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BackgroundMaternal sepsis and other maternal infections (MSMIs) are major public health concerns worldwide. However, comprehensive data on their global burden and evolving trends remain sparse. This study aims to explore the epidemiological trends of MSMIs in women of childbearing age (WCBA) from 1990 to 2019, investigate the relationship between disease burden and age, period, and birth cohorts, and then provide a prediction of MSMIs incidence and deaths.MethodsThe estimates and 95% uncertainty intervals (UIs) for the incidence and death number of MSMIs in seven age groups (15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49 years) were obtained from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. The age-standardized incidence and mortality rates of MSMIs in WCBA were estimated utilizing the age standardization by direct method. Joinpoint regression analysis was employed to investigate the changing trends of age-standardized incidence and mortality rates from 1990 to 2019. Age-period-cohort analysis was utilized to estimate the independent effects of age, period, and birth cohorts. Furthermore, a Nordpred age-period-cohort analysis was implemented to predict the global epidemiological trends through 2044.ResultsIn 2019, the estimated global age-standardized incidence and mortality rates of MSMIs in WCBA were 1072.90 (95% UI: 725.93 to 1483.46) and 0.86 (95% UI: 0.69 to 1.05), respectively. The highest disease burden existed in the African Region. From 1990 to 2019, the estimated global age-standardized incidence and mortality rates of MSMIs (AAPC: -1.32, 95% CI: −1.34 to −1.30; AAPC: -3.39, 95% CI: −4.28 to −2.48) in WCBA both demonstrated significant declining trends. The changing trends varied significantly across 6 regions and 204 countries. The effects of age, period, and cohort on incidence and mortality rates differed. From 2020 to 2044, the global age-standardized incidence rate of MSMIs in WCBA was predicted to decrease whereas the case number increases slowly.ConclusionThe global trends in MSMIs incidence and mortality generally showed a decline with considerable heterogeneity, indicating both the effectiveness and unevenness of global management of MSMIs. Moreover, the predicted increased case number highlights prominent challenges in the control of MSMIs.

The Chinese Society of Critical Care Medicine (CSCCM) has developed clinical practice guidelines for nutrition assessment and monitoring for patients in adult intensive care units (ICUs) in China. This guideline focuses on nutrition evaluation and metabolic monitoring to achieve optimal and personalized nutrition therapy for critically ill patients. This guideline was developed by experts in critical care medicine and evidence-based medicine methodology and was developed after a thorough review of the system and a summary of relevant trials or studies published from 2000 to July 2023. A total of 18 recommendations were formed and consensus was reached through discussions and reviews by expert groups in critical care medicine, parenteral and enteral nutrition, and surgery. The recommendations are based on currently available evidence and cover several key fields, including screening and assessment, evaluation and assessment of enteral feeding intolerance, metabolic and nutritional measurement and monitoring during nutrition therapy, and organ function evaluation related to nutrition supply. Each question was analyzed according to the Population, Intervention, Comparison, and Outcome (PICO) principle. In addition, interpretations were provided for four questions that did not reach a consensus but may have potential clinical and research value. The plan is to update this nutrition assessment and monitoring guideline using the international guideline update method within 3–5 years.

Background: Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, prone positioning has been widely applied for non-intubated, spontaneously breathing patients. However, the efficacy and safety of prone positioning in non-intubated patients with COVID-19-related acute hypoxemic respiratory failure remain unclear. We aimed to systematically analyze the outcomes associated with awake prone positioning (APP). Methods: We conducted a systematic literature search of PubMed/MEDLINE, Cochrane Library, Embase, and Web of Science from January 1, 2020, to June 3, 2022. This study included adult patients with acute respiratory failure caused by COVID-19. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and the study quality was assessed using the Cochrane risk-of-bias tool. The primary outcome was the reported cumulative intubation risk across randomized controlled trials (RCTs), and the effect estimates were calculated as risk ratios (RRs; 95% confidence interval [CI]). Results: A total of 495 studies were identified, of which 10 fulfilled the selection criteria, and 2294 patients were included. In comparison to supine positioning, APP significantly reduced the need for intubation in the overall population (RR=0.84, 95% CI: 0.74–0.95). The two groups showed no significant differences in the incidence of adverse events (RR=1.16, 95% CI: 0.48–2.76). The meta-analysis revealed no difference in mortality between the groups (RR=0.93, 95% CI: 0.77–1.11). Conclusions: APP was safe and reduced the need for intubation in patients with respiratory failure associated with COVID-19. However, it did not significantly reduce mortality in comparison to usual care without prone positioning.

Abstract Background A training program for intensive care unit (ICU) physicians entitled “Chinese Critical Care Certified Course” (5 C) started in China in 2009, intending to improve the quality of intensive care provision. This study aimed to explore the associations between the 5 C certification of physicians and the quality of intensive care provision in China. Methods This nationwide analysis collected data regarding 5 C-certified physicians between 2009 and 2019. Fifteen ICU quality control indicators (three structural, four procedural, and eight outcome-based) were collected from the Chinese National Report on the Services, Quality, and Safety in Medical Care System. Provinces were stratified into three groups based on the cumulative number of 5 C certified physicians per million population. Results A total of 20,985 (80.41%) physicians from 3,425 public hospitals in 30 Chinese provinces were 5 C certified. The deep vein thrombosis (DVT) prophylaxis rate in the high 5 C physician-number provinces was significantly higher than in the intermediate 5 C physician-number provinces (67.6% vs. 55.1%, p = 0.043), while ventilator-associated pneumonia (VAP) rate in the low 5 C physician-number provinces was significantly higher than in the high 5 C physician-number provinces (14.9% vs. 8.9%, p = 0.031). Conclusions The higher number of 5 C-certified physicians per million population seemed to be associated with higher DVT prophylaxis rates and lower VAP rates in China, suggesting that the 5 C program might have a beneficial impact on the quality of intensive care provision.

The dissemination of carbapenem-resistant Gram-negative bacilli (CRGNB) is a global public health issue. CRGNB isolates are usually extensively drug-resistant or pandrug-resistant, resulting in limited antimicrobial treatment options and high mortality. A multidisciplinary guideline development group covering clinical infectious diseases, clinical microbiology, clinical pharmacology, infection control, and guideline methodology experts jointly developed the present clinical practice guidelines based on best available scientific evidence to address the clinical issues regarding laboratory testing, antimicrobial therapy, and prevention of CRGNB infections. This guideline focuses on carbapenem-resistant Enterobacteriales (CRE), carbapenem-resistant Acinetobacter baumannii (CRAB), and carbapenem-resistant Pseudomonas aeruginosa (CRPA). Sixteen clinical questions were proposed from the perspective of current clinical practice and translated into research questions using PICO (population, intervention, comparator, and outcomes) format to collect and synthesize relevant evidence to inform corresponding recommendations. The grading of recommendations, assessment, development and evaluation (GRADE) approach was used to evaluate the quality of evidence, benefit and risk profile of corresponding interventions and formulate recommendations or suggestions. Evidence extracted from systematic reviews and randomized controlled trials (RCTs) was considered preferentially for treatment-related clinical questions. Observational studies, non-controlled studies, and expert opinions were considered as supplementary evidence in the absence of RCTs. The strength of recommendations was classified as strong or conditional (weak). The evidence informing recommendations derives from studies worldwide, while the implementation suggestions combined the Chinese experience. The target audience of this guideline is clinician and related professionals involved in management of infectious diseases.

The Ann Arbor system is disadvantaged in utilizing information from additional prognostic factors. In this study, we applied the Ensemble Algorithm for Clustering Cancer Data (EACCD) to create a prognostic system for lymphoma that integrates additional prognostic factors. Hodgkin and non-Hodgkin lymphoma survival data were extracted from the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute and divided into the training set (131,725 cases) and the validation set (15,683 cases). Five prognostic factors were studied: Ann Arbor stage, type, site, age, and sex. EACCD was applied to the training set to produce a prognostic system, called an EACCD system, for convenience. The EACCD system stratified patients into eight prognostic groups with well-separated survival curves. These eight prognostic groups had significantly higher accuracies in survival prediction than the 24 Ann Arbor substages. A higher-risk group in the EACCD system roughly corresponds to a higher Ann Arbor substage. The proposed system shows a good performance in risk stratification and survival prediction on both the training and the validation sets. The EACCD system expands the traditional Ann Arbor staging system by leveraging additional prognostic information and is expected to advance treatment management for lymphoma patients.

BackgroundIt is unclear what the causal relationship is between the gut microbiota and sepsis. Therefore, we employed Mendelian randomization (MR) to determine whether a causal link exists between the two.MethodsThis study used publicly available genome-wide association studies (GWAS) summary data of gut microbiota, sepsis, sepsis (critical care), and sepsis (28-day death in critical care) to perform a two-sample MR analysis. To ensure the robustness of the results, we also conducted a sensitivity analysis.ResultsFor sepsis susceptibility, inverse variance weighted (IVW) estimates revealed that Victivallales (OR = 0.86, 95% CI, 0.78–0.94, p = 0.0017) was protective against sepsis, while Lentisphaerae (OR = 0.89, 95% CI, 0.80–0.99), Gammaproteobacteria (OR = 1.37, 95% CI, 1.08–1.73), Clostridiaceae1 (OR = 1.21, 95% CI, 1.04–1.40), RuminococcaceaeUCG011 (OR = 1.10, 95% CI, 1.01–1.20), Dialister (OR = 0.85, 95% CI, 0.74–0.97), and Coprococcus2 (OR = 0.81, 95% CI, 0.69–0.94) presented a suggestive association with the development of sepsis (all p < 0.05). For sepsis (critical care), IVW estimates indicated that Lentisphaerae (OR = 0.70, 95% CI, 0.53–0.93), Victivallales (OR = 0.67, 95% CI, 0.50–0.91), Anaerostipes (OR = 0.49, 95% CI, 0.31–0.76), LachnospiraceaeUCG004 (OR = 0.51, 95% CI, 0.34–0.77), and Coprococcus1 (OR = 0.66, 95% CI, 0.44–0.99) showed a suggestive negative correlation with sepsis (critical care) (all p < 0.05). For sepsis (28-day death in critical care), IVW estimates suggested that four bacterial taxa had a normally significant negative correlation with the risk of sepsis-related death, including Victivallales (OR = 0.54, 95% CI, 0.30–0.95), Coprococcus2 (OR = 0.34, 95% CI, 0.14–0.83), Ruminiclostridium6 (OR = 0.43, 95% CI, 0.22–0.83), and Coprococcus1 (OR = 0.45, 95% CI, 0.21–0.97), while two bacterial taxa were normally significantly positively linked to the risk of sepsis-related death, namely, Mollicutes (OR = 2.03, 95% CI, 1.01–4.08) and Bacteroidales (OR = 2.65, 95% CI, 1.18–5.96) (all p < 0.05). The robustness of the above correlations was verified by additional sensitivity analyses.ConclusionThis MR research found that several gut microbiota taxa were causally linked to the risk of sepsis, sepsis in critical care, and sepsis-related 28-day mortality in critical care.

Severe pneumonia (SP) is a respiratory tract disease that seriously threatens human health. The herpesvirus detected in patients, especially with severe and immunodeficient diseases, is gradually attracting the attention of clinical doctors. However, little is known about the effect of herpesvirus on the prognosis of SP patients and the pulmonary microbial community. Here, we retrospectively analyzed respiratory samples from 45 SP patients detected by metagenomic next-generation sequencing (mNGS). A total of five types of herpesviruses were detected, with Human alphaherpesvirus 1 (HHV-1) in 19 patients, Human betaherpesvirus 5 (CMV) in 7 patients, Human betaherpesvirus 7 (HHV-7) in 6 patients, Human alphaherpesvirus 2 (HHV-2) in 5 patients, and Human gammaherpesvirus 4 (EBV) in 4 patients. Further analysis showed that the mortality of the herpesvirus-positive group was significantly higher than that of the negative group. The results also showed that HHV-1 was significantly associated with the prognosis of SP patients, while the other herpesviruses did not have a significant difference in patient mortality. A comparison of the microbial community characteristics of SP patients showed a significant difference in beta-diversity between herpesvirus-positive and negative groups. Species difference analysis showed that the herpesvirus-positive group was related to more conditional pathogens, such as Pneumocystis jirovecii and Burkholderia cepacia. In summary, our results suggest that the presence of herpesvirus is associated with the mortality of SP patients. Furthermore, enrichment of conditional pathogens in the respiratory tract of herpesvirus-positive SP patients may be a potential reason for the increased mortality.

Abstract Background We aimed to develop an early warning system for real-time sepsis prediction in the ICU by machine learning methods, with tools for interpretative analysis of the predictions. In particular, we focus on the deployment of the system in a target medical center with small historical samples. Methods Light Gradient Boosting Machine (LightGBM) and multilayer perceptron (MLP) were trained on Medical Information Mart for Intensive Care (MIMIC-III) dataset and then finetuned on the private Historical Database of local Ruijin Hospital (HDRJH) using transfer learning technique. The Shapley Additive Explanations (SHAP) analysis was employed to characterize the feature importance in the prediction inference. Ultimately, the performance of the sepsis prediction system was further evaluated in the real-world study in the ICU of the target Ruijin Hospital. Results The datasets comprised 6891 patients from MIMIC-III, 453 from HDRJH, and 67 from Ruijin real-world data. The area under the receiver operating characteristic curves (AUCs) for LightGBM and MLP models derived from MIMIC-III were 0.98 − 0.98 and 0.95 − 0.96 respectively on MIMIC-III dataset, and, in comparison, 0.82 − 0.86 and 0.84 − 0.87 respectively on HDRJH, from 1 to 5 h preceding. After transfer learning and ensemble learning, the AUCs of the final ensemble model were enhanced to 0.94 − 0.94 on HDRJH and to 0.86 − 0.9 in the real-world study in the ICU of the target Ruijin Hospital. In addition, the SHAP analysis illustrated the importance of age, antibiotics, net balance, and ventilation for sepsis prediction, making the model interpretable. Conclusions Our machine learning model allows accurate real-time prediction of sepsis within 5-h preceding. Transfer learning can effectively improve the feasibility to deploy the prediction model in the target cohort, and ameliorate the model performance for external validation. SHAP analysis indicates that the role of antibiotic usage and fluid management needs further investigation. We argue that our system and methodology have the potential to improve ICU management by helping medical practitioners identify at-sepsis-risk patients and prepare for timely diagnosis and intervention. Trial registration: NCT05088850 (retrospectively registered).

Abstract. Background:. Gut-resident macrophages (gMacs) supplemented by monocytes-to-gMacs differentiation play a critical role in maintaining intestinal homeostasis. Activating transcription factor 4 (ATF4) is involved in immune cell differentiation. We therefore set out to investigate the role of ATF4-regulated monocytes-to-gMacs differentiation in sepsis-induced intestinal injury. Methods:. Sepsis was induced in C57BL/6 wild type (WT) mice and Atf4-knockdown (Atf4+/−) mice by cecal ligation and puncture or administration of lipopolysaccharide (LPS). Colon, peripheral blood mononuclear cells, sera, lung, liver, and mesenteric lymph nodes were collected for flow cytometry, hematoxylin and eosin staining, immunohistochemistry, quantitative reverse transcription polymerase chain reaction, and enzyme-linked immunosorbent assay, respectively. Results:. CD64, CD11b, Ly6C, major histocompatibility complex-II (MHC-II), CX3CR1, Ly6G, and SSC were identified as optimal primary markers for detecting the process of monocytes-to-gMacs differentiation in the colon of WT mice. Monocytes-to-gMacs differentiation was impaired in the colon during sepsis and was associated with decreased expression of ATF4 in P1 (Ly6Chi monocytes), the precursor cells of gMacs. Atf4 knockdown exacerbated the impairment of monocytes-to-gMacs differentiation in response to LPS, resulting in a significant reduction of gMacs in the colon. Furthermore, compared with WT mice, Atf4+/− mice exhibited higher pathology scores, increased expression of inflammatory factor genes (TNF-α, IL-1β), suppressed expression of CD31 and vascular endothelial-cadherin in the colon, and increased translocation of intestinal bacteria to lymph nodes and lungs following exposure to LPS. However, the aggravation of sepsis-induced intestinal injury resulting from Atf4 knockdown was not caused by the enhanced inflammatory effect of Ly6Chi monocytes and gMacs. Conclusion:. ATF4, as a novel regulator of monocytes-to-gMacs differentiation, plays a critical role in protecting mice against sepsis-induced intestinal injury, suggesting that ATF4 might be a potential therapeutic target for sepsis treatment.

Abstract Background The impact of corticosteroids on patients with severe coronavirus disease 2019 (COVID-19)/chronic hepatitis B virus (HBV) co-infection is currently unknown. We aimed to investigate the association of corticosteroids on these patients. Methods This retrospective multicenter study screened 5447 confirmed COVID-19 patients hospitalized between Jan 1, 2020 to Apr 18, 2020 in seven centers in China, where the prevalence of chronic HBV infection is moderate to high. Severe patients who had chronic HBV and acute SARS-cov-2 infection were potentially eligible. The diagnosis of chronic HBV infection was based on positive testing for hepatitis B surface antigen (HBsAg) or HBV DNA during hospitalization and a medical history of chronic HBV infection. Severe patients (meeting one of following criteria: respiratory rate > 30 breaths/min; severe respiratory distress; or SpO2 ≤ 93% on room air; or oxygen index

Abstract. Background:. Advances in organoid culture technology have provided a greater understanding of disease pathogenesis, which has been rarely studied in sepsis before. We aim to establish a suitable organoids-based intestinal injury model for sepsis. Methods:. Stable passaged organoids were constructed and pre-treated with lipopolysaccharide (LPS) to mimic sepsis-induced intestinal injury. The LPS-induced sepsis model was used as a reference. We used quantitative real-time polymerase chain reaction to evaluate the RNA levels of inflammatory factors and antimicrobial peptides. Enzyme-linked immunosorbent assay was used to evaluate the protein levels, hematoxylin and eosin staining was used to evaluate the pathology of the small intestine of mice, and immunohistochemistry and immunofluorescence were used to evaluate the intestinal epithelial barrier function. Perkin Elmer Operetta™ was used to obtain high-resolution images of three-dimensional organoids. Results:. An LPS concentration >150 μg/mL after 24 h was identified to cause organoid growth restriction. The fluorescence intensity of zonula occludens-1 and occludins at LPS concentrations >100 μg/mL decreased significantly after 24 h. After LPS stimulation for 8 h, the RNA expression levels of interleukin (IL)-1α, tumor necrosis factor alpha, granulocyte-macrophage colony-stimulating factor, IL-6, and regenerating islet-derived protein 3 alpha, beta, and gamma increased. These results resembled those of intestinal epithelial layer alterations in a mouse sepsis model. For IL-10, the RNA expression level increased only when the LPS level >200 μg/mL for 24 h. Conclusions:. This study provides the primary intestinal in vitro model to study the effects of LPS-induced intestinal injury resembling sepsis. This model provides a platform for immune associated mechanism exploration and effective drug screening.

Abstract Background The mortality of extensively drug-resistant Gram-negative (XDR GN) bacilli-induced ventilator-associated pneumonia (VAP) is extremely high. The purpose of this study was to compare the efficacy and safety of inhaled (IH) plus intravenous (IV) polymyxin B versus IV polymyxin B in XDR GN bacilli VAP patients. Methods A retrospective multi-center observational cohort study was performed at eight ICUs between January 1st 2018, and January 1st 2020 in China. Data from all patients treated with polymyxin B for a microbiologically confirmed VAP were analyzed. The primary endpoint was the clinical cure of VAP. The favorable clinical outcome, microbiological outcome, VAP-related mortality and all-cause mortality during hospitalization, and side effects related with polymyxin B were secondary endpoints. Favorable clinical outcome included clinical cure or clinical improvement. Results 151 patients and 46 patients were treated with IV polymyxin B and IH plus IV polymyxin B, respectively. XDR Klebsiella pneumoniae was the main isolated pathogen (n = 83, 42.1%). After matching on age (± 5 years), gender, septic shock, and Apache II score (± 4 points) when polymyxin B was started, 132 patients were included. 44 patients received simultaneous IH plus IV polymyxin B and 88 patients received IV polymyxin B. The rates of clinical cure (43.2% vs 27.3%, p = 0.066), bacterial eradication (36.4% vs 23.9%, p = 0.132) as well as VAP-related mortality (27.3% vs 34.1%, p = 0.428), all-cause mortality (34.1% vs 42.0%, p = 0.378) did not show any significant difference between the two groups. However, IH plus IV polymyxin B therapy was associated with improved favorable clinical outcome (77.3% vs 58.0%, p = 0.029). Patients in the different subgroups (admitted with medical etiology, infected with XDR K. pneumoniae, without bacteremia, with immunosuppressive status) were with odd ratios (ORs) in favor of the combined therapy. No patient required polymyxin B discontinuation due to adverse events. Additional use of IH polymyxin B (aOR 2.63, 95% CI 1.06, 6.66, p = 0.037) was an independent factor associated with favorable clinical outcome. Conclusions The addition of low-dose IH polymyxin B to low-dose IV polymyxin B did not provide efficient clinical cure and bacterial eradication in VAP caused by XDR GN bacilli. Keypoints Additional use of IH polymyxin B was the sole independent risk factor of favorable clinical outcome. Patients in the different subgroups were with HRs substantially favoring additional use of IH polymyxin B. No patients required polymyxin B discontinuation due to adverse events.

Abstract. Background:. Vancomycin treatment failure against vancomycin-susceptible gram-positive cocci is not rare in the intensive care unit (ICU). One of the reasons for this is the substandard drug trough concentration. We aimed to examine the hypothesis that the target serum concentration could be reached earlier with a loading dose of vancomycin. Methods:. This retrospective cohort study was conducted at our ICU between June 2018 and June 2020 and involved patients who were suspected of having, or confirmed to have, gram-positive cocci infection and treated with vancomycin. One group of the patients was administered a loading dose of vancomycin (loading group) and compared with the group that did not receive a loading dose (control group). The baseline characteristics, vancomycin serum concentrations, and clinical outcomes were collected and analyzed. Results:. Fifty-five patients were finally included, of which 29 received a loading dose of vancomycin. The serum concentration of vancomycin before the second dose was significantly higher for the loading group than for the control group (10.3 ± 6.1 mg/L vs. 5.7 ± 4.4 mg/L, P = 0.002). The results for both groups were similar before the fifth dose (12.4 ± 7.3 mg/L vs. 10.3 ± 6.3 mg/L in the loading and the control groups, respectively; P = 0.251). The 28-day mortality was lower for the loading group than for the control group (6.7% vs. 34.6% in the loading and control groups, respectively; P = 0.026). No significant differences were observed in serum creatinine (Cr) concentrations of the two groups. Conclusion:. With the loading dose of vancomycin, the target serum concentration of vancomycin may be reached earlier without increasing the risk of acute kidney injury. Trial registration:. https://www.chictr.org.cn; ChiCTR2000035369

Background: Novel coronavirus disease 2019 (COVID-19) is an ongoing global pandemic with high mortality. Although several studies have reported different risk factors for mortality in patients based on traditional analytics, few studies have used artificial intelligence (AI) algorithms. This study investigated prognostic factors for COVID-19 patients using AI methods. Methods: COVID-19 patients who were admitted in Wuhan Infectious Diseases Hospital from December 29, 2019 to March 2, 2020 were included. The whole cohort was randomly divided into training and testing sets at a 6:4 ratio. Demographic and clinical data were analyzed to identify predictors of mortality using least absolute shrinkage and selection operator (LASSO) regression and LASSO-based artificial neural network (ANN) models. The predictive performance of the models was evaluated using receiver operating characteristic (ROC) curve analysis. Results: A total of 1145 patients (610 male, 53.3%) were included in the study. Of the 1145 patients, 704 were assigned to the training set and 441 were assigned to the testing set. The median age of the patients was 57 years (range: 47–66 years). Severity of illness, age, platelet count, leukocyte count, prealbumin, C-reactive protein (CRP), total bilirubin, Acute Physiology and Chronic Health Evaluation (APACHE) II score, and Sequential Organ Failure Assessment (SOFA) score were identified as independent prognostic factors for mortality. Incorporating these nine factors into the LASSO regression model yielded a correct classification rate of 0.98, with area under the ROC curve (AUC) values of 0.980 and 0.990 in the training and testing cohorts, respectively. Incorporating the same factors into the LASSO-based ANN model yielded a correct classification rate of 0.990, with an AUC of 0.980 in both the training and testing cohorts. Conclusions: Both the LASSO regression and LASSO-based ANN model accurately predicted the clinical outcome of patients with COVID-19. Severity of illness, age, platelet count, leukocyte count, prealbumin, CRP, total bilirubin, APACHE II score, and SOFA score were identified as prognostic factors for mortality in patients with COVID-19.

Abstract Background Coronavirus disease has heterogeneous clinical features; however, the reasons for the heterogeneity are poorly understood. This study aimed to identify clinical phenotypes according to patients’ temperature trajectory. Method A retrospective review was conducted in five tertiary hospitals in Hubei Province from November 2019 to March 2020. We explored potential temperature-based trajectory phenotypes and assessed patients’ clinical outcomes, inflammatory response, and response to immunotherapy according to phenotypes. Results A total of 1580 patients were included. Four temperature-based trajectory phenotypes were identified: normothermic (Phenotype 1); fever, rapid defervescence (Phenotype 2); gradual fever onset (Phenotype 3); and fever, slow defervescence (Phenotype 4). Compared with Phenotypes 1 and 2, Phenotypes 3 and 4 had a significantly higher C-reactive protein level and neutrophil count and a significantly lower lymphocyte count. After adjusting for confounders, Phenotypes 3 and 4 had higher in-hospital mortality (adjusted odds ratio and 95% confidence interval 2.1, 1.1–4.0; and 3.3, 1.4–8.2, respectively), while Phenotype 2 had similar mortality, compared with Phenotype 1. Corticosteroid use was associated with significantly higher in-hospital mortality in Phenotypes 1 and 2, but not in Phenotypes 3 or 4 (p for interaction

Abstract Background Expanding the tumor, lymph node, metastasis (TNM) staging system by accommodating new prognostic and predictive factors for cancer will improve patient stratification and survival prediction. Here, we introduce machine learning for incorporating additional prognostic factors into the conventional TNM for stratifying patients with lung cancer and evaluating survival. Methods Data were extracted from SEER. A total of 77 953 patients were analyzed using factors including primary tumor (T), regional lymph node (N), distant metastasis (M), age, and histology type. Ensemble algorithm for clustering cancer data (EACCD) and C‐index were applied to generate prognostic groups and expand the current staging system. Results With T, N, and M, EACCD stratified patients into 11 groups, resulting in a significantly higher accuracy in survival prediction than the 10 AJCC stages (C‐index = 0.7346 vs. 0.7247, increase in C‐index = 0.0099, 95% CI: 0.0091–0.0106, p‐value = 9.2 × 10−147). There nevertheless remained a strong association between the EACCD grouping and AJCC staging (rank correlation = 0.9289; p‐value = 6.7 × 10−22). A further analysis demonstrated that age and histological tumor could be integrated with the TNM. Data were stratified into 12 prognostic groups with an even higher prediction accuracy (C‐index = 0.7468 vs. 0.7247, increase in C‐index = 0.0221, 95% CI: 0.0212–0.0231, p‐value

Abstract Background Secondary hemophagocytic lymphohistiocytosis (sHLH) is a life-threatening hyperinflammatory event and a fatal complication of viral infections. Whether sHLH may also be observed in patients with a cytokine storm induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is still uncertain. We aimed to determine the incidence of sHLH in severe COVID-19 patients and evaluate the underlying risk factors. Method Four hundred fifteen severe COVID-19 adult patients were retrospectively assessed for hemophagocytosis score (HScore). A subset of 7 patients were unable to be conclusively scored due to insufficient patient data. Results In 408 patients, 41 (10.04%) had an HScore ≥169 and were characterized as “suspected sHLH positive”. Compared with patients below a HScore threshold of 98, the suspected sHLH positive group had higher D-dimer, total bilirubin, alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, serum creatinine, triglycerides, ferritin, interleukin-6, C-reactive protein, procalcitonin, lactate dehydrogenase, creatine kinase isoenzyme, troponin, Sequential Organ Failure Assessment (SOFA) score, while leukocyte, hemoglobin, platelets, lymphocyte, fibrinogen, pre-albumin, albumin levels were significantly lower (all P 1922.58 ng/mL), low platelets (2.28 mmol/L) were independent risk factors for suspected sHLH in COVID-19 patients. Importantly, COVID-19 patients that were suspected sHLH positive had significantly more multi-organ failure. Additionally, a high HScore (>98) was an independent predictor for mortality in COVID-19. Conclusions HScore should be measured as a prognostic biomarker in COVID-19 patients. In particular, it is important that HScore is assessed in patients with high ferritin, triglycerides and low platelets to improve the detection of suspected sHLH.

BackgroundDecreased serum albumin level (SAL) is associated with adverse clinical outcomes. We designed the present study to further assess the prognostic value of SAL in critically ill patients based on data from large intensive care unit (ICU) databases.MethodsThis retrospective cohort study recruited 18,353 patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Restricted cubic splines (RCS) were performed to visualize the association of SAL at admission with ICU and hospital mortalities. The prognostic value of SAL was analyzed using logistic regression models and receiver operating characteristic (ROC) curves in overall patients and subgroups.ResultsRestricted cubic splines revealed rapid increasing risks in ICU and hospital mortalities when SAL declined to below 30 g/l. Patients with SAL

ABSTRACT Klebsiella pneumoniae is a leading cause of highly drug-resistant infections in hospitals worldwide. Strain-level bacterial identification on the genetic determinants of multidrug resistance and high pathogenicity is critical for the surveillance and treatment of this clinically relevant pathogen. In this study, metagenomic next-generation sequencing was performed for specimens collected from August 2020 to May 2021 in Ruijin Hospital, Ningbo Women and Children’s Hospital, and the Second Affiliated Hospital of Harbin Medical University. Genome biology of K. pneumoniae prevalent in China was characterized based on metagenomic data. Thirty K. pneumoniae strains derived from 14 sequence types were identified by multilocus sequence typing. The hypervirulent ST11 K. pneumoniae strains carrying the KL64 capsular locus were the most prevalent in the hospital population. The phylogenomic analyses revealed that the metagenome-reconstructed strains and public isolate genomes belonging to the same STs were closely related in the phylogenetic tree. Furthermore, the pangenome structure of the detected K. pneumoniae strains was analyzed, particularly focusing on the distribution of antimicrobial resistance genes and virulence genes across the strains. The genes encoding carbapenemases and extended-spectrum beta-lactamases were frequently detected in the strains of ST11 and ST15. The highest numbers of virulence genes were identified in the well-known hypervirulent strains affiliated to ST23 bearing the K1 capsule. In comparison to traditional cultivation and identification, strain-level metagenomics is advantageous to understand the mechanisms underlying resistance and virulence of K. pneumoniae directly from clinical specimens. Our findings should provide novel clues for future research into culture-independent metagenomic surveillance for bacterial pathogens. IMPORTANCE Routine culture and PCR-based molecular testing in the clinical microbiology laboratory are unable to recognize pathogens at the strain level and to detect strain-specific genetic determinants involved in virulence and resistance. To address this issue, we explored the strain-level profiling of K. pneumoniae prevalent in China based on metagenome-sequenced patient materials. Genome biology of the targeted bacterium can be well characterized through decoding sequence signatures and functional gene profiles at the single-strain resolution. The in-depth metagenomic analysis on strain profiling presented here shall provide a promising perspective for culture-free pathogen surveillance and molecular epidemiology of nosocomial infections.

Abstract Background Systemic reactivation of Epstein–Barr virus (EBV) may occur in novel coronavirus disease 2019 (COVID‐19) caused by the severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2). However, the clinical consequences of EBV reactivation remain uncertain. Methods In this retrospective study, we screened 1314 patients with confirmed COVID‐19 who died or were discharged between January 1, 2020 and March 12, 2020, in Wuhan Infectious Disease Hospital, Wuhan, China. Patients who had complete data for EBV serology and cytomegalovirus (CMV) serology were eligible. Serum levels of viral capsid antigen (VCA)‐immunoglobulin G (IgG), Epstein–Barr nuclear antigen‐IgG, VCA‐IgM, early antigen (EA)‐IgG, CMV‐IgG, and CMV‐IgM were compared between survivors and nonsurvivors. Dynamic changes of laboratory tests and outcomes were compared in patients with and without ganciclovir treatment. We used 1:1 matching based on age, gender, and illness severity to balance baseline characteristics. Results EBV reactivation was present in 55 of 217 patients. EBV reactivation was associated with age (57.91 [13.19] vs. 50.28 [12.66] years, p

Abstract Background The impact of corticosteroid therapy on outcomes of patients with coronavirus disease 2019 (COVID-19) is highly controversial. We aimed to compare the risk of death between COVID-19-related ARDS patients with corticosteroid treatment and those without. Methods In this single-center retrospective observational study, patients with ARDS caused by COVID-19 between January 20, 2020, and February 24, 2020, were enrolled. The primary outcome was 60-day in-hospital death. The exposure was prescribed systemic corticosteroids or not. Time-dependent Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for 60-day in-hospital mortality. Results A total of 382 patients [60.7 ± 14.1 years old (mean ± SD), 61.3% males] were analyzed. The median of sequential organ failure assessment (SOFA) score was 2.0 (IQR 2.0–3.0). Of these cases, 94 (24.6%) patients had invasive mechanical ventilation. The number of patients received systemic corticosteroids was 226 (59.2%), and 156 (40.8%) received standard treatment. The maximum dose of corticosteroids was 80.0 (IQR 40.0–80.0) mg equivalent methylprednisolone per day, and duration of corticosteroid treatment was 7.0 (4.0–12.0) days in total. In Cox regression analysis using corticosteroid treatment as a time-varying variable, corticosteroid treatment was associated with a significant reduction in risk of in-hospital death within 60 days after adjusting for age, sex, SOFA score at hospital admission, propensity score of corticosteroid treatment, comorbidities, antiviral treatment, and respiratory supports (HR 0.42; 95% CI 0.21, 0.85; p = 0.0160). Corticosteroids were not associated with delayed viral RNA clearance in our cohort. Conclusion In this clinical practice setting, low-dose corticosteroid treatment was associated with reduced risk of in-hospital death within 60 days in COVID-19 patients who developed ARDS.

Abstract Background Since December 2019, an outbreak of Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) initially emerged in Wuhan, China, and has spread worldwide now. Clinical features of patients with COVID-19 have been described. However, risk factors leading to in-hospital deterioration and poor prognosis in COVID-19 patients with severe disease have not been well identified. Methods In this retrospective, single-center cohort study, 1190 adult inpatients (≥ 18 years old) with laboratory-confirmed COVID-19 and determined outcomes (discharged or died) were included from Wuhan Infectious Disease Hospital from December 29, 2019 to February 28, 2020. The final follow-up date was March 2, 2020. Clinical data including characteristics, laboratory and imaging information as well as treatments were extracted from electronic medical records and compared. A multivariable logistic regression model was used to explore the potential predictors associated with in-hospital deterioration and death. Results 1190 patients with confirmed COVID-19 were included. Their median age was 57 years (interquartile range 47–67 years). Two hundred and sixty-one patients (22%) developed a severe illness after admission. Multivariable logistic regression demonstrated that higher SOFA score (OR 1.32, 95% CI 1.22–1.43, per score increase, p

Abstract Background The aim of this study is to assess the prevalence of abnormal urine analysis and kidney dysfunction in COVID-19 patients and to determine the association of acute kidney injury (AKI) with the severity and prognosis of COVID-19 patients. Methods The electronic database of Embase and PubMed were searched for relevant studies. A meta-analysis of eligible studies that reported the prevalence of abnormal urine analysis and kidney dysfunction in COVID-19 was performed. The incidences of AKI were compared between severe versus non-severe patients and survivors versus non-survivors. Results A total of 24 studies involving 4963 confirmed COVID-19 patients were included. The proportions of patients with elevation of sCr and BUN levels were 9.6% (95% CI 5.7–13.5%) and 13.7% (95% CI 5.5–21.9%), respectively. Of all patients, 57.2% (95% CI 40.6–73.8%) had proteinuria, 38.8% (95% CI 26.3–51.3%) had proteinuria +, and 10.6% (95% CI 7.9–13.3%) had proteinuria ++ or +++. The overall incidence of AKI in all COVID-19 patients was 4.5% (95% CI 3.0–6.0%), while the incidence of AKI was 1.3% (95% CI 0.2–2.4%), 2.8% (95% CI 1.4–4.2%), and 36.4% (95% CI 14.6–58.3%) in mild or moderate cases, severe cases, and critical cases, respectively. Meanwhile, the incidence of AKI was 52.9%(95% CI 34.5–71.4%), 0.7% (95% CI − 0.3–1.8%) in non-survivors and survivors, respectively. Continuous renal replacement therapy (CRRT) was required in 5.6% (95% CI 2.6–8.6%) severe patients, 0.1% (95% CI − 0.1–0.2%) non-severe patients and 15.6% (95% CI 10.8–20.5%) non-survivors and 0.4% (95% CI − 0.2–1.0%) survivors, respectively. Conclusion The incidence of abnormal urine analysis and kidney dysfunction in COVID-19 was high and AKI is closely associated with the severity and prognosis of COVID-19 patients. Therefore, it is important to increase awareness of kidney dysfunction in COVID-19 patients.

Abstract Background The ongoing coronavirus disease 2019 (COVID-2019) pandemic has swept all over the world, posing a great pressure on critical care resources due to large number of patients needing critical care. Statements from front-line experts in the field of intensive care are urgently needed. Methods Sixteen front-line experts in China fighting against the COVID-19 epidemic in Wuhan were organized to develop an expert statement after 5 rounds of expert seminars and discussions to provide trustworthy recommendation on the management of critically ill COVID-19 patients. Each expert was assigned tasks within their field of expertise to provide draft statements and rationale. Parts of the expert statement are based on epidemiological and clinical evidence, without available scientific evidences. Results A comprehensive document with 46 statements are presented, including protection of medical personnel, etiological treatment, diagnosis and treatment of tissue and organ functional impairment, psychological interventions, immunity therapy, nutritional support, and transportation of critically ill COVID-19 patients. Among them, 5 recommendations were strong (Grade 1), 21 were weak (Grade 2), and 20 were experts’ opinions. A strong agreement from voting participants was obtained for all recommendations. Conclusion There are still no targeted therapies for COVID-19 patients. Dynamic monitoring and supportive treatment for the restoration of tissue vascularization and organ function are particularly important.

Abstract Background A COVID-19 outbreak started in Wuhan, China, last December and now has become a global pandemic. The clinical information in caring of critically ill patients with COVID-19 needs to be shared timely, especially under the situations that there is still a largely ongoing spread of COVID-19 in many countries. Methods A multicenter prospective observational study investigated all the COVID-19 patients received in 19 ICUs of 16 hospitals in Wuhan, China, over 24 h between 8 AM February 2h and 8 AM February 27, 2020. The demographic information, clinical characteristics, vital signs, complications, laboratory values, and clinical managements of the patients were studied. Results A total of 226 patients were included. Their median (interquartile range, IQR) age was 64 (57–70) years, and 139 (61.5%) patients were male. The duration from the date of ICU admission to the study date was 11 (5–17) days, and the duration from onset of symptoms to the study date was 31 (24–36) days. Among all the patients, 155 (68.6%) had at least one coexisting disease, and their sequential organ failure assessment score was 4 (2–8). Organ function damages were found in most of the patients: ARDS in 161 (71.2%) patients, septic shock in 34 (15.0%) patients, acute kidney injury occurred in 57 (25.2%) patients, cardiac injury in 61 (27.0%) patients, and lymphocytopenia in 160 (70.8%) patients. Of all the studied patients, 85 (37.6%) received invasive mechanical ventilation, including 14 (6.2%) treated with extracorporeal membrane oxygenation (ECMO) at the same time, 20 (8.8%) received noninvasive mechanical ventilation, and 24 (10.6%) received continuous renal replacement therapy. By April 9, 2020, 87 (38.5%) patients were deceased and 15 (6.7%) were still in the hospital. Conclusions Critically ill patients with COVID-19 are associated with a higher risk of severe complications and need to receive an intensive level of treatments. COVID-19 poses a great strain on critical care resources in hospitals. Trial registration Chinese Clinical Trial Registry, ChiCTR2000030164. Registered on February 24, 2020, http://www.chictr.org.cn/edit.aspx?pid=49983&htm=4

Backgrounds: Up to February 16, 2020, 355 cases have been confirmed as having COVID-19 infection on the Diamond Princess cruise ship. It is of crucial importance to estimate the reproductive number (R0) of the novel virus in the early stage of outbreak and make a prediction of daily new cases on the ship. Method: We fitted the reported serial interval (mean and standard deviation) with a gamma distribution and applied “earlyR” package in R to estimate the R0 in the early stage of COVID-19 outbreak. We applied “projections” package in R to simulate the plausible cumulative epidemic trajectories and future daily incidence by fitting the data of existing daily incidence, a serial interval distribution, and the estimated R0 into a model based on the assumption that daily incidence obeys approximately Poisson distribution determined by daily infectiousness. Results: The Maximum-Likelihood (ML) value of R0 was 2.28 for COVID-19 outbreak at the early stage on the ship. The median with 95% confidence interval (CI) of R0 values was 2.28 (2.06–2.52) estimated by the bootstrap resampling method. The probable number of new cases for the next ten days would gradually increase, and the estimated cumulative cases would reach 1514 (1384–1656) at the tenth day in the future. However, if R0 value was reduced by 25% and 50%, the estimated total number of cumulative cases would be reduced to 1081 (981–1177) and 758 (697–817), respectively. Conclusion: The median with 95% CI of R0 of COVID-19 was about 2.28 (2.06–2.52) during the early stage experienced on the Diamond Princess cruise ship. The future daily incidence and probable outbreak size is largely dependent on the change of R0. Unless strict infection management and control are taken, our findings indicate the potential of COVID-19 to cause greater outbreak on the ship. Keywords: Coronavirus, Mathematical model, Reproductive number, Epidemiology

Abstract Since the 2019 novel coronavirus disease (COVID-19) outbreak originated from Wuhan, Hubei Province, China, at the end of 2019, it has become a clinical threat to the general population worldwide. Among people infected with the novel coronavirus (2019-nCoV), the intensive management of the critically ill patients in intensive care unit (ICU) needs substantial medical resource. In the present article, we have summarized the promising drugs, adjunctive agents, respiratory supportive strategies, as well as circulation management, multiple organ function monitoring and appropriate nutritional strategies for the treatment of COVID-19 in the ICU based on the previous experience of treating other viral infections and influenza. These treatments are referable before the vaccine and specific drugs are available for COVID-19.

Abstract Background Currently, there are no reliable predictors of risk of development and severity of acute kidney injury (AKI) in septic patients. The surfactant protein D (SP-D) polymorphism rs721917C/T is associated with a greater susceptibility to AKI in the Chinese population. Our aim was to evaluate the value of SP-D polymorphisms rs721917C/T and of plasma SP-D levels to predict the risk of development of AKI (defined with KDIGO criterion) in septic patients. Methods The study enrolled septic patients admitted to the Critical Care Department of two tertiary care hospitals. SP-D rs721917C/T polymorphisms were determined using the PCR-SSP method. Plasma SP-D and urine NGAL contents were measured using commercially available ELISA kits. Results 330 septic patients were included. Their SOFA scores were 12 ± 3. Patients with AKI (n = 156) had higher plasma SP-D levels (median: 153 ng/mL, range 111–198 ng/mL) and urinary NGAL levels (median: 575 ng/mL, range 423–727 ng/mL) than those without AKI (SP-D median: 124 ng/mL, range 81–159 ng/mL, P = 0.001; NGAL median: 484 ng/mL, range 429–573 ng/mL). Plasma SP-D levels of AKI patients were correlated with urinary NGAL contents (r = 0.853). In 32 patients receiving continuous renal replacement therapy (CRRT), plasma SP-D levels correlated with duration of CRRT (r = 0.448). The area under the receiver operating characteristic curve for plasma SP-D levels to predict AKI was 0.84. Patients with AKI had a higher rate of rs721917 CC genotype (AKI: 35% vs. non-AKI: 20%; P = 0.012), but a significantly lower rate of TT genotype (AKI: 19% vs. non-AKI: 26%; P = 0.005). SP-D rs721917 CC genotype was an independent predictor of AKI (P = 0.044) and mortality (P = 0.014). Conclusion Our study showed that increased plasma SP-D level is associated with a higher risk of AKI in patients with sepsis. The SP-D rs721917CC genotype is an independent and significant predictor of AKI development and mortality of septic patients. The SP-D rs721917C/T polymorphisms should be further studied as diagnostic and prognostic biomarkers to facilitate early recognition of AKI.

The potential relationship among airway Candida spp. de-colonization, nebulized amphotericin B (NAB), and occurrence of ventilator-associated pneumonia (VAP) in patients who are critically ill has not been fully investigated, especially concerning effects on survival. In this observational, retrospective, cohort study in a 22-bed central intensive care unit, we included patients aged >18 years who required mechanical ventilation (MV) for >48 h, with at least two consecutive positive Candida spp. test results. Patients were categorized into NAB and no NAB (control) groups. Propensity matching at 1:1 was performed according to strict standards, and multiple Cox proportional hazard model and multivariate analyses were performed to evaluate the effects of NAB treatment. Throughout an 8-year study period, 526 patients had received MV and had positive respiratory tract Candida spp. cultures. Of these, we included 275 patients and excluded 251 patients. In total, we successfully matched 110 patients from the two groups (each group, n = 55; total population median age, 64 years; Acute Physiology and Chronic Health Evaluation II [APACHE II] score, 25.5; sequential organ failure assessment score, 9). The Candida spp. de-colonization rate was 69.1% in patients treated with NAB. VAP incidence did not differ significantly between the NAB (10.91%) and control (16.36%) groups (P = 0.405). Pseudomonas aeruginosa-related VAP rates differed significantly between the NAB (10.91%) and control (25.45%) groups (P = 0.048). Five (9.1%) patients in the NAB group died during hospitalization compared with 17 (30.9%) controls (P = 0.014). At 28 days, 9 (16.4%) and 16 (29.1%) deaths occurred in the NAB and control groups, respectively, (P = 0.088). The cumulative 90-day mortality rate differed significantly between the two groups (23.6 vs. 43.6%, P = 0.015). Multivariate logistic regression analyses indicated a decreased 90-day mortality in the NAB group (adjusted odds ratio 0.413; 95% confidence interval 0.210–0.812; P = 0.01). In subgroup analyses, the NAB-associated decreased risk of death at 90 days was consistent across subgroups of patients with a Candida score of 2, younger age (2 days. NAB may be an alternative treatment option for critically ill patients with VAP.

BackgroundThymosin alpha 1 (Tα1) is widely used to treat patients with COVID-19 in China; however, its efficacy remains unclear. This study aimed to explore the efficacy of Tα1 as a COVID-19 therapy.MethodsWe performed a multicenter cohort study in five tertiary hospitals in the Hubei province of China between December 2019 and March 2020. The patient non-recovery rate was used as the primary outcome.ResultsAll crude outcomes, including non-recovery rate (65/306 vs. 290/1,976, p = 0.003), in-hospital mortality rate (62/306 vs. 271/1,976, p = 0.003), intubation rate (31/306 vs. 106/1,976, p = 0.001), acute respiratory distress syndrome (ARDS) incidence (104/306 vs. 499/1,976, p = 0.001), acute kidney injury (AKI) incidence (26/306 vs. 66/1,976, p < 0.001), and length of intensive care unit (ICU) stay (14.9 ± 12.7 vs. 8.7 ± 8.2 days, p < 0.001), were significantly higher in the Tα1 treatment group. After adjusting for confounding factors, Tα1 use was found to be significantly associated with a higher non-recovery rate than non-Tα1 use (OR 1.5, 95% CI 1.1–2.1, p = 0.028). An increased risk of non-recovery rate associated with Tα1 use was observed in the patient subgroups with maximum sequential organ failure assessment (SOFA) scores ≥2 (OR 2.0, 95%CI 1.4–2.9, p = 0.024), a record of ICU admission (OR 5.4, 95%CI 2.1–14.0, p < 0.001), and lower PaO2/FiO2 values (OR 1.9, 95%CI 1.1–3.4, p = 0.046). Furthermore, later initiation of Tα1 use was associated with a higher non-recovery rate.ConclusionTα1 use in COVID-19 patients was associated with an increased non-recovery rate, especially in those with greater disease severity.

Diquat is a widely used herbicide that is substituted for paraquat. With paraquat off the market, cases of diquat poisoning have been gradually increasing. The kidney is the most frequently impaired organ in diquat poisoning. Few cases of multiple organ failure caused by diquat have been reported. We herein describe a 30-year-old man who orally ingested about 160 mL of enriched diquat. Despite aggressive treatment, the patient’s condition progressed to multiple organ failure and death. The pulmonary lesions in this patient were different from those previously reported. This patient did not die of renal failure but of severe respiratory failure. He exhibited three different stages of pulmonary disease. The lung lesions in this case were unique. We hope that doctors will pay more attention to the lung lesions in patients with diquat poisoning in future and find new treatment methods to save the lives of such patients.

Background: Extended/continuous infusion and therapeutic drug monitoring (TDM) of time-dependent antimicrobials are recommended for optimizing drug exposure for patients in intensive care units (ICUs), although practical application of these measures remains uncertain. We surveyed current practices in infusion and monitoring of commonly prescribed time-dependent antimicrobials in ICUs across China.Methods: From December 2019 to January 2020, we sent online questionnaires about various aspects of infusion and monitoring of time-dependent antimicrobials to intensivists across China. Responses from clinicians were matched with their professional titles using the Sankey diagram. Univariate and multivariate logistic regression analyses were performed to find factors associated with TDM.Results: A total of 3,687 ICU specialists from 31 provincial administrative regions of China responded to our questionnaires. Antibiotic stewardship (ABS) teams were available in hospitals as reported by 3,243 (88.0%) intensivists, including 1,308 (35.5%) who were ABS team members. Although most intensivists (3,490, 94.7%) were acquainted with the concept of prolonged/continuous infusion, nearly half of them (1,634, 44.3%) commonly administered β-lactam antibiotics intermittently. Nearly two-thirds of the respondents reported that their hospitals could not perform TDM. Our multivariable logistic regression analysis revealed that at the hospital level, knowledge of drug sample timing and attitude toward monitoring treatment effects, and drug trough or peak concentration influenced the decision to conduct TDM.Conclusions: We found great variability in prescribing practices, from drug administration to TDM, for several time-dependent antibiotics commonly used for patients with severe infections. Further studies are necessary to effectively evaluate strategies to promote consistent prescribing behavior.

Background: Complicated intra-abdominal infections (cIAIs) in the abdominal cavity or within an abdominal organ are numerous and frequent dangerous entities in the treatment of critically ill patients. Early clinical evaluation is necessary.Methods: This retrospective multicenter study included patients from 10 intensive care units (ICUs). Risk factors for the overall survival (OS) of patients with cIAI were selected using least absolute shrinkage and selection operator regression, and a nomogram was constructed subsequently. Calibration curve and receiver operating characteristic (ROC) curve were used to evaluate the calibration and discriminative ability.Results: In total, 544 patients diagnosed with cIAI were enrolled and divided into the study (n = 276) and validation (n = 268) sets. Sex, acute gastrointestinal injury, acute kidney injury, rare bacterium infection, Charlson score, and APACHE II score were identified as independent risk factors and were constructed for the nomogram. The nomogram showed marked calibration capability with a concordance index (C-index) of 0.909 and 0.831 in the study and validation set, respectively. Compared with the common clinical prognostic scoring system, the nomogram achieved the highest discrimination ability with an area under the curve (AUC) value of 0.91 and 0.83 in the study set and validation set, respectively.Conclusions: Our newly constructed nomogram provides a useful tool for risk stratification and prognosis evaluation of cIAI.

BackgroundIntegrating additional factors into the TNM staging system is needed for more accurate risk classification and survival prediction for patients with cutaneous melanoma. In the present study, we introduce machine learning as a novel tool that incorporates additional prognostic factors to improve the current TNM staging system.Methods and findingsCancer-specific survival data for cutaneous melanoma with at least a 5 years follow-up were extracted from the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute and split into the training set (40,781 cases) and validation set (5,390 cases). Five factors were studied: the primary tumor (T), regional lymph nodes (N), distant metastasis (M), age (A), and sex (S). The Ensemble Algorithm for Clustering Cancer Data (EACCD) was applied to the training set to generate prognostic groups. Utilizing only T, N, and M, a basic prognostic system was built where patients were stratified into 10 prognostic groups with well-separated survival curves, similar to 10 AJCC stages. These 10 groups had a significantly higher accuracy in survival prediction than 10 stages (C-index = 0.7682 vs 0.7643; increase in C-index = 0.0039, 95% CI = (0.0032, 0.0047); p-value = 7.2×10-23). Nevertheless, a positive association remained between the EACCD grouping and the AJCC staging (Spearman's rank correlation coefficient = 0.8316; p-value = 4.5×10-13). With additional information from A and S, a more advanced prognostic system was established using the training data that stratified patients into 10 groups and further improved the prediction accuracy (C-index = 0.7865 vs 0.7643; increase in C-index = 0.0222, 95% CI = (0.0191, 0.0254); p-value = 8.8×10-43). Both internal validation using the training set and temporal validation using the validation set showed good stratification and a high predictive accuracy of the prognostic systems.ConclusionsThe EACCD allows additional factors to be integrated into the TNM to create a prognostic system that improves patient stratification and survival prediction for cutaneous melanoma. This integration separates favorable from unfavorable clinical outcomes for patients and improves both cohort selection for clinical trials and treatment management.

Background: Studies have shown that dexmedetomidine improves neurological function. Whether dexmedetomidine reduces mortality or improves quantitative electroencephalography (qEEG) among patients post-craniotomy remains unclear. Methods: This single-center randomized study was conducted prospectively from 1 January 2019 to 31 December 2020. Patients who were transferred to the ICU after craniotomy within 24 h were included. The analgesic was titrated to a Critical care Pain Observation Tool (CPOT) score ≤2, and the sedative was titrated to a Richmond Agitation–Sedation Scale (RASS) score ≤−3 for at least 24 h. The qEEG signals were collected by four electrodes (F3, T3, F4, and T4 according to the international 10/20 EEG electrode practice). The primary outcome was 28-day mortality and qEEG results on day 1 and day 3 after sedation. Results: One hundred and fifty-one patients were enrolled in this study, of whom 77 were in the dexmedetomidine group and 74 in the midazolam group. No significant difference was found between the two groups in mortality at 28 days (14.3% vs. 24.3%; p = 0.117) as well as in the theta/beta ratio (TBR), the delta/alpha ratio (DAR), and the (delta + theta)/(alpha + beta) ratio (DTABR) between the two groups on day 1 or day 3. However, both the TBR and the DTABR were significantly increased in the dexmedetomidine group. The DTABR in the midazolam group was significantly increased. The DAR was significantly increased on the right side in the dexmedetomidine group (20.4 (11.6–43.3) vs. 35.1 (16.7–65.0), p = 0.006) as well as on both sides in the midazolam group (Left: 19.5 (10.1–35.8) vs. 37.3 (19.3–75.7), p = 0.006; Right: 18.9 (10.1–52.3) vs. 39.8 (17.5–99.9), p = 0.002). Conclusion: Compared with midazolam, dexmedetomidine did not lead to a lower 28-day mortality or better qEEG results in brain injury patients after a craniotomy.

Background: High-flow nasal cannula (HFNC) has been recommended as a suitable choice for the management of coronavirus disease 2019 (COVID-19) patients with acute hypoxemic respiratory failure before mechanical ventilation (MV); however, delaying MV with HFNC therapy is still a dilemma between the technique and clinical management during the ongoing pandemic.Methods: Retrospective analysis of COVID-19 patients treated with HFNC therapy from four hospitals of Wuhan, China. Demographic information and clinical variables before, at, and shortly after HFNC initiation were collected and analyzed. A risk-stratification model of HFNC failure (the need for MV) was developed with the 324 patients of Jin Yin-tan Hospital and validated its accuracy with 69 patients of other hospitals.Results: Among the training cohort, the median duration of HFNC therapy was 6 (range, 3–11), and 147 experienced HFNC failure within 7 days of HFNC initiation. Early predictors of HFNC failure on the basis of a multivariate regression analysis included age older than 60 years [odds ratio (OR), 1.93; 95% confidence interval (CI), 1.08–3.44; p = 0.027; 2 points], respiratory rate-oxygenation index (ROX) 7.0 pg/mL (OR, 3.34; 95% CI, 1.79–6.23; p < 0.001; 3 points) at HFNC initiation. A weighted risk-stratification model of these predictors showed sensitivity of 80.3%, specificity of 71.2% and a better predictive ability than ROX index alone [area under the curve (AUC) = 0.807 vs. 0.779, p < 0.001]. Six points were used as a cutoff value for the risk of HFNC failure stratification. The HFNC success probability of patients in low-risk group (84.2%) was 9.84 times that in the high-risk group (34.8%). In the subsequent validation cohort, the AUC of the model was 0.815 (0.71–0.92).Conclusions: Aged patients with lower ROX index, thrombocytopenia, and elevated IL-6 values are at increased risk of HFNC failure. The risk-stratification models accurately predicted the HFNC failure and early stratified COVID-19 patients with HFNC therapy into relevant risk categories.

Authentication plays a critical role in securing any online banking system, and many banks and various services have long relied on username/password combos to verify users. Memorizing usernames and passwords for a lot of accounts becomes a cumbersome and inefficient task. Furthermore, legacy authentication methods have failed over and over, and they are not immune against a wide variety of attacks that can be launched against users, networks, or authentication servers. Over the years, data breach reports emphasize that attackers have created numerous high-tech techniques to steal users' credentials, which can pose a serious threat. In this paper, we propose an efficient and practical user authentication scheme using personal devices that utilize different cryptographic primitives, such as encryption, digital signature, and hashing. The technique benefits from the widespread usage of ubiquitous computing and various intelligent portable and wearable devices that can enable users to execute a secure authentication protocol. Our proposed scheme does not require an authentication server to maintain static username and password tables for identifying and verifying the legitimacy of the login users. It not only is secure against password-related attacks, but also can resist replay attacks, shoulder-surfing attacks, phishing attacks, and data breach incidents.

Objective The American Joint Committee on Cancer (AJCC) system for staging cancers of the colon and rectum includes depth of tumour penetration, number of positive lymph nodes and presence or absence of metastasis. Using machine learning, we demonstrate that these factors can be integrated with age, carcinoembryonic antigen (CEA) interpretation and tumour location, to form prognostic systems that expand the tumour, lymph node, metastasis (TNM) staging system.Methods Two datasets on colon and rectal cancers were extracted from the Surveillance, Epidemiology and End Results Programme of the National Cancer Institute. Dataset 1 included three factors (tumour, lymph nodes and metastasis). Dataset 2 contained six factors (tumour, lymph nodes, metastasis, age, CEA interpretation and tumour location). The Ensemble Algorithm for Clustering Cancer Data (EACCD) and the C-index were applied to generate prognostic groups.Results The EACCD prognostic system based on dataset 1 stratified patients into 10 risk groups, analogous to the 10 stages of the AJCC staging system. There was a strong inter-system association between EACCD grouping and AJCC staging (Spearman’s rank correlation=0.9046, p value=1.6×10−17). However, the EACCD system had a significantly higher survival prediction accuracy than the AJCC system (C-index=0.7802 and 0.7695, respectively for the EACCD system and AJCC system, p value=4.9×10−91). Adding age, or CEA interpretation, or location improved the prediction accuracy of the prognostic system-involving tumour, lymph nodes and metastasis. The EACCD prognostic system based on dataset 2 and all six factors stratified patients into 10 groups with the highest survival prediction accuracy (C-index=0.7914).Conclusions The EACCD can integrate multiple factors to stratify patients with colon or rectal cancer into risk groups that predict survival with a high accuracy.

Updates to staging models are needed to reflect a greater understanding of tumor behavior and clinical outcomes for well-differentiated thyroid carcinomas. We used a machine learning algorithm and disease-specific survival data of differentiated thyroid carcinoma from the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute to integrate clinical factors to improve prognostic accuracy. The concordance statistic (C-index) was used to cut dendrograms resulting from the learning process to generate prognostic groups. We created one computational prognostic model (7 prognostic groups with C-index = 0.8583) based on tumor size (T), regional lymph nodes (N), status of distant metastasis (M), and age to mirror the contemporary American Joint Committee on Cancer (AJCC) staging system (C-index = 0.8387). We showed that adding histologic type (papillary and follicular) improved the survival prediction of the model. We also showed that 55 is the best cutoff of age in the model, consistent with the changes from the most recent 8th edition staging manual from AJCC. The demonstrated approach has the potential to create prognostic systems permitting data driven and real time analysis that can aid decision-making in patient management and prognostication.

This paper proposes a multiple-input multiple-output (MIMO) based cooperative dynamic spectrum access (DSA) framework that enables multiple primary users (PUs) and multiple secondary users (SUs) to cooperate in spectrum sharing. By exploiting MIMO in cooperative DSA, SUs can relay the primary traffic and send their own data at the same time, which greatly improves the performance of both PUs and SUs when compared to the non-MIMO time-division spectrum sharing schemes. Especially, we focus on the relay selection optimization problem among multiple PUs and multiple SUs. The network-wide cooperation and competition are formulated as a bargaining game, and an algorithm is developed to derive the optimal PU-SU relay assignment and resource allocation. Evaluation results show that both primary and secondary users achieve significant utility gains with the proposed framework, which gives all of them incentive for cooperation.