Association between self-efficacy, spiritual well-being and the willingness to provide spiritual care among nursing staff in Taiwan: a cross-sectional study.

BACKGROUND: Spiritual care plays a significant role in holistic patient care, addressing not only physical ailments but also attending to patients' emotional and spiritual well-being. While the importance of spiritual care in nursing is widely recognized, there is often a gap in understanding nurses' willingness to provide such care. This cross-sectional study aimed to explore the association between self-efficacy, spiritual well-being, and willingness to provide spiritual care among nursing staff. METHODS: The study conducted a cross-sectional survey of full-time registered nurses at a hospital in Taiwan from January 2019 to December 2019. A sample comprising 168 nurses was selected for participation in the study through a random sampling method. In addition to collecting demographic variables, the assessment tools used in the study include the General Self-Efficacy Scale (GSES) for measuring self-efficacy, the Spiritual Index of Well-Being Chinese Version (SIWB-C) for evaluating spiritual well-being, and the Spiritual Care Needs Inventory (SCNI) to gauge willingness to provide spiritual care. RESULTS: Most participants in the study were female, accounting for 98.2% (n = 165). The mean age of all 168 nurses was 37.1 ± 9.3 years. Additionally, most participants held a Bachelor's degree (79.2%, n = 133) and possessed clinical experience was 10.5 ± 9.3 years. Through logistic regression analysis, it was found that regardless of whether participants have received sufficient spiritual care training, both GSES and SIWB-C remain influential factors in determining the provision of spiritual care. CONCLUSIONS: Collaboration between healthcare management and nursing staff is essential for fostering a healthcare environment that not only appreciates the physical and spiritual dimensions of patient care but also prioritizes the enhancement of nurses ' self-efficacy and well-being.

Comparative Efficacy of Pharmacological Treatments for Acne Vulgaris: A Network Meta-Analysis of 221 Randomized Controlled Trials.

PURPOSE: Acne is an extremely common skin disease with an estimated global prevalence of 9.4%. We aim to provide comprehensive comparisons of the common pharmacological treatments for acne. METHODS: Randomized controlled trials comparing the efficacy of pharmacological therapies for acne vulgaris in patients of any age and sex and with a treatment duration of >2 weeks were included. PubMed and Embase databases were searched from inception until February 2022. Our prespecified primary end points were mean percentage reduction in total, inflammatory, and noninflammatory lesions. Treatment ranking was determined by P values. RESULTS: There were 210 articles describing 221 trials and 37 interventions included in the analysis. Our primary analysis of percentage reduction in total lesion count had 65,601 patients enrolled. Across all trials, the mean age was 20.4 years. The median duration of treatment was 12 weeks. The median total, inflammatory, and noninflammatory lesion counts were 72, 27, and 44, respectively. The most effective treatment was oral isotretinoin (mean difference [MD] = 48.41; P = 1.00), followed by triple therapy containing a topical antibiotic, a topical retinoid, and benzoyl peroxide (BPO) (MD = 38.15; P = .95) and by triple therapy containing an oral antibiotic, a topical retinoid, and BPO (MD = 34.83; P = .90). For monotherapies, oral or topical antibiotics or topical retinoids have comparable efficacy for inflammatory lesions, while oral or topical antibiotics have less effect on noninflammatory lesions. CONCLUSION: The most effective treatment for acne is oral isotretinoin, followed by triple therapies containing a topical retinoid, BPO, and an antibiotic. We present detailed comparisons of each intervention to serve as a practical database.

Performance of the European Society of Cardiology 0/1-Hour, 0/2-Hour, and 0/3-Hour Algorithms for Rapid Triage of Acute Myocardial Infarction : An International Collaborative Meta-analysis.

BACKGROUND: The 2020 European Society of Cardiology (ESC) guidelines recommend using the 0/1-hour and 0/2-hour algorithms over the 0/3-hour algorithm as the first and second choices of high-sensitivity cardiac troponin (hs-cTn)-based strategies for triage of patients with suspected acute myocardial infarction (AMI). PURPOSE: To evaluate the diagnostic accuracies of the ESC 0/1-hour, 0/2-hour, and 0/3-hour algorithms. DATA SOURCES: PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, and Scopus from 1 January 2011 to 31 December 2020. (PROSPERO: CRD42020216479). STUDY SELECTION: Prospective studies that evaluated the ESC 0/1-hour, 0/2-hour, or 0/3-hour algorithms in adult patients presenting with suspected AMI. DATA EXTRACTION: The primary outcome was index AMI. Twenty unique cohorts were identified. Primary data were obtained from investigators of 16 cohorts and aggregate data were extracted from 4 cohorts. Two independent authors assessed each study for methodological quality. DATA SYNTHESIS: A total of 32 studies (20 cohorts) with 30 066 patients were analyzed. The 0/1-hour algorithm had a pooled sensitivity of 99.1% (95% CI, 98.5% to 99.5%) and negative predictive value (NPV) of 99.8% (CI, 99.6% to 99.9%) for ruling out AMI. The 0/2-hour algorithm had a pooled sensitivity of 98.6% (CI, 97.2% to 99.3%) and NPV of 99.6% (CI, 99.4% to 99.8%). The 0/3-hour algorithm had a pooled sensitivity of 93.7% (CI, 87.4% to 97.0%) and NPV of 98.7% (CI, 97.7% to 99.3%). Sensitivity of the 0/3-hour algorithm was attenuated in studies that did not use clinical criteria (GRACE score <140 and pain-free) compared with studies that used clinical criteria (90.2% [CI, 82.9 to 94.6] vs. 98.4% [CI, 88.6 to 99.8]). All 3 algorithms had similar specificities and positive predictive values for ruling in AMI, but heterogeneity across studies was substantial. Diagnostic performance was similar across the hs-cTnT (Elecsys; Roche), hs-cTnI (Architect; Abbott), and hs-cTnI (Centaur/Atellica; Siemens) assays. LIMITATION: Diagnostic accuracy, inclusion and exclusion criteria, and cardiac troponin sampling time varied among studies. CONCLUSION: The ESC 0/1-hour and 0/2-hour algorithms have higher sensitivities and NPVs than the 0/3-hour algorithm for index AMI. PRIMARY FUNDING SOURCE: National Taiwan University Hospital.

Temporal Trends in the Microbiological Characteristics of Sepsis in the United States: A Population Based Study.

BACKGROUND: Epidemiologic studies are needed for monitoring population-level trends in sepsis. This study examines sepsis-causing microorganisms from 2006 to 2014 in the United States using data from the Nationwide Inpatient Sample database. METHODS: 7 860 686 adults hospitalized with sepsis were identified using a validated ICD-9 coding approach. Associated microorganisms were identified by ICD-9 code and classified by major groups (Gram-positive, Gram-negative, fungi, anaerobes) and specific species for analysis of their incidence and mortality. RESULTS: The rate of sepsis incidence has increased for all four major categories of pathogens, while the mortality rate decreased. In 2014, Gram-negative pathogens had a higher incidence than Gram-positives. Anaerobes increased the fastest with an average annual increase of 20.17% (p < 0.001). Fungi had the highest mortality (19.28%) and the slowest annual decrease of mortality (-2.31%, p = 0.006) in 2013, while anaerobic sepsis had the highest hazard of mortality (adjusted HR 1.60, 95% CI 1.53-1.66). CONCLUSIONS: Gram-negative pathogens have replaced Gram-positives as the leading cause of sepsis in the United States in 2014 during the study period (2006-2014). The incidence of anaerobic sepsis has an annual increase of 20%, while the mortality of fungal sepsis has not decreased at the same rate as other microorganisms. These findings should inform the diagnosis and management of septic patients, as well as the implementation of public health programs.

Association Between Aspirin Use and Sepsis Outcomes: A National Cohort Study.

BACKGROUND: Aspirin has anti-inflammatory and antiplatelet activities and directly inhibits bacterial growth. These effects of aspirin may improve survival in patients with sepsis. We retrospectively reviewed a large national health database to test the relationship between prehospital aspirin use and sepsis outcomes. METHODS: We conducted a retrospective population-based cohort study using the National Health Insurance Research Database of Taiwan from 2001 to 2011 to examine the relationship between aspirin use before hospital admission and sepsis outcomes. The association between aspirin use and 90-day mortality in sepsis patients was determined using logistic regression models and weighting patients by the inverse probability of treatment weighting (IPTW) with the propensity score. Kaplan-Meier survival curves for each IPTW cohort were plotted for 90-day mortality. For sensitivity analyses, restricted mean survival times (RMSTs) were calculated based on Kaplan-Meier curves with 3-way IPTW analysis comparing current use, past use, and nonuse. RESULTS: Of 52,982 patients with sepsis, 12,776 took aspirin before hospital admission (users), while 39,081 did not take any antiplatelet agents including aspirin before hospital admission (nonusers). After IPTW analysis, we found that when compared to nonusers, patients who were taking aspirin within 90 days before sepsis onset had a lower 90-day mortality rate (IPTW odds ratio [OR], 0.90; 95% confidence interval [CI], 0.88-0.93; P < .0001). Based on IPTW RMST analysis, nonusers had an average survival of 71.75 days, while current aspirin users had an average survival of 73.12 days. The difference in mean survival time was 1.37 days (95% CI, 0.50-2.24; P = .002). CONCLUSIONS: Aspirin therapy before hospital admission is associated with a reduced 90-day mortality in sepsis patients.

Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach.

BACKGROUND: Although machine learning (ML) algorithms have been applied to point-of-care sepsis prognostication, ML has not been used to predict sepsis mortality in an administrative database. Therefore, we examined the performance of common ML algorithms in predicting sepsis mortality in adult patients with sepsis and compared it with that of the conventional context knowledge-based logistic regression approach. OBJECTIVE: The aim of this study is to examine the performance of common ML algorithms in predicting sepsis mortality in adult patients with sepsis and compare it with that of the conventional context knowledge-based logistic regression approach. METHODS: We examined inpatient admissions for sepsis in the US National Inpatient Sample using hospitalizations in 2010-2013 as the training data set. We developed four ML models to predict in-hospital mortality: logistic regression with least absolute shrinkage and selection operator regularization, random forest, gradient-boosted decision tree, and deep neural network. To estimate their performance, we compared our models with the Super Learner model. Using hospitalizations in 2014 as the testing data set, we examined the models' area under the receiver operating characteristic curve (AUC), confusion matrix results, and net reclassification improvement. RESULTS: Hospitalizations of 923,759 adults were included in the analysis. Compared with the reference logistic regression (AUC: 0.786, 95% CI 0.783-0.788), all ML models showed superior discriminative ability (P<.001), including logistic regression with least absolute shrinkage and selection operator regularization (AUC: 0.878, 95% CI 0.876-0.879), random forest (AUC: 0.878, 95% CI 0.877-0.880), xgboost (AUC: 0.888, 95% CI 0.886-0.889), and neural network (AUC: 0.893, 95% CI 0.891-0.895). All 4 ML models showed higher sensitivity, specificity, positive predictive value, and negative predictive value compared with the reference logistic regression model (P<.001). We obtained similar results from the Super Learner model (AUC: 0.883, 95% CI 0.881-0.885). CONCLUSIONS: ML approaches can improve sensitivity, specificity, positive predictive value, negative predictive value, discrimination, and calibration in predicting in-hospital mortality in patients hospitalized with sepsis in the United States. These models need further validation and could be applied to develop more accurate models to compare risk-standardized mortality rates across hospitals and geographic regions, paving the way for research and policy initiatives studying disparities in sepsis care.

Accuracy of Heparin-Binding Protein in Diagnosing Sepsis: A Systematic Review and Meta-Analysis.

OBJECTIVES: Existing studies evaluating the accuracy of heparin-binding protein for the diagnosis of sepsis have been inconsistent. We conducted a systematic review and meta-analysis to assess the totality of current evidence regarding the utility of heparin-binding protein to diagnose sepsis in patients with presumed systemic infection. DATA SOURCE: PubMed, Embase, the China National Knowledge infrastructure, and WangFang electronic database were searched from inception to December of 2019. STUDY SELECTION: Two independent reviewers identified eligible studies. Cohort and case-control studies, which measured serum levels of heparin-binding protein among adult patients with suspected sepsis, were eligible for inclusion. DATA EXTRACTION: Two reviewers independently extracted data elements from the selected studies. A bivariate random-effects meta-analysis model was used to synthesize the prognostic accuracy measures. Risk of bias of studies was assessed with Quality Assessment of Diagnostic Accuracy Studies 2 tool. DATA SYNTHESIS: We identified 26 studies with 3,868 patients in the meta-analysis. Heparin-binding protein had a pooled sensitivity of 0.85 (95% CI, 0.79-0.90) and a pooled specificity of 0.91 (95% CI, 0.82-0.96) for the diagnosis of sepsis. There was low heterogeneity between the studies (I2 = 12%), and no evidence of publication bias was detected. Heparin-binding protein had a higher sensitivity and specificity when compared with procalcitonin (0.75 [95% CI, 0.62-0.85] and 0.85 [95% CI, 0.73-0.92]) as well as C-reactive protein (0.75 [95% CI, 0.65-0.84] and 0.71 [95% CI, 0.63-0.77]). Serial measurements of heparin-binding protein also showed that heparin-binding protein levels rose significantly at least 24 hours before a diagnosis of sepsis. CONCLUSIONS: The diagnostic ability of heparin-binding protein is favorable, demonstrating both high sensitivity and specificity in predicting progression to sepsis in critically ill patients. Future studies could assess the incremental value that heparin-binding protein may add to a multimodal sepsis identification and prognostication algorithm for critically ill patients.

Optimal initial antibiotic regimen for the treatment of acute appendicitis: a systematic review and network meta-analysis with surgical intervention as the common comparator.

BACKGROUND: The optimal antibiotic regimen for the medical management of acute appendicitis remains unknown due to a lack of head-to-head comparisons between different antibiotic regimens. METHODS: We systematically searched the PubMed, EMBASE, Scopus and Cochrane Central Register of Controlled Trials databases from their inception through to August 2020. We selected randomized controlled trials (RCTs) or observational studies comparing antibiotic therapy and appendectomy as the initial treatment for adult or paediatric patients with acute appendicitis. We performed a Bayesian network meta-analysis (NMA) to obtain the indirect comparison results between different antibiotic regimens by employing the group managed by surgery as a common comparator. Antibiotic regimens were classified into three categories: those including a carbapenem; those including a cephalosporin; and those including a ß-lactam/ß-lactamase inhibitor combination. RESULTS: A total of 9 RCTs (adults, n = 8; paediatrics, n = 1) and 12 observational studies (adults, n = 3; paediatrics, n = 9) were included in the NMA, with a total of 4551 patients. The most commonly administered regimen was a ß-lactam/ß-lactamase inhibitor combination (9/21; 43%), followed by a cephalosporin (7/21; 33%) or a carbapenem (5/21; 24%). The NMA indicated that surgery significantly increased 1 year treatment success, compared with cephalosporins [OR: 16.79; 95% credible interval: 3.8-127.64] or ß-lactam/ß-lactamase inhibitor combinations (OR: 19.99; 95% credible interval: 4.87-187.57), but not carbapenems (OR: 3.50, 95% credible interval: 0.55-38.63). In contrast, carbapenems were associated with fewer treatment-related complications compared with surgery (OR: 0.12; 95% credible interval: 0.01-0.85). CONCLUSIONS: Carbapenems might be recommended as the initial antibiotic regimen for the non-operative management of adult patients with acute appendicitis. Nevertheless, due to the imprecise estimates in our NMA, additional RCTs are needed to corroborate these findings, especially for paediatric patients.

Comparing mortality between positive and negative blood culture results: an inverse probability of treatment weighting analysis of a multicenter cohort.

BACKGROUND: The association between blood culture status and mortality among sepsis patients remains controversial hence we conducted a tri-center retrospective cohort study to compare the early and late mortality of culture-negative versus culture-positive sepsis using the inverse probability of treatment weighting (IPTW) method. METHODS: Adult patients with suspected sepsis who completed the blood culture and procalcitonin tests in the emergency department or hospital floor were eligible for inclusion. Early mortality was defined as 30-day mortality, and late mortality was defined as 30- to 90-day mortality. IPTW was calculated from propensity score and was employed to create two equal-sized hypothetical cohorts with similar covariates for outcome comparison. RESULTS: A total of 1405 patients met the inclusion criteria, of which 216 (15.4%) yielded positive culture results and 46 (21.3%) died before hospital discharge. The propensity score model showed that diabetes mellitus, urinary tract infection, and hepatobiliary infection were independently associated with positive blood culture results. There was no significant difference in early mortality between patients with positive or negative blood culture results. However, culture-positive patients had increased late mortality as compared with culture-negative patients in the full cohort (IPTW-OR, 1.95, 95%CI: 1.14-3.32) and in patients with severe sepsis or septic shock (IPTW-OR, 1.92, 95%CI: 1.10-3.33). After excluding Staphylococcal bacteremia patients, late mortality difference became nonsignificant (IPTW-OR, 1.78, 95%CI: 0.87-3.62). CONCLUSIONS: Culture-positive sepsis patients had comparable early mortality but worse late mortality than culture-negative sepsis patients in this cohort. Persistent Staphylococcal bacteremia may have contributed to the increased late mortality.

Survival Impact and Clinical Predictors of Acute Gastrointestinal Bleeding in Patients With Bloodstream Infection.

PURPOSE: The impact of gastrointestinal bleeding (GIB) on outcomes of patients with bloodstream infection (BSI) has not been studied. We aim to evaluate the risk factors and survival impact of GIB on the outcome of BSI. MATERIALS AND METHODS: This study was conducted prospectively at National Taiwan University Hospital Yunlin Branch between January 1, 2015, and December 31, 2016. Patients aged ≥18 years for who BSI was confirmed by blood cultures were enrolled and followed for 90 days. Risk factors of GIB were identified by univariable and multivariable logistic regression models. The survival impact of GIB on BSI was evaluated with the Cox proportional hazards model with inverse probability of treatment weighting. RESULTS: Of the 1034 patients with BSI, 79 (7.64%) developed acute GIB. We identified 5 independent predictors of GIB. Patients with BSI complicated with GIB had an increased 90-day mortality compared to patients without GIB (hazard ratio 1.74, 95% confidence interval: 1.14, 2.65). CONCLUSIONS: Gastrointestinal bleeding had an adverse impact on the short-term survival in patients with BSI. The clinical predictors may help identify patients who may benefit from active prevention and treatment of GIB.

Performance and Limitation of Machine Learning Algorithms for Diabetic Retinopathy Screening: Meta-analysis.

BACKGROUND: Diabetic retinopathy (DR), whose standard diagnosis is performed by human experts, has high prevalence and requires a more efficient screening method. Although machine learning (ML)-based automated DR diagnosis has gained attention due to recent approval of IDx-DR, performance of this tool has not been examined systematically, and the best ML technique for use in a real-world setting has not been discussed. OBJECTIVE: The aim of this study was to systematically examine the overall diagnostic accuracy of ML in diagnosing DR of different categories based on color fundus photographs and to determine the state-of-the-art ML approach. METHODS: Published studies in PubMed and EMBASE were searched from inception to June 2020. Studies were screened for relevant outcomes, publication types, and data sufficiency, and a total of 60 out of 2128 (2.82%) studies were retrieved after study selection. Extraction of data was performed by 2 authors according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), and the quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Meta-analysis of diagnostic accuracy was pooled using a bivariate random effects model. The main outcomes included diagnostic accuracy, sensitivity, and specificity of ML in diagnosing DR based on color fundus photographs, as well as the performances of different major types of ML algorithms. RESULTS: The primary meta-analysis included 60 color fundus photograph studies (445,175 interpretations). Overall, ML demonstrated high accuracy in diagnosing DR of various categories, with a pooled area under the receiver operating characteristic (AUROC) ranging from 0.97 (95% CI 0.96-0.99) to 0.99 (95% CI 0.98-1.00). The performance of ML in detecting more-than-mild DR was robust (sensitivity 0.95; AUROC 0.97), and by subgroup analyses, we observed that robust performance of ML was not limited to benchmark data sets (sensitivity 0.92; AUROC 0.96) but could be generalized to images collected in clinical practice (sensitivity 0.97; AUROC 0.97). Neural network was the most widely used method, and the subgroup analysis revealed a pooled AUROC of 0.98 (95% CI 0.96-0.99) for studies that used neural networks to diagnose more-than-mild DR. CONCLUSIONS: This meta-analysis demonstrated high diagnostic accuracy of ML algorithms in detecting DR on color fundus photographs, suggesting that state-of-the-art, ML-based DR screening algorithms are likely ready for clinical applications. However, a significant portion of the earlier published studies had methodology flaws, such as the lack of external validation and presence of spectrum bias. The results of these studies should be interpreted with caution.

High-sensitivity-cardiac troponin for accelerated diagnosis of acute myocardial infarction: A systematic review and meta-analysis.

OBJECTIVES: Cardiovascular disease is the leading cause of mortality and morbidity. Serial troponin tests have been endorsed as essential diagnostic steps to rule out/-in acute myocardial infarction (AMI), and hs-cTn assays have shown promise in enhancing the accuracy and efficiency of AMI diagnosis in the emergency department (ED). METHODS: A systematic review and meta-analysis of diagnostic test accuracy studies were conducted to compare the diagnostic performance of various accelerated diagnostic algorithms of hs-cTn assays for patients with symptoms of AMI. Random-effects bivariate meta-analysis was conducted to estimate the summary sensitivity, specificity, likelihood ratios, and area under receiver operating characteristic curve. RESULTS: In the systematic review consisting of 56 studies and 67,945 patients, both hs-cTnT and hs-cTnI-based 0-, 1-, 2- and 0-1 h algorithms showed a pooled sensitivity >90%. The hs-cTnI-based algorithm showed a pooled specificity >80%. The hs-cTnT-based algorithms had a specificity of 68% for the 0-h algorithm and of around 80% for the 1-, 2-, and 0-1 h algorithms. The heterogeneities of all diagnostic algorithms were mild (I2 < 50%). CONCLUSION: Both hs-cTnI- and hs-cTnT-based accelerated diagnostic algorithms have high sensitivities but moderate specificities for early diagnosis of AMI. Overall, hs-cTnI-based algorithms have slightly higher specificities in early diagnosis of AMI. For patients presenting ED with typical symptoms, the use of hs-cTnT or hs-cTnI assays at the 99th percentile may help identify patients with low risk for AMI and promote early discharge from the ED.

Activation of NOTCH1 by Shear Force Elicits Immediate Cytokine Expression in Human Chondrocytes.

Osteoarthritis is caused by overloading of joints and is characterized by inflammation-induced disruption of cartilage structure. Current treatment strategy aims to relieve inflammation and prevent further deterioration of joint function. However, how mechanical force leads to inflammation and deterioration of chondrocyte function still remains incompletely understood. To explore the force-regulated molecular mechanism, an in vitro hydraulic shear force experiment to simulate the condition of force loading was required. The result demonstrated that multiple cytokines and immune regulators, including interleukin 8, interferon ß, TRAF1 and TNFAIP3, were significantly increased by shear force within two hours of treatment. Moreover, JAG1 and HES1 were drastically upregulated as well, suggesting that NOTCH1 signaling is activated by shear force. Short-term expression of NOTCH1 intracellular domain activated a similar set of cytokines, indicating that NOTCH1 responds to shear force and activates downstream genes. When incubated under the medium conditioned by NOTCH1-activated chondrocyte, osteoblasts expressed higher levels of interferon ß and interferon λ. Together, our results indicated that NOTCH1 functions as a force sensor and promotes expression of cytokines and immune regulators from shear-force bearing chondrocytes.

Web-Based Dashboard for the Interactive Visualization and Analysis of National Risk-Standardized Mortality Rates of Sepsis in the US.

Sepsis mortality is heavily influenced by the quality of care in hospitals. Comparing risk-standardized mortality rate (RSMR) of sepsis patients in different states in the United States has potentially important clinical and policy implications. In the current study, we aimed to compare national sepsis RSMR using an interactive web-based dashboard. We analyzed sepsis mortality using the National Inpatient Sample Database of the US. The RSMR was calculated by the hierarchical logistic regression model. We wrote the interactive web-based dashboard using the Shiny framework, an R package that integrates R-based statistics computation and graphics generation. Visual summarizations (e.g., heat map, and time series chart), and interactive tools (e.g., year selection, automatic year play, map zoom, copy or print data, ranking data by name or value, and data search) were implemented to enhance user experience. The web-based dashboard (https://sepsismap.shinyapps.io/index2/) is cross-platform and publicly available to anyone with interest in sepsis outcomes, health inequality, and administration of state/federal healthcare. After extrapolation to the national level, approximately 35 million hospitalizations were analyzed for sepsis mortality each year. Eight years of sepsis mortality data were summarized into four easy to understand dimensions: Sepsis Identification Criteria; Sepsis Mortality Predictors; RSMR Map; RSMR Trend. Substantial variation in RSMR was observed for different states in the US. This web-based dashboard allows anyone to visualize the substantial variation in RSMR across the whole US. Our work has the potential to support healthcare transparency, information diffusion, health decision-making, and the formulation of new public policies.

Recording 2nd order PQ:PMMA reflective VBG for diode laser output spectrum narrowing.

Two 2nd order PQ:PMMA reflecting VBGs with Bragg wavelengths of 488.8 nm and 525.6 nm were recorded using 532 nm as the recording wavelength. The formation of 2nd order PQ:PMMA VBG is explained and simulated based on the diffusion model of the PQ molecules in the PMMA matrix. The 525.6 nm VBG successfully served as the ECDL cavity mirror of a 522 nm diode laser and achieved more than 10000-fold output spectrum narrowing.

Comparison of type B dissection by open, endovascular, and medical treatments.

OBJECTIVE: This study aimed to address the shortcomings of previous clinical trials that were inadequate to prove the superiority of thoracic endovascular aortic repair (TEVAR) in managing type B aortic dissection (TBAD) over open surgery (OS) or best medical treatment (BMT). The comparative effectiveness of these three treatments was analyzed using data of the National Inpatient Sample, a large U.S. database including patients from 4378 hospitals. METHODS: Adult patients diagnosed with a primary or secondary TBAD in the years 2005 to 2012 were included for analysis. Patients who had aortic aneurysm or received cardioplegia, valve repair, or operations on vessels of the heart were excluded. A three-category propensity score was created by using a multinomial logistic regression model, a three-way matching algorithm for 1:1:1 matching was applied, and a parallel outcome comparison between the three matched treatment groups was performed. RESULTS: Of a total of 54,971 patients included in the study, we matched 17,211 into three equal-size treatment groups (OS, 5755; TEVAR, 5695; BMT, 5761). No significant difference in the 22 baseline covariates was found in the matched cohort. We found TEVAR to have a much lower mortality rate than OS (odds ratio [OR], 0.60; 95% confidence interval [CI], 0.46-0.79) or BMT (OR, 0.62; 95% CI, 0.47-0.83). Mortality rates between OS and BMT were similar (OR, 0.97; 95% CI, 0.74-1.27). We also found TEVAR to have a lower complication rate, shorter hospitalization, and lower medical cost compared with OS. CONCLUSIONS: TEVAR is superior to BMT or OS for treatment of TBAD in terms of mortality, complications, and cost.

Comparison of outcome and cost between the open, laparoscopic, and robotic surgical treatments for colon cancer: a propensity score-matched analysis using nationwide hospital record database.

BACKGROUND: There are limited studies that compare the cost and outcome of robotic-assisted surgery to open and laparoscopic surgery for colon cancer treatment. We aimed to compare the three surgical modalities for colon cancer treatment. METHODS: We performed a cohort study using the population-based Nationwide Inpatient Sample database. Patients with a primary diagnosis of colon cancer who underwent robotic, laparoscopic, or open surgeries between 2008 and 2014 were eligible for enrollment. We compared in-hospital mortality, complications, length of hospital stay, and cost for patients undergoing one of these three procedures using a multivariate adjusted logistic regression analysis and propensity score matching. RESULTS: Of the 531,536 patients undergoing surgical treatment for colon cancer during the study period, 348,645 (65.6%) patients underwent open surgeries, 174,748 (32.9%) underwent laparoscopic surgeries, and 8143 (1.5%) underwent robotic surgeries. In-hospital mortality, length of hospital stay, wound complications, general medical complications, general surgical complications, and costs of the three surgical treatment modalities. Compared to those undergoing laparoscopic surgery, patients undergoing open surgery had a higher mortality rate (OR 2.98, 95% CI 2.61-3.40), more general medical complications (OR 1.77, 95% CI 1.67-1.87), a longer length of hospital stay (6.60 vs. 4.36 days), and higher total cost ($18,541 vs. $14,487) in the propensity score matched cohort. Mortality rate and general medical complications were equivalent in the laparoscopic and robotic surgery groups, but the median cost was lower in the laparoscopic group ($14641 vs. $16,628 USD). CONCLUSIONS: Laparoscopic colon cancer surgery was associated with a favourable short-term outcome and lower cost compared with open surgery. Robot-assisted surgery had comparable outcomes but higher cost as compared to laparoscopic surgery.

Upregulation of bone morphogenetic protein 1 is associated with poor prognosis of late-stage gastric Cancer patients.

BACKGROUND: Gastric cancer is the eighth most common cancer in Taiwan, with a 40% 5-year survival rate. Approximately 40% of patients are refractory to chemotherapy. Currently, the anti-HER2 therapy is the only clinically employed targeted therapy. However, only 7% patients in Taiwan are HER2-positive. Identifying candidate target genes will facilitate the development of adjuvant targeted therapy to increase the efficacy of gastric cancer treatment. METHODS: Clinical specimens were analyzed by targeted RNA sequencing to assess the expression levels of target genes. Statistical significance of differential expression and correlation between specimens was evaluated. The correlation with patient survival was analyzed as well. In vitro cell mobility was determined using wound-healing and transwell mobility assays. RESULTS: Expression of BMP1, COL1A1, STAT3, SOX2, FOXA2, and GATA6 was progressively dysregulated through the stages of gastric oncogenesis. The expression profile of these six genes forms an ubiquitously biomarker signature that is sufficient to differentiate cancer from non-cancerous specimens. High expression status of BMP1 correlates with poor long-term survival of late-stage patients. In vitro, suppression of BMP1 inhibits the mobility of the gastric cancer cell lines, indicating a role of BMP1 in metastasis. CONCLUSIONS: BMP1 is upregulated in gastric cancer and is correlated with poor patient survival. Suppression of BMP1 reduced gastric cancer mobility in vitro. Our finding suggests that anti-BMP1 therapy will likely augment the efficacy of standard chemotherapy and improve the treatment outcome.

Comparison of outcome and cost among open, laparoscopic, and robotic surgical treatments for rectal cancer: A propensity score matched analysis of nationwide inpatient sample data.

BACKGROUND: Population-based studies evaluating outcomes of different approaches for rectal cancer are scarce. METHODS: We conducted a retrospective cohort study using the Nationwide Inpatient Sample database between 2008 and 2012. We compared the outcomes and costs among rectal cancer patients undergoing robotic, laparoscopic, or open surgeries using propensity scores for adjusted and matched analysis. RESULTS: We identified 194 957 rectal cancer patients. Over the 5-year period, the annual admission number decreased by 13.9%, the in-hospital mortality rate decreased by 32.2%, while the total hospitalization cost increased by 13.6%. Compared with laparoscopic surgery, robotic surgery had significantly lower length of stay (LOS) (OR 0.69, 95%CI 0.57-0.84), comparable wound complications (OR 1.08, 95%CI 0.70-1.65) and higher cost (OR 1.42, 95%CI 1.13-1.79), while open surgery had significantly longer LOS (OR 1.38, 95%CI 1.19-1.59), more wound complications (OR 1.49, 95%CI 1.08-1.79), and comparable cost (OR 0.92, 95%CI 0.79-1.07). There were no difference in in-hospital mortality among three approaches. CONCLUSIONS: Laparoscopic surgery was associated with better outcomes than open surgery. Robotic surgery was associated with higher cost, but no advantage over laparoscopic surgery in terms of mortality and complications. Studies on cost-effectiveness of robotic surgery may be warranted.