PeerJ:Emergency and Critical Carehttps://peerj.com/articles/index.atom?journal=peerj&subject=4200Emergency and Critical Care articles published in PeerJConstruction and validation of a nomogram model to predict the poor prognosis in patients with pulmonary cryptococcosishttps://peerj.com/articles/170302024-03-112024-03-11Xiaoli TanYingqing ZhangJianying ZhouWenyu ChenHua Zhou
Background
Patients with poor prognosis of pulmonary cryptococcosis (PC) are prone to other complications such as meningeal infection, recurrence or even death. Therefore, this study aims to analyze the influencing factors in the poor prognosis of patients with PC, so as to build a predictive nomograph model of poor prognosis of PC, and verify the predictive performance of the model.
Methods
This retrospective study included 410 patients (78.1%) with improved prognosis of PC and 115 patients (21.9%) with poor prognosis of PC. The 525 patients with PC were randomly divided into the training set and validation set according to the ratio of 7:3. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to screen the demographic information, including clinical characteristics, laboratory test indicators, comorbidity and treatment methods of patients, and other independent factors that affect the prognosis of PC. These factors were included in the multivariable logistic regression model to build a predictive nomograph. The receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA) were used to verify the accuracy and application value of the model.
Results
It was finally confirmed that psychological symptoms, cytotoxic drugs, white blood cell count, hematocrit, platelet count, CRP, PCT, albumin, and CD4/CD8 were independent predictors of poor prognosis of PC patients. The area under the curve (AUC) of the predictive model for poor prognosis in the training set and validation set were 0.851 (95% CI: 0.818-0.881) and 0.949, respectively. At the same time, calibration curve and DCA results confirmed the excellent performance of the nomogram in predicting poor prognosis of PC.
Conclusion
The nomograph model for predicting the poor prognosis of PC constructed in this study has good prediction ability, which is helpful for improving the prognosis of PC and further optimizing the clinical management strategy.
Background
Patients with poor prognosis of pulmonary cryptococcosis (PC) are prone to other complications such as meningeal infection, recurrence or even death. Therefore, this study aims to analyze the influencing factors in the poor prognosis of patients with PC, so as to build a predictive nomograph model of poor prognosis of PC, and verify the predictive performance of the model.
Methods
This retrospective study included 410 patients (78.1%) with improved prognosis of PC and 115 patients (21.9%) with poor prognosis of PC. The 525 patients with PC were randomly divided into the training set and validation set according to the ratio of 7:3. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to screen the demographic information, including clinical characteristics, laboratory test indicators, comorbidity and treatment methods of patients, and other independent factors that affect the prognosis of PC. These factors were included in the multivariable logistic regression model to build a predictive nomograph. The receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA) were used to verify the accuracy and application value of the model.
Results
It was finally confirmed that psychological symptoms, cytotoxic drugs, white blood cell count, hematocrit, platelet count, CRP, PCT, albumin, and CD4/CD8 were independent predictors of poor prognosis of PC patients. The area under the curve (AUC) of the predictive model for poor prognosis in the training set and validation set were 0.851 (95% CI: 0.818-0.881) and 0.949, respectively. At the same time, calibration curve and DCA results confirmed the excellent performance of the nomogram in predicting poor prognosis of PC.
Conclusion
The nomograph model for predicting the poor prognosis of PC constructed in this study has good prediction ability, which is helpful for improving the prognosis of PC and further optimizing the clinical management strategy.The application of two drainage angles in neurocritical care patients with complicated pneumonia: a randomized controlled trialhttps://peerj.com/articles/169972024-02-292024-02-29Anna ZhaoHuangrong ZengHui YinJinlin WangWenming YuanChao LiYan ZhongLanlan MaChongmao LiaoHong ZengYan Li
Background
Although head elevation is an early first-line treatment for elevated intracranial pressure (ICP), the use of the head-down or prone position in managing neurocritical patients is controversial because a change in a position directly affects the intracranial and cerebral perfusion pressure, which may cause secondary brain injury and affect patient outcomes. This study compared the effects of two postural drainage positions (30° head-up tilt and 0° head flat) on the prognosis of neurocritical care patients with complicated pneumonia and a clinical pulmonary infection score (CPIS) ≥5 points to provide a reference for selecting appropriate postural drainage positions for patients with pneumonia in neurocritical care units.
Methods
A prospective randomized controlled study was conducted with 62 neurocritical care patients with complicated pneumonia. The patients were categorized into control (=31) and experimental (=31) groups in a 1:1 ratio using a simple randomized non-homologous pairing method. Emphasis was placed on matching the baseline characteristics of the two groups, including patient age, sex, height, weight, Glasgow Coma Scale score, heart rate, mean arterial pressure, cough reflex, and mechanical ventilation usage to ensure comparability. Both groups received bundled care for artificial airway management. The control group maintained a standard postural drainage position of 0° head-flat, whereas the experimental group maintained a 30° head-up tilt. The efficacy of the nursing intervention was evaluated by comparing the CPIS and other therapeutic indicators between the two groups after postural drainage.
Results
After the intervention, the within-group comparison showed a significant decrease in the CPIS (P < 0.001); procalcitonin levels showed a significant decreasing trend (P < 0.05); the arterial oxygen pressure significantly increased (P < 0.05); the oxygenation index significantly increased (P < 0.001); and the aspiration risk score showed a significant decreasing trend (P < 0.001). A between-group comparison showed no significant differences in any of the indicators before and after the intervention (P < 0.05).
Conclusion
Postural drainage positions of 30° head-up tilt and 0° head-flat can improve the CPIS and oxygenation in patients without adverse effects. Therefore, we recommend that patients under neurological intensive care and having pneumonia be drained in a 30° head-up tilt position with good centralized care of the lung infection.
Trial registration
The study, “Study of Angles of Postural Drainage in Neurocritical Patients with Pneumonia,” was registered in the Protocol Registration Data Element Definitions for Interventional Study database (# ChiCTR2100042155); date of registration: 2021-01-14.
Background
Although head elevation is an early first-line treatment for elevated intracranial pressure (ICP), the use of the head-down or prone position in managing neurocritical patients is controversial because a change in a position directly affects the intracranial and cerebral perfusion pressure, which may cause secondary brain injury and affect patient outcomes. This study compared the effects of two postural drainage positions (30° head-up tilt and 0° head flat) on the prognosis of neurocritical care patients with complicated pneumonia and a clinical pulmonary infection score (CPIS) ≥5 points to provide a reference for selecting appropriate postural drainage positions for patients with pneumonia in neurocritical care units.
Methods
A prospective randomized controlled study was conducted with 62 neurocritical care patients with complicated pneumonia. The patients were categorized into control (=31) and experimental (=31) groups in a 1:1 ratio using a simple randomized non-homologous pairing method. Emphasis was placed on matching the baseline characteristics of the two groups, including patient age, sex, height, weight, Glasgow Coma Scale score, heart rate, mean arterial pressure, cough reflex, and mechanical ventilation usage to ensure comparability. Both groups received bundled care for artificial airway management. The control group maintained a standard postural drainage position of 0° head-flat, whereas the experimental group maintained a 30° head-up tilt. The efficacy of the nursing intervention was evaluated by comparing the CPIS and other therapeutic indicators between the two groups after postural drainage.
Results
After the intervention, the within-group comparison showed a significant decrease in the CPIS (P < 0.001); procalcitonin levels showed a significant decreasing trend (P < 0.05); the arterial oxygen pressure significantly increased (P < 0.05); the oxygenation index significantly increased (P < 0.001); and the aspiration risk score showed a significant decreasing trend (P < 0.001). A between-group comparison showed no significant differences in any of the indicators before and after the intervention (P < 0.05).
Conclusion
Postural drainage positions of 30° head-up tilt and 0° head-flat can improve the CPIS and oxygenation in patients without adverse effects. Therefore, we recommend that patients under neurological intensive care and having pneumonia be drained in a 30° head-up tilt position with good centralized care of the lung infection.
Trial registration
The study, “Study of Angles of Postural Drainage in Neurocritical Patients with Pneumonia,” was registered in the Protocol Registration Data Element Definitions for Interventional Study database (# ChiCTR2100042155); date of registration: 2021-01-14.The causal effects of circulating cytokines on sepsis: a Mendelian randomization studyhttps://peerj.com/articles/168602024-02-012024-02-01Weijun FangChen ChaiJiawei Lu
Background
In observational studies, sepsis and circulating levels of cytokines have been associated with unclear causality. This study used Mendelian randomization (MR) to identify the causal direction between circulating cytokines and sepsis in a two-sample study.
Methods
An MR analysis was performed to estimate the causal effect of 41 cytokines on sepsis risk. The inverse-variance weighted random-effects method, the weighted median-based method, and MR-Egger were used to analyze the data. Heterogeneity and pleiotropy were assessed using MR-Egger regression and Cochran’s Q statistic.
Results
Genetically predicted beta-nerve growth factor (OR = 1.12, 95% CI [1.037–1.211], P = 0.004) increased the risk of sepsis, while RANTES (OR = 0.92, 95% CI [0.849–0.997], P = 0.041) and fibroblast growth factor (OR = 0.869, 95% CI [0.766–0.986], P = 0.029) reduced the risk of sepsis. These findings were robust in extensive sensitivity analyses. There was no clear association between the other cytokines and sepsis risk.
Conclusion
The findings of this study demonstrate that beta-nerve growth factor, RANTES, and fibroblast growth factor contribute to sepsis risk. Investigations into potential mechanisms are warranted.
Background
In observational studies, sepsis and circulating levels of cytokines have been associated with unclear causality. This study used Mendelian randomization (MR) to identify the causal direction between circulating cytokines and sepsis in a two-sample study.
Methods
An MR analysis was performed to estimate the causal effect of 41 cytokines on sepsis risk. The inverse-variance weighted random-effects method, the weighted median-based method, and MR-Egger were used to analyze the data. Heterogeneity and pleiotropy were assessed using MR-Egger regression and Cochran’s Q statistic.
Results
Genetically predicted beta-nerve growth factor (OR = 1.12, 95% CI [1.037–1.211], P = 0.004) increased the risk of sepsis, while RANTES (OR = 0.92, 95% CI [0.849–0.997], P = 0.041) and fibroblast growth factor (OR = 0.869, 95% CI [0.766–0.986], P = 0.029) reduced the risk of sepsis. These findings were robust in extensive sensitivity analyses. There was no clear association between the other cytokines and sepsis risk.
Conclusion
The findings of this study demonstrate that beta-nerve growth factor, RANTES, and fibroblast growth factor contribute to sepsis risk. Investigations into potential mechanisms are warranted.Association between lactic acidosis and multiple organ dysfunction syndrome after cardiopulmonary bypasshttps://peerj.com/articles/167692024-01-312024-01-31Dan ZhengGuo-Liang YuYi-Ping ZhouQiao-Min ZhangChun-Guo WangSheng Zhang
Background
The relationship between hyperlactatemia and prognosis after cardiopulmonary bypass (CPB) is controversial, and some studies ignore the presence of lactic acidosis in patients with severe hyperlactacemia. This study explored the association between lactic acidosis (LA) and the occurrence of multiple organ dysfunction syndrome (MODS) after cardiopulmonary bypass.
Methods
This study was a post hoc analysis of patients who underwent cardiac surgery between February 2017 and August 2018 and participated in a prospective study at Taizhou Hospital. The data were collected at: ICU admission (H0), and 4, 8, 12, 24, and 48 h after admission. Blood lactate levels gradually increased after CPB, peaking at H8 and then gradually decreasing. The patients were grouped as LA, hyperlactatemia (HL), and normal control (NC) based on blood test results 8 h after ICU admission. Basic preoperative, perioperative, and postoperative conditions were compared between the three groups, as well as postoperative perfusion and oxygen metabolism indexes.
Results
There were 22 (19%), 73 (64%), and 19 (17%) patients in the LA, HL, and NC groups, respectively. APACHE II (24h) and SOFA (24h) scores were the highest in the LA group (P < 0.05). ICU stay duration was the longest for the LA group (48.5 (42.5, 50) h), compared with the HL (27 (22, 48) h) and NC (27 (25, 46) h) groups (P = 0.012). The LA group had the highest incidence of MODS (36%), compared with the HL (14%) and NC (5%) groups (P = 0.015). In the LA group, the oxygen extraction ratio (O2ER) was lower (21.5 (17.05, 32.8)%) than in the HL (31.3 (24.8, 37.6)%) and the NC group (31.3 (29.0, 35.4) %) (P = 0.018). In the univariable analyses, patient age (OR = 1.054, 95% CI [1.003–1.109], P = 0.038), the LA group (vs. the NC group, (OR = 10.286, 95% CI [1.148–92.185], P = 0.037), and ΔPCO2 at H8 (OR = 1.197, 95% CI [1.022–1.401], P = 0.025) were risk factor of MODS after CPB.
Conclusions
We speculated that there was correlation between lactic acidosis and MODS after CPB. In addition, LA should be monitored intensively after CPB.
Background
The relationship between hyperlactatemia and prognosis after cardiopulmonary bypass (CPB) is controversial, and some studies ignore the presence of lactic acidosis in patients with severe hyperlactacemia. This study explored the association between lactic acidosis (LA) and the occurrence of multiple organ dysfunction syndrome (MODS) after cardiopulmonary bypass.
Methods
This study was a post hoc analysis of patients who underwent cardiac surgery between February 2017 and August 2018 and participated in a prospective study at Taizhou Hospital. The data were collected at: ICU admission (H0), and 4, 8, 12, 24, and 48 h after admission. Blood lactate levels gradually increased after CPB, peaking at H8 and then gradually decreasing. The patients were grouped as LA, hyperlactatemia (HL), and normal control (NC) based on blood test results 8 h after ICU admission. Basic preoperative, perioperative, and postoperative conditions were compared between the three groups, as well as postoperative perfusion and oxygen metabolism indexes.
Results
There were 22 (19%), 73 (64%), and 19 (17%) patients in the LA, HL, and NC groups, respectively. APACHE II (24h) and SOFA (24h) scores were the highest in the LA group (P < 0.05). ICU stay duration was the longest for the LA group (48.5 (42.5, 50) h), compared with the HL (27 (22, 48) h) and NC (27 (25, 46) h) groups (P = 0.012). The LA group had the highest incidence of MODS (36%), compared with the HL (14%) and NC (5%) groups (P = 0.015). In the LA group, the oxygen extraction ratio (O2ER) was lower (21.5 (17.05, 32.8)%) than in the HL (31.3 (24.8, 37.6)%) and the NC group (31.3 (29.0, 35.4) %) (P = 0.018). In the univariable analyses, patient age (OR = 1.054, 95% CI [1.003–1.109], P = 0.038), the LA group (vs. the NC group, (OR = 10.286, 95% CI [1.148–92.185], P = 0.037), and ΔPCO2 at H8 (OR = 1.197, 95% CI [1.022–1.401], P = 0.025) were risk factor of MODS after CPB.
Conclusions
We speculated that there was correlation between lactic acidosis and MODS after CPB. In addition, LA should be monitored intensively after CPB.A dynamic nomogram for predicting 28-day mortality in septic shock: a Chinese retrospective cohort studyhttps://peerj.com/articles/167232024-01-232024-01-23Zhijun XuMan Huang
Background
Septic shock is a severe life-threatening disease, and the mortality of septic shock in China was approximately 37.3% that lacks prognostic prediction model. This study aimed to develop and validate a prediction model to predict 28-day mortality for Chinese patients with septic shock.
Methods
This retrospective cohort study enrolled patients from Intensive Care Unit (ICU) of the Second Affiliated Hospital, School of Medicine, Zhejiang University between December 2020 and September 2021. We collected patients’ clinical data: demographic data and physical condition data on admission, laboratory data on admission and treatment method. Patients were randomly divided into training and testing sets in a ratio of 7:3. Univariate logistic regression was adopted to screen for potential predictors, and stepwise regression was further used to screen for predictors in the training set. Prediction model was constructed based on these predictors. A dynamic nomogram was performed based on the results of prediction model. Using receiver operator characteristic (ROC) curve to assess predicting performance of dynamic nomogram, which were compared with Sepsis Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation II (APACHE II) systems.
Results
A total of 304 patients with septic shock were included, with a 28-day mortality of 25.66%. Systolic blood pressure, cerebrovascular disease, Na, oxygenation index (PaO2/FiO2), prothrombin time, glucocorticoids, and hemodialysis were identified as predictors for 28-day mortality in septic shock patients, which were combined to construct the predictive model. A dynamic nomogram (https://zhijunxu.shinyapps.io/DynNomapp/) was developed. The dynamic nomogram model showed a good discrimination with area under the ROC curve of 0.829 in the training set and 0.825 in the testing set. Additionally, the study suggested that the dynamic nomogram has a good predictive value than SOFA and APACHE II.
Conclusion
The dynamic nomogram for predicting 28-day mortality in Chinese patients with septic shock may help physicians to assess patient survival and optimize personalized treatment strategies for septic shock.
Background
Septic shock is a severe life-threatening disease, and the mortality of septic shock in China was approximately 37.3% that lacks prognostic prediction model. This study aimed to develop and validate a prediction model to predict 28-day mortality for Chinese patients with septic shock.
Methods
This retrospective cohort study enrolled patients from Intensive Care Unit (ICU) of the Second Affiliated Hospital, School of Medicine, Zhejiang University between December 2020 and September 2021. We collected patients’ clinical data: demographic data and physical condition data on admission, laboratory data on admission and treatment method. Patients were randomly divided into training and testing sets in a ratio of 7:3. Univariate logistic regression was adopted to screen for potential predictors, and stepwise regression was further used to screen for predictors in the training set. Prediction model was constructed based on these predictors. A dynamic nomogram was performed based on the results of prediction model. Using receiver operator characteristic (ROC) curve to assess predicting performance of dynamic nomogram, which were compared with Sepsis Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation II (APACHE II) systems.
Results
A total of 304 patients with septic shock were included, with a 28-day mortality of 25.66%. Systolic blood pressure, cerebrovascular disease, Na, oxygenation index (PaO2/FiO2), prothrombin time, glucocorticoids, and hemodialysis were identified as predictors for 28-day mortality in septic shock patients, which were combined to construct the predictive model. A dynamic nomogram (https://zhijunxu.shinyapps.io/DynNomapp/) was developed. The dynamic nomogram model showed a good discrimination with area under the ROC curve of 0.829 in the training set and 0.825 in the testing set. Additionally, the study suggested that the dynamic nomogram has a good predictive value than SOFA and APACHE II.
Conclusion
The dynamic nomogram for predicting 28-day mortality in Chinese patients with septic shock may help physicians to assess patient survival and optimize personalized treatment strategies for septic shock.Microparticle-associated tissue factor activity correlates with the inflammatory response in septic disseminated intravascular coagulation patientshttps://peerj.com/articles/166362024-01-082024-01-08Shishuai MengBin XuWei YangMingyan Zhao
Background
Sepsis is often accompanied by the formation of disseminated intravascular coagulation (DIC). Microparticles can exert their procoagulant and proinflammatory properties in a variety of ways. The purpose of this study was to investigate the relationship between microparticle-associated tissue factor activity (TF+-MP activity) and the inflammatory response.
Methods
Data from a total of 31 DIC patients with sepsis and 31 non-DIC patients with sepsis admitted to the ICU of the First Affiliated Hospital of Harbin Medical University from December 2017 to March 2019 were collected. Blood samples were collected and DIC scores were calculated on the day of enrollment. The hospital’s clinical laboratory completed routine blood, procalcitonin, and C-reactive protein tests. TF+-MP activity was measured using a tissue factor-dependent FXa generation assay. Interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) levels were determined using ELISA kits.
Results
Compared with the non-DIC group, the DIC group had higher levels of leukocytes, neutrophils, procalcitonin, C-reactive protein, IL-1β, and TNF-α, and more severe inflammatory reactions. TF+-MP activity in the DIC group was higher than that in the non-DIC group. In sepsis patients, TF+-MP activity was strongly correlated with inflammatory response indices and DIC scores.
Conclusion
TF+-MP activity may play a major role in promoting inflammatory response in septic DIC.
Background
Sepsis is often accompanied by the formation of disseminated intravascular coagulation (DIC). Microparticles can exert their procoagulant and proinflammatory properties in a variety of ways. The purpose of this study was to investigate the relationship between microparticle-associated tissue factor activity (TF+-MP activity) and the inflammatory response.
Methods
Data from a total of 31 DIC patients with sepsis and 31 non-DIC patients with sepsis admitted to the ICU of the First Affiliated Hospital of Harbin Medical University from December 2017 to March 2019 were collected. Blood samples were collected and DIC scores were calculated on the day of enrollment. The hospital’s clinical laboratory completed routine blood, procalcitonin, and C-reactive protein tests. TF+-MP activity was measured using a tissue factor-dependent FXa generation assay. Interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) levels were determined using ELISA kits.
Results
Compared with the non-DIC group, the DIC group had higher levels of leukocytes, neutrophils, procalcitonin, C-reactive protein, IL-1β, and TNF-α, and more severe inflammatory reactions. TF+-MP activity in the DIC group was higher than that in the non-DIC group. In sepsis patients, TF+-MP activity was strongly correlated with inflammatory response indices and DIC scores.
Conclusion
TF+-MP activity may play a major role in promoting inflammatory response in septic DIC.Proteomic profiling of serum exosomes reveals acute phase response and promotion of inflammatory and platelet activation pathways in patients with heat strokehttps://peerj.com/articles/165902023-12-132023-12-13Yue LiHuan LiWenjuan MaMarc MaegeleYouqing TangZhengtao Gu
Background: The pathological mechanism of heat stroke (HS) involves the acute phase response, unbalanced immunological/inflammatory reactions, and coagulation initiation, especially platelet activation. Although exosomes contain proteins involved in these biological processes, their protein cargo levels and potential roles in HS remain unknown. This study explored the serum exosome protein expression patterns after HS and their potential roles in the pathogenesis of HS.
Methods: Blood samples were collected from ten patients diagnosed with HS upon admission to the intensive care unit (six with severe HS and four with mild HS). Samples from six healthy volunteers were included as control. Using ultracentrifugation, exosomes were prudently isolated, and their protein contents were profiled using liquid chromatography–tandem mass spectrometry analysis with isobaric tags for relative and absolute quantification-based proteomics.
Results: Compared with healthy volunteers, patients with HS showed significant changes in the levels of 33 exosomal proteins (23 upregulated and 10 downregulated). The most upregulated proteins included serum amyloid A-1 (SAA-1), von Willebrand factor (vWF), S100A8, and histone H3. In addition, SAA-1, vWF, platelet membrane glycoprotein, S100A8, and histone H3 were more enriched in the exosomes from patients with severe HS than from those with mild HS. Gene ontology analysis revealed that the HS-modulated exosomal proteins were mostly related to inflammatory response, including the acute-phase response, platelet activation/degranulation, and innate immune response. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed significant enrichment of proteins in the IL-17 signaling pathway, platelet activation, neutrophil extracellular trap formation, Fc epsilon RI signaling pathway, chemokine signaling pathway, and NOD-like receptor signaling pathway, among others. Several serum exosomal proteins, including SAA-1, vWF, and S100A8, which are related to the acute phase, inflammatory response, and platelet activation, were confirmed to be elevated in patients with HS, and were significantly correlated with disease severity, organ dysfunction, and death.
Conclusion: Overall, this study explores the potential role of the serum exosomal proteome in the inflammatory response and platelet activation in HS, suggests the pathological mechanisms underlying HS-induced injuries, and recommends reliable exosomal biomarkers for predicting HS prognosis.
Background: The pathological mechanism of heat stroke (HS) involves the acute phase response, unbalanced immunological/inflammatory reactions, and coagulation initiation, especially platelet activation. Although exosomes contain proteins involved in these biological processes, their protein cargo levels and potential roles in HS remain unknown. This study explored the serum exosome protein expression patterns after HS and their potential roles in the pathogenesis of HS.Methods: Blood samples were collected from ten patients diagnosed with HS upon admission to the intensive care unit (six with severe HS and four with mild HS). Samples from six healthy volunteers were included as control. Using ultracentrifugation, exosomes were prudently isolated, and their protein contents were profiled using liquid chromatography–tandem mass spectrometry analysis with isobaric tags for relative and absolute quantification-based proteomics.Results: Compared with healthy volunteers, patients with HS showed significant changes in the levels of 33 exosomal proteins (23 upregulated and 10 downregulated). The most upregulated proteins included serum amyloid A-1 (SAA-1), von Willebrand factor (vWF), S100A8, and histone H3. In addition, SAA-1, vWF, platelet membrane glycoprotein, S100A8, and histone H3 were more enriched in the exosomes from patients with severe HS than from those with mild HS. Gene ontology analysis revealed that the HS-modulated exosomal proteins were mostly related to inflammatory response, including the acute-phase response, platelet activation/degranulation, and innate immune response. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed significant enrichment of proteins in the IL-17 signaling pathway, platelet activation, neutrophil extracellular trap formation, Fc epsilon RI signaling pathway, chemokine signaling pathway, and NOD-like receptor signaling pathway, among others. Several serum exosomal proteins, including SAA-1, vWF, and S100A8, which are related to the acute phase, inflammatory response, and platelet activation, were confirmed to be elevated in patients with HS, and were significantly correlated with disease severity, organ dysfunction, and death.Conclusion: Overall, this study explores the potential role of the serum exosomal proteome in the inflammatory response and platelet activation in HS, suggests the pathological mechanisms underlying HS-induced injuries, and recommends reliable exosomal biomarkers for predicting HS prognosis.The mortality of hospitalized patients with COVID-19 and non-cirrhotic chronic liver disease: a retrospective multi-center studyhttps://peerj.com/articles/165822023-12-042023-12-04Pei-Jui WuI-Che FengChih-Cheng LaiChung-Han HoWei-Chih KanMing-Jen SheuHsing-Tao Kuo
Background
Patients with chronic liver disease (CLD) have a higher risk of mortality when infected with severe acute respiratory syndrome coronavirus 2. Although the fibrosis-4 (FIB-4) index, aspartate aminotransferase-to-platelet ratio index (APRI), and albumin-bilirubin grade (ALBI) score can predict mortality in CLD, their correlation with the clinical outcomes of CLD patients with coronavirus disease 2019 (COVID-19) is unclear. This study aimed to investigate the association between the liver severity and the mortality in hospitalized patients with non-cirrhotic CLD and COVID-19.
Methods
This retrospective study analyzed 231 patients with non-cirrhotic CLD and COVID-19. Clinical characteristics, laboratory data, including liver status indices, and clinical outcomes were assessed to determine the correlation between liver status indices and the mortality among patients with non-cirrhotic CLD and COVID-19.
Results
Non-survivors had higher levels of prothrombin time-international normalized ratio (PT-INR), alanine aminotransferase, aspartate aminotransferase, and high-sensitivity C-reactive protein (hs-CRP) and lower albumin levels. Multivariable analysis showed that ALBI grade 3 (odds ratio (OR): 22.80, 95% confidence interval (CI) [1.70–305.38], p = 0.018), FIB-4 index ≥ 3.25 (OR: 10.62, 95% CI [1.12–100.31], p = 0.039), PT-INR (OR: 19.81, 95% CI [1.31–299.49], p = 0.031), hs-CRP (OR: 1.02, 95% CI [1.01–1.02], p = 0.001), albumin level (OR: 0.08, 95% CI [0.02–0.39], p = 0.002), and use of vasopressors (OR: 4.98, 95% CI [1.27–19.46], p = 0.021) were associated with the mortality.
Conclusion
The ALBI grade 3 and FIB-4 index ≥ 3.25, higher PT-INR, hsCRP levels and lower albumin levels could be associated with mortality in non-cirrhotic CLD patients with COVID-19. Clinicians could assess the ALBI grade, FIB-4 index, PT-INR, hs-CRP, and albumin levels of patients with non-cirrhotic CLD upon admission.
Background
Patients with chronic liver disease (CLD) have a higher risk of mortality when infected with severe acute respiratory syndrome coronavirus 2. Although the fibrosis-4 (FIB-4) index, aspartate aminotransferase-to-platelet ratio index (APRI), and albumin-bilirubin grade (ALBI) score can predict mortality in CLD, their correlation with the clinical outcomes of CLD patients with coronavirus disease 2019 (COVID-19) is unclear. This study aimed to investigate the association between the liver severity and the mortality in hospitalized patients with non-cirrhotic CLD and COVID-19.
Methods
This retrospective study analyzed 231 patients with non-cirrhotic CLD and COVID-19. Clinical characteristics, laboratory data, including liver status indices, and clinical outcomes were assessed to determine the correlation between liver status indices and the mortality among patients with non-cirrhotic CLD and COVID-19.
Results
Non-survivors had higher levels of prothrombin time-international normalized ratio (PT-INR), alanine aminotransferase, aspartate aminotransferase, and high-sensitivity C-reactive protein (hs-CRP) and lower albumin levels. Multivariable analysis showed that ALBI grade 3 (odds ratio (OR): 22.80, 95% confidence interval (CI) [1.70–305.38], p = 0.018), FIB-4 index ≥ 3.25 (OR: 10.62, 95% CI [1.12–100.31], p = 0.039), PT-INR (OR: 19.81, 95% CI [1.31–299.49], p = 0.031), hs-CRP (OR: 1.02, 95% CI [1.01–1.02], p = 0.001), albumin level (OR: 0.08, 95% CI [0.02–0.39], p = 0.002), and use of vasopressors (OR: 4.98, 95% CI [1.27–19.46], p = 0.021) were associated with the mortality.
Conclusion
The ALBI grade 3 and FIB-4 index ≥ 3.25, higher PT-INR, hsCRP levels and lower albumin levels could be associated with mortality in non-cirrhotic CLD patients with COVID-19. Clinicians could assess the ALBI grade, FIB-4 index, PT-INR, hs-CRP, and albumin levels of patients with non-cirrhotic CLD upon admission.Significant improvement in survival outcomes of trisomy 18 with neonatal intensive care compared to non-intensive care: a single-center studyhttps://peerj.com/articles/165372023-11-292023-11-29Shigeki KoshidaKentaro Takahashi
Background
Trisomy 18 syndrome, also known as Edwards syndrome, is a chromosomal trisomy. The syndrome has historically been considered lethal owing to its poor prognosis, and palliative care was primarily indicated for trisomy 18 neonates. Although there have been several reports on the improvement of survival outcomes in infants with trisomy 18 syndrome through neonatal intensive care, few studies have compared the impact of neonatal intensive care on survival outcomes with that of non-intensive care. Therefore, we compared the survival-related outcomes of neonates with trisomy 18 between intensive and non-intensive care.
Methods
Seventeen infants of trisomy 18 admitted to our center between 2007 and 2019 were retrospectively studied. We divided the patients into a non-intensive group (n = 5) and an intensive group (n = 12) and evaluated their perinatal background and survival-related outcomes of the two groups.
Results
The 1- and 3-year survival rates were both 33% in the intensive group, which was significantly higher than that in the non-intensive group (p < 0.001). Half of the infants in the intensive care group were discharged alive, whereas in the non-intensive care group, all died during hospitalization (p = 0.049).
Conclusions
Neonatal intensive care for neonates with 18 trisomy significantly improved not only survival rates but also survival-discharge rates. Our findings would be helpful in providing 18 trisomy neonates with standard neonatal intensive care when discussing medical care with their parents.
Background
Trisomy 18 syndrome, also known as Edwards syndrome, is a chromosomal trisomy. The syndrome has historically been considered lethal owing to its poor prognosis, and palliative care was primarily indicated for trisomy 18 neonates. Although there have been several reports on the improvement of survival outcomes in infants with trisomy 18 syndrome through neonatal intensive care, few studies have compared the impact of neonatal intensive care on survival outcomes with that of non-intensive care. Therefore, we compared the survival-related outcomes of neonates with trisomy 18 between intensive and non-intensive care.
Methods
Seventeen infants of trisomy 18 admitted to our center between 2007 and 2019 were retrospectively studied. We divided the patients into a non-intensive group (n = 5) and an intensive group (n = 12) and evaluated their perinatal background and survival-related outcomes of the two groups.
Results
The 1- and 3-year survival rates were both 33% in the intensive group, which was significantly higher than that in the non-intensive group (p < 0.001). Half of the infants in the intensive care group were discharged alive, whereas in the non-intensive care group, all died during hospitalization (p = 0.049).
Conclusions
Neonatal intensive care for neonates with 18 trisomy significantly improved not only survival rates but also survival-discharge rates. Our findings would be helpful in providing 18 trisomy neonates with standard neonatal intensive care when discussing medical care with their parents.Predictive value of machine learning for the risk of acute kidney injury (AKI) in hospital intensive care units (ICU) patients: a systematic review and meta-analysishttps://peerj.com/articles/164052023-11-272023-11-27Yuan Hong DuCheng Jing GuanLin Yu LiPing Gan
Background
Recent studies suggest machine learning represents a promising predictive option for patients in intensive care units (ICU). However, the machine learning performance regarding its actual predictive value for early detection in acute kidney injury (AKI) patients remains uncertain.
Objective
This study represents the inaugural meta-analysis aiming to investigate the predictive value of machine learning for assessing the risk of AKI among ICU patients.
Methods
PubMed, Web of Science, Embase, and the Cochrane Library were all thoroughly searched from inception to June 25, 2022. Eligible studies for inclusion were those concentrating on the predictive value and the development, validation, or enhancement of a prediction model for AKI patients in the ICU. Measures of effects, including c-index, sensitivity, specificity, and their corresponding 95% confidence intervals (CIs), were employed for analysis. The risk of bias in the included original studies was assessed using Probst. The meta-analysis in our study was carried out using R version 4.2.0.
Results
The systematic search yielded 29 articles describing 13 machine-learning models, including 86 models in the training set and 57 in the validation set. The overall c-index was 0.767 (95% CI [0.746, 0.788]) in the training set and 0.773 (95% CI [0.741, 0.804]) in the validation set. The sensitivity and specificity of included studies are as follows: sensitivity [train: 0.66 (95% CI [0.59, 0.73]), validation: 0.73 (95% CI [0.68, 0.77])]; and specificity [train: 0.83 (95% CI [0.78, 0.87])], validation: 0.75 (95% CI [0.71, 0.79])].
Conclusion
The machine learning-based method for predicting the risk of AKI in hospital ICU patients has excellent predictive value and could potentially serve as a prospective application strategy for early identification. PROSPERO Registration number ID: CRD42022362838.
Background
Recent studies suggest machine learning represents a promising predictive option for patients in intensive care units (ICU). However, the machine learning performance regarding its actual predictive value for early detection in acute kidney injury (AKI) patients remains uncertain.
Objective
This study represents the inaugural meta-analysis aiming to investigate the predictive value of machine learning for assessing the risk of AKI among ICU patients.
Methods
PubMed, Web of Science, Embase, and the Cochrane Library were all thoroughly searched from inception to June 25, 2022. Eligible studies for inclusion were those concentrating on the predictive value and the development, validation, or enhancement of a prediction model for AKI patients in the ICU. Measures of effects, including c-index, sensitivity, specificity, and their corresponding 95% confidence intervals (CIs), were employed for analysis. The risk of bias in the included original studies was assessed using Probst. The meta-analysis in our study was carried out using R version 4.2.0.
Results
The systematic search yielded 29 articles describing 13 machine-learning models, including 86 models in the training set and 57 in the validation set. The overall c-index was 0.767 (95% CI [0.746, 0.788]) in the training set and 0.773 (95% CI [0.741, 0.804]) in the validation set. The sensitivity and specificity of included studies are as follows: sensitivity [train: 0.66 (95% CI [0.59, 0.73]), validation: 0.73 (95% CI [0.68, 0.77])]; and specificity [train: 0.83 (95% CI [0.78, 0.87])], validation: 0.75 (95% CI [0.71, 0.79])].
Conclusion
The machine learning-based method for predicting the risk of AKI in hospital ICU patients has excellent predictive value and could potentially serve as a prospective application strategy for early identification. PROSPERO Registration number ID: CRD42022362838.