Simple and effective risk stratification tools which allow prediction of the risk of malignant esophageal lesions are needed for the practice of opportunistic screening. The aim of the current study was to develop an improved version of the diagnostic model based on a large-scale outpatient cohort and assess the robustness and generalizability of the model through external validations. The improved diagnostic model had seven predictors and generated an area under the receiver operating characteristic curve of 0.860 in the development set. Validation of the model in two external populations also showed high discrimination power and was able to increase the detection rate of malignant esophageal lesions. This questionnaire-based diagnostic model provides an easy-to-use tool to identify high-risk individuals and will be useful for the promotion of the opportunistic screening of esophageal cancer.validation set A: 0.892, 95% confidence interval: 0.858–0.926; AUC validation set B: 0.799, 95% confidence interval: 0.705–0.894). This improved model also markedly increased the detection rate of malignant esophageal lesions compared with universal screening, demonstrating great potential for use in opportunistic screening of malignant esophageal lesions in heterogeneous populations.We aimed to develop an improved version of the diagnostic model predicting the risk of malignant esophageal lesions in opportunistic screening and validate it in external populations. The development set involved 10,595 outpatients receiving endoscopy from a hospital in Hua County, a high-risk region for esophageal squamous cell carcinoma in northern China. Validation set A enrolled 9453 outpatients receiving endoscopy in a non-high-risk region in southern China. Validation set B involved 17,511 residents in Hua County. The improved diagnostic model consisted of seven predictors including age, gender, family history of esophageal squamous cell carcinoma, smoking, body mass index, dysphagia, and retrosternal pain, with an area under the receiver operating characteristic curve (AUC) of 0.860  in the development set. Ideal discrimination ability was achieved in external validations (AUC  Esophageal cancer (EC) is one of the most common cancers and is the leading cause of cancer death globally ,2. ThereDue to the lack of typical symptoms at an early stage, most ESCC cases are diagnosed at an advanced stage with low 5-year survival . Great iFor the implementation of opportunistic screening for ESCC, two prerequisites must be considered. First, there must be confirmed evidence supporting the effectiveness of screening. Observational studies have reported that early-stage EC patients can benefit from cancer screening ,7,8, andIn a previous study, we constructed the first model predicting the risk of prevalent esophageal malignant lesions for ESCC opportunistic screening by combining five easy-to-collect predictors . That moThe development set used for the original model consisted of outpatients receiving upper gastrointestinal (GI) endoscopy at the Hua County People’s Hospital from 1 March 2017 to 20 February 2019. This hospital is located in Henan Province, which is a high-risk region in northern China . In the Validation set A was previously used for validation of the original model and enrolled outpatients undergoing endoscopy in Peking University Shenzhen Hospital from 19 June 2017 to 14 January 2019. This hospital is a tertiary hospital in Shenzhen, which is an economically dynamic city with a huge migrant population and a low incidence of ESCC in southern China . In thisTo assess the performance of the model in a general population, we further validated it in the control group of the Efficacy of endoscopic Screening for Esophageal Cancer in China (ESECC) trial  as validation set B. As described previously, ESECC is a randomized controlled trial conducted in Hua County to evaluate the efficacy and cost-effectiveness of endoscopic screening for EC [For all three datasets, inclusion criteria were: (1) age 45 to 69 years; (2) no history of cancer, mental disorder, or contraindications for endoscopy; and (3) completion of an adequate upper GI endoscopic examination .All participants in these three cohorts completed a one-on-one computer-aided standardized questionnaire to collect demographic variables and information regarding potential predictors of ESCC. Candidate predictors, which were selected based on literature review, included age, gender, socioeconomic status , cigarette smoking, alcohol consumption, consumption of hot tea, source of drinking water, family history of ESCC, body mass index (BMI), type of fuel used for cooking, exposure to fumes in the kitchen, pesticide exposure, intake of fruit and vegetables, unhealthy dietary habits, and upper GI symptoms in the last 1 month  .The outcome was defined as the detection of severe dysplasia and above (SDA) of the esophagus, which included severe squamous dysplasia, carcinoma in situ, and ESCC. For the development set and validation set A, it was ascertained based on pathological diagnoses of the biopsy specimens, that were taken from all focal lesions during upper GI endoscopic examination and reviewed independently by two experienced pathologists. The outcome for validation set B was obtained through annual follow-up via active door-to-door interviews and passive linkage with local health insurance claims data, which have been proved to have a sensitivity of over 95% in identifying cancer cases and may be an ideal data source for cancer follow-up ,13,14.The chi-squared test and the Kruskal–Wallis rank-sum test were used to compare characteristics of the participants across the three datasets for categorical and continuous variables, respectively.p < 0.05 or p < 0.5 and odds ratio > 1.3 were initially selected for multivariable logistic regression. Backward elimination using the Akaike information criterion (AIC) was adopted to determine the final multivariable model, which is to remove predictors that would increase AIC until reaching the smallest AIC. Patients with missing values or other upper GI cancers were excluded from the analysis.We used a two-step approach to develop the prediction model. The correlation of each potential predictor with the presence of SDA was first assessed using univariable logistic regression in the development set. Predictors with Receiver operating characteristic (ROC) curves were plotted to visually assess the discrimination of the final model. AUCs were calculated according to the observed and predicted values and compared using the DeLong test among the three datasets .We set different screening coverages in the development set to identify ‘high-risk’ individuals in the development set. The highest predicted probability for achieving the desired screening coverage in the development set was then applied to the two validation sets to assess the application performance of the model. We calculated the sensitivity, the average number of endoscopies needed to detect one SDA case, the detection rate, and the detection rate ratio compared to universal screening in each of the three datasets.p < 0.05 were considered statistically significant.All analyses in this study were conducted using R software . All tests were two-sided and This study was approved by the Institutional Review Board of the Peking University School of Oncology, China. Written informed consent was obtained from all the participants.The three datasets showed statistically significant differences in selected characteristics . CompareWe identified 154 (1.5%) SDA cases among 10,595 participants in the development set, and 49 (0.5%) SDA cases among 9453 participants in validation set A. In validation set B, there were 18 (0.1%), 39 (0.2%), and 66 (0.4%) SDA cases within 1-, 3-, and 5-year period of follow-up, respectively, among the 17,511 participants.Among the candidate variables, seven predictors were selected to construct the new version of the model . We provAs shown in We observed an overall AUC of 0.892 (95% CI: 0.858–0.926) in validation set A. The model also worked well in the two subsets in this dataset  b.For validation set B from a general population, the AUCs of the model were 0.799 (95% CI: 0.705–0.894), 0.748 (95% CI: 0.676–0.821), and 0.746 (95% CI: 0.692–0.801) when taking ESCC cases within 1-, 3-, and 5-year follow-up as the outcome, respectively c.We set different screening coverages to select ‘high-risk’ individuals in the development set and evaluated the application performance of the model in the two validation sets. In all three datasets, as the cutoff rose and the proportion of individuals defined as at high risk decreased, the detection rate increased notably, reflecting substantial risk enrichment of the model for patients with malignant lesions in the esophagus . For exaIn this study, we developed an improved version of diagnostic model to predict individualized risk of malignant esophageal lesions in an opportunistic screening scenario. The final model containing seven predictors demonstrated high discrimination ability in the development set as well as in two external validation sets. This model exhibited remarkable generalizability and potential for application in opportunistic screening for ESCC.For the new model in the present study, seven predictors were selected and most of them were well-recognized risk factors for ESCC. Among these predictors, we included two upper GI symptoms, dysphagia and retrosternal pain. In the traditional epidemiologic concept, screening targets asymptomatic individuals at precancerous stage in a given population. However, disease-related symptoms could not be simply distinguished as positive or none, since it is usually a continuous and gradual process from the completely asymptomatic phase to obvious symptoms that make the patients seek for medical services on their own. Patients who have not consulted healthcare providers for early warning signs, i.e., at preclinical stage, are not necessarily ‘asymptomatic’. In rural China, for example, many ESCC patients delayed seeking medical services until symptoms were quite obvious because of limited socioeconomic status and poor health awareness . In thisCompared with the original version of the model, two new variables, namely family history of ESCC and gender, were introduced in the present model. Family history has been reported as an important risk factor in most previous epidemiological studies of ESCC, particularly in China. People with a positive family history of ESCC were 1.5 to 2.5 times more likely to have/develop ESCC probably because of shared lifestyle and/or genetic susceptibility ,19,20,21We completed multidimensional validation of the model in two independent external populations, which was essential for considering/recommending application of the model in clinical practice . ValidatIn real-world screening programs for ESCC, the optimal cutoff to define ‘high-risk individuals’ in a certain population should be carefully determined in advance. This decision must be made based on overall consideration of resource availability, population coverage, and the capacity of endoscopic examination in local healthcare facilities. To facilitate decision-making in varied scenarios, we set different cutoffs for risk stratification and evaluated the application performance of the model for each cutoff, rather than simply dividing the population into various risk groups using fixed cutoff points. In situations where the screening program aims to increase the detection rate of malignant lesions to achieve the highest public health benefit as possible with limited resources, we would recommend a higher risk cutoff. For example, the risk cutoff of 0.0585372 may be used to identify the top 5% of the whole population that are predicted to be at the highest risk, for whom endoscopic screening would be recommended. With that cutoff, our model could achieve a detection rate of 12.1%  and reduce the number of endoscopies needed to detect one SDA from 68 to 8. This would greatly relieve the burden on local healthcare system. In contrast, a lower cutoff could be adopted if the human, medical, and financial resources are adequate; for example, a risk cutoff of 0.0185875 to identify 20% of the population for screening. In this case, the screening program could achieve a detection rate of 5.3%, 3.6-fold higher than that in universal screening, and could detect one SDA in every 19 endoscopic examinations on average. In the scenario where the priority of the screening program is to detect all cancer cases, we could still avoid over 30% of screening examinations compared with universal screening by adopting a cutoff of 0.0022627.As a pre-screening tool prior to the screening examinations, our model can be used, theoretically, in combination with any screening technique for esophageal cancer. Among the screening techniques currently available, upper gastrointestinal endoscopy is the gold standard and has been widely used in China and worldwide. Other screening techniques to detect esophageal cancer such as cytosponge have been reported to be simple and low-cost. The application performance of our model in combination with other screening techniques needs to be further investigated in the future based on real-world data.A limitation of the present study should also be noted. Although this is a multi-center real-world study with a large sample size, more extensive validations and calibrations in other Chinese and non-Chinese populations are needed to confirm the generalizability and robustness of the model.In summary, we developed and externally validated an improved version of the diagnostic model predicting the risk of malignant esophageal lesions for opportunistic screening of ESCC. This easy-to-use questionnaire-based risk stratification tool may be readily integrated into smart portable terminals and social media platforms, thereby greatly promoting the uptake of cancer screening programs through self-risk-assessment and self-health-management among the public. As such, high-risk individuals in the general population may for the first time be empowered to act as the initiator and decision-maker for cancer screening examination, in contrast to the traditional cancer screening strategy in which the leading role has long been taken by the government or healthcare facilities.


Research on life skills in physical education (PE) has gained great attention in recent years. However, there is a need to translate life skills measures for PE into other languages. This research adapted the Life Skills Scale for PE (LSSPE) into Chinese and provided evidence for its validity and reliability. In Study 1, the scale was cross-culturally adapted through translation and back-translation, expert feedback, pilot testing, and scale refinement to provide evidence for the content validity of the scale. Study 2 provided evidence for the factorial validity, internal consistency reliability, and test–retest reliability of the scale by testing it with 583 students. Study 3, with 390 students, provided evidence for the nomological validity of the measure, with results showing perceived teacher autonomy support and students’ basic need satisfaction were positively associated with life skills development in PE, and that controlling teaching and basic need frustration were negatively associated with life skills development. In conclusion, the results illustrate that the LSSPE can be used to evaluate Chinese-speaking students’ life skills development in PE. Life skills are defined as the skills that are required to deal with the demands and challenges of everyday life . ExampleTwo important settings in which young people develop life skills are youth sports and physical education (PE). Life skills development in sports has been extensively researched ,5,6,7, wFour primary reasons may account for why students develop these life skills specifically through PE. First, it is likely that the interactive , social , and emotional  nature of PE give students’ ample opportunities to develop these skills ,16,17. SOne measure that has been used to assess life skills development in PE is the Life Skills Scale for PE (LSSPE) , which wThe LSSS has been translated into several languages thus far, including Portuguese , French Clearly, the need to explore life skills development in PE should not be restricted to only English-speaking students; thus, there is a need to develop a valid and reliable scale in other languages. Specifically, the lack of effective tools to study the life skills of individuals in other countries, cultures, and contexts may hinder a broader understanding of life skills development across the world. In this regard, Moustaka et al.  indicateIn China, PE is a compulsory subject for all students from the first grade of primary school to grade two of university and it is included as an exam subject in the majority of schools. Students typically focus on learning motor skills and engaging in exercise and physical activity. Additionally, the core purpose of an ongoing educational revolution in China is promoting the overall development and healthy growth of primary and secondary school students. Under this educational reform, PE classes will undergo unprecedented development, meaning that the LSSPE has the potential to present rich opportunities for the improvement of PE classes in China.Specifically, the development of a Chinese version of the LSSPE would allow for future studies on life skills development in PE among Chinese speakers. Examples of potential contributions of the scale are to: (a) assess life skill programs currently or potentially used in Chinese-speaking regions of the world, (b) research the antecedents and consequences of life skills development , (c) test different theories and models of development  with the life skills scale as an outcome variables, and (d) help advance Chinese PE teaching practices .Accordingly, the overall purpose of this research was to translate the LSSPE  into ChiThe purpose of Study 1 was to translate and adapt the LSSPE into Chinese. Accurate translation and adaptation of the measure are necessary to ensure that measurement tools can successfully adapt to the target language and be used properly in the sociocultural context. Following Nascimento Junior et al.’s  procedurAfter getting the permission of the original author, a group of ten experts was assembled to oversee the process of translating and adapting the LSSPE from English to Chinese. The group included six academics with previous experience in scale development and four scientific translators. These six academics were full-time university professors; three work in the field of sports psychology, two work in physical education and sports science, and one specialized in measurement and evaluation. The four translators were experienced in translating scientific texts, and all received academic training in English-speaking countries. All of the experts were Chinese, spoke Chinese as their first language, and were proficient in English as a second language. In the first study, 30 Chinese students between 12–21 years old—a sample of students representing future use of the scale—were invited to pilot test the scale and provide a preliminary assessment of their understanding of each item and the overall content of the Chinese LSSPE (C-LSSPE).The first step in assuring content validity was to accurately translate the LSSPE through expert translation from English to Chinese. Following procedures used by Nascimento Junior et al.  to transThe updated version of the C-LSSPE was then pilot-tested among 30 Chinese PE students aged 13–21 years old  to assess the clarity of the questions. All students provided informed consent to participate in the study. They were all students who participated in PE and sports activities. By investigating students’ comprehension and understanding of the scale among a small sample size, the appropriateness of the scale with the target group can be predicted. Other scale validation studies have used this methodology ,32,33. AA content validity assessment was performed by analyzing the 43 items of the C-LSSPE to check expert agreement about categorizing items by particular life skill . ConsistM = 0.94; CCVt ranged from 0.86–1.0, M = 0.90). These findings suggested that the C-LSSPE presents clear language and relevance for Chinese-speaking students, and it maintains its validity in the context of PE. The C-LSSPE item classification agreement among experts (Kappa coefficient) for teamwork, goal setting, social skills, time management, problem solving and decision making, emotional skills, leadership, and interpersonal communication skills ranged from 0.85 to 0.91 (M = 0.87), indicating that items corresponded to their correct underlying dimension. After completion of the C-LSSPE translation steps, statistical findings indicated that translations and feedback from experts and students had produced a scale with adequate content validity.The aim of Study 1 was to create a Chinese version of the LSSPE. The content validity assessment demonstrated that the life skills items in the C-LSSPE used clear language and demonstrated practical theoretical relevance, with coefficients of content validity above 0.80  to assess the factorial validity of the scale using scores obtained from a large sample of Chinese PE students. Factorial validity involves measuring items correlating strongly with their theoretical construct  while correlating weakly or not at all with other theoretical constructs . During The first author contacted the PE department at the students’ schools to obtain approval for data collection for this study. Each student also provided informed consent before taking part in the study. Our inclusion criteria for the study were middle school, high school, and first-year college students who normally participate in PE classes and sports activities. In China, the age range of students in these schools is usually 13 to 15 years old for middle school students, 16 to 18 years old for high school students, and 19 to 22 years old for college students. It is worth noting that there are several special circumstances that may create a mismatch between the age of a student and the period of study, such as starting school late or repeating a school year. Data collection was conducted in the playground or in classrooms where students were attending classes, at a time agreed upon by the researchers, PE departments, and participants.The 43-item C-LSSPE was used to assess how participants perceived the development of the eight life skills in PE. The item stem for this scale was “PE classes have taught me to…” and example items included: teamwork , social skills , problem solving and decision making , emotional skills , leadership , time management , and interpersonal communication . Students responded to the items on a five-point Likert scale . The complete C-LSSPE is available in Mage = 15.51 years; SD = 2.55 years) were in the final sample. The students took part in PE for an average of 115.78 min per week (SD = 22.26 min). In PE classes, the students participated in a wide range of sports, including basketball, football, volleyball, track and field, martial arts, and tai chi. They participated in extracurricular sports at school for an average of 95.63 min per week. Furthermore, 40.14% of students took part in sports outside of school for an average of 150 min per week. From the sample population, 127 students  aged between 14–21 years old  were randomly included in a retest of the measure within two weeks of first completing the scale.A total of 630 students  from all regions of China participated in this study. However, 47 students were excluded from the final sample because they did not adequately or clearly respond to the survey . In total, 583 students  aged between 13–21 years (2/df), root mean square error of approximation (RMSEA) [2/df of less than 3.0 was indicative of adequate fit [To assess the factorial validity of the C-LSSPE, CFA employing robust maximum likelihood estimation was conducted using AMOS software  . This in (RMSEA) , compara (RMSEA) , and the (RMSEA) . A χ2/dfuate fit . A RMSEAuate fit . Factor uate fit  criteriaThe internal consistency reliability of the C-LSSPE was assessed through the Cronbach’s alpha, with values above 0.70 indicating acceptable internal consistency . FurtherM = 0.73). Among them, 30 items had factor loadings that were considered excellent and 11 items had factor loadings that were considered very good. Only two items had factor loadings less than 0.63, which was still designated as good. Within the second-order model, all life skills factors loaded significantly onto the higher order factor, and the factor loading coefficients ranged from 0.70 to 0.91 (M = 0.81). This indicated that all eight subscales of the C-LSSPE can be combined to calculate a total life skill scale. M = 0.65), apart from the emotional skills subscale (ICC = 0.54). According to Weir [ to Weir , these IThe aim of this study was to test whether the C-LSSPE scores correlated with theoretically relevant outcomes, in order to test nomological validity. Nomological validity refers to a construct’s relationship with other theorized constructs . Self-deMage = 16.32; SD = 2.93). The students were recruited individually, were enrolled in school, and participated in PE and sports activities. The students took part in PE for an average of 112.15 min per week (SD = 25.73) and were taking PE as an exam subject. In PE classes, the students participated in a range of sports, including basketball, football, volleyball, track and field, martial arts, and tai chi. They participated in extracurricular sports at school for an average of 112.96 min per week. Furthermore, 38.97% of students took part in sports outside school, for an average of 105.59 min per week.The sample included 390 students  between 12–21 years old   was usedThe Chinese version of the psychological needs satisfaction scale for PE (PNSSPE)  and psycp-value of less than 0.05 was required to indicate a statistically significant relationship between variables. The correlations were judged as small (r = ±0.10 to ±0.29), medium (r = ±0.30 to ±0.49), or large (r > ±0.50), based on Cohen’s criteria [Correlation coefficients were used to assess the relationships between teacher autonomy support, students’ basic psychological need satisfaction, and life skills development. A criteria .The purpose of this research was to adapt the LSSPE to Chinese and provide validity  and reliability evidence  for the scale. This was the first attempt at adapting scales that assess life skill development to Chinese that we are aware of. As with previous sports studies ,24, thisIn Study 1, we adapted and translated the LSSPE into Chinese and provided evidence for the content validity of the scale items. First, we utilized content experts—academics and translators—and a sample of students to ensure that the content validity of the original scale was maintained when translated into Chinese. We also provided evidence for the validity of the scale by calculating and presenting CCVi and CCVt values to support the content validity of the scale, which is an important and often neglected factor during the process of scale development in sports psychology .Study 2 provided evidence for the validity of the internal structure of the C-LSSPE with a large sample of students. The factorial validity of a first-order model and a second-order model was supported. Additionally, each life skill subscale and total life skills showed acceptable internal consistency reliability and test–retest reliability. Thus, the C-LSSPE can be used reliably with Chinese students to investigate the development of each of the eight life skills separately and total life skills combined. These findings align with the factorial validity and internal consistency reliability evidence for the LSSPE with English-speaking students ,14,21. IStudy 3 provided evidence for the relationships with other variables of the C-LSSPE by illustrating the expected pattern of relationships between teaching behaviors, basic need satisfaction and frustration, and life skills development. These findings support earlier research showing that PE teacher autonomy support is positively associated with students’ life skills development ,21. ThisDespite its contributions, our work has some limitations. First, in the present study, all data were collected via student self-report, which can be affected by both social desirability and memory recall . Thus, fOverall, our development of the C-LSSPE extends the research on life skills development in PE from the English-speaking to the Chinese-speaking context. To begin with, the C-LSSPE will allow practitioners and researchers to explore Chinese students’ life skills development in PE. On the one hand, this will help broaden the scope of research on youth development beyond English speakers in North America . On the Translation of the LSSPE into Chinese and subsequent analyses have demonstrated sufficient evidence for its test content, internal structure, and relationship to other variables (The Standards) . The ada


The combination of vancomycin/gentamicin (VGA) might represent a good alternative, but few studies have evaluated its efficacy in SSI prevention. (2) Methods: A single-centre retrospective study was conducted over a 13-year period in all consecutive adult patients undergoing elective cardiac surgery. Patients were stratified according to the type of antibiotic prophylaxis. CA served as the first-line prophylaxis, and VGA was used as the second-line prophylaxis. The primary endpoint was SSI occurrence at 90 days, which was defined as the need for reoperation due to SSI. (3) Results: In total, 14,960 adult patients treated consecutively from 2006 to 2019 were included in this study, of whom 1774 (12%) received VGA and 540 (3.7%) developed SSI. VGA patients had higher severity with increased 90-day mortality. Nevertheless, the frequency of SSI was similar between CA and VGA patients. However, the microbiological aetiologies were different, with more Gram-negative bacteria noted in the VGA group. (4) Conclusions: VGA seems to be as effective as CA in preventing SSI. Since the advent of antibiotics in the 1940s , antibioThus, the aim of our retrospective, single-centre study was to assess whether the combination of vancomycin and gentamicin (VGA) is a valuable alternative to cephalosporins (CA) to prevent SSI in cardiac surgery with CPB.This single-center retrospective study was performed in a tertiary care teaching hospital performing more than 1000 annual cardiac surgical procedures. Between 2006 and 2019, all consecutive patients who underwent cardiac surgery with cardiopulmonary bypass (CPB) were eligible. The exclusion criteria were a previous history of cardiac surgery in the past year and missing clinical information (including antibiotic prophylaxis).2. Acute infective endocarditis was defined as endocarditis under antibiotics at the time of surgery. Cardiac insufficiency corresponds to patients with a left ventricular ejection fraction of less than 30%.SSI was defined as the need for reoperation within 90 days after index surgery for local or systemic infection involving the sternotomy scar ,19. The Staphylococcus aureus (MRSA) and/or in patients known to be colonized by MRSA. VGA was administered after the induction and from 5 to 30 min before the surgical incision through a central line according to the following protocol: vancomycin was perfused over 1 to 2 h at a dose of 30 mg/kg, and 500 mg was added to the priming of CPB. Then, 1 g was administered 12 h after the end of surgery. Gentamicin was perfused over 30 min as a single dose of 5–6 mg/kg. All patients underwent preoperative nasal screening for S. aureus carriage and preoperative nasal decontamination with mupirocin for 5 days, most frequently started on the day before surgery ).In addition, our study suggests an increased incidence of Gram-negative bacteria in the VGA group. This association was not found in the 2012 meta-analysis, although this analysis found more postoperative Gram-negative pneumonia in the vancomycin group. This lack of association in this meta-analysis may be due to a lack of power, as our population was more than twice as large . The incNevertheless, for patients allergic to beta-lactams, gentamicin may reinforce the administration of vancomycin. Indeed, in our study, the exact start date of antibiotic prophylaxis was not collected. However, in our protocol, VGA started before the surgical incision and after the insertion of the central line. Therefore, our protocol is not in accordance with French and international recommendations , which sThis study is one of the largest studies on SSI in cardiac surgery and, more specifically, on the combination of vancomycin/gentamicin. The inclusion of patients and their surgical management were stable over time. Thus, the SSI rate was stable throughout the study. However, the use of VGA therapy decreased over time, which was possibly related to a decrease in the MRSA rate in our population.Other limitations are present. First, this is a retrospective study, which may lead to collection bias. This bias is limited by the fact that much of the information was collected prospectively. Second, it is a monocentric study, which may limit generalization. This study found SSI rates and risk factors for SSI in line with previously published studies ,39,40,41In this prolonged cohort of consecutive patients, the incidence and risk factors for SSI were comparable to those reported in the literature. VGA was more commonly used in the most severe patients than in CA. However, our results did not find any significant increase in risk of SSI. Differences in the microbiological cultures of SSI were observed according to the type of antibiotic prophylaxis. Therefore, VGA represents a valuable alternative for SSI prevention. Further studies are needed to confirm these results.


Pain is a silent global epidemic impacting approximately a third of the population. Pharmacological and surgical interventions are primary modes of treatment. Cognitive/behavioural management approaches and interventional pain management strategies are approaches that have been used to assist with the management of chronic pain. Accurate data collection and reporting treatment outcomes are vital to addressing the challenges faced. In light of this, we conducted a systematic evaluation of the current digital application landscape within chronic pain medicine.The primary objective was to consider the prevalence of digital application usage for chronic pain management. These digital applications included mobile apps, web apps, and chatbots.We conducted searches on PubMed and ScienceDirect for studies that were published between 1st January 1990 and 1st January 2021.Our review included studies that involved the use of digital applications for chronic pain conditions. There were no restrictions on the country in which the study was conducted. Only studies that were peer-reviewed and published in English were included. Four reviewers had assessed the eligibility of each study against the inclusion/exclusion criteria. Out of the 84 studies that were initially identified, 38 were included in the systematic review.The AMSTAR guidelines were used to assess data quality. This assessment was carried out by 3 reviewers. The data were pooled using a random-effects model.Before data collection began, the primary outcome was to report on the standard mean difference of digital application usage for chronic pain conditions. We also recorded the type of digital application studied  and, where the data was available, the standard mean difference of pain intensity, pain inferences, depression, anxiety, and fatigue.I2 = 82.86%; p = 0.02). After stratifying by country, we found that digital applications were more likely to be effective in some countries  than others .38 studies were included in the systematic review and 22 studies were included in the meta-analysis. The digital interventions were categorised to web and mobile applications and chatbots, with pooled standard mean difference of 0.22 , 0.30  and −0.02  respectively. Pooled standard mean differences for symptomatologies of pain intensity, depression, and anxiety symptoms were 0.25 , 0.30  and 0.37 , respectively. A sub-group analysis was conducted on pain intensity due to the heterogeneity of the results (The use of digital applications in improving pain-related symptoms shows promise, but further clinical studies would be needed to develop more robust applications.https://www.crd.york.ac.uk/prospero/, identifier: CRD42021228343. High-quality research data generated by scientifically robust study designs, improved use of clinical data, and the development of cost-effective healthcare models can change how medicine is practiced in the modern world. Digital medicine (DM), wherein multimodal and multidimensional digital tools are used to intervene in accessing and providing healthcare, is now a fundamental part of these drivers of change. Digital medicine describes a field, concerned with the use of technologies as tools for measurement, and intervention in the service of human health . Digitalbench to bedside” pathways still take considerable time •Algorithmic Data: Results produced from algorithms run on large samples of data .•Algorithmic Machine-Shared data: An algorithm shares a digital result. Limited context exists for a human to correct false positives/negatives in real-time.The future of digital medicine involves evolution of Artificial Intelligence (AI) based systems that may allow capture and dissemination of information in possible formats as below:The field of pain medicine in adults is a particularly challenging area of clinical practice for many reasons, including subjectivity associated with patient-reported outcomes and management of symptomatology with limited information on pathophysiology , 5. ConsThe ability to modify behaviour may have implications for chronic disease management. For example, according to the United States Center for Disease Control and Prevention (CDC), there are currently 96 million prediabetic patients in the US. As would be of importance, preventing those individuals from advancing to full-blown diabetes through drug and/or device therapies or behavioral modifications would have a huge impact on morbidity and health economics. Apps that allow early intervention and monitoring of prediabetes could start to shift medical practice from treatment to prevention and early intervention. Novartis (Basel) aimed at developing a contact lens that can monitor a person's blood sugar levels  automatically processes large datasets and uses this to formulate informed predictions without the need for human intervention . ML algoTo advance DM concepts and their use in pain medicine research, it is imperative to assess the global regulatory sphere. Over the last decade, a plethora of legislations and regulatory guidelines around DM have been developed by the World Health Organisation (WHO) , MedicinThe regulatory and standards required for novel innovations are also dependent on the disease classification. The current classification of chronic and acute pain conditions  identify and report the current prevalence of DM application in pain medicine; (2) identify and report the current DM application use within pain medicine. In this publication, we have explored the types of assessments, their use and deployment-related to DM applications.CRD42021248232). The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) was used to report findings.An evidence synthesis methodology was developed for the purpose of this study, with a systematic review protocol published on PROSPERO , Comparison, Outcome) strategy. An independent reviewer screened studies included within the study by reading the full text. Initial title and abstracts for identified articles were screened by 4 investigators. Inclusion and exclusion criteria were assessed against each study. This was followed with the screening of the full study article independently by 2 investigators and included into the final data pool.PubMed and ScienceDirect were used to identify relevant studies that were peer-reviewed and published in English between the 1st of January 1990 and 1st of January 2021. Search terms used included The data extraction process involved reading titles and abstracts followed by the application of the refinement protocol where the full text was reviewed and subsequently verified. Key study details such as study title, citation details, methods, findings, limitations, characteristics of the study and conclusions were extracted. Differing opinions were resolved by review and discussion between the lead authors. The authors remained unblinded regarding the publisher details. A full methodological description is demonstrated within the supplementary document .As all studies reported the mean and SD at several time points, a mathematical model was formulated as demonstrated in 0)( and follow-up 1)( and follow-up 1)( in the control group.BPI (Brief Pain Inventory), NRS , PCP-S(Profile of Chronic Pain: Screen) and pain evaluation questionnaires were used to assess pain intensity and pain interference; HADS , CES-D , BDI (Beck's Depression Inventory), PHQ-9 , DASS , GAD-7  and STAI (State-Trait-Anxiety-Inventory) were used to assess depression and anxiety; FSS  and MOS  sleep scale were used to assess fatigue and sleep. All studies reported the mean and SD of the questionnaires across several timepoints, at baseline and follow-up. The baseline questionnaire score was subtracted from the follow-up questionnaire score to standardize the data and remove the initial effect. Score changes between these two time points reflect the treatment effect. Therefore, The scales of the questionnaires were different, therefore standardized mean differences (SMD) were used to illustrate the change in the mean score of the treatment group vs. the control group from baseline to follow-up. The traditional form of SMD wasI2 were used to explain heterogeneity and Egger's test was used to detect publication bias. All procedures were finished with STATA 16.1.The risk of bias (RoB) table  has beenAMSTAR  was usedvia the meta-analysis which was based on the availability of statistics reported by the systematically included studies. The following are the outcomes of this study:- Prevalence of DM applications, including categories- Prevalence of chronic pain conditions using DM applications for self-reporting purposes- Standard Mean Difference of pain outcomes of depression, anxiety, pain inferences, and fatigue and sleep problems between DM applications and non-DM routine care- Clinical significance of the prevalence data- Research significance of the prevalence data- Critical interpretation of the identified data- Common themes identified within the prevalence dataOutcomes of this study were reported The search yielded 84 publications, with 38 , 26–62 iAll 22 studies included in the meta-analysis reported more than one pain-related symptom. One primary outcome reported in 15 studies was pain intensity. 11 reported depressive symptoms and 9 anxiety symptoms. Pain interference was reported by 4 studies. Fatigue and sleep problems were included as secondary outcomes in two and one study respectively. Meta-analyses were conducted for each outcome separately.I2 = 82.86% was identified for this group (p = 0.02). A subgroup analysis was conducted to analyse the possible source of heterogeneity.All 15 studies provided the mean and SD. Therefore, the meta-analysis was based on the mean and SD. I2 = 34.72% (p = 0.00).The 11 studies reporting depressive symptoms used various assessment tools, including the Centre for Epidemiological Studies-Depression (CES-D), Beck Depression Inventory (BDI), Patient Health Questionnaire-8 and −9 , Hospital Anxiety and Depression Scale (HADS) and the Depression Anxiety Stress Scales (DASS). Ruehlman and colleagues (2012) used CES-D and DASS to assess the depression of the participants twice. To avoid duplication we used only one (CES-D) of the means and SD of these two assessments so that 11 studies were included in meta-analysis. I2 = 88.34% (p = 0.02), indicating our factors such as sample size, country of subjects, the type of digital applications used and type of pain influence the conclusion of meta-analysis. Due to the number of studies is too small, it's hard to conduct subgroup analysis or meta-regression here. To obtain more precise and convincing conclusion, more studies are needed here.Within the 9 studies reporting anxiety as a clinical outcome among chronic pain participants, the pooled SMD was 0.37 with a 95%CI of 0.05–0.69 . The SMDFour studies reported pain interference, an important outcome in pain research. Two studies reported on fatigue and one study on sleep issues. The forest plots for these factors are illustrated below .The pooled SMD for fatigue was 0.29, indicating the treatment group improved following the completion of the DM application use. However, this conclusion is not statistically significant given the 95%CI of −0.18 to 0.76. This could be due to the presence of only 2 studies, and more is needed to reach a conclusion.The pooled SMD for sleep issues was −0.04 with a 95%CI of −0.4 to 0.32. This indicates that DM applications did not improve sleep-related issues and is of a lower score compared to the control group. However, to provide a more comprehensive conclusion to this phenomenon, further studies would be required.Subgroup analysis was conducted to identify the source of raised heterogeneity when considering studies reporting on pain intensity. Initial analysis considered the categories of DM applications which included web-applications, mobile apps and chatbots. The analysis is demonstrated in The pooled SMD for web-applications was 0.22, indicating web-applications could reduce the intensity of pain compared to the control group. The pooled SMD of mobile apps was 0.30. This demonstrates a larger effect size in relieving the intensity of pain compared to control groups and to those using web-applications. The pooled SMD for chatbots was −0.02, indicating chatbots have a limited effect in reducing the intensity of pain in patients compared to the controls. Heterogeneity remained high in all three subgroups, so a second subgroup analysis was conducted based on exposure of pain symptoms. The pain exposure sub-group analysis included identified specific pain conditions: fibromyalgia, back pain, chronic pain, osteoarthritis pain, menstrual pain, and cancer-related pain .I2 = 92.23%). Chronic pain and osteoarthritis pain groups reported an I2 of 82.44% and 85.19% respectively. However, due to the limited number of studies, pain and digital application exposures, the effect size could not be comprehensively assessed. A third subgroup analysis was conducted based on geographical locations  and Germany (I2 = 45.91%). The heterogeneity may well be due to nationality and ethnicity.A sub-group analysis by country found that DM applications appear to be effective within populations in America, China, Germany, and Netherlands, while for Ireland and Norway, a statistically significant effect was lacking. Only mild heterogeneity levels were indicated for America . Sun et al. (2017) reported a SMD of 1.34 with a 95% CI of 0.72–1.96. Therefore, DM applications appear to have a positive impact on patients.The sensitivity analysis reveals DM applications appear to benefit patients. However, to conclusively demonstrate a statistical significance more studies would be required. The The sensitivity analysis shown in p-value is 0.932, indicating the lack of a small study effect. However, there are 5 studies that fell outside the 95%CI which could affect our detection of publication bias. The p-value is not high but it is limited by the data and experimental quality.Publication bias was assessed and reported using funnel plots and Egger's test to examine the small-study effect. Publication bias appears to be smaller among studies associated with fatigue and sleep, and higher in studies demonstrating pain intensity, depression, anxiety, and pain interferences. There is a lack of significant publication bias based on the funnel plot , below. p-values of 0.838 and 0.712 respectively. Pain inferences  reported adult participants were in favour of using DM-based self-management interventions for chronic pain management . PatientThe benefits of harnessing DM within the context of pain medicine could improve both clinical and patient-reported outcomes. Evidence-gathering to support therapeutic efficacy for pharmacological or surgical treatments requires effective and robust methodology, yet rigid traditional trial designs remain inefficient and struggle with implementation into clinical practice, limiting sustainability within healthcare systems. Computer-based technology could address these obstacles in research. The flexibility and accessibility of digital technology enables a more convenient and improved consenting process. This could allow easier enrolment and participation in studies for populations disadvantaged by mobility or literacy issues. Increased recruitment and retention lead to larger study populations with greater data validity, and aids researchers by speeding up recruitment and assessment of large trial populations.Digital clinical trials are becoming more poignant to test various complex and technological interventions, as well as a conducting follow-up of participants in large multi-center global clinical trials. Digital clinical trials are key in collating all the above factors, as it is a fundamental tool in assessing the efficacy and safety of novel drugs, medical devices, and health system interventions. In the era of COVID-19, digital clinical trials have proven to be highly effective and valuable for continuity of clinical research. Traditional clinical trials have demonstrated the validity, acceptability, and sustainability of the interventions, whilst digital clinical trials could leverage technologies to engage and report trial-specific measurements associated with the interventions being tested at a lower cost . ConceptUnified approaches of conducting DM application assessments were lacking across all 3 categories identified and reported within the scope of this study. As a result, the pooled analysis conducted limits the generalizability of the findings. It is evident that the lack of validation in digital applications is another rate-limiting factor in furthering the use of these among clinical populations.In terms of DM overall, the clinical databases through which they operate would been to be encrypted and backed up to ensure data reliability and protection from information loss , 18. TheResearch papers and databases were used in this review. Whilst the findings are compelling, there is the absence of real-world clinical studies to further validate these findings. A study where a digital medicine software is used in a clinical setting would develop understandings in the applicability and feasibility of such technology. Comparison between control and experimental participant group would enable outcomes to be assessed for efficacy and outcome monitoring.It would be insightful to see application to a wider variety of healthcare disciplines to understand the various data management processes that would go underway . This woThe pain medicine ecosystem has a plethora of research studies, although those in population research, prevention, clinical trials, and education, as well as training, need to evolve if improvements are to be made clinically. This could integrate evolving DM concepts, including AI applications, that could improve patient-reported outcomes. It is, therefore, important to conduct further well-designed digital clinical trials.real-world environments could be used to test novel DM applications, given the complexities around conducting pain research. Similarly, it may be beneficial for patients to gain access to DM applications more quickly, especially those managing chronic pain. Therefore, a paradox of “no evidence, no implementation vs. no implementation, no evidence” is a challenge to clinicians, patients, policymakers, and clinical researchers alike. Using simulation methods, where possible, could provide an alternative method to overcome this paradox, although there may be limitations that would need considering as it not always feasible to design precise simulations or perform competency validation. The proliferation of digital technologies would provide the leverage to optimise global care by way of mobile platforms, to open better avenues, and to measure outcome data from wearable devices. These applications use real-world data that could benefit patients and clinicians alike. Thus, the use of DM in pain medicine could promote a myriad of benefits.Another concern based on evidence ascertained in this study is the minimal use of clinical trials to test DM applications; therefore, the efficacy and efficiency of these, as well as the generalizability to a wider population, remain limited. Pragmatic and novel methods of conducting clinical trials would be beneficial in providing credible evidence before these DM applications are used within clinical practice. Alternatives such as simulation studies using


Automatic contouring was able to significantly reduce the time required in the procedure, simplifying the workflow, and reducing interobserver variability. Its implementation was able to improve the radiation therapy workflow in our department.Proper delineation of both target volumes and organs at risk is a crucial step in the radiation therapy workflow. This process is normally carried out manually by medical doctors, hence demanding timewise. To improve efficiency, auto-contouring methods have been proposed. We assessed a specific commercial software to investigate its impact on the radiotherapy workflow on four specific disease sites: head and neck, prostate, breast, and rectum. For the present study, we used a commercial deep learning-based auto-segmentation software, namely Limbus Contour (LC), Version 1.5.0 . The software uses deep convolutional neural network models based on a U-net architecture, specific for each structure. Manual and automatic segmentation were compared on disease-specific organs at risk. Contouring time, geometrical performance , and dosimetric impact (DVH differences) were evaluated. With respect to time savings, the maximum advantage was seen in the setting of head and neck cancer with a 65%-time reduction. The average DSC was 0.72. The best agreement was found for lungs. Good results were highlighted for bladder, heart, and femoral heads. The most relevant dosimetric difference was in the rectal cancer case, where the mean volume covered by the 45 Gy isodose was 10.4 cm Radiation therapy (RT) is an important treatment option in the management of cancer. It aims at delivering a high radiation dose to target cancer cells to ensure clinically required tumor control probability and concomitantly spare the nearby healthy tissues to prevent acute RT-related toxicity and late effects.Accurate contouring of Clinical Target Volumes (CTV) and Organ at Risk (OAR) is important for treatment planning and delivery. Generally, the segmentation of tumor regions and normal tissues is manually performed by the clinical staff, based on the images acquired during planning computed tomography (CT). This approach is prone to a high degree of inter and intra observers’ variability, being time-consuming, and representing a bottleneck in the planning workflow .To improve the efficiency of this process, auto-contouring methods have been proposed. One of the most popular approaches is atlas-based segmentation ,3. HowevA commercial deep learning-based auto-segmentation software, Limbus Contour (LC), Version 1.5.0 , which uses deep convolutional neural network models based on a U-net architecture specific for each structure, was recently introduced in our institution. The software relies on models trained, using public datasets ,7,8,9,10LC obtains information related to the acquisition protocol by reading the DICOM metadata of the CT images. The corresponding auto-segmentation model is then automatically used to create auto-segmented contours that are exported alongside the CT images to the treatment planning software to be eventually edited and then validated by the clinicians.Four disease sites were selected for the present study, namely Head and Neck (H&N), prostate, rectum, and breast cancer. We focused on these four settings, considering their high frequency and important impact on the radiotherapy workflow. For each type of treatment, three patients treated in our center were selected.For H&N, we chose oropharyngeal cancer to guarantee the standardization of OARs contouring. Patients eligible for the study received radical radiotherapy. The prescription dose was 70 Gy delivered in 35 fractions for the curative setting. The prostate setting consisted of patients who received exclusive radiotherapy on prostate gland and seminal vesicles. A moderate hypofractionated schedule was proposed: 70 Gy on prostate gland and 63 Gy on seminal vesicles in 28 fractions, delivered with a simultaneous integrated boost. For rectal cancer, patients offered pre-operative RT were considered. The prescription dose was 50 Gy on the gross tumor volume and positive nodes, and 45 Gy on the elective volumes, in 25 fractions. Finally, patients with left-sided breast cancer who underwent conservative surgery were selected. In this case, the prescription dose was 45 Gy for whole breast irradiation and 50 Gy on the tumor bed, given with a concomitant boost, in 20 fractions.Each patient underwent a planning CT scan in supine position; to prevent patient’s displacements during treatment, immobilization devices were used: thermoplastic mask for H&N, knee wedge and foot lock for prostate and rectum treatments, breast board for breast cases. Planning CT images were acquired with a Canon Aquilion LB V6.3 series scanner  with 120 kVp tube load. The slice thickness was 3 mm for H&N cancer and 5 mm for other diseases. The in-plane pixel size was 1 mm × 1 mm for all acquisitions.Four different RO, each with expertise in the specific clinical setting, manually delineated the four-treatment districts following national and international consensus guidelines ,20,21,22The same CT acquisitions were contoured by LC and the images, together with the RTstructure DICOM file, were then sent to the Treatment Planning System (TPS) Eclipse . The LC structure set was later duplicated on the TPS. One structure set has been reviewed by the competent RO and, if necessary, the contours were modified; the second was not submitted to any change.For H&N cancer, contoured OARs were fifteen . For prostate cases, five structures were considered . For rectal cancer, four OARs were accounted for . Finally, for breast cancer contoured structures were four .We recorded the time spent performing the manual contour for each CT scan. Moreover, the time required for LC to generate OARs on a consumer grade system  was also evaluated. Finally, the time spent by the ROs to review and, if necessary, edit the contours performed by LC was measured. The overall duration of contouring using LC (LC contouring plus ROs review) was compared to the time required to perform manual contouring, which was used as a reference. In this way, the time difference—absolute and relative—between the two contouring methods was obtained.3, the volume percentage variation was considered. Conversely, for smaller structures, the absolute change in volume was analyzed, since the percentage variation was not considered indicative, given that small variations in volume lead to large percentage variations.The manually contoured structures (MC) were compared with those generated by LC by means of three indicators: volume variation, Dice Similarity Coefficient (DSC) and shift of the center of mass. For structures with a volume greater than 15 cmDSC  is a meaA dosimetric analysis was performed to evaluate the effects of unsupervised use of LC on the assessment of dose distribution.The original treatment plan, optimized and clinically approved with the manually contoured volumes, was recalculated on the LC contoured structure-set using the AAA algorithm (version 15.6.06) of Eclipse TPS, the same as the original plan.The differences in the Dose Volume Histograms (DVH) between the two structure sets were then evaluated and plans were compared using the metrics reported in For serial organs, metrics associated with maximum dose were used, while for parallel organs the average dose or dose too large volume were considered.The absolute and percentage variations of the contouring times are shown in 3. The associated uncertainty is expressed in terms of ±1 standard deviation. The OAR with the minimum variation (1%) is lung; the structures with the greatest percentage variation are bowel and oral cavity, with mean percentage variations of 65% and 32%, respectively.3 are reported in 3.The absolute volume variations for structures with a volume smaller than 15 cmThe absolute value of the three-dimensional displacement of the center of mass is represented, for all the structures, in 3 for the MC structures versus 289.4 cm3 for the LC ones.In The present study explores the effects of commercial deep-learning based software for auto-contouring on the clinical workflow of a radiation oncology department at a tertiary cancer hospital. In particular, the focus was on timesaving and on the accuracy of the contoured structures.To accurately assess the time reduction, we evaluated the clinical settings having the highest impact on the workflow in our radiotherapy department. In addition, for each disease site we focused on, all the OARs included in the clinical routine were considered.Limbus performance was already analyzed by other authors, who investigated multi-observer variability , qualitaThe possibility to save time is greater in anatomical districts characterized by a greater number and complexity of OARs. Our data are similar to those reported in the literature. As an example, in the setting of lung cancer, Lustberg et al.  showed aLC provides good results, as no gross contouring errors were found. This high-quality performance is highlighted by the average DICE Index of 0.72 which can be considered acceptable in clinical practice . HoweverAs can be seen by center of mass and geometrical analyses, there is a difference in bowel manual contouring versus automatic segmentation. LC considers as bowel the entire abdominal cavity, extending the caudal limit including the whole inferior abdomen, regardless of the presence of the intestinal loops. During manual contour, however, bowel was considered as abdominal cavity whose caudal limit is defined by the presence of intestinal loops ,25,26. TRegarding the oral cavity, the differences are due to different approaches in contouring; similar results are found by Zhong et al. . LC consThe low DSC for penile bulb is an expected finding, as the anatomical markers or the necessary soft tissue contrast for the penile bulb is generally lacking on CT. To best identify penile bulbs and reduce great contouring variability, some authors have stressed the importance of performing an MRI or CT scan with contrast in the urethra for optimal identification of the penile bulb .About brachial plexuses, the institutional practice is not to contour the complete brachial plexus until, laterally, the thoracic wall because for oropharynx tumors the dose to the brachial plexus axillary trunk is negligible . This chA disagreement in the cranial limit of plexuses was also found. During manual contouring, the brachial plexuses start from the spinal nerves through the neural foramina from the C4–C5 (C5 nerve roots) to the T1–T2 (T1 nerve roots) level. In LC the cranial level of brachial plexus is often higher, such as C2–C3, probably due to the position of neck. These issues explain differences in DSC values for brachial plexuses (about 0.7) compared to those found by D’Aviero et al.  (about 0Regarding parotid glands, no significant changes in geometric parameters were found. However, there is a non-negligible variation of dosimetric indicator. Although the shape and position of parotid glands are similar in manual contouring and LC, minimal differences could drastically affect dosimetric parameters because of the proximity of parotid glands to PTV and to the steep dose gradients. These results are similar to those reported by Nelms et al. .Good results were found for lungs, femoral heads and bladder. DSC values for these OARs were similar to those found by Wong et al. for bladder, femoral heads  and lungA limitation of the study is the low number of patients analyzed for each setting. However, the analysis considers all OARs involved in the clinical workflow for the considered anatomical regions. This allows for a comprehensive assessment of the impact of LC on radiotherapy routine and considers all the steps of the radiotherapy planning process, from contouring to dosimetric consequences of the unsupervised use of LC. A complete description of LC impact on radiotherapy routine can provide useful information.As a novelty, this study provides quantitative evidence of the time savings achieved by LC use. These values are realistic, thanks to the number of contoured structures. Furthermore, it is possible to identify the anatomical sites which most benefit from LC. Dosimetric evaluation shows that, although DVH differences are not significant in most cases, LC contoured structures must always be supervised by an expert contourer. Otherwise, especially in regions near to high dose gradients, there may be relevant dosimetric variations.Although an accurate visual review by an expert clinician is still required, LC can significantly reduce the time required for contouring and simplify the workflow leading to treatment planning. Its implementation also allows reducing interobserver variability and improving the interpretation of radiological anatomy. Furthermore, LC can support staff training and the continuous assessment of clinical contouring and structure segmentation.


There were statistically significant differences (p = 0.01) in instances of URTI clusters among non-influenza respiratory pathogens between 2011 and 2019. There were also statistically significant differences (p < 0.001) in instances of URTI clusters in different locations between 2011 and 2019. In all the pathogens of URTI clusters (odds ratio (OR) = 1.89–2.25, p = 0.002–0.004), most single infections were influenza A viruses . Respiratory syncytial virus single infections were most numerous  among the non-influenza respiratory pathogens of URTI clusters. Of the institutions where URTI clusters occurred, schools had the most cases  . After the categorization of isolated virus strains by gene sequencing, it was found that, of the seasonal influenza A viruses, the H1N1 subtype viruses were predominantly A/California/07/2009, A/Michigan/45/2015, and A/Brisbane/02/2018, and the H3N2 subtype viruses were predominantly A/Hong Kong/4801/2014, A/Singapore/INFIMH-16–0019/2016, and A/Switzerland/8060/2017, during 2017–2019. Of the influenza B viruses, B/Brisbane/60/2008 (B/Vic) was the dominant type, and some were B/Massachusetts/02/2012 (B/Yam) and B/PHUKET/3073/2013 (B/Yam). This study is the first report of confirmed events of URTI clusters from surveillance data provided by the Taiwan CDC (2011–2019). This study highlights the importance of long-term, geographically extended studies, particularly for highly fluctuating pathogens, for understanding the implications of the transmission of URTI clusters in Taiwanese populations. Knowledge gaps and important data have been identified to inform future surveillance and research efforts in Taiwan.Clusters of acute upper respiratory tract infections are mainly caused by type A or B influenza virus. Numerous factors modify the risk of upper respiratory tract infection (URTI) cluster transmission. The purpose of this study was to investigate the epidemiological characteristics, differences, and epidemic trends in influenza viruses and in non-influenza respiratory pathogens, and the distribution of the sites of URTI cluster events in Taiwan from 2011 to 2019. We examined the publicly available annual summary data on 1864 confirmed URTI clusters in the Taiwan Centers for Disease Control (Taiwan CDC) from 2011 to 2019. URTI clusters were mainly divided into 1295 clusters of influenza virus infections, 149 clusters of non-influenza respiratory pathogen infections, 341 clusters of pathogens not detected by routine tests, and 79 clusters of unchecked samples. There were statistically significant differences ( Influenza is an acute viral respiratory disease. It is characterized by rapid outbreak, is widespread, and has serious complications. For children, the flu is more dangerous than the common cold. Children under the age of 5 years, especially those under the age of 2 years, are at higher risk for serious flu-related complications. Globally, the incidence of influenza in children under the age of 5 years is estimated to be ninety million cases per year . The CDCThe main pathogens causing influenza are influenza viruses. In terms of virus taxonomy, influenza viruses belong to the Orthomyxoviridae family. Depending on the antigenicity of the nucleoprotein, they can be divided into four types: A, B, C, and D, with a segmented single-stranded RNA gene body ,4,5.The influenza incubation period is about 1 to 4 days ,4. The iUpper respiratory tract infection (URTI) cluster incidents are a public health issue to which global health units attach great importance . Taiwan This study does not require ethical approval as it involves information freely available in the public domain, and the analysis of open dataset sources, where the data are properly anonymized ,15,16.1. The symptoms of URTI: they must meet one or more of the following symptoms: fever, cough, sore throat, shortness of breath, runny nose.2. URTI cluster case definition: a case with upper respiratory tract symptoms that is related to a person, time, and place and is judged to be a suspected cluster infection that is likely to spread.This study used the Taiwan National Infectious Disease Statistics System (TNIDSS) public database and the statistics of communicable disease and surveillance reports of the Taiwan Disease Control Agency website . The TNIIn addition, this study uses data from the “Viral Infectious Disease Contract Laboratory Surveillance System”. The specimens mainly come from suspected patients in the outpatient, emergency, and inpatient clinics of the medical center where the contract laboratory is located, as well as suspected patients in about 165 scheduled medical examination points nationwide. Patients with suspected influenza must meet the definition of influenza-like cases . In this study, the genetic sequence data of the influenza virus were analyzed for each year.p-values of less than 0.05 were considered statistically significant.The research structure was as follows: the retrospective surveillance database analysis of all local URTI cluster events in the database from 2011 to 2019. We determined the number of URTI clustering events from 2011 to 2019 and examined the differences and trends in the distribution of their epidemiological characteristics (types of URTIs causing pathogens and URTI clustering sites). We used the numbers (N) and percentages (%) of categorical variables to present pathogen detections and pathogen infections  in each year for URTI clusters. Chi-squared tests or Fisher’s exact tests (when expected numbers in cells were less than 5) were used to examine the differences in the distributions of the categorical variables. To estimate the effect of different types of pathogens  and different institutions  on the risk during different calendar years ), the logistical model was the estimated odds ratio with 95% CIs. All statistical analyses were performed using SPSS software . All statistical tests were 2-sided with an alpha level of 0.05. The p < 0.001) in numbers of URTI clusters among respiratory pathogens between 2011 and 2019 (p = 0.01) in numbers of URTI clusters among non-influenza pathogens between 2011 and 2019 (p < 0.001) in the numbers of URTI clusters in different public places between 2011 and 2019  . The numand 2019 . Furtherand 2019 . There wand 2019 . The occand 2019 . There wand 2019 .After the categorization of isolated virus strains by gene sequencing, it was found that of the seasonal influenza A viruses, the H1N1 subtype viruses were predominantly A/Brisbane/02/2018. The H3N2 subtypes were predominantly A/Singapore/INFIMH-16–0019/2016, while the rest were A/Switzerland/8060/2017 and A/Hong Kong/4801/2014. Of influenza B viruses, B/Colorado/06/2017(B/Vic) was the dominant type, and some were B/Washington/02/2019(B/Vic) and B/PHUKET/3073/2013(B/Yam) in Taiwan in 2019 .Influenza A virus infections were most common  in URTI clusters, and influenza B virus infections were the second most common  between 2011 and 2019 . Among nSchools were the most common location of viral URTI clusters in Taiwan, 2011–2019. Influenza A virus was the main cause of the viral URTI clusters. The respiratory syncytial virus was the main cause of the non-influenza URTI clusters. This study confirmed that the combination of locations at high risk of URTI clusters  and etiological substances  may lead to URTI clusters. In addition, the event numbers of URTI clusters showed an increasing trend during 2015–2017 in schools, both for pathogenic virus (influenza A virus) and for non-influenza respiratory virus (adenovirus).Influenza A virus is the main pathogen responsible for URTI cluster incidents in Taiwan. It is the main pathogen, accounting for approximately 65.9% of all known pathogens (970/1472). It can also be seen that the number of influenza clustering incidents has been increasing year-by-year (43 cases in 2011 rose to 370 cases in 2019), which means that influenza clusters are still a gap in Taiwan’s epidemic prevention. It is recommended that the government should form an expert committee to propose effective epidemic-prevention strategies and should jointly fight epidemics together with the public to prevent or slow down their spread. In addition, some studies have reported that influenza outbreaks are seasonal, causing large-scale illnesses and severe disease transmission [Influenza viruses in the upper respiratory tract are transmitted through droplets and contact and thus are prone to rapid spread in crowded places and often cause large-scale clusters. For example, a cluster of influenza A infection occurred in a chronic male ward of a psychiatric hospital in Taipei in 2007. Among 87 chronic psychiatric patients, 32 patients (36.8%) and 1 nurse in the ward had upper respiratory tract infectious symptoms, and the specimens of 25 cases cultivated influenza A virus. Furthermore, in five patients (15.6%) the disease was complicated by pneumonia . During Doi et al. reported that, in Japan, most of the clusters of URTIs caused by non-influenza respiratory viruses in 2014 were due to respiratory syncytial virus . Our stuIn Taiwan, clusters of URTIs occur in crowded, confined spaces. During the investigation period of this study, it was shown that there was a statistically significant difference in the number of incidents of URTI clustering in different types of locations. In 2011, 2013–2014, and 2017–2019, schools were the location of the majority of URTI clusters. In 2012, 2015, and 2016, densely populated institutions were the main locations. The results of this study not only showed that schools and densely populated institutions were the most common places for URTIs to cluster, they also clarified that the annual variation in cluster locations makes effective prevention and control difficult. This increases the burden on society and depletes medical resources. It is necessary to monitor the changing trends of locations of clusters over a long period and conduct follow-up research. Schools accounted for 41.6% of all the URTI clusters reported to TNIDSS. A higher percentage of URTI clusters in schools was also reported in China . HoweverComplete sequences were obtained for four influenza A(H1N1) virus samples isolated from cases that occurred during the 2017 epidemic season in Kerala, South India. Sequence analysis showed mutations that differentiate this strain from the reference strain A/California/07/2009 virus . The resIn recent years, due to the increase in public healthcare awareness, large-scale URTI cluster incidents have often attracted public attention. For example, in July 2019, an outbreak of influenza-like illness or a cluster of URTIs occurred in a college in Kaohsiung City, Taiwan. At least 100 people developed symptoms of URTIs, such as fever and cough, and 109 people were diagnosed with influenza-like illness . In the Because the influenza virus changes very rapidly, in addition to mastering the distribution of the number of cases, the monitoring of influenza also requires efficient laboratory testing to identify the type, variability, transmission, and pathogenicity of the virus. In addition, complete influenza virus surveillance will not only help to master the source and route of disease transmission but also help to diagnose the disease and confirm the appropriateness of antiviral drugs, so as to improve the medical quality, control the epidemic and transmission of influenza, and reduce the social cost of medical treatment. Taking this study as an example, based on the observation and recording of the relevant data on URTI clusters in the “statistical query and monitoring network of infectious diseases” published on the internet, this study uses empirical public health science methods to explore the epidemiological characteristics, differences, or trends in URTI clusters over the years. It applies the medical evidence available to public health services in order to prevent or slow down outbreaks of clusters of URTIs, evaluate exposure to hazards, or change the lifestyles of susceptible people through health education, so as to improve people’s health, which is necessary.This study has some main limitations. Firstly, the “statistical data of infectious diseases” published by the Taiwan CDC on the network platform only provides basic epidemiological data about URTI cluster events; there are no clinical data. Therefore, this study cannot compare the differences or trends in patients’ clinical data or symptoms. However, this study provides authentic positive confirmed cases announced by the Taiwan CDC. Second, this study only monitors the influenza virus by collecting samples from designated doctors, and from outpatient, emergency, and inpatient patients suspected to be infected with influenza virus, in medical centers where national and contract laboratories are located. There is no information on the genotypes of influenza viruses or other respiratory virus strains in patients with upper respiratory tract clusters. In addition, the genetic relationship between domestic and foreign virus strains cannot not be elucidated. Third, the definition of influenza cases is based on information on the official website of the Taiwan CDC, which does not specify what temperature is used to define fever . Therefore, we are not sure of the definitive clinical definition of fever. Fourth, the definition of influenza cases based on the information on the official website of the Taiwan CDC does not specify a time-variant, which is necessary in cases where a different symptom appears in the same child within 14 days from the first symptom after an initial recovery. Therefore, we cannot be sure if these are part of the same case or a new case. These limitations are not of significant importance in relation to this study and the interpretation of the results, and said limitations may not affect the validity of our results. Our findings strongly recommend that government institutions collect and publicly announce detailed pathological causes and clinical criteria of UTRI clusters and allow researchers to use more complete data to analyze them in-depth. One advantage of this study is that the existing network platform of Taiwan’s health department keeps data regarding URTI clustering for many years, so that public health  researchers or institutions can use these data to enhance scientific research on infectious disease epidemiology in Taiwan.These results may be worthy of attention from the government health departments for use in decision-making or as a reference for clinical or epidemiological expert research. Our results suggest that government departments should continue to support new laboratory techniques and diagnostic standards to increase knowledge on epidemiological characteristics and data. This will help with tracking URTI cluster incidence and discussing their epidemic patterns, trends, and risk factors in the future.


Corynebacterium diphtheriae and the resulting unique and severe clinical sequelae. Our patient was a young man with no known pre-existing conditions that presented in cardiopulmonary arrest. We contrast this case with prior instances of non-toxigenic C. diphtheriae strain infection in the United States and summarize the literature that suggests systemic infection can result in cardiogenic toxicity. We speculate on a possible missed, pre-existing condition that could have increased this patient’s susceptibility to poor clinical outcome.Here we document a rare, acute, infection caused by non-toxigenic  Corynebacterium diphtheriae is a gram-positive, rod-shaped, non-motile, non-sporulating, unencapsulated bacillus  and adult Tetanus-Diphtheria vaccination (Tdap) and booster (Td) largely eradicated cases of respiratory diphtheria in the United States (U.S.) and other developed countries . Since 2tigation , 14.Seroconversion following the primary series of Tdap vaccination in children is high (94% of patients), although this rate drops when vaccination occurs off-schedule . For aduC. diphtheriae. Toxigenic and non-toxigenic strains of C. diphtheriae are morphologically indistinguishable  by his family via personal automobile. According to the family, the patient was unconscious for approximately 10 minutes during which time he did not receive cardiopulmonary resuscitation (CPR). Upon arrival, he was found to be in cardiac arrest; the patient was not alert or oriented to person, place, or time, cool to the touch, had no agonal respirations, no radial pulse on palpation, no activity on cardiac monitor, no heartbeat on auscultation, pupils that were equal, and 4 mm dilated but non-reactive. The patient’s Glasgow Coma Scale score was 3. A CPR protocol was initiated immediately. Spontaneous circulation was achieved after three rounds of epinephrine administration. The patient was admitted to an isolated room in the Intensive Care Unit (ICU), intubated, and placed on a ventilator with a sedation regimen. A 12-lead EKG was obtained following stabilization of the patient demonstrating ST changes consistent with lateral wall ischemia .Vital signs, laboratory values, including a toxicology screen, and urinalysis  were allC. diphtheriae (anaerobic bottles) and Klebsiella pneumoniae (both aerobic and anaerobic bottles) as identified with polymerase chain reaction (PCR) analysis  b.i.d. for empiric, broad-spectrum coverage as recommended by the Infectious Disease team which also prescribed a 10-day course with 875/125 mg Amoxicillin/Clavulanate potassium (Augmentin) b.i.d. by mouth outpatient. As the patient could not be directly interviewed during his acute presentations we cannot be sure whether the patient was experiencing symptoms prior to his presentation. This is in part why the Pediatric Infectious Disease services empirically treated the patient for K. pneumo at the time of his first admission.Review of the patient’s medical charts revealed one other admission nearly 1 year prior to the current presentation. At that time, the patient also presented in a state of unresponsiveness after he was found reportedly “sleeping” in his room by his sibling who described labored breathing. The patient presented to the hospital in a state of shock. He received atropine 0.5 mg IV bolus and fluids. The patient was sedated, intubated, and transferred to the ICU. Naloxone (Narcan) 0.4 mg IV was administered empirically, and Psychiatry Services were consulted for possible toxin ingestion. Urine and blood toxicology analysis were unremarkable  and urinFurther workup included a computerized tomography scan of the cranium, cervical spine, abdomen, thorax; no significant findings were reported. Cardiac electrocardiography (ECG) showed sinus tachycardia and a prolonged QTc interval of 572 ms . Repeat The patient was extubated and discharged 4 days following his admission. He was scheduled for outpatient follow up with Pediatric Cardiology Services. A stress test performed in that setting was normal with one premature ventricular contraction. Repeat cardiac echocardiogram and CT angiogram of coronary arteries were performed showing non-structural cardiac disease. He was referred for genetic testing for further work-up of a suspected genetic cardiac abnormality due to a family-reported (but unconfirmed) paternal uncle who passed away suddenly from a heart attack at the age of 40 in Honduras. The patient did not follow up for this genetic testing, likely due to financial limitations.C. diphtheriae, indicating carrier status. In addition to Tdap boosters, IM Penicillin G for adult, family household and close contacts were chosen for treatment after discussion between Suffolk County Department of Health and the in house Infectious Disease team. The patient’s antibiotic course of piperacillin-tazobactam was extended, and cefepime 2,000 mg q.d. was added to the regime. Subsequent two-draw blood cultures on days 2 and 5 had no growth.Presently, testing confirmed the strain to be non-toxigenic. As per the CDC’s Investigational New Drug protocol, antitoxin is only in cases of early detection of toxin-producing strains . As per The patient’s progress was poor; due to the extended period without protected airway and circulation, the patient suffered irreversible anoxic brain injury. His family asked that “everything be done for him” and that the Chaplain’s Office, wherein representatives provide spiritual or religious support at the bedside, be involved in his case. Palliative Care Services were also consulted.Given the patient’s prior cardiac history and workup, and current presentation of cardiac arrest with pulseless electrical activity, Electrophysiology (EP) Services was consulted, and the patient was kept on telemetry monitoring as part of his ICU care. That team confirmed the likelihood of a prolonged QTc and recommended continued avoidance of exacerbating medications for which review of concomitant medications was performed. A 2D echocardiogram demonstrated left ejection fraction (LVEF) of 50–55%. The patient was not considered a candidate for any EP intervention given his poor functional status and prognosis.°C) for a period of 4 days. A suprapubic catheter and feeding tube were placed. On day 9 of the patient’s admission, his ventilatory status improved and a tracheostomy was performed, but he continued to produce oropharyngeal secretions requiring suctioning every few hours. Two bronchoscopies were performed; cultures of which grew ventilator-associated species- Staphylococcus aureus and Stenotrophomonas maltophilia (On day 2 of admission, the patient deteriorated into status epilepticus and was started on 1,000 mg IV levetiracetam q.12.h. Overnight on day 2, he was noted to have a fever and continued to spike fevers daily (maximum temperature of 39.0tophilia , for whiC. diphtheria in the U.S. in 2021. Similar cases of bacteremia and significant clinical sequelae resulting from non-toxigenic diphtheria are rare (C. diphtheria is uncommon in developed countries (To the best of our knowledge this is the second case of systemic infection with a strain of are rare . In deveare rare , 30. Ourountries . Such caountries , not as We suspect that the patient held a congenital prolonged QT syndrome that remained subclinical up to the time of his first admission and that was possibly exacerbated by his infectious, inflammatory state as has been suggested by prior literature , 33. ThiFinally, we acknowledge the cultural and socio-economic factors present in our patient that are associated with greater overall health risks and complications. Social and cultural determinants of health are a much-discussed issue which result in lack of access to, and use of, preventive and primary care, as well as lack of established trust with the medical system –39. Our C. diphtheriae in vaccinated populations.The case characterized here resulted in a complex cascade of clinical consequences that we hope will spur conversation among critical care, infectious disease, medical genetic, and cardiology specialists. We hope practitioners will consider at which points in the healthcare system efforts could have ameliorated a better outcome and the lingering future threat of disease resulting from infection with non-toxigenic forms of The original data contributions presented in this study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the patient or next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.GA and DR were responsible for manuscript drafting and editing. DR was responsible for literature review, final formatting, and submission. SS facilitated discussions with the CDC and NYS Department of Health. GA, SS, SM, SG, PS, and CH oversaw care of the patient, interpreted patient data, and contributed meaningful discussions and edits to the manuscript. All authors approved the final version of the work.