSV) vaccines for adults aged 60 years and older using shared clinical decision-making. Understanding the severity of RSV disease in adults can help guide this clinical decision-making. Objective: To describe disease severity among adults hospitalized with RSV and compare it with the severity of COVID-19 and influenza disease by vaccination status. Design, Setting, and Participants: In this cohort study, adults aged 18 years and older admitted to the hospital with acute respiratory illness and laboratory-confirmed RSV, SARS-CoV-2, or influenza infection were prospectively enrolled from 25 hospitals in 20 US states from February 1, 2022, to May 31, 2023. Clinical data during each patient's hospitalization were collected using standardized forms. Data were analyzed from August to October 2023. Exposures: RSV, SARS-CoV-2, or influenza infection. Main Outcomes and Measures: Using multivariable logistic regression, severity of RSV disease was compared with COVID-19 and influenza severity, by COVID-19 and influenza vaccination status, for a range of clinical outcomes, including the composite of invasive mechanical ventilation (IMV) and in-hospital death. Results: Of 7998 adults (median [IQR] age, 67 [54-78] years; 4047 [50.6%] female) included, 484 (6.1%) were hospitalized with RSV, 6422 (80.3%) were hospitalized with COVID-19, and 1092 (13.7%) were hospitalized with influenza. Among patients with RSV, 58 (12.0%) experienced IMV or death, compared with 201 of 1422 unvaccinated patients with COVID-19 (14.1%) and 458 of 5000 vaccinated patients with COVID-19 (9.2%), as well as 72 of 699 unvaccinated patients with influenza (10.3%) and 20 of 393 vaccinated patients with influenza (5.1%). In adjusted analyses, the odds of IMV or in-hospital death were not significantly different among patients hospitalized with RSV and unvaccinated patients hospitalized with COVID-19 (adjusted odds ratio [aOR], 0.82; 95% CI, 0.59-1.13; P = .22) or influenza (aOR, 1.20; 95% CI, 0.82-1.76; P = .35); however, the odds of IMV or death were significantly higher among patients hospitalized with RSV compared with vaccinated patients hospitalized with COVID-19 (aOR, 1.38; 95% CI, 1.02-1.86; P = .03) or influenza disease (aOR, 2.81; 95% CI, 1.62-4.86; P < .001). Conclusions and Relevance: Among adults hospitalized in this US cohort during the 16 months before the first RSV vaccine recommendations, RSV disease was less common but similar in severity compared with COVID-19 or influenza disease among unvaccinated patients and more severe than COVID-19 or influenza disease among vaccinated patients for the most serious outcomes of IMV or death.

Sedation versus general anesthesia on all-cause mortality in patients undergoing percutaneous procedures: a systematic review and meta-analysis.

BACKGROUND: The comparison between sedation and general anesthesia (GA) in terms of all-cause mortality remains a subject of ongoing debate. The primary objective of our study was to investigate the impact of GA and sedation on all-cause mortality in order to provide clarity on this controversial topic. METHODS: A systematic review and meta-analysis were conducted, incorporating cohort studies and RCTs about postoperative all-cause mortality. Comprehensive searches were performed in the PubMed, EMBASE, and Cochrane Library databases, with the search period extending until February 28, 2023. Two independent reviewers extracted the relevant information, including the number of deaths, survivals, and risk effect values at various time points following surgery, and these data were subsequently pooled and analyzed using a random effects model. RESULTS: A total of 58 studies were included in the analysis, with a majority focusing on endovascular surgery. The findings of our analysis indicated that, overall, and in most subgroup analyses, sedation exhibited superiority over GA in terms of in-hospital and 30-day mortality. However, no significant difference was observed in subgroup analyses specific to cerebrovascular surgery. About 90-day mortality, the majority of studies centered around cerebrovascular surgery. Although the overall pooled results showed a difference between sedation and GA, no distinction was observed between the pooled ORs and the subgroup analyses based on RCTs and matched cohort studies. For one-year all-cause mortality, all included studies focused on cardiac and macrovascular surgery. No difference was found between the HRs and the results derived from RCTs and matched cohort studies. CONCLUSIONS: The results suggested a potential superiority of sedation over GA, particularly in the context of cardiac and macrovascular surgery, mitigating the risk of in-hospital and 30-day death. However, for the longer postoperative periods, this difference remains uncertain. TRIAL REGISTRATION: PROSPERO CRD42023399151; registered 24 February 2023.

The Association between Anemia and Mortality of Severe Pneumonia COVID-19 Patients in the High Care Unit of a Tertiary Hospital in Jakarta.

BACKGROUND: Numerous studies explored the association between anemia and mortality in patients with severe pneumonia due to COVID-19. However, the findings were inconsistent. Therefore, this study was conducted to investigate the association between anemia at HCU admission and in-hospital mortality in severe pneumonia COVID-19 patients. METHODS: This retrospective cohort study obtained data on 110 COVID-19 patients with severe pneumonia who were admitted to the HCU between January, 1st 2021, and May 31st, 2021. Patients were categorized as anemic and non-anemic based on the World Health Organization (WHO) guidelines. The demographic and clinical characteristics of the subjects were described. The Chi-squared test was carried out followed by a logistic regression test to determine the association of anemia and mortality. RESULTS: Anemia was observed in 31% of 110 patients with severe pneumonia COVID-19. The source population consisted of 60.9% men and 39.1% women with a median age of 58 years. The most prevalent comorbidity was hypertension (38.2%), followed by diabetes mellitus (27.2%), renal diseases (19.1%) and heart diseases (10%). TAnemia on HCU admission was associated with in-hospital mortality in patients with severe pneumonia COVID-19 (RR: 2.794, 95% CI 1.470-5.312). After adjusting comorbidities as confounding factors, anemia was independently associated with mortality (RR: 2.204, 95% CI: 1.124-4.323, P < 0.021). The result also showed anemic patients had longer lengths of stay and higher levels of D-dimer than non-anemic patients. The median duration length of stay among the anemic and non-anemic was 16 (11-22) and 13 (9-17) days, respectively. The median D-dimer among the anemic and non-anemic was 2220 µg/ml and 1010 µg/ml, respectively. CONCLUSION: There is a significant association between anemia at HCU admission and mortality in patients with severe pneumonia COVID-19 during hospitalization.

Outcome of right ventricular microaxial pump support in patients undergoing cardiac surgery.

Right ventricular failure (RVF) after cardiac surgery is associated with an in-hospital mortality rate of up to 75%. Microaxial flow pumps are one of the mechanical circulatory supports (MCS) options available for the treatment of RVF, however the specifics of timing and indication for MCS, as well as predictors for survival, remain unclear due to a dearth of published data. We evaluated the clinical outcome of patients treated with Impella-RP for predictors of mortality and the hemodynamic effects of the pump. This is a single-center retrospective observational study involving adult patients who underwent cardiac surgery with cardiopulmonary bypass between January 2019 and December 2020 in cardiac surgery and required therapeutic management of RVF with an Impella-RP. Overall, 18 patients were included and analyzed for factors that could be associated with mortality, or that could be predictors of patient outcomes for this population. Treatment of RVF with Impella-RP improved the patient hemodynamics significantly and had a survival rate of 61% within 30 days. Patients with isolated CABG or better liver function before implantation had a better survival rate, which may indicate that underlying disease and timing of implantation are significant for successful treatment of RVF.

Positive association between sodium-to-chloride ratio and in-hospital mortality of acute heart failure.

Previous studies have suggested that levels of sodium and chloride in the blood may be indicative of the prognosis of different medical conditions. Nevertheless, the assessment of the prognostic significance of the sodium-to-chloride (Na/Cl) ratio in relation to in-hospital mortality among individuals suffering from acute heart failure (AHF) remains unexplored. In this study, the participants were selected from the Medical Information Mart for Intensive Care IV database and divided into three groups based on the Na/Cl ratio level upon admission. The primary results were the mortality rate within the hospital. Cox regression, Kaplan-Meier curves, receiver operator characteristic (ROC) curve analysis and subgroup analyses were utilized to investigate the correlation between the admission Na/Cl ratio and outcomes in critically ill patients with AHF. A total of 7844 patients who met the selection criteria were included in this study. After adjusting for confounders, the multivariable Cox regression analysis revealed that the baseline Na/Cl ratio significantly elevated the risk of in-hospital mortality among critically ill patients with AHF (HR = 1.34, 95% CI 1.21-1.49). Furthermore, when the Na/Cl ratio was converted into a categorical factor and the initial tertile was taken as a point of comparison, the hazard ratios (HRs) and 95% confidence intervals (CIs) for the second and third tertiles were 1.27 (1.05-1.54) and 1.53 (1.27-1.84), respectively. Additionally, a P value indicating a significant trend of < 0.001 was observed. ROC curve analysis showed that Na/Cl ratio had a more sensitive prognostic value in predicting in-hospital mortality of AHF than the sodium or chloride level alone (0.564 vs. 0.505, 0.544). Subgroup examinations indicated that the association between the Na/Cl ratio upon admission and the mortality rate of critically ill patients with AHF remained consistent in the subgroups of hyponatremia and hypochlorhydria (P for interaction > 0.05). The linear relationship between the Na/Cl ratio and in-hospital mortality in AHF patients indicates a positive association.

Improving predictions: Enhancing in-hospital mortality forecast for ICU patients with sepsis-induced coagulopathy using a stacking ensemble model.

The incidence of sepsis-induced coagulopathy (SIC) is high, leading to increased mortality rates and prolonged hospitalization and intensive care unit (ICU) stays. Early identification of SIC patients at risk of in-hospital mortality can improve patient prognosis. The objective of this study is to develop and validate machine learning (ML) models to dynamically predict in-hospital mortality risk in SIC patients. A ML model is established based on the Medical Information Mart for Intensive Care IV (MIMIC-IV) database to predict in-hospital mortality in SIC patients. Utilizing univariate feature selection for feature screening. The optimal model was determined by calculating the area under the curve (AUC) with a 95% confidence interval (CI). The optimal model was interpreted using Shapley Additive Explanation (SHAP) values. Among the 3112 SIC patients included in MIMIC-IV, a total of 757 (25%) patients experienced mortality during their ICU stay. Univariate feature selection helps us to pick out the 20 most critical variables from the original feature. Among the 10 developed machine learning models, the stacking ensemble model exhibited the highest AUC (0.795, 95% CI: 0.763-0.827). Anion gap and age emerged as the most significant features for predicting the mortality risk in SIC. In this study, an ML model was constructed that exhibited excellent performance in predicting in-hospital mortality risk in SIC patients. Specifically, the stacking ensemble model demonstrated superior predictive ability.

Changes in diagnostic patterns and resource utilisation in Swiss adult ICUs during the first two COVID-19 waves: an exploratory study.

BACKGROUND AND AIM: The coronavirus disease 2019 (COVID-19) outbreak deeply affected intensive care units (ICUs). We aimed to explore the main changes in the distribution and characteristics of Swiss ICU patients during the first two COVID-19 waves and to relate these figures with those of the preceding two years. METHODS: Using the national ICU registry, we conducted an exploratory study to assess the number of ICU admissions in Switzerland and their changes over time, characteristics of the admissions, the length of stay (LOS) and its trend over time, ICU mortality and changes in therapeutic nursing workload and hospital resources in 2020 and compare them with the average figures in 2018 and 2019. RESULTS: After analysing 242,935 patient records from all 84 certified Swiss ICUs, we found a significant decrease in admissions (-9.6%, corresponding to -8005 patients) in 2020 compared to 2018/2019, with an increase in the proportion of men admitted (61.3% vs 59.6%; p <0.001). This reduction occurred in all Swiss regions except Ticino. Planned admissions decreased from 25,020 to 22,021 in 2020 and mainly affected the neurological/neurosurgical (-14.9%), gastrointestinal (-13.9%) and cardiovascular (-9.3%) pathologies. Unplanned admissions due to respiratory diagnoses increased by 1971 (+25.2%), and those of patients with acute respiratory distress syndrome (ARDS) requiring isolation reached 9973 (+109.9%). The LOS increased by 20.8% from 2.55 ± 4.92 days (median 1.05) in 2018/2019 to 3.08 ± 5.87 days (median 1.11 days; p <0.001), resulting in an additional 19,753 inpatient days. The nine equivalents of nursing manpower use score (NEMS) of the first nursing shift (21.6 ± 9.0 vs 20.8 ± 9.4; p <0.001), the total NEMS per patient (251.0 ± 526.8 vs 198.9 ± 413.8; p <0.01) and mortality (5.7% vs 4.7%; p <0.001) increased in 2020. The number of ICU beds increased from 979 to 1012 (+3.4%), as did the number of beds equipped with mechanical ventilators (from 773 to 821; +6.2%). CONCLUSIONS: Based on a comprehensive national data set, our report describes the profound changes triggered by COVID-19 over one year in Swiss ICUs. We observed an overall decrease in admissions and a shift in admission types, with fewer planned hospitalisations, suggesting the loss of approximately 3000 elective interventions. We found a substantial increase in unplanned admissions due to respiratory diagnoses, a doubling of ARDS cases requiring isolation, an increase in ICU LOS associated with substantial nationwide growth in ICU days, an augmented need for life-sustaining therapies and specific therapeutic resources and worse outcomes.

Comparison of nine trauma scoring systems in prediction of inhospital outcomes of pediatric trauma patients: a multicenter study.

Hereby, we aimed to comprehensively compare different scoring systems for pediatric trauma and their ability to predict in-hospital mortality and intensive care unit (ICU) admission. The current registry-based multicenter study encompassed a comprehensive dataset of 6709 pediatric trauma patients aged ≤ 18 years from July 2016 to September 2023. To ascertain the predictive efficacy of the scoring systems, the area under the receiver operating characteristic curve (AUC) was calculated. A total of 720 individuals (10.7%) required admission to the ICU. The mortality rate was 1.1% (n = 72). The most predictive scoring system for in-hospital mortality was the adjusted trauma and injury severity score (aTRISS) (AUC = 0.982), followed by trauma and injury severity score (TRISS) (AUC = 0.980), new trauma and injury severity score (NTRISS) (AUC = 0.972), Glasgow coma scale (GCS) (AUC = 0.9546), revised trauma score (RTS) (AUC = 0.944), pre-hospital index (PHI) (AUC = 0.936), injury severity score (ISS) (AUC = 0.901), new injury severity score (NISS) (AUC = 0.900), and abbreviated injury scale (AIS) (AUC = 0.734). Given the predictive performance of the scoring systems for ICU admission, NTRISS had the highest predictive performance (AUC = 0.837), followed by aTRISS (AUC = 0.836), TRISS (AUC = 0.823), ISS (AUC = 0.807), NISS (AUC = 0.805), GCS (AUC = 0.735), RTS (AUC = 0.698), PHI (AUC = 0.662), and AIS (AUC = 0.651). In the present study, we concluded the superiority of the TRISS and its two derived counterparts, aTRISS and NTRISS, compared to other scoring systems, to efficiently discerning individuals who possess a heightened susceptibility to unfavorable consequences. The significance of these findings underscores the necessity of incorporating these metrics into the realm of clinical practice.

Influence of diabetes and other risk factors on in-hospital mortality following kidney transplantation: an analysis of the Spanish National Hospital Discharge Database from 2016 to 2020.

INTRODUCTION: To assess time trends in incidence, clinical characteristics, complications, and hospital outcomes among patients with type 1 diabetes (T1D), with type 2 diabetes (T2D), and patients without diabetes who underwent kidney transplant (KT); to identify variables associated with in-hospital mortality (IHM); and to determine the impact of the COVID-19 pandemic. RESEARCH DESIGN AND METHODS: We used a nationwide discharge database to select KT recipients admitted to Spanish hospitals from 2016 to 2020. We stratified patients according to diabetes status. We used multivariable logistic regression to identify the variables associated with IHM. RESULTS: A total of 14 594 KTs were performed in Spain (T2D, 22.28%; T1D, 3.72%). The number of KTs rose between 2016 and 2019 and and decreased from 2019 to 2020 in all groups. In patients with T2D, the frequency of KT complications increased from 21.08% in 2016 to 34.17% in 2020 (p<0.001). Patients with T2D had significantly more comorbidity than patients with T1D and patients without diabetes (p<0.001). Patients with T1D experienced KT rejection significantly more frequently (8.09%) than patients with T2D (5.57%).COVID-19 was recorded in 26 out of the 2444 KTs performed in 2020, being found in 6 of the 39 patients deceased that year (15.38%) and in 0.83% of the survivors.The variables associated with IHM were comorbidity and complications of KT. The presence of T1D was associated with IHM (OR 2.6; 95% CI 1.36 to 5.16) when patients without diabetes were the reference category. However, T2D was not associated with a higher IHM (OR 0.86; 95% CI 0.61 to 1.2). CONCLUSIONS: The COVID-19 pandemic led to a decrease in the number of transplants. Patients with T1D have more rejection of the transplanted organ than patients with T2D. Fewer women with T2D undergo KT. The presence of T1D is a risk factor for IHM.

Prior pneumococcal vaccination improves in-hospital mortality among elderly population hospitalized due to community-acquired pneumonia.

BACKGROUND: Pneumococcal vaccination is a preventive method to reduce pneumonia related mortality. However, real-world data on efficacy of the pneumococcal vaccine in reducing mortality is lacking, especially in elderly patients. This study was conducted to assess the effects of prior pneumococcal vaccination in elderly pneumonia patients. METHODS: The data was procured from the Health Insurance Review and Assessment and Quality Assessment database. Hospitalized patients who met the criteria of community-acquired pneumonia (CAP) were included and they were grouped according to vaccination state. Patients were aged ≥ 65 years and treated with beta-lactam, quinolone, or macrolide. Patients were excluded when treatment outcomes were unknown. RESULTS: A total of 4515 patients were evaluated, and 1609 (35.6%) of them were vaccinated prior to hospitalization. Mean age was 77.0 [71.0;82.0], 54.2% of them were male, and mean Charlson comorbidity index (CCI) was 3.0. The patients in the vaccinated group were younger than those in the unvaccinated group (76.0 vs. 78.0 years; P < 0.001), and showed higher in-hospital improvement (97.6 vs. 95.0%; P < 0.001) and lower 30-day mortality (2.6 vs. 5.3%; P < 0.001). After adjusting confounding factors such as age, gender, CURB score and CCI score, the vaccinated group demonstrated a significant reduction in 30-day mortality (hazard ratio [HR] 0.58, 95% confidence interval [CI] 0.41-0.81; P < 0.01) and in-hospital mortality (HR 0.53, 95% CI0.37-0.78; P < 0.001) compared to the unvaccinated group in multivariate analysis. Vaccinated group showed better 30-day survival than those in non-vaccinated group (log-rank test < 0.05). CONCLUSIONS: Among elderly hospitalized CAP patients, prior pneumococcal vaccination was associated with improved in-hospital mortality and 30-day mortality.

Value of modified qSOFA, glucose and lactate in predicting prognosis in children with sepsis in the PICU.

The purpose was to investigate how well age-adjusted modified quick Sequential Organ Failure Assessment (qSOFA) scores paired with blood glucose and lactate levels predict the outcomes of septicemic children in the pediatric intensive care unit (PICU). One hundred children who were diagnosed with sepsis and septic shock in the PICU of Henan Children's Hospital were eligible, and other 20 patients in the same hospital at different times were selected as a validation set. Respiratory rate (RR), heart rate (HR), capillary refill time (CRT), and Alert, Voice, Pain, Unresponsive (AVPU) scale were included in the age-adjusted modified qSOFA scoring criteria for scoring. The primary outcome was 28-day all-cause mortality. The predictive values were evaluated by the ROC curve. In the sepsis group, 50 patients were male, and 50 patients were female. The 28-day all-cause mortality rate was 52%. Fifty-one patients with age-adjusted modified qSOFA scores >1. The serum lactate level was 2.4 mmol/L, and the blood glucose level was 9.3 mmol/L. The AUCs for the age-adjusted modified qSOFA score, serum lactate and blood glucose levels for the prediction of 28-day all-cause mortality in children with sepsis were 0.719, 0.719 and 0.737, respectively. The cut-off values were one point, 3.8 mmol/L and 10 mmol/L, respectively. The AUC of the age-adjusted modified qSOFA score for the validation set of was 0.925. When the three indices were combined, the AUC was 0.817, the Hosmer-Lemeshow goodness-of-fit test showed χ2 = 2.428 and p = .965. When children with sepsis are admitted to the ICU, we recommend performing rapid scoring and rapid bedside lactate and glucose testing to determine the early prognosis.

Impact of center volume on in-hospital mortality in adult patients with out­of­hospital cardiac arrest resuscitated using extracorporeal cardiopulmonary resuscitation: a secondary analysis of the SAVE-J II study.

Recently, patients with out-of-hospital cardiac arrest (OHCA) refractory to conventional resuscitation have started undergoing extracorporeal cardiopulmonary resuscitation (ECPR). However, the mortality rate of these patients remains high. This study aimed to clarify whether a center ECPR volume was associated with the survival rates of adult patients with OHCA resuscitated using ECPR. This was a secondary analysis of a retrospective multicenter registry study, the SAVE-J II study, involving 36 participating institutions in Japan. Centers were divided into three groups according to the tertiles of the annual average number of patients undergoing ECPR: high-volume (≥ 21 sessions per year), medium-volume (11-20 sessions per year), or low-volume (< 11 sessions per year). The primary outcome was survival rate at the time of discharge. Patient characteristics and outcomes were compared among the three groups. Moreover, a multivariable-adjusted logistic regression model was applied to study the impact of center ECPR volume. A total of 1740 patients were included in this study. The center ECPR volume was strongly associated with survival rate at the time of discharge; furthermore, survival rate was best in high-volume compared with medium- and low-volume centers (33.4%, 24.1%, and 26.8%, respectively; P = 0.001). After adjusting for patient characteristics, undergoing ECPR at high-volume centers was associated with an increased likelihood of survival compared to middle- (adjusted odds ratio 0.657; P = 0.003) and low-volume centers (adjusted odds ratio 0.983; P = 0.006). The annual number of ECPR sessions was associated with favorable survival rates and lower complication rates of the ECPR procedure.Clinical trial registration: https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000041577 (unique identifier: UMIN000036490).

A study of hospitalized COVID-19 patients with AKI in a setting of multiracial developing country.

BACKGROUND: The commonest indication for hospitalization in COVID-19 patients is hypoxemia or severe respiratory symptoms. However, COVID-19 disease may result in extrapulmonary complications including kidney-related pathology. The reported incidence of renal involvement related to COVID infection varies based on geographical location. OBJECTIVE: This study aimed to assess the incidence rate of AKI in hospitalized COVID-19 patients and identify risk factors and prognostic predictors. METHOD: In this retrospective study, we recruited hospitalized COVID-19 patients from January 2021 until June 2021 at the University Malaya Medical Center. The inclusion criteria were hospitalized for ≥ 48 h with confirmed COVID-19 infection and at least 18 years old. Patient demographic and clinical data were collected from electronic medical records. The staging of AKI was based on criteria as per KDIGO guidelines. RESULTS: One thousand five hundred twenty-nine COVID patients fulfilled the inclusion criteria with a male-to-female ratio of 759 (49.6%) to 770 (50.3%). The median age was 55 (IQR: 36-66). 500 patients (32.7%) had diabetes, 621 (40.6%) had hypertension, and 5.6% (n = 85) had pre-existing chronic kidney disease (CKD). The incidence rate of AKI was 21.1% (n = 323). The percentage of COVID patients in different AKI stages of 1,2 and 3 were 16.3%, 2.1%, and 2.7%, respectively. Fifteen hospitalized patients (0.98%) required renal replacement therapy. 58.8% (n = 190) of AKI group had complete recovery of kidney function. Demographic factors included age (p < 0.001), diabetes (p < 0.001), hypertension (p < 0.012), CKD (p < 0.001), and vaccination status (p = 0.042) were associated with an increased risk of developing AKI. We found that the AKI cohort had statistically significant lower platelet counts and higher ferritin levels than the non-AKI cohort. AKI is a risk predictor of prolonged hospitalization (p < 0.001) and higher mortality rates (P < 0.001). CONCLUSION: AKI is a common clinical complication among hospitalized COVID-19 patients. The etiology of AKI is multifactorial and may have an adverse impact on patient morbidity and mortality.

A new nomogram to predict in-hospital mortality in patients with acute decompensated chronic heart failure and diabetes after 48 Hours of Intensive Care Unit.

BACKGROUND: The study set out to develop an accurate and clinically valuable prognostic nomogram to assess the risk of in-hospital death in patients with acute decompensated chronic heart failure (ADCHF) and diabetes. METHODS: We extracted clinical data of patients diagnosed with ADCHF and diabetes from the Medical Information Mart for Intensive Care III database. Risk variables were selected utilizing least absolute shrinkage and selection operator regression analysis, and were included in multivariate logistic regression and presented in nomogram. bootstrap was used for internal validation. The discriminative power and predictive accuracy of the nomogram were estimated using the area under the receiver operating characteristic curve (AUC), calibration curve and decision curve analysis (DCA). RESULTS: Among 867 patients with ADCHF and diabetes, In-hospital death occurred in 81 (9.3%) patients. Age, heart rate, systolic blood pressure, red blood cell distribution width, shock, ß-blockers, angiotensin converting enzyme inhibitors or angiotensin receptor blockers, assisted ventilation, and blood urea nitrogen were brought into the nomogram model. The calibration curves suggested that the nomogram was well calibrated. The AUC of the nomogram was 0.873 (95% CI: 0.834-0.911), which was higher that of the Simplified Acute Physiology Score II [0.761 (95% CI: 0.711-0.810)] and sequential organ failure assessment score [0.699 (95% CI: 0.642-0.756)], and Guidelines-Heart Failure score [0.782 (95% CI: 0.731-0.835)], indicating that the nomogram had better ability to predict in-hospital mortality. In addition, the internally validated C-index was 0.857 (95% CI: 0.825-0.891), which again verified the validity of this model. CONCLUSIONS: This study constructed a simple and accurate nomogram for predicting in-hospital mortality in patients with ADCHF and diabetes, especially in those who admitted to the intensive care unit for more than 48 hours, which contributed clinicians to assess the risk and individualize the treatment of patients, thereby reducing in-hospital mortality.

[Construction and validation of an in-hospital mortality risk prediction model for patients receiving VA-ECMO: a retrospective multi-center case-control study].

OBJECTIVE: To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation (VA-ECMO). METHODS: We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January, 2015 and January, 2022 using a convenience sampling method. The patients were divided into a derivation cohort (201 cases) and a validation cohort (101 cases). Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients, based on which a risk prediction model was established in the form of a nomogram. The receiver operator characteristic (ROC) curve, calibration curve and clinical decision curve were used to evaluate the discrimination ability, calibration and clinical validity of this model. RESULTS: The in-hospital mortality risk prediction model was established based the risk factors including hypertension (OR=3.694, 95% CI: 1.582-8.621), continuous renal replacement therapy (OR=9.661, 95%CI: 4.103-22.745), elevated Na2 + level (OR=1.048, 95% CI: 1.003-1.095) and increased hemoglobin level (OR=0.987, 95% CI: 0.977-0.998). In the derivation cohort, the area under the ROC curve (AUC) of this model was 0.829 (95% CI: 0.770-0.889), greater than those of the 4 single factors (all AUC < 0.800), APACHE II Score (AUC=0.777, 95% CI: 0.714-0.840) and the SOFA Score (AUC=0.721, 95% CI: 0.647-0.796). The results of internal validation showed that the AUC of the model was 0.774 (95% CI: 0.679-0.869), and the goodness of fit test showed a good fitting of this model (χ2=4.629, P>0.05). CONCLUSION: The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation, calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system, and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.

The combination of kidney function variables with cell cycle arrest biomarkers identifies distinct subphenotypes of sepsis-associated acute kidney injury: a post-hoc analysis (the PHENAKI study).

BACKGROUND: The severity and course of sepsis-associated acute kidney injury (SA-AKI) are correlated with the mortality rate. Early detection of SA-AKI subphenotypes might facilitate the rapid provision of individualized care. PATIENTS AND METHODS: In this post-hoc analysis of a multicenter prospective study, we combined conventional kidney function variables with serial measurements of urine (tissue inhibitor of metalloproteinase-2 [TIMP-2])* (insulin-like growth factor-binding protein [IGFBP7]) at 0, 6, 12, and 24 h) and then using an unsupervised hierarchical clustering of principal components (HCPC) approach to identify different phenotypes of SA-AKI. We then compared the subphenotypes with regard to a composite outcome of in-hospital death or the initiation of renal replacement therapy (RRT). RESULTS: We included 184 patients presenting SA-AKI within 6 h of the initiation of catecholamines. Three distinct subphenotypes were identified: subphenotype A (99 patients) was characterized by a normal urine output (UO), a low SCr and a low [TIMP-2]*[IGFBP7] level; subphenotype B (74 patients) was characterized by existing chronic kidney disease (CKD), a higher SCr, a low UO, and an intermediate [TIMP-2]*[IGFBP7] level; and subphenotype C was characterized by very low UO, a very high [TIMP-2]*[IGFBP7] level, and an intermediate SCr level. With subphenotype A as the reference, the adjusted hazard ratio (aHR) [95%CI] for the composite outcome was 3.77 [1.92-7.42] (p < 0.001) for subphenotype B and 4.80 [1.67-13.82] (p = 0.004) for subphenotype C. CONCLUSIONS: Combining conventional kidney function variables with urine measurements of [TIMP-2]*[IGFBP7] might help to identify distinct SA-AKI subphenotypes with different short-term courses and survival rates.