Background: Ten to thirty percent of stroke patients suffer from post-stroke delirium. This leads to a longer hospital stay and increased mortality. Therefore, early detection and treatment are needed. All established delirium screening tools require some degree of language function. We sought to investigate whether the Intensive Care Delirium Screening Checklist (ICDSC) is suitable for delirium screening in patients with post-stroke aphasia.Methods: A prospective cohort study was carried out in adult patients consecutively admitted to the Stroke Unit of University Hospital Tuebingen, between July 2017 and December 2018. The index test, ICDSC, was compared with the DSM-V diagnostic criteria as reference standard. Measures of diagnostic precision and the degree of agreement were obtained.Results: Three hundred and forty six patients were included in the analysis. Aphasia was present in 231 (66.8%) and absent in 115 (33.2%) patients. Delirium was present in 83 out of 231 (36%) patients with aphasia and 32 out of 115 (27.8%) patients without aphasia (p = 0.132). For patients without aphasia, sensitivity and specificity at the established cut-off value of ≥ 4 points were 100% and 78%, respectively. For patients with aphasia, the test demonstrated inferior performance, with a sensitivity and specificity of 98% and 55%, respectively. It was necessary to increase the cut-off value to ≥ 5 points. Through this, sensitivity was 90%  and specificity was 75% . The degree of agreement to the DSM-V criteria was “substantial” (Cohen's κ = 0.61).Conclusion: For the purpose of delirium screening in patients with aphasia, increasing the ICDSC cut-off value to ≥ 5 points enables effective screening. Further studies are necessary to characterize post-stroke delirium. Delirium is characterized by an acute, fluctuating and reversible state of inattention, confusion or an altered level of consciousness. Essentially, delirium is “a decompensation of cerebral function in response to one or more pathophysiological stressors” . The recTo prevent these complications, delirium has to be detected early through validated screening tools to enable consequent treatment. To this end, two delirium screening tools are commonly used: the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and the Intensive Care Delirium Screening Checklist (ICDSC) . The CAMThere continues to be a need for validated and feasible delirium screening tools for neurologically critically ill patients . SpecifiSingle-center prospective cohort study.The study was carried out in all adult patients consecutively admitted to the Stroke Unit (SU) at University Hospital Tuebingen between July 2017 and December 2018. Exclusion criteria were: (i) a duration of stay in the Stroke Unit of <24 h; (ii) a Richmond Agitation-Sedation Scale (RASS) level of −5 or −4 for the majority (>50%) of the stay; (iii) patients on mechanical ventilation or in shock; (iv) diagnosis of delirium or exposure to benzodiazepines on admission; (v) an incomplete record of the National Institutes of Health Stroke Scale (NIHSS), RASS and ICDSC during the stay. Of the 1,737 screened patients, 346 patients were eligible for further analysis.The index test was the Intensive Care Delirium Screening Checklist (ICDSC), administered on admission and every 8 h for the whole duration of the stay in the Stroke Unit. The ICDSC encompasses eight items, including: alteration of consciousness level, inattention, disorientation, hallucination or psychosis, psychomotor agitation or retardation, inappropriate speech or mood, sleep/wake cycle disturbance, and symptom fluctuation. Absence of symptoms is scored with 0 and presence of symptoms is scored with 1 point in each of the items. A cut-off score of 4 points is considered to be indicative of delirium, while a score of >4 points does not reflect the severity of delirium , but mayDelirium assessment based on the Diagnostic and Statistical Manual of the American Psychiatric Association (DSM-V) diagnostic criteria was the reference standard. We additionally gave consideration to information obtained from third-party medical history, previous observations on the patient's behavior and records on pre-admission cognitive status, if available. Assessment was performed by an independent consultant neurologist, who was blinded for index test results of the ICDSC.The Richmond Agitation-Sedation Scale (RASS) and the National Institutes of Health Stroke Scale (NIHSS) were assessed upon admission and every 6 h for the whole duration of SU stay. Assessment of language function was carried out by a consultant neurologist as part of the NIHSS.To compare measures of diagnostic accuracy, cross tabulation for two categorical variables was carried out. Sensitivity (TPR), specificity (TNR), positive predictive value (PPV), and negative predictive value (NPV) were calculated.t-test and Pearson's chi-squared test were used where appropriate. The significance level was set at p < 0.05.Descriptive statistical analysis was carried out to determine differences in the baseline characteristics between aphasic and non-aphasic patients. Student's Cohen's Kappa (κ) was calculated to measure the degree of agreement between the gold-standard DSM-V diagnostic criteria and diagnosis of delirium as per a given ICDSC cut-off value. The strength of agreement, denoted by ranges of Kappa statistics, was labeled as proposed by Landis and Koch . StatistThe study was approved by the ethics committee of the University Hospital Tuebingen (752/2018BO2). Informed consent was waived for this study.Three hundred and forty six patients were included in the analysis. On admission or during hospital stay, aphasia was present in 231 (66.8%) and absent in 115 (33.2%) patients on admission. There was no significant difference in age and gender distribution between groups. The demographic and medical characteristics of the study population are given in p < 0.0001). The average ICDSC score was significantly higher in patients with aphasia, and every item on the ICDSC contributed significantly more often to the score (Patients with aphasia scored higher than patients without aphasia on the NIHSS (12.3 vs. 3.6 mean score) and spent a significantly longer time in the intensive care unit . Cross tabulation of the index test results in patients with and without aphasia is given in The target condition, delirium, according to the reference standard DSM-V diagnostic criteria, was present in 83 out of 231 (36%) patients with aphasia and 32 out of 115 (27.8%) patients without aphasia  and 78% , respectively. The degree of agreement to the DSM-V diagnostic criteria was “substantial” (Cohen's κ = 0.67). Increasing the cut-off value by 1 point resulted in a decrease of sensitivity from 100% to 81%.For patients with aphasia, specificity of the ICDSC at a cut-off value of ≥ 4 points was 55% . The degree of agreement to the DSM-V criteria was “moderate” (Cohen's κ = 0.45). However, at a cut-off value of ≥ 5 points on the ICDSC, specificity increased to 75% , sensitivity was still at 90% , and the degree of agreement to the DSM-V criteria was “substantial” (Cohen's κ = 0.61).Further subgroup analysis on aphasia severity was performed. The ICDSC test performance was worse in patients with global aphasia  . At a cuLanguage is disrupted by both post-stroke delirium and post-stroke aphasia. In delirium, a number of higher cognitive functions are affected, including working memory, attention and visuospatial processing. While the impact of delirium on language function has been recognized in all major classification systems , the literature on language dysfunction in delirious patients is scarce , 14.Delirium screening is challenging if speech comprehension or speech production are impaired. In a survey of healthcare providers working in acute stroke, the majority of respondents reported difficulties using delirium screening tools in aphasic patients . FurtherIn our study, we found that the established cut-off value of ≥4 points on the ICDSC was not suitable for the detection of delirium in patients with aphasia, since the specificity dropped to 55%. These patients had a higher average ICDSC score and every item on the ICDSC contributed more often to the score, especially for “altered level of consciousness” and “inappropriate speech or mood”. To reflect this, we propose to raise the cut-off value of the ICDSC to ≥5 points for patients with aphasia. In our cohort, this resulted in a sensitivity and specificity of 90% and 75%, respectively. This compares favorably to a previous meta-analysis on the ICDSC in delirium screening, in which the pooled sensitivity and specificity were 74% and 82%, respectively  . SamplinDelirium screening of aphasic patients is a diagnostic dilemma which is encountered often in neurocritical care. To our knowledge, this is the first study to examine the performance of this delirium screening tool in aphasic patients. For effective delirium screening in aphasic patients, the ICDSC cut-off value has to be increased from ≥4 points to ≥5 points.Our results may improve delirium screening sensitivity, assisting healthcare professionals in recognizing delirium in patients with aphasia. This also enables further studies of this cohort and may aid in characterizing post-stroke delirium.The datasets generated for this study are available on request to the corresponding author.The studies involving human participants were reviewed and approved by University Hospital Tuebingen (752/2018BO2). The patients/participants provided their written informed consent to participate in this study.CB and AM created concept and design of the study, jointly acquired, and analyzed the data and wrote the manuscript. JZ and VS acquired and analyzed the data and critically reviewed the manuscript. M-IS, HL, YW, SP, and UZ helped with the study design and critically reviewed the manuscript.SP received speaker's honoraria and consulting honoraria from Bayer, Boehringer-Ingelheim, Bristol-Myers Squibb/Pfizer, Daiichi Sankyo, and Werfen, reimbursement for congress traveling and accommodation from Bayer and Boehringer-Ingelheim, and research support from Bristol-Myers Squibb/Pfizer (significant), Boehringer-Ingelheim, Daiichi Sankyo (significant), and Helena Laboratories . All competing interest are outside of the present work. UZ has received grants from European Research Council, German Research Foundation, German Ministry of Education and Research, Biogen Idec GmbH, Servier, and Janssen Pharmaceuticals NV, all not related to this work; and consulting honoraria from Biogen Idec GmbH, Bayer Vital GmbH, Bristol Myers Squibb GmbH, Pfizer, CorTec GmbH, Medtronic GmbH, all not related to this work. HL received grants from the German Research Foundation (DFG), the German Federal Ministry of Education and Research (BMBF), Bial, and speaker's or consulting honoraria or travel support from Bial, BioMarin, Desitin, Eisai, and UCB, all not related to the current work. 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.


This study aimed to verify the association between autonomic cardiac function (CAF) and the integration of caloric expenditure by physical activity (PA) intensity, sedentary behavior (SB), and sleep quality (PSQI) in active young men. Thirty-five subjects were included, and caloric expenditure in moderate-to-vigorous and light-intensity PA, SB, and PSQI were assessed using questionnaires. Heart rate variability (HRV) was recorded for short periods of time in the supine and orthostatic positions. Multiple linear regression was realized unadjusted and adjusted for covariables, such as age, body mass index, and fat mass. No adjusted analysis indicated that, in the supine position, there were negative associations between the SB and the TP, HF, and NorHF indices, and positive associations between SB and NorLF and LF/HF. In the orthostatic position, an interaction between SB and NorLF was found. Significance of proportion with the TP, HF, and LF/HF indices was confirmed. When adjusted, for the supine position, negative interactions were documented between SB and the TP as well as the HF indices, and between PSQI and the LF/HF index, with interference under the HF and LF/HF indices. Finally, our findings indicate that the proposed approach interacts with CAF, and SB is significantly related to CAF in young active men. A healthy lifestyle is a key component to promote healthy aging and to reduce the risk of cardiovascular events, entailing, among other aspects, the engagement in regular physical activity (PA), reduced sedentary behavior (SB), and good sleep quality ,2,3.The autonomic nervous system (ANS) has an important role in homeostasis, modulating blood pressure, heart rate, and peripheral vascular resistance. Moreover, ANS function is an important indicator of health, both at rest and in response to different stimuli . Heart rHealthy adults with an active lifestyle demonstrate higher HRV than their sedentary peers . HoweverTaken together, these findings indicate that SB and poor sleep quality have deleterious effects on health, regardless of the level of PA ,15 and t2; nonsmokers considered to be low health risk according to medical history [The sample consisted of 35 young adults who satisfied the following criteria: 18–40 years old; male; body mass index (BMI) between 18.5 and 30 kg/m history ; free ofr2) of up to 0.25 (average) for an adequate statistical power of 0.80 and a level of significance of 0.05.In addition, statistical power calculations that were previously performed indicating that a sample of 35 participants is sufficient for a model with five predictors to detect association values with an effect size  and basic physiological data were collected. The volunteers laid on a stretcher for a period of 10 minutes, after which a three-minute electrocardiogram was recorded at rest and the presence of sinus node rhythm was verified, which, when found, started to record the HRV. The evaluation occurred in the baseline condition, while the volunteers were at rest in the supine and orthostatic position. Once they had maintained this position for 10 min, their HRVs were recorded for a period of five minutes. Subsequently, participants were asked to adopt the orthostatic posture at the edge of the bed; two minutes after assuming this position, volunteers’ HRVs were recorded for an additional five minutes ,22.2). Polar©  was used to the characterization of heart rate (HR) and Microlife©  was used to gauge systolic and diastolic blood pressure . Mean arterial pressure (MAP) was calculated by the formula DBP + (SBP − DBP)/3 [Measurements of weight (kg) and height (cm) were performed with Filizola-Model 31 scale; percentage of fat mass (%FM) by Bio-eletrical Impedance ; and BMI (kg/m− DBP)/3 . The volThe International Physical Activity Questionnaire (IPAQ), short form, version 8, was used to quantify the level of physical activity. IPAQ is recommended for national prevalence studies because it makes international comparison possible. This version contains eight items related to the frequency (days per week) and duration (times per day) of vigorous, moderate and light intensity physical activity, as well as the frequency and duration of sedentary behavior (such as sitting) during the week ,25.To calculate the weekly energy expenditure of each study volunteer, their energy expenditure was multiplied according to the activity performed, considering the weekly frequency and the duration of the energy expenditure (average time in minutes/week).To convert the data obtained through IPAQ into metabolic equivalent (MET), the average for each intensity domain proposed by Heymsfield  was usedBy multiplying the MET value of the activity performed by the weekly frequency and duration, the caloric expenditure in MET minutes/weeks was calculated. To convert to kilocalories , the value obtained was multiplied by the weight and divided by 60 min. Thus, the caloric expenditure value of each activity was expressed in kcal during the week .Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Each score is assigned a certain number of points; the maximum score is 21 points. Scores higher than 5 indicate poor sleep quality . Once th® V800 [The automatic generation of the time series of the R-R intervals was performed using the POLAR® V800 . The timPrior to HRV analysis, each series of R-R intervals was visually checked on a beat-to-beat basis for sinus rhythm validation and identification of non-sinusoidal and ectopic beats, artifacts, and signal reliability. Spurious, occasional, and possibly discrepant beats were excluded from the series without adding new ranges. The R-R range series was highly stable and stationary, as estimated by the percentage differences of means and standard deviations between three divided segments of the series.The HRV was analyzed in the frequency domain by means of different established standard indices ,6. The fData were expressed as median and interquartile ranges (25–75%). The comparison between the different positions (supine vs. orthostatic) and their descriptive variables was made based on the crude values, using the Wilcoxon paired test.For multiple linear regression, several procedures were adopted. Initially, the data had normality and homogeneity verified by Shapiro-Wilk and Levenne tests, respectively. Since normality and homogeneity were not verified for most variables, all data were transformed into log10 and retested. With this, the normality and homogeneity of the data were confirmed. The multicollinearity between the independent variables was verified through the Pearson correlation coefficient and the multicollinearity index to establish the best model.r, r2, F, and the significance value of F were attested to verify the pertinence of the crude model for each studied variable. For Blocks 1 and 2, the coefficient of determination r2 was used, as well as its percentage, in order to determine the proportion of variation explained by each block of variables added.All variables inserted in the models were selected based on primary theoretical links and subsequently adjusted based on the fact that they did not violate statistical laws . Based op < 0.05 and F < 0.05.All procedures were performed using the Statistical Package for Social Sciences 22.0®  and G * Power 3.0®  programs.The significance level adopted was Participants were considered active (>150 min/week) and had higher caloric expenditure in vigorous and moderate intensity activities than in the light intensity domain. These participants were also considered to have low levels of SB (<3360 min/week) and were classified with good sleep quality .p < 0.05). About HRV indices, after standing there was a reduction of predominantly vagal control (HF and NorHF), and an increase in sympathetic predominance (LF and NorLF). Moreover, in the supine position the participants showed an “anphotonic” characteristic (LF/HF = 1.12) whereas, in the orthostatic position, a “sympathicotonic” condition was observed (LF/HF = 6.16).p = 0.00), HF  and NorHF , and positive for the indices: NorLF  and LF/HF ratio . after assuming the orthostatic position, there was a positive and significant association with the indication “sympatho-vagal” NorLF index .When analyzing the crude model in relation to HRV , in the F = 2.65, Sig. F = 0.04), HF , and LF/HF ratio  while, in the orthostatic position, no significant interactions were found.p = 0.03) and HF , and with the sleep quality, which presents significant and negative scores with the LF/HF ratio . In the orthostatic position, no significant associations were found.Regarding the analysis of the adjusted model , in the F = 2.97, Sig. F = 0.03), and the sympatho-vagal balance LF/HF ratio . However, no significant association was found in the orthostatic position.Finally, when the proportion of interference and the crude model’s significance were verified together with their covariates , as The present study verified whether a lifestyle approach combining caloric expenditure in vigorous and moderate intensity PA, with caloric expenditure in low intensity PA, SB and sleep quality are associated with autonomic cardiac function. However, some aspects should be emphasized: (1) the change of body position generated significant stress on the hemodynamic parameters evaluated, confirming differences in organic control in the positions studied; (2) SB showed greater importance than the other analyzed aspects, interacting in a damaging way the ANS activity, favoring greater sympathetic activity, and decreasing parasympathetic activity in the supine and orthostatic rest positions. As even with the addition of covariates, this aspect still remains significant; (3) sleep quality presented a negative interaction with the sympatho-vagal balance in the supine rest position and; (4) the lifestyle approach used in this study showed a significant interaction with the CAF, both in an isolated manner and in a covariate set, as the main mediator under the vagal component.Changes in body position lead to adjustments to maintain homeostasis . HoweverNevertheless, the findings of the present study agree with the subject matter literature as a general physiological response for healthy adults, as indicated by the studies of Acharya et al. , Gilder The association of each variable of the crude model with the HRV indices show/highlight that SB was the variable with the most prominent influence on HRV of active young men, anticipating a reduction of vagal modulation in the supine position for a more “sympathicotonic” profile at rest and a greater sympathetic component (NorLF) in the orthostatic position due to this habit. In this sense, the literature has enriched our understanding of this theme over the course of the previous century, and it is a well-known fact that independent of the level of PA the excessive exposure to SB is associated with an increased risk of mortality ,38,39. AHowever, studies analyzing the mechanisms underlying the deleterious effects of SB are still lacking, and SB possibly acts independently from PA to affect health. Recent studies have shown that when SB is interspersed with sudden bursts of PA, it may be an effective alternative to improve cardiovascular outcomes ,42. AlthChau et al.  conducteThe relative lack of significance of the results of the present study as for the case of the variables adopted for caloric expenditure by intensity of PA, which in turn was determined by the PA levels  of the sample investigated . Future It must be emphasized that sleep interference in the ANS and sleep quantity have a paradoxical relationship—extended sleep time is positively associated with SB, while short sleep time is associated with poor quality of life and diverse cardiovascular outcomes . Roach eThe integrated lifestyle approach used in this study confirms the significance of the interaction between global cardiac autonomic modulation and the vagal component. Although the lifestyle components have already been addressed in other studies ,50,51, tThe adjustment of the lifestyle approach for age and body composition parameters (Percentage of fat and BMI) pointed out in this study presents negative interactions of SB with the global modulation TP index and with the predominance of the vagal HF index, the interaction between the sleep quality and the “sympathovagal” LF/HF ratio was similar. In this sense, current literature presents evidence that age is inversely related to autonomic control ,53,54. RKahlhöfer et al. , examineIt is also believed that the increase in relative values and the maintenance of significance when the ratio of interaction is verified between the adjusted model and HRV, more specifically with the vagal HF indices and the LF/HF ratio, confirm the importance of the aforementioned associations in a global context of interaction between the cardiovascular system and physiological behavior.This study has several methodological limitations. First, all lifestyle aspects’ data were extracted from self-reported questionnaires. Alternative tools with the same validity and reproducibility have not yet been discovered. Second, the statistical transformation of the data into Log10 does not allow the creation of formulas that estimate the HRV values from the behavioral data, so that the estimation of the data would only serve the values in Log10 and that, later, when reconverted to the data, already lose their association. In this case, the transformation had the appropriate statistical support and was based on answering the question proposed here; however, estimating “non-normal” data from codes is a step no longer possible with the results obtained here. Finally, the limited sample size makes it difficult to generalize the results.This study verified that an integrated lifestyle approach by caloric expenditure in physical activities of vigorous and moderate intensities, caloric expenditure in light intensity physical activities, sedentary behavior, and sleep quality are associate with cardiac autonomic function, assessed by heart rate variability indices in young active men. In this population, sedentary behavior was the main lifestyle-related factor associated with autonomic cardiac function at rest.


To compare differences in central corneal thickness (CCT), corneal curvature, and other corneal measurements of children with diabetes mellitus (DM) and healthy children, and to investigate related factors.  This was a case-control study. From January to February 2018, 50 children with diabetes mellitus were selected as a case group, and 46 healthy children and adolescents without diabetes mellitus were selected as a control group. Corneal topography and CCT were analyzed using a corneal topography measuring apparatus and biometrics (IOL Master). In the diabetic group, we analyzed whether age, course of disease, sex, glycosylated hemoglobin, triglyceride level, total cholesterol, body mass index (BMI), parental BMI, birth history, feeding history, pregnancy, or puerperal history were related to corneal morphology.  There was a significant difference in CCT between groups, but no significant differences were found in corneal diameter, corneal curvature R1 or R2, or corneal topography. Central corneal thickness was not correlated with other clinical factors in the diabetes group.  Early screening and close follow-up of keratopathy in children with diabetes are imperative. According to the 8th edition of the Global Diabetes Map released by the International Diabetes Federation, about 425 million adults worldwide suffered from diabetes in 2017. This number is expected to reach 629 million by 2045 [diabetes . EpidemiDiabetes and its associated chronic complications are a heavy burden to patients, families, and society . DiabeteNCT03587948). It is a part of Shanghai Children and Adolescent Diabetes Eye study (SCADE) [This was a hospital-based case-control study  . From JaParticipation in the study was voluntary for both participants and their guardians, and all signed informed consent after the purpose and process of the study was explained in detail.The research team comprised 3 ophthalmologists at the Shanghai General Hospital and Children's Hospital of Fudan University in Shanghai, 3 optometrists, and 15 auxiliary staff. The ophthalmologist with experience in the diagnosis of ocular diseases and knowledge of their epidemiology was the project director.The examination was conducted in the ophthalmology clinic at Children's Hospital of Fudan University in Shanghai. We followed the methods of Li et al. . First, Next, the eye examination was performed. The examination comprised several tests. First, an ophthalmic slit lamp biomicroscopy  examination of the eyelids, conjunctiva, cornea, anterior chamber, iris, pupil, and lens was performed. Second, a corneal topographic examination  was performed. In this examination, the corneal morphology was analyzed digitally by a computer image processing system, and the corneal shape and regularity were analyzed as a whole. Third, biometry  was used to measure the axial length, lens thickness, pupil diameter, anterior chamber depth, and central corneal thickness (CCT). Fourth, a noncontact tonometer was used to measure the level of intraocular pressure .Finally, within 6 months, the results of routine bloodwork were obtained at Children's Hospital of Fudan University in Shanghai.Diabetes diagnoses (both type 1 and type 2) were based on the WHO diagnostic criteria , which aE-value). (5) Q: the aspheric coefficient. This represents the nonspherical nature and shape of the cornea along the meridian interface. Clinically, it signifies the degree of corneal curvature. Q = 0 represents a perfectly spherical surface. When Q > 0, it represents a flat center and a steep edge.On the corneal topographic map, we obtained five measures. (1) Steep K (D): the meridian direction and value of the maximum refractive power. Clinically, this represents the maximum curvature of the simulated cornea. (2) Flat K (D): the direction and value of the meridian line at an angle of 90 degrees with Steep K. Clinically, this represents the simulated curvature perpendicular to the maximum curvature of the cornea. (3) Astigmatism (D): an indication of corneal astigmatism. (4) Eccentricity (D): an indication of the change of refraction from the central cornea to the peripheral cornea. In clinical practice, the greater the difference between the central and peripheral corneal curvatures, the greater the corneal eccentricity , and Children's Hospital of Fudan University in Shanghai ).Due to the high correlation between the two eyes of normal individuals, all ocular results were analyzed with right eye data.2 (m2). SPSS version 24 was used in statistical analysis. Measurement data are expressed as averages ± standard deviation, and categorical data are expressed as frequencies and percentages.In this study, BMI was calculated as body weight (kg) divided by heightt test was used if the distribution was normal; otherwise, a Mann-Whitney nonparametric test was used.The Kolmogorov–Smirnov test was used to determine whether the measurement data conformed to the normal distribution. A chi-squared test or Student's t-test or Mann–Whitney nonparametric test was used to find significant differences in corneal topographic maps and corneal thickness values between the diabetic and the control group. Subsequently, Pearson correlation analysis was used to find clinical factors which were significantly correlated. A P value <0.05 was considered statistically significant.First, an independent samples P > 0.05)  and 2 patients with type 2 diabetes mellitus (4%). Another 46 healthy subjects participated in the study as a control group. There were no significant differences in gender, age, birth weight, birth length, or BMI between groups ( > 0.05) .P < 0.05)  .P > 0.05)  .P < 0.05). In addition, we found no significant differences in R1, R2, or corneal diameter between the two groups. We believe that differences in race, age, duration of diabetes, endothelial cell density (ECD), and blood glucose control among children with diabetes mellitus may be the main reason for the differences in CCT results between studies in China and abroad.This is the first study in China to examine corneal morphological changes in children with diabetes. There are few reports on corneal morphologic changes in children with diabetes. According to the results of a PUBMED search, there are currently 4 foreign studies –16 exploA change in corneal thickness depends primarily on the degree of matrix dehydration , which rCompared with foreign studies, we have collected a greater number of bodily factors, such as hematological examination results, parental status, family history, pregnancy and birth history, feeding history, and other factors related to the occurrence and development of children. However, we did not find factors related to CCT value. Unlike the current study, previous studies of adult diabetic patients showed that CCT values were correlated with duration of the disease  which isThe limitations of this study are as follows: (1) The study was conducted at a single center with a small sample size. The subjects of this study are students who are busy during the semester, so we were only able to use winter vacation in 2018 to carry out the study. The participants signed informed consent before inclusion. 2. This study is a cross-sectional study. At present, we are preparing for a multicenter clinical study and follow-up observation.In conclusion, this study found that CCT in children with diabetes mellitus was significantly lower than in healthy children and adolescents. Because children and adolescents lack the ability to accurately describe the subjective symptoms of the eye and cannot cooperate well during clinical examination, the incidence of keratopathy is easily overlooked. The long onset time has a significant negative effect on the ocular surface structure and eye health. Therefore, it is suggested that more attention should be paid to the corneal lesions of children with diabetes mellitus. Early screening and close follow-up of corneal diseases should be done and, once identified, treated in a timely manner.


Other-directed, Lighthearted, Intellectual, and Whimsical playfulness. For narrowing this gap in the literature, we conducted two studies addressing the associations of playfulness with health, activity, and fitness. The main aim of Study 1 was a comparison of self-ratings (N = 529) and ratings from knowledgeable others (N = 141). We tested the association of self- and peer-reported playfulness with self- and peer-reported physical activity, fitness, and health behaviors. There was a good convergence of playfulness among self- and peer-ratings . Data show that both self- and peer-ratings are differentially associated with physical activity, fitness, and health behaviors. For example, self-rated playfulness shared 3% of the variance with self-rated physical fitness and 14% with the pursuit of an active way of life. Study 2 provides data on the association between self-rated playfulness and objective measures of physical fitness  using a sample of N = 67 adults. Self-rated playfulness was associated with lower baseline and activity (climbing stairs) heart rate and faster recovery heart rate . Overall, Study 2 supported the findings of Study 1 by showing positive associations of playfulness with objective indicators of physical fitness (primarily cardio-respiratory fitness). The findings represent a starting point for future studies on the relationships between playfulness, and health, activity, and physical fitness.Adult playfulness is a personality trait that enables people to frame or reframe everyday situations in such a way that they experience them as entertaining, intellectually stimulating, or personally interesting. Earlier research supports the notion that playfulness is associated with the pursuit of an active way of life. While playful children are typically described as being active, only limited knowledge exists on whether playfulness in adults is also associated with physical activity. Additionally, existing literature has not considered different facets of playfulness, but only global playfulness. Therefore, we employed a multifaceted model that allows distinguishing among  In particular, its correlates with variables of physical functioning in adult life are widely unknown. Nevertheless, a growing number of studies exist that support the notion that playfulness  may serve an important role in several life domains of adults too. Amongst others, it has been shown that playfulness relates to positive outcome variables such as coping  and they are capable of using their playfulness even under difficult situations to resolve tension . Playfulness is also associated with a preference for complexity rather than simplicity and a preference for—and liking of—unusual activities, objects and topics, or individuals” Proyer,  p. 114.homo ludens in Rahner, Hence, it is argued that playfulness in adults also contributes to other life domains —rather than entertainment alone, which has been highlighted as its main function in earlier definitions  Lighthearted, (c) Intellectual, and (d) Whimsical playfulness . In this sense, playfulness may facilitate greater physical activity as those higher in playfulness have greater skills in certain areas  and use them accordingly , or in the sense that playfulness supports the development and acquisition of certain health-related skills.Thirdly, those high in playfulness may be in general more interested in , Proyer  found po, Proyer  in deali, Proyer  showed tOther-directed  or Lighthearted  facet] may be more strongly correlated with different indicators of health, activity, and fitness than a single global score that averages playfulness across different domains. Also, the findings so far relied on self-reports for both playfulness and indicators of health, activity, and fitness and it is unclear to what extent these results are due to a shared method influence. The problem in this case is that “[…] one has no way of distinguishing trait variance from unwanted method variance”  activities with others in comparison to other, more cognitive aspects of playfulness. We assume that there are indirect effects of having more contact with others and either inviting them to join an own activity or participating in theirs. This type of playful exchange with others should be particularly helpful in engaging in activities. Of course, not all of these will be positively associated with health and physical fitness but leading a more active way of life should also include physical activities. The other facets are expected to show comparatively smaller or no relationships with health, fitness, and well-being.Study 1 examines the relationships of self-and peer-rated global playfulness and its facets with mental and physical health (self-ratings) as well as physical activity, physical fitness, and health-behaviors (self- and peer-ratings). Based on earlier findings Proyer, , we exper = 0.37 between self- and parents' ratings, and relationships of r = 0.36 and r = 0.30 when testing college and hometown acquaintances, respectively. We expect overlap in the range of these coefficients in the present study. We also expect robust convergence among self-and peer-ratings for our measures of activity, fitness, and health behaviors. However, it must be noted that some of these may be more difficult to observe than others. It has been argued that personality traits differ in their observability/evaluativeness . Previous studies found that self- and peer-rated playfulness converges in a range of 0.44–0.57 across the four OLIW-facets in a mixed sample of highly acquainted people  aged 18–78 years  took part in an online survey. A breakdown into age-categories shows that a large portion of participants were between 18 and 29 years old (43.5%), 10.8% were between 30 and 39, 20.6% were between 40 and 49, 15.3% were between 50 and 59, and 9.8% were 60 years or older. A large part of the sample (41.6%) had a degree from a university or a university of applied sciences (BSc or higher), 36.1% held a degree allowing them to attend a university or a university of applied sciences, 16.3% completed vocational training, 5.8% have completed mandatory school, and only one participant (0.2%) had not completed mandatory school. Most participants (50.3%) were Swiss, or German (43.2%). More than half of the participants were currently in a relationship (60.3%), 33.3% were single, 5.1% were divorced/separated, and 1.3% were widowed. Most participants were currently employed (67.5%). Overall, the sample is diverse regarding age and other demographic characteristics.A total of M = 39.78, SD = 14.94). The largest portion of peer-raters was the romantic partner of the person who provided the self-report (48.9%), a family member (27.7%), or a (close) friend (23.4%).About a fourth of the sample  also provided peer-reports of the playfulness measures. The peer-raters were mostly female (53.9%) and aged 17 to 83  with seven items each on a 7-point scale . A sample item is “I can use my playfulness to bring joy to other people or cheer them up” (Other-directed playfulness). Internal consistencies ranged from α = 0.66  to α = 0.77 .The Subjective Physical and Mental Health; assessed with one item each, ranging from 0 (= “very bad”) to 10 (= “very good”). Single-item ratings of the subjective health status have been reported to be stable . The internal consistency of the total scale was high (α = 0.83). Additionally, Wiesmann et al. , and by contacting participants from earlier (unrelated) studies. All participants gave informed consent and completed all instruments online. After the end of the survey, participants were asked to forward the link of the online study to a person who knows them well (no further restrictions/inclusion criteria were implemented). These people were asked to complete peer-ratings of the SMAP, the OLIW, and the GLA, the FFB-MOT, and the MHB-39.Participants were not financially compensated but received an automated feedback on their individual scores upon completion of the study and had the opportunity to enter a prize draft for one of 10 online shopping vouchers worth 25 Swiss Francs. Peer-raters did not receive any incentive for participation.rs >0.46), while all other relationships outside the main axis were smaller in size . We also examined the agreement among self- and peer-ratings for activity, fitness, and health behaviors. Again, the relationships were high and ranged between r = 0.47 and r = 0.74 (mean = 0.68), while the correlations between the same constructs  were numerically higher than those between different constructs  and small to medium-sized relationships with age . Therefore, we controlled for the influence of gender and age in all main analyses.Further correlational analyses (not reported in full detail) revealed small relationships with gender  and showed positive relationships to health behaviors overall . Lighthearted playfulness positively related to mental and physical health and activity but was unrelated to physical fitness. It showed positive relationships to leading an active way of life and substance consumption, and negative relationships to compliance. Intellectual playfulness was positively associated with mental health, the global activity level, and all fitness measures (with the exception of strength), and was positively related to health behaviors overall, safety, leading an active way of life, and diet. Finally, Whimsical playfulness was unrelated to health, and fitness (with the exception of flexibility), but went along with higher levels of global activity. Further, it was related to health behaviors overall, safety, leading an active way of life, and diet (positive), and compliance (negative).Global playfulness was widely unrelated to health, activity, and fitness but showed associations with health behaviors such as leading an active way of life or substance consumption (both positive), and compliance (negative) in self-ratings. r = 0.02; range = ) and in most cases correlation coefficients failed to reach statistical significance. For a better understanding of the relationships between self- and peer-rated playfulness and the tested measures, we computed vector correlationsr = 0.38) and Intellectual (r = 0.43) playfulness, there was a more substantial overlap for Other-directed and Lighthearted (r = 0.64) as well as Whimsical playfulness (r = 0.56). Hence, the inspection of single coefficients showed that differences  in the correlational patterns existed particularly for global and Intellectual playfulness.When analyzing the peer-ratings , Other-directed (r = 0.76), Lighthearted (r = 0.85), and Whimsical (r = 0.73) while the lowest overlap existed for Intellectual playfulness (r = 0.51). Hence, the relationships between self- and peer-rated playfulness seem to widely converge in the sense that they share overlap in their relationships toward physical activities and health. However, the findings do not indicate a perfect overlap and should be interpreted cautiously. In any case they support the notion that the reported associations cannot be explained by a common method bias in the self-ratings of playfulness and the other measures.We analyzed the relationships between Other-directed, Intellectual, and Whimsical) were positively related to activity, and went along with leading an active way of life.Peer-rated global playfulness positively related to some health behaviors (mostly leading an active way of life) and showed some negative relationships to fitness. Most playfulness facets  showed the most robust associations with Other-directed and Intellectual playfulness. For physical fitness, no robust relationships across multiple data sources were observed, except for a positive correlation between flexibility and Whimsical playfulness and small relationships between Intellectual playfulness and cardiorespiratory fitness and flexibility. Health behaviors overall were mostly positively related to Other-directed and Intellectual playfulness. All facets of playfulness were positively related to pursuing an active way of life; as expected Other-directed playfulness was the numerically strongest correlate in self- and peer-ratings. Finally, Intellectual playfulness was positively related to safety and negatively to compliance, whereas Lighthearted playfulness positively related to substance consumption.When combining the findings of the different data sources and focusing on those that were found in multiple combinations of self- and peer-ratings, Other-directed and Intellectual playfulness). In line with the literature . The relationships between Intellectual playfulness and activity/health might reflect previous findings of the correlation between cognitive ability and engaging in health behaviors , the sample covered a broad range from very active and healthy to not very active and unhealthy people. The same was true for playfulness: The whole range of the theoretical scale in the playfulness measures was represented and means were comparable to what has been reported before for samples from the general population Proyer, , 2014b.In Study 2, we address some limitations of Study 1 by testing the association of playfulness with physical activity and fitness with different, more rigorous methodological approaches, including objective measures. We used an interview approach for assessing physical activity. The strength of this approach is that we had the possibility of directly inquiring about activity and discussing questions with each of the participants, rather than have to rely on the answers in questionnaires. Of course, it must be acknowledged that these data are also self-reports. Additionally, we administered a broad array of field tests, covering cardiorespiratory fitness . The expectation was that greater levels of playfulness would be associated with more playful activities in a standardized time period. Secondly, participants completed the task for assessing their dexterity twice; namely, once under the standard condition and once in an impaired condition using goggles that simulate different levels of alcohol intoxication. These are typically used within driver education programs to demonstrate varying degrees of visual impairments due to intoxication. Participants could freely choose the level of impairment for doing this task and were allowed to try them out as long as they wanted. We expected that playful people select stronger levels of impairment as this would allow for greater expressions of their playfulness and since playfulness is associated with a mastery orientation Proyer,  and a liOther-directed and Intellectual playfulness with all tested aspects of activity and fitness. For dexterity, we expected even stronger relationships in the impairment condition than in the standard condition, since playful people are hypothesized to adapt quicker to new circumstances and are willing to work under less structured external conditions  aged from 19 to 75  took part in Study 2. A large part of the sample (43.3%) has a degree from a university or a university of applied sciences, 40.3% have a degree allowing them to attend a university or a university of applied sciences, 14.9% completed vocational training, and 1.5% have completed mandatory school. Most participants (89.6%) are Swiss. About half of the participants were currently in a relationship (70.1%), 26.9% single, and 3.0% were divorced or separated. Most participants were employed (61.2%). Thus, based on the demographic composition, the sample is highly comparable to the sample of Study 1. Further, as planned, we have successfully over-sampled low-scorers  and high-scorers  for being able to differentiate among participants with more extreme expressions, rather than having a larger number of participants in the middle range. Finally, the sample was also diverse with regard to their body mass index, which ranged from 16.5 to 31.0 .A total of r = 0.21 following Gignac and Szodorai's . Thus, medium-to-large effects can be detected through conventional null-hypothesis significance testing. Therefore, we will interpret correlations in terms of its effect size. Our effect size of interest is set at odorai's  recommenShort Measure of Adult Playfulness , and by contacting participants from earlier (unrelated) studies. The participants completed online versions of the playfulness instruments. After completion, they were invited to the lab study that took place at the University of Zurich. Depending on the availability of the participants, the lab study took place a couple of days to several weeks after the completion of the online study. Three instructors (two psychology students and one graduate student) were trained by the principal investigators to conduct the lab studies. This study had two parts, an activity part and a playfulness part. At the beginning of the lab study, participants were informed again on the study and gave informed consent. Afterwards, the participants' height and weight were measured and participants put on the chest strap for measuring the heart rate. Then, the interview on the physical activity during the last 7 days (IPAQ) was conducted. The administration of the IPAQ took about 5 min on average. We measured the participants' heart rate during 5 min while sitting. Afterwards, participants conducted the Stair-Climbing Exercise. During the stair climbing, the heart rate was continuously measured. Immediately after the stair climbing, participants sat down for 1 min during which the recovery of the heart rate was measured. Afterwards, participants completed the Hand-Grip Strengths Test, the Sit-To-Stand Test, and the Sit-And-Reach Test.Subsequently, participants were told that the instructor has to process the so far collected data and they have to wait for about 5 min. However, they were invited to look at some materials that will be used later on in the experiment . Participants were introduced to three “drunk buster goggles” that simulate different degrees of alcohol intoxication . The participants were invited to try out and play with some items . During these 5 min, the instructor was paying attention to which goggles the participants try on and what items they played with, for assessing objective indicators of playful behaviors. Afterwards, participants conducted the Test of Fine Motor Functions twice: Once in a normal, unimpaired condition and a second time using a drunk buster goggle of their choice. Together with the participants' behaviors during the waiting time, this choice should serve as a more objective indicator for playfulness. Finally, the participants were debriefed and received a reimbursement of 25 Swiss Francs for their participation. The full procedure of Study 2 is given in Table Lighthearted playfulness  but also nonsignificant trends for Intellectual [r = 0.14], Whimsical [r = 0.13], and Other-directed [r = 0.08] playfulness) and fitness measures .First, we analyzed the relationships of playfulness and its facets with the data from the interview on physical activity in the last 7 days, in order to replicate the findings of Study 1 using a different methodology Table  and whilOther-directed and Lighthearted playfulness were positively related to the total amount of time spent physically active in the last 7 days as derived from the interview, and negatively related to the amount of time spent sitting . Other-directed playfulness went along with more time spent with moderate or vigorous activity, whereas Lighthearted playfulness was positively related to the time spent walking. The other playfulness facets and global playfulness showed fewer and smaller relationships to the different types of activities. When looking at the more objective indicators of playfulness, we found positive associations between the number of items participants played with and total activity and the time spent with vigorous activity. Further, the level of impairment of the chosen goggle showed a tendency to go along with more time spent walking and with moderate activity.Table Second, we examine the objective measures of fitness and strengths and their relationships with playfulness and its facets Table .Other-directed playfulness, while there were also some effects for Intellectual and Whimsical playfulness. All playfulness facets—but not global playfulness—were positively related to hand and forearm strength. Lighthearted and Whimsical playfulness went along with better back- and leg flexibility. Other-directed playfulness tended to go along with better lower body strength and endurance. Also, there were trends toward positive relations to hand and finger dexterity in the unimpaired condition, while Lighthearted and Whimsical playfulness went along with better performance and Intellectual playfulness with worse performance in the impairment condition.The table shows that playfulness demonstrated mostly the expected pattern with objective of fitness, strength, and dexterity: Lower heart rates  went along with higher scores in global playfulness, M = 4.69, SD = 1.36) and the strength of the chosen impairment in the goggle that is, the level of simulated alcohol intoxication. Most participants (59.7%) chose the weakest goggle simulating a blood alcohol content (BAC) of 0.04–0.06%, 16.4% chose the goggle of medium intensity (0.06–0.08% BAC), and 23.9% chose the strongest goggle (0.08–0.15% BAC). Preliminary analyses showed, that these indicators were indeed related to playfulness: The strength of the chosen goggle positively related to global  and Lighthearted playfulness , whereas the relationships with the other facets were mostly in the intended direction, but did not reach significance . The number of items played with was unrelated with self-rated playfulness , and the strength of the chosen goggle . Since these indicators do not allow for fine-grained distinctions and are rather rough assessments of playful behavior, we considered these associations with the trait-measures of playfulness to be adequate for considering these indicators as objective measures of playfulness.Finally, we analyzed the relationships of the objective indicators of playfulness; these are the number of items the participants played with during the waiting time  but with few exceptions, all effects were in the expected direction and were highly similar to those from the self-reports on playfulness.Further, we found that the number of items participants played with during the waiting time was associated with greater strength and endurance in the lower body. Also, those who chose goggles simulating higher levels of intoxication tended to show a lower baseline heart rate. No other robust effects were found  and warrants further verification. As noted for so-called objective personality tests in the Cattellian tradition . Nevertheless, a limitation for the usage of the selection of the degree of visual impairment as an approximation for playful behavior is that it will require further validation in future studies.The more exploratory analyses on the self-selected visual impairment show that greater playfulness was associated with the selection of greater impairments, which may increase the play-experience, but also could be interpreted as a sign of competitiveness. The latter has already been discussed in previous research in its association with play and playfulness  is an anomaly in comparison with the other coefficients. This finding requires replication (as is warranted for the other findings) and most likely seems to be attributable to specifics of this particular sample. While we caution against over-interpretation, future research is warranted to test how robust this association is.Again, this study highlights the importance of differentiating among different facets of playfulness as they have different predictive value. The findings also show that a global assessment can only give a general sense of the direction of the associations, but cannot provide a more fine-grained differentiation. It should be noted that the size of the correlation coefficients between Several limitations in these studies must be addressed: Again, the sample is imbalanced with respect to the male:female ratio. Further, the question of the generalizability of the findings needs to be discussed. We have tested a rather diverse sample in Study 1 , but, of course, the samples are not fully representative, nor gender balanced. However, since most relationships with demographic characteristics were rather small, and we corrected for influences of age and gender, we do not have much reason to doubt the validity of the findings. However, it is possible that there was a sampling effect . Although our sample was diverse in this regard, we did not find participants that were not physically active at all. Thus, some effects might be underestimated in the present study since no physically non-active participants were tested. While we were able to replicate some findings of Study 1 with Study 2, some reported effects (those on the more objective measures) warrant replication in future studies using independently collected and more representative samples. Although coefficients were in the expected range, the sample size allowed us to detect mainly medium-to-large effects through testing statistical significance. Hence, we interpreted smaller effects cautiously and upon effect size . Whimsical playfulness, on the other hand, seems to be widely unrelated to physical activity . Hence, future studies should examine the distinct effects of single facets in the prediction of health-related outcomes.Overall, our studies show that playfulness is positively correlated with greater levels of activity, specific aspects of fitness (mostly cardiorespiratory fitness), and specific health behaviors (mostly leading an active way of life). Whereas the different facets of playfulness vary in their relationships with indicators of physical activity, The relationships reported in these studies are generally small in terms of size but robust across different methods and cannot be explained by a method bias (shared method variance). The relationships can also be found when using more objective measures of physical activity, rather than the self- and peer-ratings. As expected, correlations are smaller due to the use of different methods. However, most relationships between playfulness and physical activity were in the expected direction.Theory of Planned Behavior (TPB), a social-cognitive model that proposes attitudes and beliefs , influence intentions to be active, which in turn determines actual behavior . However, an initial working model could be proposed to conduct research that explores the direction of the relationship and test underlying mechanisms between playfulness and physical activity, and mental and physical health. Such a model could be framed in the context of health behavior models. Personality variables can affect health through influencing a person's compliance with health-oriented behaviors . Positive affect may have a wide ranging influence on well-being—very much in the sense of Fredrickson's  notion oIntellectual types of playfulness .  Proyer,  may be p Proyer,  and may Future studies should examine these hypotheses in both acute studies and within longitudinal designs to assess potential health-benefits and outcomes  in more detail. If playing and being playful facilitates the emergence of positive emotions  and testing whether this influences physical activity determinants and levels over time. Experience sampling methods, where participants indicate levels of playfulness, positive affect and activity across the day, could elucidate the interplay between these components, and help identify relevant situations and behaviors for intervention studies. Another area to research would be the fit between type of physical activities pursued and preference in specific domains of playfulness. In this respect, observation studies of extreme groups in natural environments would be helpful  to relate behavior to playfulness. Appealing to an adult's sense of playfulness seems advisable when developing interventions to increase engagement in physical activity. One might think of the development of a program that facilitates physical activity in a way that demands certain levels of playfulness . This trend has already started and various behavior change programs have been developed with the goal of “gamifiying” more traditional interventions  might be higher in playfulness than the general population since learning and practicing skills might be facilitated by playfulness. In fact, Study 2 provided some first insights on how playful individuals might acquire skills: Those high in playfulness chose to perform the fine-motor task in a more playful way in the self-selected vision impairment condition–even if there was no necessity to do so and this leads to a decreased performance in a current task. However, this attitude of seeking and playing with challenge might explain how playfulness adds to the acquisition and mastering of new skills.This study was carried out in accordance with the recommendations of the Swiss Psychological Association with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. According to the local ethics committee , the present study did not require a formal approval.RP, FG, and EB: conception and design of the work; RP and FG: data collection; RP, FG, EB, and KB: data analysis and interpretation; RP and FG: drafting the article; RP, FG, EB, and KB: critical revision of the article; RP, FG, EB, and KB: final approval of the published version.The authors declare that this study received funding from Unilever. EB was a staff member of Unilever R&D and contributed to the objectives, design of the study and the final manuscript.


Predictive biomarkers of response to immune-checkpoint inhibitors (ICIs) are an urgent clinical need. The aim of this study is to identify manageable parameters to use in clinical practice to select patients with higher probability of response to ICIs. Two-hundred-and-seventy-one consecutive metastatic solid tumor patients, treated from 2013 until 2017 with anti- Programmed death-ligand 1 (PD-L1)/programmed cell death protein 1 (PD-1) ICIs, were evaluated for baseline lactate dehydrogenase (LDH) serum level, performance status (PS), age, neutrophil-lymphocyte ratio, type of immunotherapy, number of metastatic sites, histology, and sex. A training and validation set were used to build and test models, respectively. The variables’ effects were assessed through odds ratio estimates (OR) and area under the receive operating characteristic curves (AUC), from univariate and multivariate logistic regression models. A final multivariate model with LDH, age and PS showed significant ORs and an AUC of 0.771. Results were statistically validated and used to devise an Excel algorithm to calculate the patient’s response probabilities. We implemented an interactive Excel algorithm based on three variables  which is able to provide a higher performance in response prediction to ICIs compared with LDH alone. This tool could be used in a real-life setting to identify ICIs in responding patients. In the era of immunotherapy, several biological and biochemical factors have been investigated as potential biomarkers of tumor response/resistance to immune-checkpoint inhibitors (ICIs). Select patients is an important clinical need in an attempt to offer them the best therapeutic workup, to avoid unnecessary side effects, and to optimize the use of economic resources. In order to identify a predictive tool of response to ICIs, we evaluated the available and manageable parameters that could ameliorate the selection of patients. In this context, lactate dehydrogenase (LDH) is a potentially interesting, cheap and easy-to-detect biomarker of response ,2,3,4. IPotential biomarkers of response/resistance to immunotherapy other than serum LDH, such as intratumor Programmed death-ligand 1 (PD-L1) expression, tumor microenvironment characteristics, tumor mutational load, mismatch-repair deficiency, and neutrophil-lymphocyte (N/L) ratio in peripheral blood, have been extensively investigated . UnfortuHere, we describe an algorithm based on baseline serum LDH levels, patient Performance Status (PS) and age, which could help clinicians to provide more accurate identification of patient candidates to ICIs.In our study, we enrolled 271 metastatic solid tumor patients treated at Fondazione IRCCS—Istituto Nazionale dei Tumori with anti PD-1 and anti PD-L1 mAbs from April 2013 to August 2017. Patients were evaluated for baseline LDH serum level, PS, age, N/L ratio, type of immunotherapy, number of metastatic sites, histology, and sex. Overall, the population was made up of 43.2% (117) lung cancer, 22.1% (60) melanoma and 34.7% (94) miscellaneous other solid tumors , 1 thyroid, 1 germ cell tumor, 2 gynecologic, 3 gastric, 5 head and neck (H&N), 4 colorectal, 5 sarcoma, 6 biliary tract, 6 mesothelioma, 26 renal, and 33 urothelial). Patient’s characteristics of training, validation and overall cohort are reported in LDH normalized. The median value of LDH normalized distribution was −27.7%, the lower quartile −38.48% and the upper −3.96%. A minimum extreme value was observed at −66.96% and a maximum at 954.79%. LDH normalized distributions in the training and validation cohorts when considering all patients  with LDH normalized, with an odds ratio estimate (OR) equal to 0.792 for any LDH increment of 10%. We also found a significant positive association between age and tumor response, with an OR of 1.426 for any 10-year increment , and an inverse association between ECOG PS with an OR equal to 0.530 for 1 vs. 0 score  or N/L ratio with an OR equal to 0.899  and tumor response. Then, a logistic multivariate model was built by including these four variables, and a backward selection procedure was performed. Baseline LDH serum levels, age and PS were independently associated with the probability of responding to the treatment, with a statistically significant (p < 0.05) or borderline significant  association; therefore, they were retained in the final model. On the other hand, the N/L ratio was removed because it was not independently associated with the chance of responding . The predictive capability of the final model was evaluated by generating a receive operating characteristic curve (ROC) and using as a pivotal statistic the area under the ROC curve (AUC). A satisfactory predictive capability [LDH normalized univariate model and the final one turned out to be significantly different to zero . By applying the training coefficients to the validation set, the model was statistically validated showing a significant AUC of 0.685  ; of note, clinical response was significantly associated  . When thp-value: 0.0220).Finally, we compared the performance (in terms of AUC) of the predictor built starting from the final model, to that derived from the only N/L ratio. As reported in The renewed interest for immunotherapy in the last years and the recent introduction of several ICIs in the clinical practice have redefined the therapeutic strategies of different solid tumors. The efficacy of the immunological approach was first proven in advanced melanoma with the anti CTLA-4 mAb Ipilimumab . ThereafIn contrast, measuring LDH serum level is a simple and low-cost evaluation that has already been proposed as a biomarker predictive of tumor response/resistance to regorafenib , temsiroLDH serum levels have been historically considered to reflect the total number of viable and biologically active cancer cells inside a tumor mass; therefore, its inverse association with patient prognosis and/or tumor response to chemotherapy was mainly attributed to the association between serum LDH levels and tumor burden. However, LDH is a metabolic enzyme that takes crucially part to the glycolytic pathway, which is aberrantly activated in several human cancers to fuel tumor bioenergetics and anabolic needs ,33. Of nIn order to improve the predictive capability of the LDH serum level, we combined it with other clinical parameters for which a rationale exists to test them as predictive biomarkers. To this aim, we have created an interactive Excel tool based on three variables  which is able to provide high accuracy in response prediction to ICIs if compared with LDH alone. Our retrospective analysis confirms that patients with high baseline LDH serum levels have a statistically significant reduced probability of achieving a clinical response during treatment with ICIs, especially in patients who are younger and have poorer performance status.Since the N/L ratio, which reflects systemic cancer-related inflammatory status, has been proposed as a biomarker of resistance to chemo-immunotherapy, we decided to evaluate its impact on the patient’s response to ICIs . We obseThe algorithm that we developed and validated in this study could provide a base to guide physicians in a real-life setting to better plan a therapeutic strategy tailored to patient characteristics and potentially able to identify patients more likely to benefit from ICIs. The clinical relevance of our findings is related to the easy detectability and manageability of the variables tested. Indeed, information about age, baseline LDH serum levels and PS can be collected quickly, already during the medical examination.The main limits of our study consist in its retrospective nature, the heterogeneity of tumor histologies included, and the relatively small number of patients enrolled. Prospective studies in larger populations and focused on specific tumor types have already started in order to validate our results.® 6000 analyser , using a UV-test. The catalytic activity of LDH was determined by the measurement of decreased absorbancy of nicotinamide adenine dinucleotide at 340 nm as a result of catalytic reduction of pyruvate to lactate. From January 2013 to July 2015, the normality reference range was 230–460 Units per liter (U/L); since August 2015, it has changed to 20–480 U/L.The evaluation of LDH was performed at baseline. All measures were performed in our laboratory, with COBASLDH normalized). In order to investigate the relationship between the clinical response and continuous variables and to detect possible nonlinear effects, we resorted to a logistic regression model based on restricted cubic splines. A training set, consisting of all patients treated before the 1st of January 2016 , was used to build models which were tested on a validation set including patients treated since the 1st of January 2016 . The relationships between each variable and the clinical response (DC vs. DP) were investigated by resorting to a logistic regression model in both univariate and multivariate fashion. The hypothesis of OR equal to 1 was tested using the Wald Statistic. All the variables resulted statistically significant (α = 0.05) in univariate analysis was considered in the initial model of multivariate analysis, and a backward selection procedure was used to obtain the final model. We investigated the predictive capability of the multivariate model by means of the AUC. The nonparametric approach of DeLong and Clarke–Pearson [Discrete variables (line and type of therapy (anti-PD1 vs. anti-PDL1), number of metastatic sites, histology, and sex) were opportunely categorized by taking into consideration their clinical function and according to their distributions. Concerning the continuous variables, age and N/L ratio were used in their original scale, whereas for LDH, an appropriate transformation was applied to the original values in order to normalize levels determined by the UV-test with the two different normal reference ranges. All the analyses were performed in terms of percentage increase with respect to the upper limit of each specific range (–Pearson  was used–Pearson . All staIdentifying responder patients before starting immunotherapy is an important clinical need in order to define the best therapeutic workup, avoid unnecessary side effects and efficiently use the economic resources. The clinical relevance of our findings is related to the easy detectability and manageability of the variables tested. Indeed, information about age, baseline LDH serum levels and PS can be collected quickly, already during the medical examination.The main limits of our study consist in its retrospective nature, the heterogeneity of tumor histologies included, and the relatively small number of patients enrolled. Prospective studies in larger populations and focused on specific tumor types have already started in order to validate our results.


In order to assess nursing students’ informatics competency, we need a comprehensive Korean version scale that reflects the important advances in nursing informatics and can make up for the lack of an existing measure. This study aimed to cross-culturally adapt the Self-Assessment of Nursing Informatics Competencies Scale (SANICS) into Korean (K-SANICS) and verify its validity and reliability with nursing students.The design of this study was a methodological approach to translate and evaluate the Korean version tool (K-SANICS). A total of 254 nursing students at four universities in Korea completed a structured questionnaire including background characteristics and the K-SANICS. Reliability and validity of the 30-item K-SANICS were evaluated using Cronbach’s α, content validity, factor analysis, and contrasted groups approach.Cronbach’s α was .95. Exploratory factor analysis was performed to verify the scale’s construct validity, identifying 30 items across six categories: advanced skills for clinical informatics, basic application skills, basic computer skills, roles in nursing informatics, skills for clinical applications, and attitude toward computers in nursing.The K-SANICS may be used as a reliable assessment tool of nursing students’ nursing informatics competencies. It is expected that the K-SANICS will contribute to establishing, operating, and evaluating nursing informatics curricula and also can be used in a clinical setting. Remarkable advances in information technology have led to the implementation of systems utilizing a diversity of such technologies in healthcare settings. For example, the Electronic Nursing Record system, which was first implemented in Korea in 2003, had reached a penetration rate of 70% as of 2012 [With this trend in the current healthcare environment, informatics competency, which refers to the ability to perform nursing tasks and roles related to informatics activities, is one of the fundamental competencies demanded of nurses , 4. ThisThere are several instruments to measure nursing informatics competency, and the concepts they encompass vary widely. The Nursing Informatics Competency Questionnaire by Staggers et al. , which hNevertheless, existing informatics competency scales did not reflect important advances in the field, such as standardized terminology, which is key for sharing and reusing data from the Electronic Medical Record and Electronic Health Record systems, and wireless communication, which is essential for using mobile health devices and wearable health trackers. Thus, these factors were included in the development of the Self-Assessment of Nursing Informatics Competencies Scale (SANICS) in 2009 . The SANThe SANICS was validated and was internally consistent for nursing students with various educational and demographic backgrounds. Moreover, the high responsiveness of the SANICS indicates its strong ability to detect significant changes in informatics competencies . HoweverThe design of this study was a methodological approach to culturally adapt and evaluate the Korean version SANICS with a multi-regional cross-sectional survey.Study participants were third- and fourth-year nursing students attending nursing schools offering a 4-year nursing bachelor program. Four universities of three provinces were selected with convenient sampling procedure. We only included third- and fourth-year students, who had exposure to hospital information systems during their clinical training. First and second-year students who did not participate in clinical practice were excluded.There are diverse opinions and empirical rules about the appropriate sample size for factor analysis . A samplThis study was approved by the Institutional Review Board of Hoseo University . Participants were recruited through advertisements on school boards. Students who wished to participate in the study gathered at the study briefing. The assistants provided a hard copy with information about the purpose and aim of the study, confidentiality and anonymity of participation, voluntary refusal to participate or study withdrawal, and harm and benefits, even after providing consent and completing the survey. An information and consent form approved by the IRB was used. To eliminate any coercion that might occur in the professor-student relationship, one of the researchers, not the professor of the school, explained the purpose of the study in detail. The survey was conducted only for those who understood this information and agreed to participate and completed a written consent form. The informed consent forms and completed questionnaires were stored in an electronic format in the researcher’s locked computer in the laboratory. Personal information that may identify study participants (except for gender and age) was neither collected nor used in the results reporting. All study data, including consent forms was managed in accordance with the Bioethics and Safety Act . The aboThe development process of the K-SANICS involved translation, reverse translation, revision, content validity verification, and a pilot survey with preliminary items.In this study, a four-step conceptual review process was applied based on the guidelines proposed in previous studies , 22. Founot relevant and 1 = very relevant).In order to establish the content validity of the preliminary measure, a panel of four experts, including specialists with expertise in nursing education and clinical nursing informatics currently working at a hospital in Korea, reviewed the preliminary items and rated each of them using the content validity index (CVI). They evaluated the relevance and suitability of all 30 items of the K-SANICS using a 4-point Likert-type scale  in Korean. There were no reverse score items. The higher the score, the higher the competency.The preliminary K-SANICS includes 30 items and a 5-point Likert-type scale .Background characteristics were analyzed using descriptive statistics. The mean and standard deviation of each item of the K-SANICS were obtained, and the total scores were calculated.Reliability of the K-SANICS was evaluated by using Cronbach’s alpha for internal consistency and corrected item-total correlations for the item analysis .With respect to validity of the K-SANICS, three types of validity tests were performed: content validity was analyzed by experts, exploratory factor analysis with rotated varimax and the contrasted group approach was used to assess construct validity . We calcOf the 254 participants, 89.0% were women, and the average age was 22.25 years range 21–24). The mean score for satisfaction with major was 3.91 out of 5. A total of 48.0% of the students had related informatics education experiences at school or at the academy school, and 32.7% had computer-related certifications. The need for computer education and informatics education by nursing students was high, with 82.3 and 87.8%, respectively  and 30 (using wireless devices for data input) with an average score of 4.35 and 4.33 on a 5-point scale. The items with the lowest scores were items 1  and 2 (encouraging myself and others to use information systems or application programs), with an average score of 2.99 and 2.85, respectively . Thus, the study data were appropriate for the factor analysis. Six factors of the K-SANICS with eigenvalues > 1.00 were extracted: We named Factor 1 “advanced skills for clinical informatics” , as the items included in the factor measure higher-level skills used in clinical settings, beyond basic computer skills. We named Factor 2 “basic application skills” , as the items measure the skills to apply basic information technology. We named Factor 3 “basic computer skills” , as it includes items that measure such skills. Factor 4’s name was “roles in nursing informatics” , as it includes items that measure roles as a pre-service nurse in clinical systems. We named Factor 5 “skills for using clinical applications” , as it includes items that measure practical application skills in clinical settings. Finally, Factor 6 was named “attitude toward using computers in nursing” , as it includes items that measure the students’ attitude toward using computers in nursing and informatics competence , and Bartlett’s test of sphericity was significant , 8.4% (Factor 2), 6.5% (Factor 3), 4.7% (Factor 4), 3.8% (Factor 5), and 3.6% (Factor 6). The factor loadings of the items ranged from .55 to .82, indicating correlations among the items. Cronbach’s alpha for the extracted factors ranged from .64 to .93 (Table p < .001) (Table p < .001) and the level of satisfaction with major   mentioned that nursing informatics competency is one of the five essential competencies that every nurse should possess . Stagger mentioneChanges in the factor composition of the K-SANICS in relation to the original instrument were not anticipated. Unlike the original instrument, the K-SANICS reflects latest information technologies, such as wireless communication –14. HoweThe original SANICS comprises perception about one’s role as a nurse, basic computer knowledge and skills, application and wireless skills, and attitudes. Moreover, the items in SANICS reflect interprofessional informatics skills that support interpersonal communication, patient-centered care and team collaboration . HoweverIn the K-SANICS, the reliability of the 30 items was also high, with a Cronbach’s alpha of .95. Corrected item-total correlation coefficients for each item ranged from .35 to .76. As a reliability coefficient greater than .60 is sufficient in exploratory studies . We can In the contrasting group analysis, students who had received informatics education had higher K-SANICS scores than did those without previous education. Furthermore, students with computer certification and those with higher satisfaction with their major showed higher K-SANICS scores. In a previous study that compared graduate and undergraduate students using the SANICS, both groups showed similar scores in basic computer skills, attitudes about informatics, and wireless communication skills, but graduate students scored slightly higher on clinical informatics . BecauseIn addition, the information technology applied to the medical field is developing and changing rapidly. The concept and scope of nursing information competencies have been defined differently . TherefoAlthough this study established the validity and reliability of the K-SANICS, it has some limitations. First, the generalization of our findings should be done carefully, as our data were collected from nursing undergraduates from colleges in a few regions in Korea. Second, as this was the first study to use K-SANICS, there is a lack of cumulative verification of the reliability and the validity of K-SANICS. We have identified the lack of a stability test in the form of test-retest as the third limitation of our study. Despite the limitations of this study, we believe that the K- SANICS could be useful in research as well as in the development of informatics curricula for nursing students.We expect the validated scale to contribute to improving nursing students’ and clinical nurses’ informatics competency through its use in the implementation and establishment of nursing informatics content in the clinical curriculum. Furthermore, improving the nursing informatics competency of students will contribute to them having the skills necessary to deliver good quality care as registered nurses.


Clavibacter michiganensis subsp. sepedonicus, Pectobacterium atrosepticum, and P. carotovorum subsp. carotovorum, and provided detailed information on the phytosanitary status of selected regions and geographical spread of individual pathogens. Information on the occurrence of mixed infections, including their composition, was the first data set of this kind for Russia. The study is the first large-scale screening of a wide range of potato pathogens conducted in network mode using unified methodology and standardized qPCR micromatrices. The data represent valuable information for plant pathologists and potato producers and indicate the high potential of the combined use of matrix PCR technology and network approaches to data collection and analysis with the view to rapidly and accurately assess the prevalence of certain pathogens, as well as the phytosanitary state of large territories.Viral and bacterial diseases of potato cause significant yield loss worldwide. The current data on the occurrence of these diseases in Russia do not provide comprehensive understanding of the phytosanitary situation. Diagnostic systems based on disposable stationary open qPCR micromatrices intended for the detection of eight viral and seven bacterial/oomycetal potato diseases have been used for wide-scale screening of target pathogens to estimate their occurrence in 11 regions of Russia and to assess suitability of the technology for high-throughput diagnostics under conditions of field laboratories. Analysis of 1025 leaf and 725 tuber samples confirmed the earlier reported data on the dominance of potato viruses Y, S, and M in most regions of European Russia, as well as relatively high incidences of  Potato belongs to the world’s staple crops with the global production volume over 375 million tons . BillionViral and viroid infections of potatoes are especially dangerous because of potential infection transmission via seed tubers due to the vegetative reproduction of the crop. Among more than 40 viruses and viroids infecting cultivated potatoes, eight (potato leaf roll virus (PLRV), potato virus Y (PVY), potato virus X (PVX), potato virus A (PVA), potato virus S (PVS), potato virus M (PVM), potato mop-top virus (PMTV), and potato spindle tuber viroid (PSTVd)) are economically the most significant in terms of their global distribution and potential negative effect. Single-virus infection may result in the yield loss reaching 80–90% for PVY and PLRV, 50% for PVX, and up to 20–40% for the other five viruses ,4. MixedClavibacter michiganensis subsp. sepedonicus , Ralstod losses ), and peUnlike with fungal pathogens, once the symptoms of either viral or bacterial infection appear, there are no control methods available for these pathogens; then, only preventive methods may be applied. Therefore, the permanent monitoring of these pathogens appears crucial in large countries like Russia, whose territories cover different climatic zones. Unfortunately, there is no integrated monitoring system for major viral and bacterial potato diseases in Russia, and only a few pathogens or regions are referred to often in available studies ,16,17,18A similar situation is also common in other countries. Reports are focused on the monitoring of one or two pathogens within the whole country  pathogens of potato [Earlier, we developed and validated test systems for two micromatrices intended for the detection of eight viruses and viroids , and seven bacterial/oomycetal  were infected with C. michiganensis subsp. sepedonicus, which belongs to the list of regulated nonquarantine pathogens. The maximum diversity of DNA-based pathogens was observed in Kostroma, Tver’, and Irkutsk regions  was 33.3%, 29.5%, 28%, and 27.2%, respectively.The occurrence of different pathogens in infected samples is shown in P. atrosepticum, P. carotovorum subsp. carotovorum, and C. michiganensis subsp. sepedonicus, which were detected in 16, 14, and 8 samples with mixed infection, respectively; at the same time, R. solanacearum was the only pathogen not observed in multi-pathogen affected samples (Mixed (multi-pathogen) infection was observed in 18 samples from five regions . Among them, there were five combinations of two pathogens, three combinations of three pathogens, and one sample contained four pathogens b. Domina samples a,b.O, PVS, PVM, and PVYNTN (nine regions each), while other viruses were observed in two regions each except PMTV, which was observed in three regions. The highest level of PVYO presence was observed in Tver’ and Leningrad regions, as well as in the Republic of Tatarstan . The highest level of PVS infection was revealed in Samara and Irkutsk regions, as well as in the Republic of Tatarstan .The same index for PVM reached a maximum in Nizhni Novgorod, Tver’, and Moscow regions, as well as in the Republic of Tatarstan ; finally, in the case of PVYNTN, the maximum level of its presence was registered in the Tver’ and Leningrad regions .Results of the survey of viral infection of potato across the studied regions are shown in The maximum diversity of RNA-based infections was observed in Nizhny Novgorod (PSTVd and seven viruses including both PVY forms) and Irkutsk (PSTVd and six viruses including both PVY forms), as well as in Leningrad and Samara (six viruses including both PVY forms) regions, while only one virus type was detected in Krasnodar Krai and Stavropol’ Krai . High leO (38.5%), PVM (25.6%), and PVYNTN (11.9%); note that the total frequency of PVY  was 55.8%, which made this virus the most frequent among other target pathogens. Other pathogens were observed in <6% of infected samples. In relation to the total pool of samples tested, only the first two pathogens were observed with the frequency exceeding 10% ; in the case of total PVY, this index was 16.4%.The occurrence of different pathogens in infected samples is shown in O, PVM, and PVYNTN dominated in the samples with mixed infection, while the rarest species were PMTV, PLRV, and PSTVd. Note that PVA was detected in 11 samples in two regions (predominantly in the Nizhny Novgorod region), always in mixed infections . The maximum number of samples with mixed infection was collected in Nizhny Novgorod, Irkutsk, Samara, and Leningrad regions , whereas the percentage of samples with mixed infection in the total number of samples was the highest in the Tver’ region and Republic of Tatarstan . In relation to the total number of infected samples, the percentage of mixed infection varied from 22.2%  to 61.1% (Republic of Tatarstan).O + PVS (31 samples) followed by PVM + PVS (17 samples) and PVYO + PVYNTN (13 samples); these three variants composed 55.5% of the total pool of samples with revealed mixed infections.In total, we revealed 10 two-pathogen, 8 three-pathogen, and 5 four-pathogen combinations. The maximum number of viral combinations was observed in Nizhny Novgorod (14) and Irkutsk (9) regions; in other cases, 2‒6 combinations were observed. The most frequent combination across the whole set of samples was PVYSuccessful management of potato diseases requires constant monitoring of the presence of the corresponding pathogens at individual locations of cultivation and in seed material to have a comprehensive understanding of the current situation and to assess the prospects of the diseases’ development and spread. This is especially important for viruses and bacteria, for which no control measures exist after the first manifestation of the symptoms. For some viruses transmitted by insects, such monitoring may provide timely insecticidal treatments of the infected and neighboring fields to prevent the spread of pathogens from infection nodes. Finally, detection of quarantine and regulated pathogens may result in a scheduling of infected fields for several years.D. dianthicola and D. solani [P. carotovorum incidence (2–15%). It was reported also that there was evidence of a significant presence of C. michiganensis subsp. sepedonicus (23–50%) in Russian seed potatoes, as well as R. solanacearum likely occurred in the southern regions of Russia [P. atrosepticum and C. michiganensis subsp. sepedonicus in the infected potato for all regions was between 28% and 29.5% that was in agreement with a previous study [Dikeya pathogens in the samples collected in 2015–2018  were reduced with respect to the previous report conducted in 2014 (up to 36%) [Dickeya spp. and a significant reduction of the occurrence of P. atrosepticum and P. carotovorum subsp. carotovorum ; in the same study, a significant infection of analyzed samples with other potato pathogens, P. wasabiae and P. carotovorum subsp. brasiliensis was reported .As for bacterial potato pathogens and their occurrence in Russia, there are only two reports describing the distribution of several target pathogens in the period of 2009–2013 ,18. It w. solani . Re-examus study . At the  to 36%) . This fa to 36%) . AccordiIn the case of viral potato pathogens, information about the current situation in Russia is very limited and mainly describes the situation in separate regions. For example, field monitoring performed in the Far East in 2005 and 2008 showed the prevalence of PVX and PVM infections, as well as a wide occurrence of PSTVd . Recent The performed survey allowed us to obtain a large volume of relevant information in relation to the 15 target DNA- and RNA-based pathogens. In this aspect, our study is the first large-scale survey of a wide range of potato pathogens in Russian regions. The studies describing the occurrence of more than five potato pathogens include the surveys of five potato viruses in Tunisia  and ChiThus, our study is the first large-scale screening of a wide range of potato pathogens in Russian regions located in different climatic zones, conducted in a network mode using a unified methodology and standardized qPCR micromatrices. It provides detailed information on the phytosanitary status of selected regions and the geographical spread of individual pathogens, and is the first one to give detailed information on the presence of mixed infections, including their composition, in potato fields of Russia. The results of this survey will most likely be used for further harmonization of seed certification in the Russian Federation  with intThe study was carried out in 2015–2018 on the basis of 11 regional branches of the Russian Agricultural Center (RAC) in Kaliningrad, Leningrad, Tver’, Moscow, Kostroma, Nizhny Novhorod, Irkutsk regions, Stavropol’ Krai, Krasnodar Krai, and the Republic of Tatarstan, and at the private potato producing company from the Samara region . Potato samples  were collected from commercial fields located in the corresponding regions in accordance to the standard recommendations  in the sAccording to preceding laboratory trials  and at tO and PVYNTN forms), PVX, PVA, PVS, PVM, PLRV, and PMTV, as well as PSTVd. The matrix design provides for simultaneous examination of two samples per matrix.RT-PCR micromatrix “Potato pathogens. RNA” was used for simultaneous detection and identification of specific RNA sequences of PVY  according to the manufacturer’s recommendations. DNA samples were stored at −20°C until use. After installation of the corresponding ready-to-use micromatrix into a holder, the whole reaction zone was completely covered with a sealing layer of mineral oil (620 μL), avoiding bubble formation. DNA or RNA samples were mixed with a 10× PCR buffer  at a 1:9 ratio. One microliter of a resulted sample or deionized water (negative control) was added into each well under the sealing oil layer according to a particular matrix topology. C. michiganensis subsp. sepedonicus, P. atrosepticum, P. carotovorum subsp. carotovorum, and D. solani was followed using channel 1 (FAM). For PLRV, PVYNTN, PVX, P. infestans, D. dianthicola, R. solanacearum, and the internal control (IC), the channel 2 (ROX) was used. Signal recording, calculation of threshold cycles (Ct), and analysis of the results were performed automatically using an AriaDNA software package . Statistical treatment of data was carried out using an MS Excel 2003 program package.Real-time PCR/RT-PCR was performed using a two-beam AriaDNA® Microchip Amplifier . Standard thermal cycling conditions included initial denaturation (94 °C for 120 s) followed by 45 cycles of 94°C for 5 s and 60 °C for 25 s. For RNA samples, the process included a preliminary reverse transcription stage (37 °C for 20 min). Detection of fluorescence related to PSTVd, PVYo, PVS, PMTV, PVA,