Complexity Score Research Articles

Salient Measures of Hospitalist Workload

The ideal hospitalist workload and optimal way to measure it are not well understood. To obtain expert consensus on the salient measures of hospitalist workload. This qualitative study used a 3-round Delphi technique between April 5 and July 13, 2022, involving national experts within and external to the field. Experts included hospitalist clinicians, leaders, and administrators, as well as researchers with expertise in human factors engineering and cognitive load theory. Three rounds of surveys were conducted, during which participants provided input on the salient measures of hospitalist workload across various domains. In the first round, free-text data collected from the surveys were analyzed using a directed qualitative content approach. In the second and third rounds, participants rated each measure's relevance on a Likert scale, and consensus was evaluated using the IQR. Percentage agreement was also calculated. Seventeen individuals from 14 organizations, encompassing clinicians, leaders, administrators, and researchers, participated in 3 rounds of surveys. In round 1, participants provided 135 unique qualitative comments across 10 domains, with 192 unique measures identified. Of the 192 measures presented in the second round, 6 (3%) were considered highly relevant, and 25 (13%) were considered moderately relevant. In round 3, 161 measures not meeting consensus were evaluated, with 25 (16%) considered highly relevant and 95 (59%) considered moderately relevant. Examples of measures considered highly relevant included a patient complexity score and outcome measures such as savings from hospital days avoided and clinician turnover. In this qualitative study measuring hospitalist workload, multiple measures, including those quantifying work demands and the association of those demands with outcomes, were considered relevant for measuring and understanding workloads. The findings suggest that relying on traditional measures, such as productivity-related measures and financial measures, may offer an incomplete understanding of workloads and their association with key outcomes. By embracing a broader range of measures, organizations may be able to better capture the complexity and nuances of hospitalist work demands and their outcomes on clinicians, patients, and organizations.

Creating complexity matrix for classifying artificial intelligence applications in e-commerce: New perspectives on value creation

This research paper provides a comprehensive exploration of the role of Artificial Intelligence (AI) in value creation within the e-commerce sector, focusing on how task and information complexity affect AI deployment. It first outlines the historical development of value theory and value creation, highlighting the shift from traditional modes to modern interactive and co-creation models. Following this, the paper delves into AI’s potential in various e-commerce dimensions including personalization, product recommendation, supply chain efficiency, and more. The centrepiece of the study is a detailed matrix classifying AI into Automated Intelligence, Assisted Intelligence, and Augmented Intelligence, based on the complexity of tasks they execute and the information they analyse. This research study engaged a panel of fifteen industry and academic experts to critically examine and assign complexity scores to various Artificial Intelligence applications within the e-commerce and similar sectors. The experts evaluated task and information complexity, thereby enabling a classification of the applications into a comprehensible matrix. This classification not only provides a guide for AI system design and evaluation but also enhances understanding of their functional dynamics. The paper contributes theoretically by advancing our understanding of AI as a value creator in e-commerce and practically by offering a roadmap for businesses to adopt and leverage AI technologies. As AI continues to revolutionize the e-commerce sector, the findings of this study provide invaluable insights for businesses seeking to gain a competitive advantage in the digital marketplace.

PENYEMPURNAAN PROSES REKONSILIASI MELALUI SAKTI: PENERAPAN METODE BUSINESS PROCESS IMPROVEMENT PADA AKUNTANSI PEMERINTAH PUSAT REPUBLIK INDONESIA

REFINING RECONCILIATION PROCESS THROUGH SAKTI: AN APPLICATION OF BUSINESS PROCESS IMPROVEMENT ON GOVERNMENT ACCOUNTING IN REPUBLIC OF INDONESIASAKTI full module Implementation as an integrated government accounting system, bring significant changes on reconciliation business process for state financial transactions. MonSAKTI reconciliation business process requires an improvement to be able to maximize the reporting process and minimize reconciliation time process. This study uses Business Process Modelling and Notation (BPMN) diagram to analyze and evaluate business process as-is and business process to-be and Business Process Improvement (BPI) to reform and enhance the performance of to existing business processes. The result from analyzing and evaluating business process as-is and business process to-be is improvement on real value added process, lessen on business value added process and eliminate non value added process, so the processing time is down to 33,33% and system complexity score reduce to 19,30%.

Complexity analysis of VMAT prostate plans: insights from dimensionality reduction and information theory techniques

Abstract Introduction: Volumetric Modulated Arc Therapy (VMAT) is a state-of-the-art prostate cancer treatment, defined by high dose gradients around targets. Its unique dose shaping incurs hidden complexity, impacting treatment deliverability, carcinogenesis, and machine strain. This study compares various aperture-based VMAT complexity indices in prostate cases using principal component and mutual information analyses. It suggests essential properties for an ideal complexity index from an information-theoretic viewpoint. Material and methods: The following ten complexity indices were calculated in 217 VMAT prostate plans: circumference over area (CoA), edge metric (EM), equivalent square field (ESF), leaf travel (LT), leaf travel modulation complexity score for VMAT (LTMCSV), mean-field area (MFA), modulation complexity score (standard MCS and VMAT variant MCSV), plan irregularity (PI), and small aperture score (SAS5mm). Principal component analysis (PCA) was applied to explore the correlations between the metrics. The differential entropy of all metrics was also calculated, along with the mutual information for all 45 metric pairs. Results: Whole-pelvis plans had greater complexity across all indices. The first three principal components explained 96.2% of the total variance. The complexity metrics formed three groups with similar conceptual characteristics, particularly ESF, LT, MFA, PI, and EM, SAS5mm. The differential entropy varied across the complexity metrics (PI having the smallest vs. EM the largest). Mutual information analysis (MIA) confirmed some metrics’ interdependence, although other pairs, such as LTMCSV/SAS5mm, LT/MCSV, and EM/SAS5mm, were found to share minimal MI. Conclusions: There are many complexity indices for VMAT described in the literature. PCA and MIA analyses can uncover significant overlap among them. However, this is not entirely reducible through dimensionality reduction techniques, suggesting that there also exists some reciprocity. When designing predictive models of quality assurance metrics, PCA and MIA may prove useful for feature engineering.

Prospective evaluation of an enhanced recovery after surgery (ERAS) pathway in a Norwegian cohort of patients with suspected or advanced ovarian cancer

ObjectiveThis prospective cohort study evaluated the introduction of an enhanced recovery after surgery (ERAS) pathway in a tertiary gynecologic oncology referral center. Compliance and clinical outcomes were studied in two...

Surgical complexity score as a predictor of surgical site infection in dentoalveolar surgeries

Introduction: Postoperative surgical site infections represent one of the most frequent complications related to health care and can increase morbidity and mortality, in addition to increasing treatment costs. Objectives: This study evaluated surgical site infections incidence after dentoalveolar surgeries of retained third molars. The article presents the development of a surgical complexity score that can be used as a predictive method for surgical site infections risk in dentoalveolar surgeries. Methodology: In this cross-sectional observational study, the sample was obtained for convenience, from medical records of patients diagnosed with tooth retention and who underwent dentoalveolar surgery of third molars, from 2015 to 2020. Demographic variables of patients, characteristics of the surgery and information regarding the diagnosis of surgical site infections in the postoperative period were collected. Results: A total of 360 medical records were analyzed, with 59 surgical site infection cases diagnosed (16.4%). There was a statistical difference (p<0.05) in the bivariate analysis correlating infection with time of procedure, type of incision and performance of ostectomy and tooth sectioning. Logistic regression analysis to identify the probability of infection showed no significance for any of the individual variables, except when they are combined composing the surgical complexity score, which was then significantly higher in surgical site infections cases. Conclusions: The surgical complexity score developed can be a new predictive tool for the occurrence of surgical site infections in dentoalveolar surgeries, taking into account that the greater the complexity of surgery, the greater risk.

Prognostic Markers in Pediatric Acute Liver Failure

Introduction: Acute liver failure (ALF), although rare in children, is a complex progressive pathology, with multisystem involvement and high mortality. Isolated variables or those included in prognostic scores have been studied, to optimize organ allocation. However, its validation is challenging. This study aimed to assess the accuracy of several biomarkers and scores as predictors of prognosis in pediatric ALF (PALF). Methods: An observational study with retrospective data collection, including all cases of ALF, was defined according to the criteria of the Pediatric Acute Liver Failure Study Group, admitted to a pediatric intensive care unit (PICU) for 28 years. Two groups were defined: spontaneous recovery (SR) and non-SR (NSR) – submitted to liver transplantation (LT) or death at PICU discharge. Results: Fifty-nine patients were included, with a median age of 24 months, and 54% were female. The most frequent etiologies were metabolic (25.4%) and infectious (18.6%); 32.2% were undetermined. SR occurred in 21 patients (35.6%). In NSR group (N = 38, 64.4%), 25 required LT (42.4%) and 19 died (32.2%), 6 (15.7%) of whom after LT. The accuracy to predict NSR was acceptable for lactate at admission (AUC 0.72; 95% CI: 0.57–0.86; p = 0.006), ammonia peak (AUC 0.72; 95% CI: 0.58–0.86; p = 0.006), and INR peak (AUC 0.70; 95% CI: 0.56–0.85; p = 0.01). The cut-off value for lactate at admission was 1.95 mmol/L (sensitivity 78.4% and specificity 61.9%), ammonia peak was 64 μmol/L (sensitivity 100% and specificity 38.1%), and INR peak was 4.8 (sensitivity 61.1% and specificity 76.2%). Lactate on admission was shown to be an independent predictor of NSR on logistic regression model. Two prognostic scores had acceptable discrimination for NSR, LIU (AUC 0.73; 95% CI: 0.59–0.87; p = 0.004) and PRISM (AUC 0.71; 95% CI: 0.56–0.86; p = 0.03). In our study, the PALF delta score (PALF-ds) had lower discrimination capacity (AUC 0.63; 95% CI: 0.47–0.78; p = 0.11). Conclusions: The lactate at admission, an easily obtained parameter, had a similar capacity than the more complex scores, LIU and PRISM, to predict NSR. The prognostic value in our population of the promising dynamic score, PALF-ds, was lower than expected.

Deep learning assisted high throughput screening of ionic liquid electrolytes for NRR and CO2RR

Nonaqueous ionic liquids (ILs) with high solubility of both N2 and CO2 have a greater potential to be used as electrolytes for nitrogen reduction reaction (NRR) and electrocatalytic CO2 reduction reaction (CO2RR) due to the reduced effects of hydrogen evolution reactions (HER) and the high conductivity as well as the low viscosity. However, conventional experimental methods for screening ILs electrolytes are time consuming and labor intensive. In this work, a deep learning-assisted ILs screening approach was investigated to find the ILs electrolytes in practical applications. About 40,000 experimental data were collected for six ILs properties including viscosity, conductivity, melting point, density, N2 solubility and CO2 solubility. Graph neural network (GNN) was used to predict the properties of ILs and exhibited superior performance compared to traditional machine learning models. In addition, the transfer learning (TL) approach was employed to enhance the model prediction on a small dataset. To achieve high-throughput screening, a virtual database was constructed with 2 million ILs structures. Taking the properties of [P6,6,6,14][eFAP], the IL with higher Faradaic conversion efficiency, as the input thresholds, we performed high throughput screening of the virtual dataset, obtained 141 ILs based on the Synthetic Complexity Score (SCScore), in which [B(CN)4]- ILs and [ClO4]- ILs accounted for 29.3% and 15.7%, respectively, and finally identified 8 ILs superior to [P6,6,6,14][eFAP] as ideal electrolytes materials for both NRR and CO2RR that had been reported to be synthesizable. This data-driven model can streamline electrolytes selection and design, accelerating the development of IL electrolytes for electrochemical systems.

Pediatric ERCP: Factors for Success and Complication A 17-Year, Multisite Experience.

Endoscopic retrograde cholangiopancreatography (ERCP) is an increasingly utilized procedure in pediatric populations. A lack of dedicated pediatric research has led endoscopists to extrapolate adult risk factors and preventative strategies to children. The aim of this multisite, retrospective study was to identify risks for adverse events, procedure failure, and prolonged courses in pediatric patients undergoing ERCP. Pediatric patients who had an ERCP at one of our academic centers were identified by query of their electronic medical records. Pre-procedure and post-procedure data were collected with ERCP-related adverse events defined according to the consensus criteria developed by Cotton et al, 2010. Between 1/2004 and 1/2021, 287 children had a total of 716 ERCPs. The procedure success rate was 95.5% with no mortality and an adverse event rate of 12.7%. Younger age was associated with increased case complexity, increased adverse events, and an increased rate of repeat ERCP. Case complexity score correlated with increased procedure time (p < 0.001) and increased adverse events (tau 0.24, p < 0.01), Stent removal and pancreatic stenting were more likely to precede an adverse event. Pancreatitis, pancreatic divisum, and pancreatic stricture/stenosis were associated with increased adverse events and rates of repeat ERCP. Pediatric ERCP adverse event rates are higher than adults. The complexity grading system proposed by the Cotton et al appears to have applicability to pediatric patients. Young age and interventions affecting the pancreatic duct are associated with adverse ERCP outcomes in pediatrics.

Life span-associated ferroptosis-related genes identification and validation for hepatocellular carcinoma patients as hepatitis B virus carriers.

Hepatitis B virus (HBV)-infected population accounts for approximately 50% of all hepatocellular carcinoma (HCC) cases and has a relatively poor prognosis. Although the significant role of ferroptosis in the development and therapeutic response of various cancers has been validated, the key ferroptosis-related genes (FRGs) on the stratification of HBV-associated HCC are still unclear. Through the random forest, GSVA and Cox regression analyses, we established a comprehensive prognostic system covering multiple FRGs to elevate the predictive accuracy for the survival rate of HBV-related HCC using information obtained from public databases. The association between key FRGs and the immune microenvironment was evaluated, and the molecular mechanism was identified by GSEA and SNV analyses. Finally, the differential expression of key FRGs was validated by immunohistochemistry staining of patient tissue microarrays. Within the top 10 key FRGs, EPAS1 and GABARAPL1 were taken as protective factors, and SQLE, RAD51AP1, RPL8, CAPG, RRM2, SLC1A5, SLC38A1, and SRC were the other eight dangerous markers. Cox regression analysis combined with clinicopathological features indicated the independent prognostic efficacy of GSVA complex score based on these FRGs. In addition, key FRGs were related to immune and metabolic-related functions. Especially, the immunohistochemical analysis of SQLE in 50 clinical samples showed significantly higher expression in HBV+ HCC tissues. These results indicate that 10 FRGs may be potential biomarkers and therapeutic targets for long-term survival in HBV-related HCC.

Do malpractice claim clinical case vignettes enhance diagnostic accuracy and acceptance in clinical reasoning education during GP training?

BackgroundUsing malpractice claims cases as vignettes is a promising approach for improving clinical reasoning education (CRE), as malpractice claims can provide a variety of content- and context-rich examples. However, the effect on learning of adding information about a malpractice claim, which may evoke a deeper emotional response, is not yet clear. This study examined whether knowing that a diagnostic error resulted in a malpractice claim affects diagnostic accuracy and self-reported confidence in the diagnosis of future cases. Moreover, suitability of using erroneous cases with and without a malpractice claim for CRE, as judged by participants, was evaluated.MethodsIn the first session of this two-phased, within-subjects experiment, 81 first-year residents of general practice (GP) were exposed to both erroneous cases with (M) and erroneous cases without (NM) malpractice claim information, derived from a malpractice claims database. Participants rated suitability of the cases for CRE on a five-point Likert scale. In the second session, one week later, participants solved four different cases with the same diagnoses. Diagnostic accuracy was measured with three questions, scored on a 0–1 scale: (1) What is your next step? (2) What is your differential diagnosis? (3) What is your most probable diagnosis and what is your level of certainty on this? Both subjective suitability and diagnostic accuracy scores were compared between the versions (M and NM) using repeated measures ANOVA.ResultsThere were no differences in diagnostic accuracy parameters (M vs. NM next step: 0.79 vs. 0.77, p = 0.505; differential diagnosis 0.68 vs. 0.75, p = 0.072; most probable diagnosis 0.52 vs. 0.57, p = 0.216) and self-reported confidence (53.7% vs. 55.8% p = 0.390) of diagnoses previously seen with or without malpractice claim information. Subjective suitability- and complexity scores for the two versions were similar (suitability: 3.68 vs. 3.84, p = 0.568; complexity 3.71 vs. 3.88, p = 0.218) and significantly increased for higher education levels for both versions.ConclusionThe similar diagnostic accuracy rates between cases studied with or without malpractice claim information suggests both versions are equally effective for CRE in GP training. Residents judged both case versions to be similarly suitable for CRE; both were considered more suitable for advanced than for novice learners.

Development of complexity categories for an investigational drug services complexity scoring tool to assess pharmacy effort in clinical trial initiation and maintenance.

Research pharmacy effort required to safely and compliantly manage investigational products (IP) varies between studies. No validated tool exists in the United States to evaluate these differences in effort. The Vizient Pharmacy Research Committee Investigational Drug Services (IDS) Subcommittee previously developed a systematic complexity scoring tool (CST) through expert consensus to assign a complexity score for pharmacy effort. This project seeks to develop and validate complexity categories based on CST scores. Vizient member institutions in IDS assigned a CST complexity score and a perceived complexity category (low, medium, or high) for study initiation and maintenance. Receiver operating characteristic (ROC) curve analysis defined the best CST score cutoff points for each complexity category. Comparing the CST-assigned to the user-perceived complexity category determined whether the CST-assigned complexity category aligned with practitioner assignment. A total of 322 responses were used to determine complexity score categories. The AUC values for study initiation and maintenance were 0.79 (P < 0.001) for the low/medium boundary and 0.80 (P < 0.001) for the medium/high boundary, suggesting the performance of the CST is good. The agreement between CST-assigned and user-perceived complexity categories was 60% for study initiation and 58% for maintenance. The Kendall rank correlation coefficient between the raters and ROC categories was strong, with a value of 0.48 for study initiation and 0.47 for maintenance. Development of the CST allows IDS pharmacies to objectively measure the complexity of clinical trials, which is a significant step towards assessing workload and guiding resource allocation.

An Approach for Measuring Complexity Degree of International Engineering Projects

With the increasing trend of globalization, countries actively join the international engineering market, increasing the complexity of projects. An appropriate method for assessing project complexity can help project managers recognize the current situation and solve problems. However, existing complexity studies ignored the contribution of human element. The impact of human activities on the complexity of socio-economic systems is concerned in the Harmony Management Theory (HMT), therefore, this study proposed a complexity measurement based on the Harmony Management Theory. Firstly, an evaluation indicator system including three dimensions of organizational, technological, and environmental complexity is proposed through a literature review, Back-Propagation Neural Network-Decision Making Trial and Evaluation Laboratory (BP-DEMATEL) method, and Interval-valued intuitionistic Fuzzy Sets (IIFS) are used to calculate complexity scores. Then, a case study of Yawan high-speed railway project is conducted to verify the effectiveness of the proposed method. The main conclusions are as follows: (1) The complexity measurement based on harmony theory can be carried out from three aspects: Organization, technology, and environment. (2) The overall complexity performance of case project is 0.52, showing a medium level. (3) Technical complexity is the most important factor of the case project. The method proposed in this study can identify the influencing factors of complexity and calculate the comprehensive evaluation value of complexity. Based on the final quantified results, managers can formulate appropriate measures and match the project with appropriate resources so as to improve the performance of International Engineering Projects (IEPs).

Demands of surgical teams in robotic-assisted surgery: An assessment of intraoperative workload within different surgical specialties

BackgroundCurrent approaches to assessing workload in robotic-assisted surgery (RAS) focus on surgeons and lack real-world data. Understanding how workload varies by role and specialty aids in identifying effective ways to optimize workload. MethodsSURG-TLX surveys with six domains of workload were administered to surgical staff at three sites. Staff reported workload perceptions for each domain on a 20-point Likert scale, and aggregate scores were determined per participant. Results188 questionnaires were obtained across 90 RAS procedures. Significantly higher aggregate scores were reported for gynecology (Mdn ​= ​30.00) (p ​= ​0.034) and urology (Mdn ​= ​36.50) (p ​= ​0.006) than for general (Mdn ​= ​25.00). Surgeons reported significantly higher scores for task complexity (Mdn ​= ​8.00) than both technicians (Mdn ​= ​5.00) (p ​= ​0.007), and nurses (Mdn ​= ​5.00). ConclusionsStaff reported significantly higher workload during urology and gynecology procedures, and experienced significant differences in domain workload by role and specialty, elucidating the need for tailored workload interventions.

Development of a Medical Complexity Score for Pediatric Aerodigestive Patients

To develop a complexity scoring system to characterize the diverse population served in pediatric aerodigestive clinics and help predict their treatment outcomes. A 7-point medical complexity score was developed through an iterative group consensus of relative stakeholders to capture the spectrum of comorbidities among the aerodigestive population. One point was assigned for each comorbid diagnosis in the following categories: airway anomaly, neurologic, cardiac, respiratory, gastrointestinal, genetic diagnoses, and prematurity. A retrospective chart review was conducted of patients seen in the aerodigestive clinic who had ≥2 visits between 2017 and 2021. The predictive value of the complexity score for the selected outcome of feeding progression among children with dysphagia was analyzed with univariate and multivariable logistic regression. We analyzed 234 patients with complexity scores assigned, showing a normal distribution (Shapiro Wilk P=.406) of the scores 1-7 (median,4; mean, 3.50 ± 1.47). In children with dysphagia, there was waning success in the improvement of oral feeding with increasing complexity scores (OR,0.66; 95% CI, 0.51-0.84; P=.001). Tube-fed children with higher complexity scores were incrementally less likely to achieve full oral diet (OR,0.60; 95% CI, 0.40-0.89; P=.01). On multivariable analysis, neurologic comorbidity (OR, 0.26; P<.001) and airway malformation (OR, 0.35; P=.01) were associated with a decreased likelihood to improve in oral feeding. We propose a novel complexity score for the pediatric aerodigestive population that is easy to use, successfully stratifies diverse presentations, and shows promise as a predictive tool to assist in counseling and resource use.

Adoption of antenatal care conversation mapping among health care providers in Saudi Arabia: Application of the diffusion innovation theory.

To measure the factors influencing on the adoption of antenatal care conversation mapping among health care providers in Riyadh (Saudi Arabia), using the diffusion innovation theory. 88 healthcare providers (Riyadh) were recruited using a non-probability convenient sampling technique were trained on how to use a newly developed antenatal care conversation map. Data was collected by self-administrated questionnaire on health education services, adoption of conversation map and diffusion of innovation variables. The JMP statistical software from SAS version 14 was used to perform data analysis. Printable tools were most common as used by 72.7% of participants and 83.0% of them did not hear about conversation map. The total mean score of diffusion of innovation variables showed was in general high. The total mean score of relative advantage and observability was high in participants aged between 40 to less than 50 years, while the total mean score of compatibility, complexity, and trialability was high in participants aged from 50 years and more. Significant differences were obtained in both compatibility and trialability considering the health educators specialty, p = 0.03 and p = 0.027 respectively. The linear correlations between diffusion of innovation variables was significantly positive (p-value <0.01). All of diffusion of innovation variables were positive as per the opinion of the participants. Applying the conversation map on other health topics in Saudi Arabia and other Arabic-speaking countries is warranted. Measuring and evaluating the adoption rate of conversation mapping among health care providers on other health topics should be explored.

A182 Impact of Multidisciplinary Patient Complexity Scoring on Bariatric Surgery Outcomes

A182 Impact of Multidisciplinary Patient Complexity Scoring on Bariatric Surgery Outcomes

Combining sarcopenia and ASA status to inform emergency laparotomy outcomes: could it be that simple?

Risk assessment for emergency laparotomy (EL) is important for guiding decision-making and anticipating the level of perioperative care in acute clinical settings. While established tools such as the American College of Surgeons National Surgical Quality Improvement Program calculator (ACS-NSQIP), the National Emergency Laparotomy Audit Risk Prediction Calculator (NELA) and the Portsmouth Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity calculation (P-POSSUM) are accurate predictors for mortality, there has been increasing recognition of the benefits from including measurements for frailty in a simple and quantifiable manner. Psoas muscle to 3rd lumbar vertebra area ratio (PM:L3) measured on CT scans was proven to have a significant inverse association with 30-, 90- and 365-day mortality in EL patients. A retrospective analysis was conducted of 500 patients admitted to four Australian hospitals who underwent EL during 2016-2017, and had contemporaneous abdomino-pelvic CT scans. Radiological sarcopenia was measured as PM:L3 ratios. ASC-NSQIP, NELA and P-POSSUM were retrospectively calculated. Univariate and multivariate logistic regression modelling was used to assess these ratios and scores, as well as American Society of Anaesthesiologists (ASA) classification separated into ASA I-III and IV/V (simplified ASA), as potential predictors of 30-, 90- and 365-day mortality. PM:L3, simplified ASA, ACS-NSQIP, NELA and P-POSSUM were each statistically significant predictors of 30-day, 90-day and 365-day mortality (P < 0.001). Logistic regression models of 30-, 90- and 365-day mortality combining PM:L3 (P = 0.001) and simplified ASA (P < 0.001) exhibited AUCs of 0.838 (0.780, 0.896), 0.805 (0.751, 0.860) and 0.775 (0.729, 0.822), respectively, which were comparable to that of ACS-NSQIP and NELA. Combining the semi-physiological parameter ASA classification with PM:L3 provides a quick and simple alternative to the more complex established risk assessment scores and is superior to PM:L3 alone.

Plan quality and treatment efficiency assurance of two VMAT optimization for cervical cancer radiotherapy.

34 cervical cancer patients with definitive radiation were retrospectively analyzed. Each patient has four plans: FMO with fixed jaw plans (FMO-FJ) and no fixed jaw plans (FMO-NFJ); SPO with fixed jaw plans (SPO-FJ) and no fixed jaw plans (SPO-NFJ). Dosimetric parameters, Modulation Complexity Score (MCS), Gamma Pass Rate (GPR) and delivery time were analyzed among the four plans. For target coverage, SPO-FJ plans are the best ones (P≤0.00). FMO plans are better than SPO-NFJ plans (P≤0.00). For OARs sparing, SPO-FJ plans are better than FMO plans for mostly OARs (P≤0.04). Additionally, SPO-FJ plans are better than SPO-NFJ plans (P≤0.02), except for rectum V45Gy. Compared to SPO-NFJ plans, the FMO plans delivered less dose to bladder, rectum, colon V40Gy and pelvic bone V40Gy(P≤0.04). Meanwhile, the SPO-NFJ plans showed superiority in MU, delivery time, MCS and GPR in all plans. In terms of delivery time and MCS, the SPO-FJ plans are better than FMO plans. FMO-FJ plans are better than FMO-NFJ plans in delivery efficiency. MCSs are strongly correlated with PCTV length, which are negatively with PCTV length (P≤0.03). The delivery time and MUs of the four plans are strongly correlated (P≤0.02). Comparing plans with fixed or no fixed jaw in two algorithms, no difference was found in FMO plans in target coverage and minor difference in Kidney_L Dmean, Mu and delivery time between PCTV width≤15.5cm group and>15.5cm group. For SPO plans, SPO-FJ plans showed more superiority in target coverage and OARs sparing than the SPO-NFJ plans in the two groups. SPO-FJ plans showed superiority in target coverage and OARs sparing, as well as higher delivery efficiency in the four plans.

High correlation of the subjective elbow value with Mayo Elbow Performance Score and Oxford Elbow Score in patients with elbow dislocation

The purpose of this study was to analyze the correlation of the Subjective Elbow Value (SEV) with 2 widely used elbow scoring systems: Mayo Elbow Performance Score (MEPS) and Oxford Elbow Score (OES) in patients following elbow dislocation. In this retrospective single-center study, patients who sustained an elbow dislocation between January 2008 and December 2019 and were at least 2 years out from injury were included. SEV, OES and MEPS were assessed and statistical correlation was calculated using Pearson's correlation coefficient. A total of 114 patients (61 male, 53 female) with a mean age of 47.1 years (range, 16-70) were analyzed following elbow dislocation. The mean SEV was 87.4% (95% confidence interval (CI) 84.2-90.7), mean MEPS was 88.1 (95% CI 85.1-91.0) points and mean OES was 40.0 (95% CI 38.4-41.7) points. Both MEPS (r=0.710, P<.001), and OES (r=0.764, P<.001) demonstrated high correlation with the SEV. This study demonstrates that the SEV is a valid tool to assess overall status of the elbow in patients following elbow dislocations and presents an expressive but easy to perform addition to more complex scoring systems.