Risky decision-making is highly influenced by emotions and can lead to fatal consequences. Attempts to reduce risk-taking include the use of mindfulness-based interventions (MBI), which have shown promising results for both emotion regulation (ER) and risk-taking. However, it is still unclear whether improved emotion regulation is the mechanism responsible for reduced risk-taking. In the present study, we explore the effect of a 5-week MBI on risky driving in a group of repeat traffic offenders by comparing them with non-repeat offenders and repeat offenders without training. We evaluated the driving behavior of the participants through a driving simulation, and self-reported emotion regulation, both before and after the intervention. At baseline, poor emotion regulation was related to a more unstable driving behavior, and speeding. The group that received mindfulness training showed improved performance during risky driving situations and had fewer accidents, although their overall driving behavior remained largely unchanged. The observed trend toward improved emotion regulation was not significant. We discuss whether other effects of MBI – such as self-regulation of attention – could underlie the observed reduction in risky driving in the initial stages. Nonetheless, our findings still confirm the close relationship between emotion regulation skills and risky driving. Daily life involves constant decision-making with regard to what actions to take and some situations can lead us to take certain risks, e.g., when we are in a rush or in a bad or even euphoric mood. In fact, the factors that modulate the process of risky decision making include emotion , impulsiIn driving environments in particular, risky driving and low perception of risk have been found to be influenced by emotions  and emotDue to the influence of ER on risky driving, one promising strategy for reducing road fatalities could be the use of interventions that, through the improvement of ER skills, lead to safer driving behavior . One wayMindfulness, understood as a trait, is the natural mindful tendency of each individual  and has Thus, in the light of these findings, we aimed to test the effectiveness of a MBI in reducing risky driving behavior in a group of repeat traffic offenders, measuring behavioral change through a driving simulation. This type of measurement has been used to study real driving behavior, with a correspondence between real and simulated driving . SpecifiM = 34.39, SD = 14.57) recruited in an online survey from the University of Granada , as well as during a rehabilitation course run by a driving school, where drivers recover their points lost because of traffic rule violations. All participants were drivers with a valid driving license. The greater number of men represents the gender differences in driving violations present in the population , or reporting as having usually exceeded speed limits by more than 20% of the permitted speed. Sixty repeat offenders, meeting at least one of these criteria, and 29 non-repeat offenders, meeting none of these criteria, completed the baseline and post-intervention evaluations.Half of the risky drivers were selected for a 5-week MBI program dependent on their weekly availability, which was established prior to testing, to gather the greatest number of participants for the intervention groups. At four different time points along the 2-year period of data collection, we grouped the participants who coincided at the same weekday availability, resulting in a quasi-randomized controlled trial. The drop-out rate of the mindfulness training following the second session was 6 out of the 30 participants.N = 29), repeat offenders , and repeat offenders who received mindfulness training , km driven per year and in life, months of holding a driver license, number of rehabilitation courses, number of lost points, number of traffic fines, and frequency of exceeding speed limits.Lack of emotional awareness (six items), Impulse control difficulties (six items), Non-acceptance of emotional response (seven items), Difficulties engaging in goal-directed behavior (five items), Lack of emotional clarity (five items), and Limited access to emotion regulation strategies (seven items). The internal consistency of the scale is adequate (Cronbach’s α = 0.88).The Spanish version of the Difficulties Emotion Regulation Scale DERS;  measuresSelf-Blame (Cronbach’s α = 0.61), Rumination (Cronbach’s α = 0.74), Catastrophizing (Cronbach’s α = 0.72), Other-Blame (Cronbach’s α = 0.79), Acceptance (Cronbach’s α = 0.64), Positive reinforcing (Cronbach’s α = 0.89), Refocus on planning (Cronbach’s α = 0.83), Positive reappraisal (Cronbach’s α = 0.8), and Putting into perspective (Cronbach’s α = 0.83). The first four and the remaining five subscales were grouped into negative and positive ER strategies , respectively, as suggested by the original authors , of speed in a risk situation (km/h), and of exceeded speed limits (km/h), length of time spent exceeding speed limits (sec), average throttle rotation (%), variance of steering wheel (rad), front and rear brake force (kg), number of accidents, and the average rating of performance in each risk situation, calculated by the HRT, ranging from A (good performance) to D (accident), taking into account variables, such as speed when entering the risk situation and distance to crash with an object. This last value is coded from 1 to 4 with lower values indicating greater risk-taking and worse performance in a risk situation. Exceeded speed limits, speed in risk situations, and performance ratings are calculated for the two urban courses only, since the HRT software does not register measures of speed limits or risk situations in the mountain road scenario.The mindfulness-based training was adapted from the Mindfulness-Based Stress Reduction (MBSR) program widely used in research . The proSD = 69.15) and varied across the participants due to their availability. Therefore, the length of this interval was included as a factor in the data analysis.The participants were selected according to their self-reported traffic violations, which were requested by means of an online survey (see participants section). The baseline and post-intervention evaluation was the same. Participants came to the research center and, as a part of a broader project, filled in the questionnaires and completed the driving simulation, with the order based on the availability of the facilities (HRT and computer room) and participants’ temporal availability. The average interval between both evaluations was approximately 4 months  and R Studio  were used for analyses, along with p value null hypothesis statistical testing (NHST) and Bayesian methods.JASP statistical software , education level , age , or driving experience .We found no differences between the three groups in terms of gender (Pearson’s 10) was calculated for all possible models compared to the null model, as well as the BFInclusion for each predictor  and subscales as within-subject factors, and group  as between-subject factors, using age and interval between evaluations as covariates. To support our hypothesis with Bayesian methods, the Bayes Factor /] with group as the between-subjects factor and age and interval between evaluations as covariates.For variables with significant time × group interactions, mediation analysis was conducted. To explore the magnitude of the intervention effect, an ANCOVA was carried out on the Behavior Shift Index BSI; , definedAs accident rate is not a continuous variable, these rates are analyzed by categorizing the difference between baseline and post-intervention evaluation into improved (difference > 0), unchanged (difference = 0), and worse performance (difference < 0). A multinomial regression was conducted, and risk ratios were estimated with group  as the between-subjects factor and age and interval between evaluations as covariates.Finally, we explored whether ER and driving behavior are related, conducting a partial correlation analysis between the BSI values of all questionnaire subscales and the driving behavior indices, using age as a covariate. We also confirmed a general relationship between ER and the driving behavior indices at baseline in the whole sample .F = 3.919, p = 0.024, η2 = 0.085, BFInclusion = 2.255], as well as a main effect of age  and no differences between the two control groups (p > 0.4). The ANCOVA on BSI scores, indicating the magnitude of changes, revealed a main effect of group  and no main effect of age . However, there was a tendency for the R-M group to show improvement in the DERS and the negative scales of the CERQ, which can be observed in No time × group interaction effect was found for ER [DERS: In summary, participants who were trained in mindfulness do not show differences in ER but showed improved performance in risk situations and had fewer accidents in comparison with both control groups. It is also worth noting that while age is an important factor in the prediction of driving behavior, this factor has almost no influence on the magnitude of improvement observed as a consequence of the intervention.In the current study, we explored the effect of MBI on driving behavior and ER. We evaluated the performance on a driving simulation and self-reported ER scores of a group of repeat offenders trained in mindfulness and compared these measures with those of two control groups, one of repeat offenders and another of non-repeat offenders. We found that the intervention had an effect on accidents and evaluation of performance in risk situations, but no effect on ER and most of the behavioral indices. However, driving indices were closely related to the performance ratings at baseline, while the magnitude of change was related to the one of performance ratings, being greatest in the mindfulness trained group.The R-M group of our study had fewer accidents and performed better in a risk situation, although no differences were found in terms of the other driving indices, such as speed, acceleration, and driving direction. However, these indices are closely related to performance ratings in risk situations, and the magnitude of change observed in these measures is strongly associated with the change in performance ratings in the R-M group, pointing to the possibility that most of the indices are enhanced in a similar way. As mentioned earlier, the length of the intervention could have played a role in the non-significance of some of these effects, which might be greater in a follow-up study.Previous research on the effect of mindfulness training on driving behavior is still scarce. In fact, there is only one study exploring changes in driving simulation, which found a (non-significant) reduction in traffic violations in students enrolled in a Buddhism course . Since tFurthermore, our findings showed that age is one of the most important predictors of risky driving behavior on the simulator, characterized by speeding, an instable direction, and low evaluations in the performance in risk situations, which is in line with previous research . HoweverIn the present study, we found no differences in ER following the 5-week MBI, although the pattern of results points to less ER difficulties and a reduction of negative ER strategies, such as ruminations, catastrophizing, and blaming oneself or others. Studies with a longer intervention – usually 8 weeks – have found enhanced ER . The patients/participants provided their written informed consent to participate in this study.ACt, ACn, AM, and SB designed the experiment. LM-C and SB carried out the testing of participants. CV-L and EC-V designed and performed the intervention. SB and ACt analyzed the data. SB and LM-C drafted the manuscript. All authors contributed to the critical revision of the manuscript and approved the final version.CV-L and EC-V were employed by the company Presentia.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Background and Objectives: Abnormal concentrations of bioelements  have been associated with physical and emotional dysfunctions, including depression. This association, however, has not been analyzed in testosterone deficiency syndrome (TDS) or patients with depressiveness, i.e., when individual symptoms do not form the picture of a full-syndrome depressive disorder. This study aimed to assess the relationship between concentrations of selected bioelements and the incidence of depressive symptoms in men aged 50 years and older with a concurrent testosterone deficiency syndrome. Material and Methods: Blood samples were taken from 314 men; the mean age of the population was 61.36 ± 6.38 years. Spectrophotometric method for biochemical analysis of magnesium (Mg), manganese (Mn), chromium (Cr), copper (Cu), and zinc (Zn) was used. The diagnosis of testosterone deficiency syndrome (TDS) was based on the total testosterone (TT), free testosterone (FT), estradiol (E2), and dehydroepiandrosterone sulfate (DHEAS) levels by ELISA. Each participant completed the Androgen Deficiency in Aging Male (ADAM) questionnaire, as well as the Beck Depression Inventory (BDI-Ia) measuring the severity of depressive symptoms. Results: Emotional disturbances manifested as depressive symptoms were diagnosed in 28.7% of all participants and testosterone deficiency syndrome in 49.3%. In the TDS group, the analysis showed a significant correlation between the level of manganese  and chromium  with the incidence of depression. Conclusions: The results of our study demonstrated a relationship between manganese and chromium concentrations with the incidence of depression in men aged 50 years and older with a concurrent testosterone deficiency syndrome. This may indicate that there is a correlation between these bioelements, as well as emotional disorders manifested as depressive symptoms in aging men with a diagnosed testosterone deficiency. It is estimated that the prevalence of depression and depressiveness, i.e., individual symptoms that do not form the picture of a full-syndrome depressive disorder, increases among people over 65 years old . The mosThe reasons for the occurrence of depressive changes can be divided into psychosocial factors, related to loss of employment, financial independence, as well as change in social position, and into biological factors, among which the most important are degeneration of the central nervous system progressing with age and a reduction of neurotransmitter activity ,4.Clinical depression and single depressive symptoms in aging men may be caused by a gradual decrease in testosterone concentration associated with aging, which may eventually lead to testosterone deficiency syndrome (TDS) ,6. The mThe relationship between the incidence of TDS and depressive disorders may be associated with the neuroprotective effect of testosterone achieved by inhibiting the toxic effect of glutamate ,10.N-methyl-D-aspartate receptor (NMDA), which results in increased Ca2+ transport [The glutamate activates the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPA) and ransport . This acransport . AntidepWhen analyzing the pathophysiology of depression symptoms, we should note the changes in concentrations of bioelements, as they may underlie the mechanisms leading to emotional disorders as well as clinical depression ,14,15,16Bioelements also affect the total (TT) and free (FT) testosterone concentration, as well as estradiol levels, and thus may negatively or positively affect the development of testosterone deficiency syndrome in aging men . This study aimed to assess the relationship between the concentration of bioelements and the incidence of depression in men over the age of 50 with a concurrent testosterone deficiency syndrome.This cross-sectional study included 314 men between 50 and 70 years old recruited from primary healthcare facilities (POZ) in Szczecin, Poland. Before the study began, each participant gave their voluntary consent to participate in the study and was acquainted in detail with the course and objectives of the study. The study excluded people undergoing oncological treatment; those with thyroid disease; those receiving neuroleptics, antidepressants, and supplements containing studied bioelements and treated with steroid therapy; those undergoing testosterone replacement therapy; individuals with depression at any stage diagnosed by a psychiatrist; or those diagnosed with TDS.On the basis of the presence of testosterone deficiency syndrome, participants were assigned to one of two groups. Group I included 155 people with TDS. Group II included 159 people without TDS. Patients in both groups were assigned to a subgroup with and without the depressive disorder, which was diagnosed on the basis of the Beck Depression Inventory (BDI-Ia). Research procedures and analyses were the same for all participants. The study flowchart (according to STROBE guidelines) is shown in The study was performed in accordance with the Declaration of Helsinki after it was approved by the Bioethical Committee of the Pomeranian Medical University in Szczecin, Poland (2012-12-10 no. KB-0012/159/12). Each patient enrolled in the study signed an informed consent form for participation and study procedures. In terms of personal data protection, the analysis was performed on dehumanized (anonymous) data. Three types of questionnaires were used in the study: a dedicated questionnaire prepared by the authors, the Morley questionnaire, and the Beck Depression Inventory (BDI-Ia). The first questionnaire included an interview regarding basic sociodemographic data and medical history information, focusing on determining the presence of possible contraindications in participating in the study. The questionnaire created by J.E. Morley was used to assess the symptoms of testosterone deficiency . It consThe Beck Depression Inventory (BDI-Ia) was used to measure the severity of depressive symptoms and included 21 multiple-choice questions with a range of disjunctive questions related to current mood, level of self-esteem, relationships with other people, appetite, quality of sleep, and fear for one’s health and life . The ansIn patients from both study groups, 9 mL of fasting blood was drawn from a venipuncture into tubes with gel separator and clot activator, which were then centrifuged and stored at −80 °C in 1.5 mL microtubes. Bioelements were analyzed by optical emission spectrometry with inductively coupled plasma . The analysis was carried out in axial and radial orientation. Tested bioelements included magnesium (Mg), manganese (Mn), chromium (Cr), copper (Cu), and zinc (Zn).3  was added to each tube, and the tubes were left for 30 min. After this time, 1 ml of unstabilized 30% H2O2 solution  was added. Next, all samples were placed in Teflon vessels and heated at 180 °C for 35 min using a microwave system. After this time, the samples were cooled to room temperature and transferred to 15 ml acid-washed polypropylene tubes. A 25-fold dilution was made before ICP-OES measurement. A volume of 400 µL was taken and enriched with a standard to a final concentration of 0.5 mg/L yttrium 1 ml 1% Triton . It was then diluted with 0.075% nitric acid  to give a volume of 10 ml. The samples were stored at the temperature of 8 °C. A blank sample was prepared by adding 300 µL of nitric acid and diluting it in the same way as the test sample.Samples of 0.75 ml were thawed to room temperature and microwaved with the MARS 5 system, CEM. Next, the material was transferred to polypropylene tubes, 2 ml of 65% HNOMultifactor calibration standard samples for Cu, Cr, Mg, Mn, Zn, Se, and Mo analysis and phosphorus ICP Standard  were prepared with different concentrations of elements, as well as the test and the blank sample. Deionized water  was used. The wavelengths (in nanometers) for individual elements were as follows: Cr—283.563 nm, Cu—324.754 nm, Mg—285.213 nm, Mn—260.569 nm, Zn—213.856 nm. The analyses were performed in the Biochemical Laboratory of the Pomeranian Medical University.Total testosterone (TT), free testosterone (FT), estradiol (E2), and dehydroepiandrosterone sulfate (DHEAS) levels were determined by ELISA, using reagents in ready-made kits  at the Medical Analytics Department of the Laboratory Diagnostics Department of Pomeranian Medical University in Szczecin.Testosterone deficiency syndrome (TDS) was diagnosed on the basis of the results of laboratory tests with a TT result of less than 2.5 ng/ml or 3.5–2.5 ng/ml when clinical symptoms were assessed using the ADAM  questionnaire, supplemented by affirmative answers to questions proposed by the European Menopause and Andropause Society referring to the less frequent occurrence of morning erections and sexual thoughts and more frequent erectile dysfunction .p-value of ≤0.05 was regarded as statistically significant.The normality of quantitative data distribution was assessed using the Shapiro–Wilk test. Quantitative data were evaluated using the Mann–Whitney U test. Qualitative variables were analyzed using the chi-squared test or chi-squared test with Yates correction. Multivariate logistic regression analysis adjusted for age, smoking and marital status, education, occupational activity, body mass index (BMI), and waist-hip ratio (WHR) classifications was performed. The statistical analysis was performed using the Statistica 13 licensed program . A The full characteristics of the study group are presented in The results regarding the parameters included in the analysis are presented in p = 0.005) and chromium (p = 0.022) levels was observed in patients with a known testosterone deficiency syndrome. Out of participants from the first study group, an increase in mean manganese  and chromium  levels with the presence of depression. The results are presented in The analysis also showed no significant correlation between the selected concentrations of bioelements and depression among patients from the group without known testosterone deficiency syndrome and with TDS. In the TDS group, the analysis showed a significant correlation between manganese  levels and negative fractions in the case of sex hormone binding globulin (SHBG), suggesting a positive effect of this bioelement on patients suffering from TDS . In the On the other hand, a proven positive correlation between magnesium concentration and TT concentration may show the significance of this bioelement when determining the pathomechanisms of testosterone deficiency syndrome . In our A meta-analysis carried out by Ni et al. in 2018, with results collected from other studies, indicated a significant relationship, one that increases with age, between the incidence of depression symptoms and copper concentration. The authors additionally suggested that this bioelement is a biomarker for a full-blown disease . This wa1A), as is the case with SSRIs, which reduce receptor sensitivity and inhibit serotonin reuptake in the synaptic cleft. This mechanism has been broadly described by Duboszewska et al. [The relationship between depressive and anxiety disorders and zinc is one of the most extensively described in the literature around issues related to this work ,42. In aa et al. . Moreovea et al. . Additionally, in the case of testosterone deficiency syndrome, zinc deficiency seems to be one of the components of the pathomechanism due to the negative correlation with SHBG, causing the body’s access to free testosterone fractions . Other sThe results of our study showed the relationship between manganese and chromium concentration and the occurrence of depression in men over 50 years of age with a concurrent testosterone deficiency syndrome. This may indicate the relationship between these bioelements, and emotional disorders manifested as depressive symptoms in aging men with a diagnosed testosterone deficiency.The most significant limitation of our study was the ambiguity of the classification criteria of testosterone deficiency syndrome. There are many standards set by various TDS testing organizations around the world. However, in the above study, we chose those accepted by the International Society of Andrology (ISA), International Society for the Study of the Aging Male (ISSAM), European Association of Urology (EAU), European Academy of Andrology (EAA), and American Society of Andrology (ASA) in 2009. An additional difficulty is the limited amount of literature available on bioelements and their impact on the functioning of cognitive processes. Moreover, the power of the investigations was obtained slightly lower than 0.8; therefore, our results need confirmation in a larger patient population with depressive symptoms and TDS. No information related to alcohol consumption, detailed medical history, or physical activity that could affect the results presented in the study was collected. We believe that in order to increase the credibility of the results, the number of study participants should be increased in the future. Free testosterone determination was performed by ELISA, which may cause inaccuracy in the determination of this parameter.


Morbidity and mortality associated with non-valvular atrial fibrillation (NVAF) imposes a substantial economic burden on the UK healthcare system.An existing Markov model was adapted to assess the real-world cost-effectiveness of rivaroxaban and apixaban, each compared with a vitamin K antagonist (VKA), for stroke prevention in patients with NVAF from the National Health Service (NHS) and personal and social services (PSS) perspective.The model considered a cycle length of 3 months over a lifetime horizon. All inputs were drawn from real-world evidence (RWE): baseline patient characteristics, clinical event and persistence rates, treatment effect , utility values and resource use. Deterministic and probabilistic sensitivity analyses were performed.The incremental cost per quality-adjusted life year was £14,437 for rivaroxaban, and £20,101 for apixaban, compared with VKA. The probabilities to be cost-effective compared with VKA were 90% and 81%, respectively for rivaroxaban and apixaban, considering a £20,000 threshold. In both comparisons, the results were most sensitive to clinical event rates.These results suggest that rivaroxaban and apixaban are cost-effective vs VKA, based on RWE, considering a £20,000 threshold, from the NHS and PSS perspective in the UK for stroke prevention in patients with NVAF. This economic evaluation may provide valuable information for decision-makers, in a context where RWE is more accessible and its value more acknowledged. As part of the core reimbursement dossier, Health Technology Assessment bodies require both the clinical and economic evaluations of new technologies –4. RandoRCTs and RWE differ in several aspects. First, RCT populations are selected based on inclusion/exclusion criteria, and are treated under highly regulated conditions, while RWE reflects the situation in a real-world patient population. Second, RCT sample size is limited whereas RWE can be based on a large sample size. Third, the timeframe of RCTs is usually short, with only a selection of outcomes, and long-term outcomes are often not available. RWE can provide results on a broader range of outcomes than are typically observed in RCTs, and can bestow more longitudinal insights whilst RCTs are usually focused on first-time event data collection ,4. RWE iThis paper aims to provide an illustration of a cost-effectiveness model considering RWE, using as an example an economic evaluation of oral anticoagulation treatment for the prevention of stroke in patients with non-valvular atrial fibrillation (NVAF), in clinical practice in the UK.Atrial fibrillation (AF) is a condition characterized by an abnormal heart rhythm resulting from irregular electrical signals. It is the most prevalent cardiac arrhythmia and can manifest as chest pain, dyspnoea, palpitation and dizziness or loss of consciousness . AssociaOral anticoagulation has been established as a cornerstone of the management of patients with NVAF and has been shown to reduce the incidence of stroke and mortality . Oral anAn existing Markov model was updated to assess the comparative costs and outcomes of rivaroxaban and apixaban, each compared with VKA, for the first-line treatment of adult patients with NVAF and with more than one risk factor for stroke . This anAs described elsewhere , the modAfter initial treatment allocation, patients can discontinue their initial treatment, switch from rivaroxaban (or from apixaban) to VKA, switch from VKA to another VKA, or stop treatment, i.e. switch from any treatment to no treatment. Whatever the treatment, long-term consequences of events (first and subsequent) were considered until death.The model outcomes included the number of IS, the number of MI and the number of bleeds (ICH and GI), as well as the total QALYs, the total life-years (LY) gained, the total costs and the incremental cost per QALY or per LY gained.All inputs are presented in 2DS2-VASc score (=1) and 90% had a high CHA2DS2-VASc score (≥2).To ensure generalizability of the NVAF population in the UK, the model was populated with patient and clinical characteristics drawn from a recent UK database study on AF . PatientTransition probabilities of the VKA arm were derived from existing RWE studies providing event rates per patient for IS, MI, ICH and GI bleeds . The proAs the risk of discontinuation is unlikely to be constant over time, the model was updated to capture the evolution of persistence with time . DiscontA background mortality rate was applied to all states within the model, as identified from the latest UK life tables available (2016) . A numbeUtility values were derived from UK studies –35. No uThe cost categories comprise drug acquisition costs, administration costs, VKA monitoring costs and costs associated with clinical events. All resource use and costs were taken from RWE studies or reference costs, and all costs were inflated to 2018 levels when necessary. NHS reference costs were used where possible, especially for drug acquisition calculations or management costs, such as ICH bleeding and MI management costs, or VKA monitoring costs.A deterministic sensitivity analysis (DSA) was conducted to test the impact of variations in the parameters included in the model, and a probabilistic sensitivity analysis (PSA) was performed to evaluate the uncertainty of the model parameters on the cost-effectiveness results. In addition, several specific scenarios were considered.The first scenario considers the inclusion of utility decrements related to treatment: a utility decrement of 0.013 was associated with VKA and a utility decrement of 0.002 was associated with rivaroxaban and apixaban therapy ,13. A sePatients treated with rivaroxaban experienced incremental gains in both QALYs (0.12) and LYs (0.15) compared with VKA: rivaroxaban was associated with fewer cases of MI , and a lower rate of strokes  and ICH bleeds (0.036 vs 0.042 i.e. a reduction of 15%), but was associated with a higher rate of GI bleeds . From the NHS and PSS perspective, the benefits translated into an incremental cost per QALY of £14,437 and an incremental cost per LY of £11,299.Patients treated with apixaban experienced a lower rate of ICH bleeds (0.027 vs 0.042 i.e. a reduction of 37%) and GI bleeds (0.063 vs 0.088 i.e. a reduction of 29%) compared with VKA, however, no reductions were observed for rates of MI and strokes because the associated HRs were close to, or equal to 1. This translated into incremental gains in both QALYs (0.09) and LYs (0.12) compared with VKA, and into an incremental cost per QALY of £20,101 and an incremental cost per LY of £14,912.Cost-effectiveness scatterplots for rivaroxaban vs VKA and for apixaban vs VKA are presented respectively in Several scenarios were conducted. First, applying a utility decrement associated with NOAC and VKA therapy (scenario 1) reduced the ICER to £11,630 per QALY gained for rivaroxaban, and to £15,660 per QALY gained for apixaban. Finally, considering treatment incident studies only from the meta-analysis (scenario 2) reduced the ICER to £13,721 per QALY gained for rivaroxaban, and increased to £25,166 per QALY gained for apixaban.The use of NOACs for the prevention of stroke in patients with NVAF is an ideal example to test RWE in a cost-effectiveness analysis. RCTs have shown NOACs to be at least as efficacious as VKA for the prevention of stroke or systemic embolism in patients with NVAF –40, and Existing cost-effectiveness analyses of NOACs have found these treatments to be cost-effective –44. AlthA review of the UK NICE dossiers for the four available NOACs and of their associated appraisals –14 reveaThe model structure of this cost-effectiveness analysis was based on the previous submission of rivaroxaban to NICE ; no majoThis model is considered to be a RWE cost-effectiveness model as all the evidence came from RWE. The initial population is based on a RWE study, to reflect the characteristics of patients with AF in the UK. Patients progress between health states according to transition probabilities derived from RWE: RWE is considered both for event rates for VKA, but also for treatment effects for rivaroxaban and apixaban. The treatment effects were taken from RWE meta-analyses performed for each drug separately vs VKA , as wellThe results of the present analysis are consistent with the NICE evaluations ,13, wherWhen compared with VKA, while apixaban was associated with a decrease in the rate of GI bleeds, rivaroxaban was associated with fewer strokes. Because of the high management cost of this event, a strong impact on ICER was observed. The ICER vs VKA was below £20,000, suggesting rivaroxaban is cost-effective from the NHS and PSS perspective. For apixaban, the ICER was slightly above the threshold, however, more than 80% of the simulations showed apixaban to be cost-effective, suggesting these results should be interpreted with caution.This confirms previous results submitted to NICE ,13, but Although efforts were made to ensure the best structure and approach were used, considering clinician and health economist experts’ validation, several limitations should be considered. First, as in all models, this approach should be considered as a simplification of what is expected in real life. A number of assumptions are used to reflect adequately the long-term consequences of NVAF. Second, the use of multiple RWE studies included in the meta-analyses to estimate all treatment effect parameters raises the question of uncertainty, linked to the heterogeneity of RWE studies. The influence of several factors was investigated by repeating the meta-analysis of the RWE studies using several scenarios, by varying population characteristics or type of statistical adjustment used to control bias and adjusting for the quality of studies included . Some vaThis RWE economic analysis demonstrated that rivaroxaban is cost-effective vs VKA, from the NHS and PSS perspective, with an incremental cost per QALY of £14,437. Because of a lower efficacy in terms of MI and IS rate reduction, the ICER for apixaban vs VKA was £20,101 per QALY, slightly above the UK threshold of £20,000 per QALY; however, the sensitivity analyses showed a probability to be cost-effective exceeding 80%. Although several limitations are associated with this study, particularly due to the heterogeneity of RWE studies, these results are considered stable, providing valuable information to decision-makers, in a context where RWE is more accessible, and its value more acknowledged.


Chronic wounds have been a great burden to patients and the health care system. The popularity of the internet and smart devices, such as mobile phones and tablets, has made it possible to adopt telemedicine (TM) to improve the management of chronic wounds. However, studies conducted by different researchers have reported contradictory results on the effect of TM on chronic wound management.The aim of this work was to evaluate the efficacy and safety of TM in chronic wound management.We systematically searched multiple electronic databases  to identify eligible studies published from inception to June 12, 2019. Inclusion criteria were randomized controlled trials (RCTs) and interventional cohort studies that investigated the use of TM in chronic wound management. RCT and observational data were analyzed separately. A meta-analysis and qualitative analysis were conducted to estimate endpoints.P=.13), and wound healing around 1 year . Noninferiority criteria of TM were met. A decreased risk of amputation in patients receiving TM was revealed . The result of cohort studies showed that TM was more effective than standard care , whereas the outcome efficacy RR of wound healing around 1 year  and 3 months  was not significantly different between TM and standard care. Noninferiority criteria of TM were met for wound healing around 1 year in cohort studies.A total of 6 RCTs and 6 cohort studies including 3913 patients were included. Of these, 4 studies used tablets or mobile phones programmed with apps, such as Skype and specialized interactive systems, whereas the remaining 8 studies used email, telephone, and videoconferencing to facilitate the implementation of TM using a specialized system. Efficacy outcomes in RCTs showed no significant differences in wound healing (hazard ratio [HR] 1.16, 95% CI 0.96-1.39; Currently available evidence suggests that TM seems to have similar efficacy and safety, and met noninferiority criteria with conventional standard care of chronic wounds. Large-scale, well-designed RCTs are warranted. A chronic wound is defined as a break in the skin that failed to progress through a normal sequence of repair in 4-8 weeks . Venous Telemedicine (TM) is the use of telecommunication technologies to provide remote clinical services to patients to improve the quality of individual treatments. The concept of TM dates back to the 19th century. It was practiced via telegraph, telephone, and radio before the internet existed ,4. With Within wound care, TM could support access to expertise in remote areas to improve management of chronic wounds in geographically challenging environments ,9. BecauFindings from qualitative studies show positive results with several systematic reviews in recent years being published -16. WithOur objective was to conduct a systematic review and meta-analysis of randomized and interventional cohort studies. We sought to investigate whether TM follow-up in community care in collaboration with specialists in wound center is noninferior to the conventional standard care of chronic wounds.The systematic review and meta-analysis were conducted in accordance with recommendations by the Cochrane Collaboration  and the A systematic search of databases  was conducted to identify eligible studies published from inception to June 12, 2019. The reference lists of all identified articles and reviews were searched for potentially eligible studies. Only published articles were included. The search strategy is available in The bias of RCTs included in the systematic review was assessed using the Cochrane’s tool for assessing risk of bias , whereasData extraction was performed independently by two reviewers (LC1 and LC2). Any discrepancies were resolved by discussion or by a third investigator (XR). All studies included in the meta-analysis had to be either RCTs or cohort studies. The prespecified primary outcomes were wound healing; the secondary outcomes were all-cause mortality, amputation, number of consultations, and patient experience.P values were estimated for endpoints in wound healing, all-cause mortality, and amputation using a random-effect statistical model (DerSimonian and Laird method). Heterogeneity was assessed using the I2 statistic. Subgroup analysis was conducted to investigate the heterogeneity. According to clinical heterogeneity of the wound care model in the control arm, the studies were divided into 2 subgroups. In the community-based model, patients in the control arm received mainly routine wound care by general nurses in community or rural areas, who might not have enough expertise in wound care. In this model, patients might not receive standard care of wound management. By contrast, in the wound center-based model, patients received regular standard outpatient follow-up in the wound center. Sensitivity analysis was conducted by investigating the difference between random and fixed effects model as to effective measures. P values ≤.05 were considered statistically significant.A meta-analysis was performed using Stata 12.0 (Stata Corp) and RevMan 5.3 . Hazard ratio (HR) and associated statistics were either extracted directly from articles or estimated from Kaplan–Meier curves . Where sIn addition, we tested the hypothesis of noninferiority of TM follow-up for the primary efficacy outcomes. We adopted a Δ=–0.15 as margin of minimum clinically important differences ,28. For A total of 12,007 potential studies were identified by the systematic search. Of these, 58 studies were selected for full review. Ultimately, 12 trials met the inclusion criteria, comprising a total of 3913 patients. Of these 5 were cluster RCTs -21,29,30The selected studies ,27,29-33The result of assessment of risk of bias is presented in P=.01; I2=60.6%; I2 statistic of HR was 60.6% (P=.04), consistent with moderate heterogeneity of the analysis. In analysis stratified by study design, there was a trend in favor of TM in RCTs . The lower boundary of HR in RCTs was higher than 0.85, and the criteria of noninferiority of TM were met for wound healing. In addition, statistical difference was demonstrated in cohort studies demonstrating that TM had a decreased risk of allowing unhealed ulcers . We conducted a subgroup analysis of RCTs to investigate whether a different model of TM organization would result in different clinical effects. The studies that adopted the wound center–based model had a pooled HR of 1.13 , and the criteria of noninferiority of TM were met  and cohort studies . However, these statistical trends were in favor of TM, and the criteria of noninferiority of TM were met.Eight studies -22,29,31P=.67; I2=80.8%; Two studies ,33 reporP=.01). In this study, no exact number of healed wounds and time to healing were provided, and therefore, the study was not considered in the quantitative analysis.One study  revealedAnother study  adopted P=.03) and more severe pressure ulcers. Although wounds in the TM group took longer time to heal and required more resources, it seems as though a greater change in size for pressure ulcers and other wounds occurred.In the trial with uneven distribution of severity and type of wounds among groups , the TM P=.94; I2=62.6%; P=.89; I2=59.5%) and cohort studies . Subgroup analysis of RCTs reveals there was a statistically significant decreased risk of all-cause mortality in patients receiving TM in the community-based model ; however, no statistical difference in mortality in the wound center–based model was demonstrated  [P<.001).Three studies reported on the number of consultations. One RCT  revealedP=.20) . These tP=.20) , which aOne study  evaluateP=.42). Another 2 studies [A total of 4 studies ,21,22,32 studies  revealedThe sensitivity analysis is presented in In this review, we included 6 RCTs and 6 cohort studies comprising 3913 patients to evaluate the effect of TM in chronic wound management. We adopted both HR and RR to evaluate the effect of TM. In RCTs, we observed no significant differences in the primary clinical outcome efficacies HR and RR around 1 year, and noninferiority criteria were met. In cohort studies, the outcome efficacy HR was in favor of TM, whereas the efficacy RR around 1 year was not significantly different between TM and conventional standard of care of chronic wounds. Overall, these results showed that TM was noninferior to conventional standard of care. In terms of mortality, TM was not significantly different from control in both RCTs and cohort studies. A decreased risk of amputation was observed in patients receiving TM. A few studies performed qualitative analysis on the number of consultations, patient satisfaction, and economic evaluation with the results showing that TM was not worse than conventional standard of care of chronic wounds. Therefore, TM seems to be a safe and effective method in the management of chronic wounds.We carefully observed the difference of primary outcome between RCTs and cohort studies and found that the enrolled studies in RCTs were mainly wound center-based models, whereas those in cohort studies were all community-based models. Therefore, we speculate that the organization model may have a great influence on the effect of TM on wound healing; in particular, the community-based model may benefit from the implementation of TM. A possible explanation may be that in the community-based model, TM allowed patients in remote and rural settings easier access to multidisciplinary management which has been demonstrated to be an effective and efficient way of chronic wound management ,36.Subgroup analysis of RCTs suggested that in a community-based model, patients in the TM group have a decreased risk of mortality. Both the positive primary outcome in cohort studies and the decreased mortality are in favor of TM in the community-based model. This demonstrates that it is promising to take advantage of TM in community or remote rural areas.P=.83) as well as similar ulcer healing rate . A 10-year study of 5795 patients in France also provided an example of how TM might be of benefit in wound care [To our knowledge, this review included the largest number of patients with different types of wounds. The results of this review coincide with the systematic review by Tchero et al , which iund care .P=.0001). In the authors’ opinion, the dependence of TM on secondhand information from a nurse could have caused some vital information to be missed. Therefore, it is worth noting that the severity of wounds and other commodities should be taken into consideration when health care participants are considering the use of TM to manage chronic wounds.Although similar mortality rates were revealed between TM and conventional care of chronic wound, the result of a well-designed RCT  revealedFor the first time, we learned that the difference between the community- and wound center–based wound management models might seriously influence the effect of TM. A subgroup analysis was conducted to clarify the difference. Differing results between these two models indicate that it is prudent to understand the management model before interpreting the studies on TM in chronic wound management.This study has several limitations. First, we only searched 3 databases and did not include non-English literature. Although we tried to identify articles from reference lists of other reviews, it is possible that some studies in other databases or published in other language were overlooked. Second, we included RCTs and interventional cohort studies in the analysis, and thus, a potential source of bias might be introduced. Third, several studies ,32,33 weFirst, for RCTs, although blinding of outcome measurement would not seriously influence the results, nonblinding of participants might bias the effect. In future studies, more importance should be assigned to the blinding of participants and health care providers. For example, all participants can receive treatment/suggestions via TM, but the information would not be sent to wound center specialists. In this way, performance bias could be reduced to a minimum.Second, subgroup analysis indicates that TM in the community-based model is superior to standard primary care of chronic wounds by presenting with better outcomes and less mortality. Therefore, it is promising to take advantage of TM in community or remote rural areas. However, the number of studies in this aspect is limited and most studies are cohort studies. Thus, in future studies, well-designed, large-scale RCTs should be performed to verify the effect of TM in the community-based model.Third, subgroup analysis indicates that TM in the wound center-based model is similar to standard of care of chronic wounds. Therefore, it is necessary to investigate whether TM can have better performance in other aspects. Only a few studies showed that TM was not worse than conventional standard of care regarding number of consultations, patient satisfaction, and economic evaluation. Thus, in future studies, these aspects can be included in the design of trials to investigate the effect of TM.Finally, results in this systematic review and meta-analysis also shed some light on clinical practices. If health care practitioners would like to use TM to improve wound healing, they do not have to worry about delayed wound healing. For those patients who lived far away from wound center, TM can provide appropriate wound management.TM is noninferior to conventional standard care of chronic wounds. TM might be a prosperous method for improving outcomes of patients living in remote or rural areas. However, owing to the relatively low quality of evidence, well-designed and adequately powered RCTs are further needed to confirm the role of TM.


A total of 378 radiomic features were extracted from a single tumor region of interest (ROI) of each patient on each phase of CT images. Imaging features were extracted from plain CT and contrast-enhanced CT (CECT) images. After dimensionality reduction, a radiomics signature was constructed. A combination model was constructed by incorporating the rad-score and CT radiological features. An independent group of 38 patients from hospital #2 was used to validate the prediction models. The model performances were evaluated by receiver operating characteristic (ROC) curve analysis, and decision curve analysis (DCA) was used to evaluate the clinical effectiveness of the models. The radiomics signature model was constructed and the rad-score was calculated based on selected imaging features from plain CT and CECT images.Analysis of variance and multivariable logistic regression analysis showed that location, lymph node metastases, and rad-score were independent predictors of tumor malignant status. The ROC curves showed that the accuracy of the support vector machine (SVM)-based prediction model, radiomics signature, location and lymph node status in the training set was 0.854, 0.772, 0.679, and 0.632, respectively; specificity was 0.869, 0.878, 0.734, and 0.773; and sensitivity was 0.731, 0.808, 0.723, and 0.742. In the test set, the accuracy was 0.835, 0.771, 0.653, and 0.608, respectively; the specificity was 0.741, 0.889, 0.852, and 0.812; and the sensitivity was 0.818, 0.790, 0.731, and 0.716.The combination model based on the radiomics signature and CT radiological features is capable of evaluating the malignancy of PG tumors and can help clinicians guide clinical tumor management. Parotid gland (PG) tumors are rare and account for approximately 1%–3% of all head and neck tumors . KnowledCurrently, multiple imaging techniques are available to study the parotid region, such as ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI). Although CT is not a first-line method for parotid gland tumor evaluation, it can be used to help clinicians evaluate PG tumors to confirm the presence of a parotid mass, assess the extent of tumor especially in the deep lobe, and detect enlarged lymph nodes, to facilitate the determination of benign or malignant nature of the tumor for appropriate treatment. However, CT involves radiation, and various neoplasms may have similar imaging features on CT , 4. FurtRadiomics is new method of mining objective and quantitative features such as the shape, intensity, and energy of regions of interest from medical images  and run length matrix (RLM) features), describing the relationships between image voxels far beyond the traditional visual features we can obtain and thus reflecting the underlying genetic and biological variability of the analyzed tissue, which can promote accurate diagnosis and individualize cancer treatment . Recent However, as mentioned above, it is difficult to distinguish benign from malignant PG tumors with conventional CT images, but considering the novelty of radiomics and the powerful performance of tumor differential diagnosis in other field, we hypothesize that radiomics analysis based on conventional CT images can be used to distinguish between benign and malignant PG tumors. The purpose of this study is to utilize conventional CT images to extract PG tumor-related radiomic features and combine them with conventional radiological features to build a classification model for distinguishing benign and malignant PG tumors.This retrospective study was approved by Ethics Committee of Zhejiang Provincial People’s Hospital. All patients’ informed consents were waived for the retrospective nature of this study.The research method was carried out in accordance with the relevant guidelines and regulations. Patients’ clinical and image data were obtained from routine clinical records and the picture archiving and communication systems (PACS) of the hospital.A retrospective review of clinical and radiological databases was performed from January 1, 2017, to January 30, 2020, in hospital #1 and from Jan 1, 2019, to January 30, 2020, in hospital #2. The inclusion criteria were as follows: (1) patients with PG-related symptoms or masses; (2) confirmation of the PG tumor by surgery and postoperative pathological diagnosis; and (3) non-contrast computed tomography (NCCT) and contrast enhanced computed tomography (CECT) images of the head and neck containing the PG obtained within 2 weeks before the operation. The exclusion criteria were as follows: (1) CECT images with obvious artifacts, such as artifacts from false teeth, motion artifacts, etc.; (2) fine needle aspiration performed before imaging of the PG; or (3) patients with parotid lesions less than 1.0 cm in diameter. Medical records from 208 patients were initially analyzed, and 125 patients were finally included in this study (see CT scans were performed with a multi-slice CT scanner (Siemens 40) or a 64 multidetector scanners  with the following parameters: tube voltage of 120 kVp; tube current of 150 mA; section thickness of 3 mm; and section interval of 3 mm. The scanning ranged from the base of the skull to the inlet of the thorax. The CECT images were obtained after an intravenous injection of 80–100 ml of nonionic iodinated iopamidol containing 370 mg iodine per ml  at 3–4 ml/s. Arterial-phase CECT images were obtained 35 seconds after contrast material injection.Clinical parameters, including age, sex, disease duration, and smoking status, were collected from the hospital medical record system. All original CT images were reviewed and assessed by two experienced head and neck radiologists who were blinded to the clinical data, including tumor location , maximum diameter, distribution , shape (round or not), capsule (with or without), regularity (regular or irregular), margin (clear or unclear), density , enhancement (enhanced or non-enhanced), cystic degeneration (with or without), lymph node metastasis (with or without), hemorrhage (with or without), calcification (with or without), and enhancement type (slight-moderate or obvious). The definition of some radiological features can be found in the 3 voxel size, intensity normalizing, and standardizing the gray levels to range from 1 to 32  format and imported to ITK-SNAP software for three-dimensional manual segmentation of the region of interest (ROI). The ROI of each case was manually drawn on the CECT images by two independent head & neck radiologists (Radiologist X with 11 years of experience and Radiologist W with 6 years of experience) who were blinded to the clinical information, carefully avoiding the vessels, bones and lymph nodes. All ROIs were then replicated to the NCCT images, and manual correction was also performed to adjust small deviations in delineating the ROI boundaries. All ROIs from the NCCT and CECT images were uploaded into AK analysis software  for feature extraction. To eliminate the potential impact of different imaging parameters on the extracted features, we preprocessed the segmented images, including resampling the images to 1×1 ×1 mm 1 to 32 .; therefore, the dimensions of the extracted features were reduced to address this issue. Analysis of variance was first performed on the extracted features to select those features that were statistically significant. Subsequently, the minimum redundancy maximum correlation (mRMR) algorithm was used to reduce the dimensions of the selected features as well as to select the features that had the highest correlation with the tumor classification and had the smallest redundancy between one another. After that, the emerging gradient boosting decision tree (GBDT) algorithm was used to further reduce the dimensionality of the preselected features. In this study, feature selections were performed on both the NCCT and CECT images of all cases and finally obtained a joint feature set containing NCCT and CECT image features. Based on these selected features, logistic regression was used to construct the radiomics signature.The preprocessed images were used to extract the radiomics features, including the histogram, Haralick, FormFactor, gray level co-occurrence matrix (GLCM), run length matrix (RLM) and gray level size zone matrix (GLZSM) features. In this study, a joint feature set was obtained from both the NCCT and CECT images. The most robust features of the two separate ROI datasets from the two radiologists were used to ensure the reproducibility and repeatability of the radiomics features . SpearmaTo determine the correlation between the radiomics signature and tumor classification, a logistic regression (LR)-based signature model based on the combined feature set was used to calculate a score to reflect the actual tumor classification in the training set, defined as the rad-score, which was then used to determine the effectiveness of the signature models in differentiating between patients with benign and malignant parotid tumors. The formula of the model used in the training set was then employed to calculate the scores for the test set.The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the accuracy of the radiomics signature in both the training and validation sets. The calibration performance was assessed with the calibration curve for the continuous variables. Furthermore, decision curve analysis (DCA) was used to assess the clinical efficiency of the radiomics signature in classifying the tumor by calculating the net benefit.One-way analysis of variance was performed for each potential predictor variable including clinical characteristics, radiological characteristics, and the radiomics signature in the training group, and then multivariable logistic regression was used on the preselected features with significant differences to obtain the predictors that were ultimately employed for model construction. As machine learning can provide highly accurate and reliable models to improve clinical oncology decisions, in this study, we chose a support vector machine (SVM) to build a combined prediction model based on the selected predictors. The performance of the model was validated with the training set and the test set separately, including calibration performance assessed with the calibration curve, diagnostic accuracy using ROC analysis and net benefit evaluated by DCA. In addition, the tumor prediction value of each patient in the training set and test set was calculated according to the model, the cut-off value of the ROC curve was used to divide parotid tumors into low-risk and high-risk groups, and the clinical effectiveness was determined by the actual tumor classification in the different groups. SPSS 17.0 software  was used to evaluate the normality of the distribution of the dataset using the Kolmogorov-Smirnov test and to perform the chi-square test for the categorical data. The T test is used for normally distributed variables, and the Mann-Whitney test is used for non-normally distributed variables. The conditional forward stepwise selection method was applied for the multivariable logistic regression model. MedCalc15.8 software  was used to assess the ROC curves for the diagnostic performance of the models, and differences between the various AUCs were compared with the DeLong test. R statistical software was used for all other statistical analyses. The “mRMRe” and “gbm” packages were used for mRMR and GBDT analyses, respectively. DCA plots were generated with the “dca. R” package. Two-tailed p-values less than 0.05 were considered statistically significant.A total of 125 patients  with PG tumors were included from two medical centers. The results showed that there was no significant difference between the included and excluded datasets see Table 3.A total of 378 radiomics features were extracted from a single ROI; thus, 756 radiomics features were extracted from each patient in the two scan phases. Among these features, 14 retained after feature dimensionality reduction, including 5 features from NCCT images  and 9 features from CECT images . Logistic regression was used to construct the radiomics signature. The rad-scores were significantly different between the training group and the test group. The predictive effects of the two groups of patients were favorable, with AUCs of 0.772 and 0.771, specificities of 0.878 and 0.889, and sensitivities of 0.808 and 0.790, respectively .PP was employed by GE Healthcare.The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


XGBoost, random forest, support vector machine, and logistic algorithms were used to generate predictive models. Receiver operating characteristic curves were used to evaluate and compare the predictive performance of each model. The parameters including tumor size, age, race, sex, primary site, histological subtype, grade, laterality, T stage, N stage, surgery, radiotherapy, chemotherapy, distant metastases to other sites , and marital status were selected to construct all predictive models. The XGBoost model had a better performance in both training and validation sets as compared with other models in terms of accuracy. Our data suggested that the XGBoost model is the most precise and personalized tool for predicting the 1-year survival rate for NSCLC patients with BM. This model can help the clinicians to design more rational and effective therapeutic strategies.Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall survival for these patients is usually perishing. However, a model with high accuracy for predicting the survival of NSCLC with BM is still lacking. Here, we aimed to establish a model based on artificial intelligence for predicting the 1-year survival rate of NSCLC with BM by using extreme gradient boosting (XGBoost), a large-scale machine learning algorithm. We selected NSCLC patients with BM between 2010 and 2015 from the Surveillance, Epidemiology, and End Results database. In total, 5973 cases were enrolled and divided into the training ( Early-stage lung cancer is usually asymptomatic. Hence, lung cancer is frequently diagnosed at a late stage , 2. Non-A TNM staging system is a tool based on pathological anatomy, which can assist clinicians to develop effective treatment strategies and improve the patients' prognosis . HoweverTherefore, in the current study, we extracted the NSCLC patients with BM from the Surveillance, Epidemiology, and End Results (SEER) database and searched for an ideal AI model to predict the 1-year survival of NSCLC with BM by testing the XGBoost and other traditional algorithms.All NSCLC patients with confirmed BM in the SEER database between 2010 and 2015 were selected for this study. The inclusion criteria were as follows: (a) patients diagnosed with lung cancer on histology, (b) the histologic type of NSCLC, and (c) patients with BM. The exclusion criteria were as follows: (a) lung cancer not the primary cancer, (b) patients without complete clinicopathological characteristics, demographic information, or follow-up information, and (c) follow-up time < 1 month at the follow-up deadline. Finally, we extracted 5973 NSCLC patients with BM from 309,056 lung cancer patients. The study population was distributed to the training and validation sets with a ratio of 7 : 3. The classification process was completely randomized, and it was performed in R software. In addition, we retrospectively collected data for NSCLC patients with BM from the Affiliated Hospital of Chengde Medical University (AHOCMU) between 2015 and 2019 as an external validation set for our research.Based on the specific patient information available in the SEER database, we selected 19 variables that may affect the prognosis of NSCLC with BM, including age, sex, race, tumor size, tumor site, histological type, grade, laterality, surgery, chemotherapy, radiotherapy, TNM staging, distant metastasis sites , insurance status, and marital status.The primary site is defined according to the International Classification of Diseases for Oncology (ICD-O) codes: main bronchus (C34.0), lobe (C34.1-C34.3), overlapping lesion of the lung (C34.8), and lung, if not otherwise specified (C34.9). The histological type is defined in accordance with the following ICD-O-3 codes: adenocarcinoma , squamous cell carcinoma , and other NSCLC . Regarding marital status, we excluded the misleading data of unmarried or domestic partner, and then, “unmarried,” “separated,” “single,” and “widow” were all included in the unmarried group. The insurance status was divided into insured and uninsured; “any Medicaid,” “insured,” and “insured/no specific” were included in the insured group. All cases in the present study were staged using the 7th edition of the AJCC TNM staging system.p < 0.05 revealed by the univariate analysis were further included in the multivariate logistic analysis to determine independent prognostic factors of NSCLC patients with BM. Next, these independent prognostic factors identified by the multivariate logistic analysis were used to construct a nomogram for predicting the 1-year survival of NSCLC with BM.The variables that might be related to prognosis were analyzed by the univariate analysis. Then, variables with Before the sample feature data is put into the model for classification, the data was preprocessed first. In the dataset used in the study, age and size are continuous variables, and the rest is classified. For continuous, we adopted standardization for age and size to speed up the training. The formula is as follows:t − 1), t − 1), t − 1) degree of loss function, and Ω(ft) is the complexity of model f(t). In the setup of the hyperparameters, the best values were determined by performing a grid search.To calculate the distance accurately in some machine learning models, we used one-hot encoding for multiclassification variables. The tree-based model has an excellent performance to calculate the importance of features. XGBoost was used to rank feature importance, and eventually, significant variables were included in our model building. After variable selection, there were 17 feature variables left. We also used XGBoost, an ensemble machine learning method predicting the residuals of prior models, and then combined together to make the final prediction. XGBoost uses second-order Taylor series to estimate the value of the loss function and further reduces the likelihood of overfitting by application of regularization. The objective function is as follows:We have also established three other prediction models based on RF, SVN, and logistic algorithms, respectively. To evaluate the performance of each prediction model, receiver operating characteristic (ROC) curves were used to quantify and compare the predictive performance of the XGBoost model and other prediction models.According to the inclusion and exclusion criteria, 5973 NSCLC patients with BM were selected from the SEER database, and an additional 114 NSCLC patients with BM were identified from the AHOCMU for this study. In addition, 4183 patients were enrolled in the training set; the rest 1790 patients were included in the validation set. Patient demographic and clinicopathologic features are presented in The univariate analysis is presented in Correlated features are redundant and may decrease the performance of ML algorithms. The correlations between the features are depicted in After grid search, the parameters of the best model were determined . Using ROC analysis, the prediction model using XGBoost achieved a fitted AUC of 0.792 in the training set .We depicted the ROC curves for the XGBoost model and the single prognostic factor in training and validation sets, respectively. As shown in In order to assess the advantage of the prediction model generated by the XGBoost algorithm, we also compared it with other models. The training and validation sets of each model were depicted with ROC curves, and the corresponding AUCs were calculated. In the training set, the accuracy of the XGBoost model for predicting survival (AUC = 0.792) was higher than that of RF (AUC = 0.740), SVM (AUC = 0.730), and logistic (AUC = 0.752) . The XGBAlthough NSCLC with BM may obtain longer survival than before with advancement of various treatment methods and drugs, accurate prediction of survival for NSCLC with BM remains to be necessary and a challenge for clinicians. This study established and validated the XGBoost model as the most appropriate model for predicting 1-year survival of NSCLC with BM. In essence, the XGBoost model achieved an AUC of 0.792, 0.786, and 0.764 in the training, internal validation, and external validation sets, respectively. Compared with other models, it showed better reliability and accuracy , which cTo our knowledge, this study is the first research to establish a prognostic model for NSCLC with BM by using AI-based models on large-scale populations. The major differences between our study and the others could be summarized as follows. First, we scaled down the research objects to NSCLC instead of the entire lung cancer patient population. It was important as the histological subtype affected the prognosis dramatically, which was in line as previously reported –19. SecoAccording to our study, tumor size is a significant factor affecting the patient prognosis, which has not been recognized previously –13. T stAlthough deep learning is accessible in the academics and industry, the boosting algorithm based on a tree model still plays a significant role in some subjects, showing dominance in structured information. The boosting algorithm has been proved to be effective in the predictive model of classification and regression tasks in practice. Traditional regression model and machine learning methods, such as Cox regression and SVM, are limited in terms of learning capacities, which need many artificial feature engineering. The tree-based model is a nonlinear model, which has the advantages of a natural feature combination and strong feature expressive capacity . Tree-baOur research had some advantages. First, the SEER database provided complete follow-up information of patients covering a large scope. Second, our AI model could provide personalized survival prediction for patients, thereby improving personalized treatment. Finally, our AI model can be used to predict the survival of other NSCLC patients with BM, as all the information used to predict survival is easily accessible, and our model can be performed as software-based or web-based tool optimization. However, this study has certain limitations. First, this study was a retrospective study while prospective randomized clinical trials are needed to provide high-level evidence for clinical application. Second, we could not obtain specific information about the treatment, such as chemotherapy drugs and protocols, radiation doses, and specific surgical procedures.We used the XGBoost algorithm to build an AI model that predicts the 1-year survival of NSCLC with BM. The XGBoost model has higher accuracy and better performance than models generated from other algorithms. Furthermore, the XGBoost model can be integrated into existing healthcare information systems, so we propose that the XGBoost model could be used as a practical clinical prediction model to help clinicians develop better and more reasonable treatment programs.


VEGF) gene polymorphisms have been shown to be associated with the risk of diabetic retinopathy (DR), but the results were inconsistent. The aim of this study was to systematically assess the associations between VEGF gene polymorphisms and different types of DR (nonproliferative DR and proliferative DR).  Vascular endothelial growth factor  and 95% confidence intervals (CIs) were calculated, and subgroup analyses were conducted by ethnicity. Sensitivity analysis was conducted to assess the stability of the results. Publication bias was assessed by using the Egger regression asymmetry test and visualization of funnel plots. A systematic review was conducted for polymorphisms with a high degree of heterogeneity (I2 > 75%) or studied in only one study.  Electronic databases PubMed, Embase, Web of Science, CNKI, and WANFANG DATA were searched for articles on the associations between VEGF SNPs and nonproliferative DR (NPDR) as well as proliferative DR (PDR), respectively. There were significant associations between rs2010963 and NPDR in Asian ; and rs2010963 is associated with PDR in total population , either Asian  or Caucasian . Rs833061 is associated with PDR in Asian . Rs699947 is associated with NPDR in the total population  and associated with PDR in Asian .  A total of 13 and 18 studies analyzed the associations between  Rs2010963, rs833061, and rs699947 are associated with NPDR or PDR, which may be involved in the occurrence and development of DR. With the change of modern people's lifestyle, diabetes mellitus (DM) has become a serious public health problem in the world, which has seriously affected the life quality of patients and brings huge medical and economic burden to the society , 2. DiabVEGF [VEGF gene is located on chromosome 6p21.3, whose single nucleotide polymorphisms (SNPs) can affect gene expression by altering key regulatory sequences or by altering mRNA stability at key regulatory loci [VEGF gene polymorphisms and NPDR or PDR, but the results were inconsistent [Vascular endothelial growth factor (VEGF) is a special type of cytokine, which is secreted by various cells such as vascular endothelial cells and smooth muscle cells, and plays an important role in regulating blood vessel formation, tumor growth and development and atherosclerosis . Study hVEGF , 12, sugory loci . In recensistent –15. The VEGF gene polymorphisms and DR [VEGF SNPs and DR in general without distinguishing NPDR or PDR. In addition, some new studies on the association of VEGF SNPs and different types of DR have been published recently. Therefore, in this study, we completed an updated systematic review and meta-analysis to evaluate the association between VEGF SNPs and NPDR as well as PDR.Meta-analysis can increase the statistical efficiency by quantitatively synthesizing the results of individual studies . Althougs and DR , 17–19, This meta-analysis was performed according to the recommendations for improving the quality of meta-analyses of genetic association studies and in accordance with the guidelines of the Human Genome Epidemiology Network . EvaluatVEGF SNPs and different types of DR that have been published up to November 6, 2019. The terms used for search were (“diabetic retinopathy∗” OR “diabetes retinopathy∗” OR “DR∗”) AND  AND (“gene∗” OR “polymorphism∗” OR “mutation∗” OR “single nucleotide polymorphism∗” OR “SNP∗” OR “variant∗”)  to identify articles on the association between VEGF gene polymorphisms with confirmed NPDR or PDR in humans. The inclusion criteria were as follows: (1) case-control studies investigating the association between VEGF SNPs and NPDR or PDR; (2) enough genotype data were available to calculate odds ratios (ORs) and 95% confidence intervals (CIs); and (3) both type 1 DM and type 2 DM met the inclusion criteria. The exclusion criteria were as follows: insufficient information for available data, reviews, comments, meeting abstracts, animal models, and case report. If duplication or overlapping data occurred, only the study that included the largest individuals was included.Eligible articles included studies assessing the association of Two authors (LM Hu and CM Gong) independently extracted the data from the included studies, and disagreements were resolved by consensus with a third author (JX Yan) and discussion. The following characteristics were extracted from the selected studies: the first author, year of publication, country, ethnicity, sample size, mean age, sex, duration of diabetes, numbers or frequencies of genotypes and alleles, and the Hardy–Weinberg equilibrium (HWE) status . Ethnicity was classified as Asian and Caucasian. The Newcastle–Ottawa quality assessment scale (NOS) was used to assess the quality of studies included in this meta-analysis. Studies with NOS scores ≥ 6 were regarded as high quality.Z test. The pooled results were evaluated by the dominant model, recessive model, and allelic model. The heterogeneity between studies was assessed using I2 statistic and corresponding P value. When P < 0.1 or I2 > 50%, significant heterogeneity was considered, and the random-effect model was used. Otherwise, the fixed-effect model was used. Subgroup analyses were performed by ethnicity. In addition, if there was a high degree of heterogeneity (I2 > 75%) [P < 0.05 was considered statistically significant.The distribution of genotypes and alleles between case and control group was compared by the Chi-square test. Pooled ORs and corresponding 95% CIs were calculated to evaluate the strength of association by using a fixed-effect model or random-effect model. The significance of pooled OR was determined by the 2 > 75%)  or identVEGF SNPs and NPDR [VEGF SNPs and PDR [A total of 1668 studies were retrieved in the initial search, and 1 study was identified through the relevant references check. After the duplication was removed, 6 SNPs of 18 studies were finally included. The flow chart describing study selection process is shown in and NPDR , 23–32,  and PDR , 23–37. Nine studies including 959 cases and 1357 controls investigated the association between rs2010963 and NPDR, in which 7 studies were conducted in Asian and 2 in Caucasian. Twelve studies including 1431 cases and 2126 controls investigated the association between rs2010963 and PDR, in which 8 studies were conducted in Asian and 4 in Caucasian.P = 0.023; recessive model: OR = 1.48, 95%CI = 1.11 − 1.99, P = 0.009; allelic model: OR = 1.26, 95%CI = 1.08 − 1.47, P = 0.003) , either Asian  or Caucasian   . The CC = 0.004) .Two studies of rs2010963 polymorphism and NPDR in the Caucasian population were conducted in Egypt and Poland, respectively, and their genotype distribution in the case group was opposite, leading to greater heterogeneity between studies. There was no association between rs2010963 and NPDR in Egypt. However, the CC genotype and C allele frequency in NPDR group was significantly higher than that in the control group in Poland .Five studies investigated the association between rs3025039 and NPDR as well as PDR. There was a high degree of heterogeneity between studies, so we made a descriptive summary of the results. Studies showed that the T allele of rs3025039 was negatively associated with NPDR and PDR in Chinese population, but it was positively associated with NPDR and PDR in South Korea. Rs3025039 was associated with PDR in Japan. No association was found between rs3025039 and NPDR in India. However, the association between rs3025039 and PDR in India lacks a unified conclusion Tables  and 2.Four studies investigated the association between rs833061 and NPDR risk. They were conducted in Pakistani, Chinese, and Polish. The results showed that rs833061-C was positively associated with NPDR in Pakistani, but the direction of the results was inconsistent among Chinese. No association was found in Polish .P = 0.012)  .A total of four studies with 559 cases and 927 controls involving rs1570360 polymorphism and NPDR risk were included in this meta-analysis. No association was found between rs1570360 and NPDR .Five studies studied the association between rs1570360 polymorphism and PDR; there was a high degree of heterogeneity that was not suitable for merging the results. These studies found that the A allele of rs1570360 was associated with PDR risk in the Indian and European population, while it had a negative association in the Pakistani population. However, no association was found between rs1570360 and PDR in Korean and Japanese .P = 0.002)  .P = 0.033; allelic model: OR = 1.48, 95%CI = 1.17 − 1.88, P = 0.001)  .Two studies analyzed the association between rs13207351 polymorphism and PDR risk. Due to the high heterogeneity, the summary results were that as follows: the G allele of rs13207351 was positively associated with PDR in Pakistani, while this allele had a negative association in European .Due to the fact that the association of rs2010963 with NPDR and PDR was conducted in 9 and 12 studies, respectively, Begg's funnel plot and the Egger's regression asymmetry test were used to assess publication bias. No publication bias was examined in the dominant model .For the association between rs2010963 and NPDR as well as PDR, sensitivity analysis was used to assess the impact of each individual study on the pooled results by sequentially remove each eligible study. Deletion of any study has no significant effect on the results (Supplementary VEGF gene polymorphisms, there were some other SNPs that were studied [Except the above  studied , 37–39.  studied , or assoVEGF gene polymorphisms and risk of different types of DR. The results showed that rs2010963 was associated with NPDR in Asian and associated with PDR in the total population, either Asian or Caucasian. Rs833061 and rs699947 polymorphisms were associated with PDR in Asian, while rs699947 was associated with NPDR risk in the total population.DR is one of the most serious microvascular complications of DM, and it is the leading cause of visual impairment . EvidencVEGF is the main regulator of physiological and pathological vascular growth. It can induce the increase of retinal vascular permeability, the destruction of blood retinal barrier and the formation of new blood vessels in DR, which is closely associated with the occurrence and development of DR [VEGF small interfering RNA can inhibit choroidal neovascularization and vascular permeability [VEGF is associated with DR. Studies have shown that VEGF gene polymorphisms, such as rs2010963, rs699947, and rs3025039, are significantly associated with serum VEGF levels [VEGF SNPs and DR susceptibility, and some studies have conducted meta-analysis, but the results were not consistent. The most studied polymorphism of VEGF was rs2010963. Although most studies showed that there was no association between rs2010963 and DR, and a recent meta-analysis did not find association between them [nt of DR . Animal eability , furtherF levels , 45, andF levels . A few seen them . Consisteen them , 47, whiVEGF gene polymorphisms and DR found that the C allele of rs833061 was positively associated with DR susceptibility [A recent meta-analysis of the association between tibility . Consisttibility . In thistibility . These rtibility . Howevertibility . These rVEGF gene polymorphisms and NPDR as well as PDR. Fourth, some other potential confounders, such as age, sex, duration of DM, glycemic control, genetic, and environmental interactions, may also affect the results. However, the results did not change after excluding studies containing patients with type 1 DM, and this meta-analysis increased the statistical power of the analysis, provided the latest comprehensive evidence for the association between VEGF gene polymorphisms and NPDR as well as PDR susceptibility. Moreover, we conducted subgroup analyses of different types of DR based on ethnicity, obtained relatively stable results through sensitivity analysis and publication bias evaluation, so the results were more credible and convincing.Several limitations of this study need to be considered. First, different genotyping methods used among studies may lead to inconsistent test results. Second, the inclusion of both type 1 DM and type 2 DM in some studies may have an impact on the results. Third, due to the lack of study at present, we did not analyze by country; and for SNPs with large heterogeneity between studies or studied only in one study, no conclusion can be drawn, and more exploration and research are needed to determine the association between The results indicated that rs2010963 is associated with NPDR in Asian and associated with PDR in total population, either Asian or Caucasian. Rs833061 and rs699947 polymorphisms are associated with PDR in Asian, and rs699947 is associated with the occurrence of NPDR in the total population. Considering that DR is a multifactorial disease, many environmental and genetic factors may be involved in DR, and the genetic susceptibility of different types of DR may be different in different populations. Therefore, further large-scale studies on risk factors and pathological mechanisms of different types of DR are needed in different populations.


The Pearson product–moment correlation analysis showed that SRIS and TCTDI were significantly positively correlated (p < 0.01). ELP has a significant impact on the self-reflection and critical thinking of first-year nursing students, which can be used as a reference for the education of nursing students. During these turbulent times, it is especially vital for faculties to provide experiential learning instead of the traditional teaching concept. This article focuses on the unique needs and concerns of nursing educators and nursing students in the face of the COVID-19 pandemic. During social distancing, interacting with other human beings has been restricted. This would undermine the experiential learning of nursing students. Hence, it is important to develop and evaluate an experiential learning program (ELP) for nursing education. A pre-test and post-test design were used. The study was conducted in a university in Central Taiwan. A total of 103 nursing students participated in the study from February to June 2019. The study intervention was the experiential learning program (ELP), including bodily experiences and nursing activities with babies, pregnant women, and the elderly. After the intervention, the students completed the self-reflection and insight scale (SRIS) and Taiwan Critical Thinking Disposition Inventory (TCTDI) as outcome measures. An independent  The world is facing unprecedented challenges in the face of a global pandemic. Coronavirus disease 2019 (COVID-19) has, to date, killed thousands worldwide ,4,5. NurThis article focuses on the unique needs and concerns of nursing educators and nursing students in the face of the COVID-19 pandemic. In this study, the curriculum of ELP activities is designed to guide students to discuss topics and promote their interest in learning through multiple teaching methods and change the classroom learning atmosphere so that students can strengthen their attitudes, abilities, and skills and enhance the core nursing practice while discovering facts and problems, helping them become competent caregivers trusted by their patients and families. The rising tension in nursing is palpable, and, for many of us, this is unprecedented. Reflection is viewed as a learning strategy and a method to improve professional nursing practice ,11. DeweCritical thinking is a form of high-level thinking in which individuals must have an objective attitude to judge the value of things, decide whether they are true or false, good or evil, and draw a conclusion through introspection and logical reasoning. In the English term “critical thinking”, “critical” comes from the root “skeri” and the Greek word “kriterion”. The former refers to cutting, separation, or analysis, while the latter refers to the standard of judgment ,21. “CriExperience is the process of experiencing something or a feeling ,24. ExpeDewey established the relationship between learning and experience through reflective observations to assist students in learning by doing ,15,25,26This study was a one-group, pre-test–post-test design. Participants had to take the ELP, which was carried out during the semester. The ELP included real intelligent baby care, maternity experience, and elderly experience. After the intervention of ELP, we asked the participants to complete the outcome measures. The details of the intervention are as follows.With the real intelligent baby, students needed to judge when to take care. For example, there were chips in the diapers and baby bottles. When the intelligent babies cried and needed care, the students had to first use their hands to touch the chip induction area, and then comfort, breastfeed, and change diapers according to the needs of the intelligent babies. Each participant brought the smart baby home for two days to immerse themselves in the experiential learning.Through the personal experience of wearing a pregnancy dress for 2 h, one can experience the mother’s hard work when she is pregnant. Students can experience the physiological changes produced by the mother during pregnancy, fetal limb pressure, weight gain of 25–30 pounds, and changes in body shape, etc. Students wore assistive appliances for the elderly to experience the deterioration of physical function after age, with the help of creating visual impairment, restricted movement, decreased mobility, reduced sensation of kyphosis, hand sensitivity, experience joint stiffness, fatigue, weakness, as well as physical situations such as a change in mind image and a decline in balance.After ELP, students had to write journals and participated in a group discussion to share their experiences related to the experiential learning with real intelligent baby care, maternity experience, and elderly experience.After the institutional review board approved the study protocol, we recruited a convenience sample of 103 first-year nursing students from a university in Central Taiwan from February 2019 to June 2019.The demographic data form was used to collect participants’ characteristics. Outcome measures included the self-reflection and insight scale (SRIS) and the Taiwan Critical Thinking Disposition Inventory (TCTDI).The self-reflection and insight scale (SRIS) is a Likert scale that assessed the nursing students’ self-reflection with a total of 20 questions and assigned 6 points for each question, ranging from 1 (least matched) to 6 (highly matched). The scale score in total ranges from 20 to 120 points, with higher scores indicating stronger self-reflection ability. Cronbach’s α coefficient for the total scale was 0.79 . The SRIThe Taiwan Critical Thinking Disposition Inventory (TCTDI) developed by Yen was used to measure the nursing students’ perception of critical thinking. This scale was composed of 20 questions and had four dimensions: systematicity/analyticity (9 items), open-mindedness (4 items), inquisitiveness (3 items), and reflective thinking (4 items). Each question was answered using a 6-point Likert-type scale ranging from 1 (least matched) to 6 (highly matched), and higher scores indicated higher critical-thinking intention and skill. A previous study noted that the Cronbach’s α of the dimensions ranged from 0.83 to 0.92 . Recent The study was approved by the Human Experiment and Committee of Asia University Medical Research Committee. Instructions and a written consent form were provided with the questionnaire and the questionnaire was completed on a voluntary basis. Personal information of each participant was kept confidential by using coded IDs instead of student names. The author’s permission was obtained for the use of SRIS and TCTDI. After receiving a verbal briefing on the research and completing informed consent, all participants were asked to complete the demographic data form, SRIS, and TCTDI. One research assistant in each class was invited to assist in participant recruitment and questionnaire distribution. The pre-test data were collected at the semester start date, while the post-test data were collected at the end of the semester (eighteen weeks later). T-test and the Pearson product–moment correlation analysis were performed. SPSS statistical software  was adopted for the analysis. Descriptive statistics included percentage, mean, and standard deviation. Independent p = 0.01) ((p < 0.001)  and 86 were female (83.50%); most students were at the age of 18 (63.10%). Self-reflection averaged 70.33 points (SD = 7.13) in the pre-test and 72.94 points (SD = 6.80) in the post-test. There was a significant difference between the pre-test and post-test scores in total  . Additio = 0.01) . In addi< 0.001) .p < 0.001). In the study by Chen and Pai (2018), using the same measures, i.e., TCTDI and SRIS, the authors pointed out that self-reflection and critical thinking would affect each other, although their study sample was a group of nursing students carrying out nursing practicum just before their graduation. However, our findings showed that the ELP had similar effects. In other words, results from both freshmen and students about to graduate demonstrated that self-reflection and critical thinking had positively correlated. This study’s results demonstrated that the total scores of self-reflection and critical thinking had a significantly positive correlation (In our study, the participants’ self-reflection and critical thinking improved after taking the ELP. As the articles appealed, with the actual participation of learners, they can experience the essence of their own learning ,30. AddiThe theory of experiential learning argues that, during the learning process, if students have personal experiences to internalize their knowledge through cooperation, reflection, questioning, and action, they can apply what they have learned and strengthen their abilities of reflection and critical thinking . In our The articles showed that ELP creates a real and interactive learning environment. Students can provide feedback and reflection under the guidance of teachers during care activities and can repeatedly learn about knowledge, communication, and critical thinking skills related to nursing, which can enhance students’ experiential learning, boost their self-confidence, and promote their communication and teamwork skills ,28,29,30This study has several limitations. Students’ self-assessment of self-reflection and critical thinking using the questionnaire poses limitations such as subjectivity, although this is the most common form used. In addition, it is uncertain whether the difference between pre-test and post-test comes entirely from the course since a control group is absent in this study.This research suggested that schools at all levels incorporate ELP into the learning process so that students can strengthen their attitudes, abilities, and skills in their learning activities.This study manifested that self-reflection and critical thinking might share a core, which resulted in the significantly positive correlation between SRIS and TCIDI. The nature of experiential learning is that students learned through active participation, gaining knowledge and insights. Our intervention, the curriculum of ELP activities, helped the students to increase their abilities of self-reflection and critical thinking. As the ELP program can be performed without facing people, it is suitable for use during a pandemic.