Early-life exposures may influence lung function at different stages of the life course. However, the relative importance of characteristics at different stages of infancy and childhood are unclear.To examine the associations and relative importance of early-life events on lung function at age 24 years.1), FEV1/FVC and forced expiratory flow at 25–75% of FVC) were standardised for sex, age and height. The proportion of the remaining variance explained by each characteristic was calculated. The association and relative importance (RI) of each characteristic for each lung function measure was estimated using linear regression, adjusted for other characteristics in the same and previous categories.We followed 7545 children from the Avon Longitudinal Study of Parents and Children from birth to 24 years. Using previous knowledge, we classified an extensive list of putative risk factors for low lung function, covering sociodemographic, environmental, lifestyle and physiological characteristics, according to timing of exposure: 1) demographic, maternal and child; 2) perinatal; 3) postnatal; 4) early childhood; and 5) adolescence characteristics. Lung function measurements , forced expiratory volume in 1 s (FEV1 (RI 0.5–4.6%). Higher lean mass and childhood asthma were associated with decreased FEV1/FVC (RI 0.6–0.8%).Lower maternal perinatal body mass index (BMI), lower birthweight, lower lean mass and higher fat mass in childhood had the largest RI (0.5–7.7%) for decreased FVC. Having no siblings, lower birthweight, lower lean mass and higher fat mass were associated with decreased FEVMaternal perinatal BMI, birthweight, childhood lean and fat mass and early-onset asthma are the factors in infancy and childhood that have the greatest influence on early-adult lung function. e.g. birth weight) and childhood characteristics  had the most influence on lung function in early adulthoodPerinatal characteristics (https://bit.ly/3TggF1Q Lung development commences in early gestation and lung growth continues up until early adulthood (20–25 years of age) when a physiological plateau in lung function is attained –3. Low mNumerous studies have investigated variables that might influence lung function growth and related respiratory diseases in childhood and adolescence. Identified variables include prenatal stress ; mode ofWe analysed data from a large population-based British birth cohort to investigate associations of a wide range of characteristics covering early-life events through adolescence with lung function in early-adult life, around the time of expected peak lung function attainment. Our aims were to examine numerous characteristics  to identsupplementary material. Briefly, 14 541 pregnant women resident in Avon, UK, with expected delivery dates between 1 April 1991 and 31 December 1992 were recruited, and their 14 062 live-born children were monitored prospectively. The 7545 participants who had lung function measured at least once at ages 8, 15 and 24 years were included in this study. A flow chart of the study participants is provided in supplementary material.We studied participants in the Avon Longitudinal Study of Parents and Children (ALSPAC), a British population-based birth cohort. The study protocol has been presented previously –34, and post hoc for quality assurance by JH. Lung function at ages 15 and 24 years was measured before and 15 min after receiving 400 µg of salbutamol [i.e. forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1) and forced expiratory flow at 25–75% of FVC (FEF25–75%), among the best three technically acceptable flow-volume curves was used for analyses. Standardised post-bronchodilator lung function scores  at age 24 years were used as the outcomes. Our sd scores were not adjusted for race because the majority (96.3%) of participants in our study population (n=7545) were from the same ethnic group (described as white).Spirometry was performed according to American Thoracic Society/European Respiratory Society criteria , 36 by tlbutamol , 38. Thesupplementary material.We considered sociodemographic, environmental, lifestyle and physiological characteristics based on a review of the literature , 28, 39,We compared the characteristics of the study population (n=7545) with those of the original cohort . Participants in the study population with (n=2800) and without (n=4745) lung function measurements at age 24 years were also compared.To increase power and minimise selection bias, multiple imputation (20 imputed datasets) by chained equations was performed to impute missing data of investigated characteristics and lung function outcomes at age 24 years . ImputatWe estimated associations with lung function at age 24 years according to temporal ordering of life-course stages, starting with demographic, maternal and child characteristics. First, mutually adjusted associations of these characteristics with each lung function parameter at age 24 years were estimated using multivariable linear regression models fitted to each of the 20 imputed datasets, with results combined using Rubin's rules . We then2) in lung function at age 24 years when all characteristics in the stage were added to a model including the retained characteristics (those with p≤0.1) from previous stages, if any. This has been referred to as stage incremental R2. Within each stage, we derived the increment in R2 attributed to each characteristic  by adding the characteristics one by one to a model. A characteristic's contribution to a stage incremental R2 depends on the order in which the characteristic is added to the model among other characteristics in the same stage. A characteristic appears to contribute more to a stage's incremental R2 when it is added first due to correlations between characteristics in the same stage. Therefore, we derived incremental R2 for each characteristic by averaging its contribution to the stage incremental R2 over all its possible orderings among the set of characteristics in its stage.For each stage, we calculated the increment in the explained variance . RI was derived using the Lindeman, Merenda and Gold method [supplementary material.All analyses were conducted using the statistical software R, version 3.5.0 (d method  from thed method . Furthersupplementary table S1). Spirometry measurements were taken for 88%, 51% and 37% of participants at ages 8, 15 and 24 years, respectively (supplementary table S2), for observed and imputed data (supplementary table S1) and for participants with and without lung function measurements at age 24 years (supplementary table S3). The summary statistics for lung function outcomes at age 24 years were similar in observed and imputed data (supplementary table S4). The amount of missing data for each characteristic and lung function measurement in the study population is depicted in supplementary figure S1.Among 7545 participants with at least one spirometry measurement at ages 8, 15 or 24 years, 51% were female, 18.3% had a single mother, 57.5% had a mother with a low educational level, 47.3% had a maternal history of asthma or allergy, 3.4% had family financial difficulties, 53.7% had siblings, 5.4% were born preterm, 10.5% were born with caesarean section, and 20.9% and 30.2% had maternal smoking and anxiety during pregnancy, respectively  and 15 years (range 0.46–0.48) (supplementary table S5). This degree of correlation enabled missing lung function data at age 24 years to be imputed by including earlier measurements of lung function in the imputation models.sd, 95% CI 0.05–0.20) and FEV1 , and family financial difficulties with low FEV1 . Associations of parity with FVC and FEV1 were slightly attenuated  when additionally adjusted for birthweight. Among perinatal characteristics, higher birthweight was associated with higher FVC  and FEV1  per kg, and higher perinatal body mass index (BMI) and maternal smoking during pregnancy were associated with higher FVC . Higher maternal age at delivery was associated with higher FEV1 . Among early-childhood characteristics, higher lean mass (LM) and lower fat mass (FM) at age 9 years were associated with higher FVC  and FEV1 . Among adolescence characteristics, smoking at age 14 years was associated with higher FVC , with no evidence of an association with FEV1    and 3.1/FVC  and FEF25–75% , family financial difficulties with lower FEF25–75%  and parity with higher FEF25–75% . Among perinatal characteristics, preterm delivery was associated with lower FEV1/FVC  and FEF25–75% , and higher maternal perinatal BMI and maternal smoking during pregnancy with lower FEV1/FVC . Among early-childhood characteristics, higher LM was associated with lower FEV1/FVC  but higher FEF25–75% , and asthma at age 7.5 years with lower FEV1/FVC  and FEF25–75%    and 5.1/FVC or FEF25–75%.There was little evidence for associations between postnatal characteristics and lung function outcomes, and for associations between adolescence characteristics and FEV2 of sd score models) were 10.8%, 6.7%, 3.5% and 2.4% for FVC, FEV1, FEV1/FVC and FEF25–75%, respectively.After adjusting for sex, age and height, the proportions of remaining variance in lung function parameters explained by studied characteristics , birthweight (RI=0.5%), LM (RI=4.6%) and FM (RI=0.5%) were the most important influences. For FEV1/FVC, maternal perinatal BMI (RI=0.5%), maternal smoking during pregnancy (RI=0.5%), LM (RI=0.8%) and asthma at age 7.5 years (RI=0.6%) had the greatest relative importance among studied characteristics. Asthma had the most important influence (RI=0.7%) on FEF25–75% .Similar results for the associations and RI with lung function were obtained when restricting our analyses to only participants with measured (non-imputed) lung function at age 24 years  and birth order on four major lung function parameters . Although exposure to air pollution (source-specific particulate matter with diameter ≤10 µm) during early childhood was associated with reduced lung volumes, we showed that it had much less influence on maximally attained levels of FVC and FEV1 compared to other characteristics such as birthweight and childhood body composition.This large population-based birth cohort study investigated the associations of sociodemographic, environmental, lifestyle and physiological characteristics from prenatal to adolescence with lung function at age 24 years  and derived the RI of each of these characteristics. With information on many exposures, our study showed that influences of perinatal and early-childhood characteristics were relatively larger than those of demographic, postnatal and adolescence characteristics. However, all influences were modest, 1. These associations are described in another report from this study population looking at lung function at age 15 years [1. Moreover, we found that higher LM at age 9 years was associated with lower FEV1/FVC at age 24 years, which is likely to be attributable to LM having a higher influence on FVC than on FEV1. A similar finding, with a wider confidence interval, has been reported in a previous study [1/FVC at age 15 years. Our present study provides more evidence for such an association.Our findings are in-line with the well-established evidence suggesting general primary roles of early-life exposures on adult lung function , 17, 28.15 years . Importa1/FVC (which was barely influenced by birthweight).Previous studies provided strong and consistent evidence of an association of lower birthweight with adult restrictive lung function impairment, with weaker evidence for airflow obstruction . Our stu1/FVC and mid-expiratory flow than on lung volumes. Similar associations were reported with lung function in adolescence [As might have been anticipated, having asthma by the age 7 years had a greater influence on FEVlescence , 48.1 reduction and airflow limitation than in FVC reduction.A previous study showed that poverty is associated with lower lung function in adolescence . Our stuSome of our findings are more difficult to interpret and explain. For example, having siblings was associated with increased lung function. Similar findings were previously reported for lung function in childhood , 51 with1/FVC, suggesting possible dysanapsis of lung growth, i.e. a physiological incongruence between the growth of the lung parenchyma and the calibre of the airways [e.g. adolescents with larger lung volume might be more likely to initiate smoking. Because smokers were defined as those who have ever smoked at least one cigarette, this result does not account for the amount of smoking. Studying sub-categories of smoking might reveal more on the association between smoking in adolescence and lung function in early adulthood.Collider bias, residual confounding effects or a combination of both might also be a plausible explanation for the association between maternal smoking during pregnancy and higher FVC. We found clear evidence of detrimental effects of maternal smoking during pregnancy on FEV airways . The ass1/FVC but increased FVC, suggesting that children of thinner mothers tended to have worse lung volumes. This may be a consequence of poor maternal perinatal nutrition and/or of poor childhood feeding for children of thinner mothers [Higher maternal perinatal BMI was associated with reduced FEV mothers .Early-life exposure to higher air pollution (source-specific particulate matter with diameter ≤10 µm) is believed to have an impact on developing lungs . Our fine.g. birthweight and childhood asthma, with impaired lung function in late adulthood [There has long been interest in the relationship of persistent low lung function from early life with chronic pulmonary disease in later life but the importance of modifiable early-life characteristics on lung function has been unclear. Our study addressed roles of early-life characteristics, provided evidence for their association and quantified their RI on lung function in early adulthood, around the timing of its physiological maximum. This is relevant for a better understanding of lung function growth and factors likely to contribute to lower maximal lung function attainment. Our study suggests that the association of early-life risk factors, dulthood , 8, 12 idulthood .Because various characteristics may influence, to a different extent, different lung function parameters, our assessment for RI of these characteristics can be beneficial in identifying the major determinants of restrictive and obstructive lung patterns. Our findings, together with earlier work showing evidence of lung function tracking throughout the life course, can help prioritise public health policies directed at children that target risk factors of low lung function in later life.This study offers insights into the roles and relative importance of many early-life events on lung function at age 24 years, with all these characteristics simultaneously investigated. Given that many of these characteristics are clustered , studiesWe used post-bronchodilator lung function parameters because they better represent the maximal lung function attained than their corresponding pre-bronchodilator values. The latter are not optimal when the study sample includes asthmatic patients because lung function measurement may be affected by reversible airway limitation.via such unmeasured confounders, although we believe that our extensive adjustments for potential confounding minimised the effects of such a bias. There is some evidence that men may reach maximal lung function later than women and we cannot rule out that this could have a small effect on our findings. Identification of the pathways through which characteristics affect lung function was beyond our remit. Our study adjusted only for events that are potential confounders, i.e. that occur earlier or at the time of exposure. However, mediation is a possible mechanism whereby earlier characteristics may influence lung function through factors that occur later, e.g. childhood characteristics might be mediators of perinatal characteristics.Despite adjustments for a wide range of relevant characteristics, this study, like all observational studies, is still liable to residual confounding by unmeasured characteristics such as diet and physical activity that were only available for a small number of participants in our cohort. Furthermore, mutual adjustments of characteristics in the life-course stage might induce collider bias 1. Maternal perinatal BMI, smoking during pregnancy, preterm delivery, impaired childhood respiratory health and increased LM at age 9 years were associated with lower FEV1/FVC at age 24 years, with the largest detrimental effect from childhood asthma and LM. Childhood asthma, low LM and preterm delivery played the largest roles in low FEF25–75%.Beside well-known variables included in lung function equations (sex and height), our study provides evidence for associations of perinatal and childhood characteristics with early-adult lung function and quantifies their relative importance. Birthweight, having siblings, LM and FM at age 9 years were the most important influences on early-adult FVC and FEVOur findings highlight the importance of early-life characteristics in lung function and suggest public health polices targeting modifiable risk factors in childhood may improve maximally attained lung function and minimise poor respiratory health in later life.10.1183/13993003.01316-2020.Supp1Please note: supplementary material is not edited by the Editorial Office, and is uploaded as it has been supplied by the author.ERJ-01316-2020.SupplementSupplementary material 10.1183/13993003.01316-2020.Shareable1This one-page PDF can be shared freely online.ERJ-01316-2020.ShareableShareable PDF


Active surveillance (AS) is a standard option for low-risk prostate cancer patients wishing to preserve their quality of life by avoiding or delaying radical treatment side effects. We investigated the consequences of postponing radical prostatectomy (RP) according to stringent or more expansive criteria at inclusion in active surveillance. Features at radical prostatectomy of men withdrawn from AS showed that most of them still have favorable pathology. Frequency of unfavorable pathology was associated with wider entry criteria, PSA density (PSAD) and age, and time spent in active surveillance. Nonetheless, they are restricted to local tumor extension and positive surgical margins, but do not include tumor grade or lymph node involvement. The prognostic implications of these findings remain uncertain, and a longer follow-up is needed.3) and low-risk  patients undergoing subsequent RP. The Kaplan–Meier method and log–rank test analyzed APF-free survival. Stratified mixed effects models analyzed association. Results: Out of 21,169 patients on AS, 1742  underwent delayed RP. Most (60.8%) did not have APFs. APFs occurred more frequently  and earlier  in LR patients, and consisted of pT ≥ 3  or R1 , but not of GG ≥ 3 or node involvement. Age , PSAD , and number of positive cores  were independently associated with APFs. Conclusions: AS stands as a safe option for low-risk patients, and most do not have APFs at surgery. Wider entry criteria are associated with pT3 and R1. The prognostic implications remain uncertain.Background: Little is known about the consequences of delaying radical prostatectomy (RP) after Active Surveillance (AS) according to stringent or wider entry criteria. We investigated the association between inclusion criteria and rates, and timing of adverse pathological findings (APFs) among patients in GAP3 cohorts. Methods: APFs  were accounted for in very low-risk (VLR: grade group [GG] 1, cT1, positive cores < 3, PSA < 10 ng/mL, PSA density [PSAD] < 0.15 ng/mL/cm Prostate cancer (PCa) is the second most incident cancer amongst men worldwide. More than 1,400,000 new cases per year occur globally. The highest rates are recorded in Northern and Western Europe, the Caribbean, Australia/New Zealand, Northern America, and Southern Africa . TherefoThe purpose of active surveillance (AS) is to reduce overtreatment by avoiding active therapy of indolent cancer or postponing curative treatment up to the occurrence of disease progression. Most world-wide AS protocols include patients with low-risk PCa and assume disease progression as tumor size increasing or as a worsening in the biopsy score (upgrading of the Grade Group) . NonetheThe main study aim is to investigate how the treatment delay could differently affect the outcome for those patients discontinuing AS. We focus on men with Grade Group (GG) 1 PCa enrolled in AS and compare different inclusion criteria (LR sub-group vs. VLR sub-group). Adverse pathological findings (APFs) at definitive pathology of subsequent radical prostatectomy (RP) were chosen as prognostic endpoints.https://gap3.movemberprojects.com, accessed on 12 July 2022). A centralized database was created to share data from worldwide AS cohorts. GAP3 requirements included the recruitment of a minimum of 50 patients per year and an active patients’ registry for two years. Each participating center had an active registry of AS patients and ethical approval for sharing digital patient data in a centralized global database. Medical ethical approval and patient consent for AS were managed in compliance with local requirements by each registry. GAP3 database version “gap3data_3.2” was queried for this project.In 2014, the Movember Consortium started the GAP3 initiative to promote and accelerate research on AS in PCa patients  testing, digital rectal examination, and repeat biopsies, which may have triggered radical treatment whenever disease re-classification or progression occurred. Multiparametric MRI was not routinely used prior to biopsy at the time of patient recruitment, and this prevents us from conducting an adequate analysis.3. Information about cancer involvement per core was mostly unavailable and was not included in this analysis. LR criteria included patients having PSA ≤ 10 ng/mL, clinical stage T1 or T2 , alone or in combination with adjuvant treatments , were identified. Those fulfilling all criteria for very low risk (VLR) and low risk (LR) sub-groups were considered for the analyses. VLR criteria included PSA < 10 ng/mL, clinical stage T1, Gleason Score (GS) 3 + 3, corresponding to ISUP 2016 GG 1 adenocarcinoma, up to two cores containing cancer, and PSA density (PSAD) < 0.15 ng/mL/cmcriteria ), GG1 adAS discontinuations were categorized as in the GAP3 database: “protocol reasons”, “without evidence of progression” and “other/unknown reasons”. “Protocol reasons” included clinical progression, pathological progression , PSA progression , and radiologic progression. Drop-outs “without evidence of progression” included patient or physician choices. “Other reasons” included any other or unknown reasons.AS duration and time to eventual APF were calculated as the interval elapsed between the date of diagnosis and the date of surgery.A central review of biopsy pathology was not performed. About 5% of patients only had data on multi-parametric MRI and no inference was performed according to this information.Descriptive statistics were used for patients’ population characteristics at diagnosis.APFs rates from definitive pathology were compared between the sub-groups. Patients were deemed to have an APF if they experienced any of the following: GS ≥ 4 + 3 (GG ≥ 3), pT ≥ 3, positive surgical margins, and lymph nodes involvement.p < 0.05 was considered significant.Differences between LR and VLR were assessed by the Student’s t-test and Fisher’s Exact test. The Kaplan–Meier method and log–rank test were used to analyze APF-free survival between the sub-groups. Univariate and multivariate mixed effects models estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the association between APFs and preoperative patients risk factors, including: age, PSA, PSAD, clinical T-stage, number of positive cores, Charlson Comorbidity Index, ethnicity, smoking habit, and reasons for AS discontinuation. In all the models, individual site cohorts were used as stratified levels. Clinically significant variables are included in the final model. Odds ratios were also used to measure the association between biopsy schedules and APFs in stratified mixed effect models. All the tests were two-sided and Statistical analyses were performed using R version 3.6.0. Survival analysis was performed using ‘survival’ (version 3.1.12), ‘BoutrosLab.statistics.survival_0.4.20′ and ‘BoutrosLab.Plotting.survival_3.0.10′ packages in R .Each institution achieved IRB approval and agreement for sharing digital patient data.At the time of the analysis, the GAP3 database included 21,169 men enrolled in AS protocols. The entirety of this database comprised patients with low or favorable intermediate risk PCa who underwent AS between 1990 and 2018 .Out of the total of 1742 prostatectomies, APFs were reported in 683 (39.2%): 228 (31.7%) in the VLR and 455 (44.6%) in the LR sub-group, respectively. The median time to APF was 62.6 months (95% CI: 55.4–71.8) in the VLR sub-group and 40.3 months (95% CI: 36.3–44.1) in the LR sub-group (p < 0.001). The median time to event is 73.9 months for those younger than 55 years and 29.1 months for those between 71 and 80 years.Univariable and multivariable analyses A,B assesp = 0.061) or unknown/other reasons display a lower risk of APF (p = 0.031).Mixed effect models have been used to investigate variables which might be associated with APF C. In mulComplete data regarding repeat biopsies during AS were available in 1324 (76%) of cases. Descriptive statistics of number and timing of biopsy during AS are reported in p < 0.001; Mann–Whitney U test). A positive trend between the number of biopsy sets and APFs was found in all sub-groups . However, a significantly higher rate of APFs was found among patients undergoing surgery after disease progression than patients undergoing surgery without or unknown disease progression. Nonetheless, the high proportion of favorable features at definitive pathology may lead to the consideration that AS exit criteria are still imperfect in preventing overtreatment. Patients in the LR sub-group underwent RP earlier than VLR patients and displayed a significantly higher rate of APFs, consisting of greater pathological T stage and rate of positive margins, but not of worst Grade Group; no difference was found in lymph node involvement as well, possibly due to small numbers. APFs tended to occur earlier among LR than VLR patients. The reasons for this time delay remain unclear and may depend on tumor biology or on different surveillance strategies .Previous experiences addressing outcomes according to risk stratification in GG1 patients undergoing delayed RP are limited, but they have hinted at differences in the rate of organ-confined disease and surgical margin status, but not in grade reclassification rate . Age, PSLR patients underwent a more intensive biopsy schedule, including earlier first re-biopsy, and had more biopsy sets during surveillance than VLR patients. Although the number of biopsy sets is associated with risk of APFs, it remains unclear if the frequency of examinations could be a consequence of un-measured clinical features that induced clinicians to personalize the timing of biopsies. Different PSA kinetics may differently trigger extra-biopsies or treatment. Moreover, patients with no cancer at the first surveillance biopsy underwent less biopsy sets as well as had a lower rate of APFs. Tumor absence in the re-staging biopsy has been confirmed to predict AS outcome .The main study strength is represented by large and composite numbers from world-wide expert centers that recruit hundreds of patients, permitting to have a real-world scenario of AS in prostatic cancer. Consequently, limitations include those inherent of such a nature and design. First, it is unclear to which extent these findings express the well-known imprecision of random prostate biopsy since the diagnosis. A sampling error occurs in 13.1% to 50% of men having cancer suitable for AS undergoing immediate RP ,20,21,22Second, the high proportion of missing data about the reason for leaving AS confines the generalization of our findings. Moreover, our findings focused on selected patients undergoing radical prostatectomy, and we cannot exclude possible biases due to treatment choice. Indeed, patients undergoing radiation therapy  were oldThird, we included positive surgical margins as an adverse outcome, even though we recognize the limitations of this parameter. Indeed, positive margins may be more dependent on the surgical technique rather than representing a biomarker of aggressiveness. The recorded rate eventually reveals the real life picture of such a heterogeneous cohort. Actually, positive margins have been seen as an unfavorable event in some instances, and not in others ,22,26.Fourth, we could not benefit from molecular biomarkers that may improve risk allocation over current clinical models by acting independently of tumor grading and risk group .Finally, we lacked information on follow-up after surgery to assess any difference in harder outcomes according to APFs. Data on biochemical recurrence status will possibly extend the range of our findings. APFs stand as possible drivers for postoperative strategies, but their prognostic meaning in patients undergoing RP after AS remains unclear .A review by Van den Bergh et al. found that curative treatment delay from months to even years were not associated with worse outcomes in men with LR prostatic cancer . A more Finally, a recent series compared adverse pathology and the recurrence-free survival of patients undergoing radical prostatectomy after biopsy progression during AS. They did not find any difference between early (≤6 months) and late (6 months-5 years) neither in adverse pathology  rate nor in 3-years recurrence-free survival .Different AS entry criteria are significantly associated with the rate and timing of non-organ confined disease and with margin status but not with upgrading to GG3 or higher. Some parameters, namely PSAD and age, show a strong association with APFs and may underline a possible selection process.AS stands as a safe option in men with LR prostate cancer, but most of them still have favorable findings at definitive pathology. The implementation of biological and imaging drivers may improve selection both at entry and at exit time to restore the imbalance generated by overdiagnosis and to limit overtreatment. Further insights are needed to assess the prognostic impact of each APF of those patients undergoing delayed surgery.


The Home and Community Social Behavior Scales (HCSBS) is a rating scale that assesses social competence and antisocial behavior among children and youths between ages 5–18. The present study aimed to investigate the psychometric properties of the HCSBS by applying item response theory (IRT).The HCSBS was completed by parents of 551 Norwegian children refereed to three independent interventions towards problem behaviors. Data used in this study was collected before the interventions started. IRT was carried out in R version 4.0.0 to investigate HCSBS items, subscales and main scales.The results showed that the two-dimensional IRT models for social competence and antisocial behavior were the most appropriate. The measurement precision of the scales was high for a large range of the latent spectrum, and estimated reliabilities were satisfactory. Model evaluations indicated that the overall model fit for the scales were acceptable, but some misfit existed with respect to specific item pairs.The results indicate that the HCSBS is a reliable measurement instrument although there is still a potential for improvement by revising some of the items.The online version contains supplementary material available at 10.1186/s40359-023-01045-1. Children and adolescents with behavioral problems show an increased risk for developing negative outcomes like school dropout, social exclusion, law breaking, psychopathology, and other health-related problems –3. The cA growing body of research has demonstrated an inverse association between child conduct problems and social competence –11. Thatr =  − 0.42) between behavioral problem and social competence [r =  − 0.47, p < 0.001) when both constructs were assessed by parents, but considerable lower when one of the constructs were reported by a parent and the other by a teacher . However, several of the studies relied on different measurement instruments to assess child problem behavior and social competence, and some date back to the 1980s and early 1990s, and have shown varying psychometric properties [A considerable number of studies show that there is a significant association between child problem behavior and social competence, however, not all children with problem behavior are socially unskilled, or vice versa. It may, in fact, be difficult to disentangle the temporal precedence of the two concepts. Some findings suggest that poor social competence may contribute to maintain or increase the intensity of child problem behaviors , as it fmpetence . The magoperties . OverallThe Home and Community Social Behavior Scales (HCSBS ) is a paItem response theory (IRT) comprises a family of flexible statistical models and techniques that can be used to evaluate the psychometric properties of a scale, improve scoring accuracy, increase measurement precision, and form the basis for evaluating item properties , 36. In In this study, we utilized IRT to investigate three research questions. First, we investigate dimensionality of the Social competence  and the Antisocial behavior  scales as measured by HCSBS, by comparing one-dimensional models with two-dimensional models for each scale. For the two-dimensional models, the different subscales of Scale A and Scale B were considered as measuring separate but correlated dimensions of social competence and antisocial behavior, respectively. We evaluate the estimated models with respect to the model fit and item fit. Second, we infer the item and scale properties for the subscales Peer relations  and Self-management/compliance , and Antisocial/aggressive behavior  and Defiant/disruptive behavior , using item category probability curves, item information functions, and test information functions. Third, we estimate IRT model-based reliability indices for sum scores and IRT scores to evaluate the precision of measurement of the scale scores.The benefits of IRT are a more realistic model for item responses , improved evaluation of item properties, increased measurement precision through pattern scoring, full-information methods for estimation, and access to detailed tools to evaluate scale properties such as scale difficulty via test characteristic curves and scale precision from test information functions. To our knowledge, this is the first study to evaluate the HCSBS using IRT and as such the study provides important additional information on the properties of the HCSBS, which is useful for practitioners and researchers alike.Data derived from 551 children who were enrolled into three independent interventions aimed to reduce child conduct problems –42. The M = 8.56, SD = 2.35) and 50 (36.5%) were girls. Parents were on average 37.42 years (SD = 6.34). Among the participating children, 66 (48.2%) lived with both biological parents, 21 (15.3%), and 50 (36.5%) lived with single parents. The average gross annual family income was 509,610 Norwegian Kroner (SD = 347.70), which is approximately $51,873, representing an upper middle income level. According to parent self-report, 37 (27%) had a college or higher university degree, 83 (60.6%) had finished high school, and 17 (12.4%) had completed junior high school or elementary school. Most of the parents had Norwegian background (126 or 92%), only one (0.7%) was from another western European country, and 8 (7.3%) reported “other” ethnicity. Sample 2 included children from 198 families recruited from 9 municipalities in Norway. Child age ranged from 3 to 12 years , and 39 (19.7%) were girls. The average age of the reporting parent was 36.30 years (SD = 6.07). Among the participating children, 106 (53.5%) lived with both biological parents, 29 (14.6%) with a parent cohabiting with another adult, and 63 (31.8%) lived with single parents. The average family income was 564.090 Norwegian Kroner (SD = 267.05), which is approximately $ 57,469 and representing an upper middle income level. Parent self-report showed that 80 (40%) had a college or higher university degree, 96 (48.5%) had finished high school, and 22 (11.1%) had completed junior high school or elementary school. Most parents reported a Norwegian background (182 or 92%), and 16 (7.2%) reported “other” ethnicity.Sample 1 consisted of children from 137 families, recruited from 11 agencies situated in different municipalities in Norway. Children were between the ages of 3 and 12 , and 69 (31.9%) were girls. The average age of the parents was 35.31 years (SD = 6.08). Hundred and ten children (50.9%) lived with both biological parents, 27 (12.5%) with a parent cohabiting with another adult, and 79 (36.6%) lived with single parents. The average gross annual family income was 539.110 Norwegian Kroner (SD = 328.29), which is approximately $54, 827 and represents an upper middle income level. Among the parents, 85 (39.4%) had a college or higher university degree, 114 (52.8%) had finished high school, and 17 (7.9%) had completed junior high school or elementary school. Most of the parents had a Norwegian background (202 or 93.5%), four (1.9%) were from other western European countries, and the remaining 10 (4.6%) reported “other” ethnicity.The Home and Community Social Behavior Scales (HCSBS)  is a scrWe used the statistical programming environment R Version 4.0.0  and the Item response theory (IRT) analysis We estimated unidimensional and multidimensional graded response models (GRM) [ls (GRM)  and genels (GRM)  for the ls (GRM) . The funls (GRM) . To charls (GRM) . To assels (GRM) .Dimensionality We evaluated the dimensionality of each of the scales (A and B) by fitting a series of models. First, we specified unidimensional models for each of the subscales Peer relations , self-management/compliance , Antisocial/aggressive  and defiant/disruptive . If the unidimensional models for each subscale were considered acceptable, we specified models for all the items in Scales A and B, respectively. Hence, for the items in Scale A, we specified (1) a unidimensional model and (2) a two-dimensional model where the correlated latent variables were related to the Peer relations or self-management/compliance items. For the items in Scale B, we specified (1) a unidimensional model and (2) a two-dimensional model where the correlated latent variables were related to Antisocial/aggressive or defiant/disruptive items. For either scale, we compared the model fit between the unidimensional and two-dimensional models using likelihood ratio tests.Model evaluation Model fit was assessed via the limited-information fit statistic M2 [2) and the standardized root mean square residuals (SRMSR), where RMSEA2 ≤ 0.089 and SRMSR < 0.05 indicated good approximate model fit [istic M2 , with thodel fit , and witodel fit . Residuaatistics , 53.Reliability estimation The reliability of the sum scores were estimated using Monte-Carlo computer simulations [ulations . We alsoulations .r =  − 0.59 (p < 0.001). Additional file The mean of Scale A1 was 41.52  whereas Scale A2 had mean 31.96 . The mean of Scale B1 was 22.04  and Scale B2 had mean 22.37 . The total scales showed means of 73.21  and 44.41 , for Scale A and B, respectively. The total scores correlated 2 (0.080 and 0.071 ≤ 0.089) but some lack of fit according to the SRMSR (0.069 and 0.082 > 0.05). Meanwhile, A2 and B1 showed evidence of some misfit according to both the RMSEA2 (0.109 and 0.108 > 0.089) and the SRMSR (0.071 and 0.074 > 0.05). However, we judged the fit of the unidimensional models for each subscale to be sufficiently good to pursue further analyses. Regarding the models for the total scales of social competence  and antisocial behavior , scale A showed significantly better model fit as a two-dimensional model rather than a one-dimensional model (p < 0.001). The correlation between the two latent variables representing Peer relations and Self-management/compliance was estimated to be 0.725 . The model fit for the two-dimensional model showed good approximate fit with respect to the RMSEA2 (0.073 ≤ 0.089) but some misfit considering the SRMSR (0.077 > 0.05). For scale B, the two-dimensional model also fitted better than the one-dimensional model (p = 0.009) but the correlation between the latent variables representing Antisocial/aggressive and Defiant/disruptive was estimated to be very high at 0.979, with 95% CI . The model fit of the two-dimensional model showed good approximate fit with respect to the RMSEA2 (0.088 ≤ 0.089) but some misfit with the SRMSR (0.079 > 0.05). The item fit statistics are included in Additional file p = 0.047), and 9 (p = 0.025) of Scale A and items 9 (p = 0.048) and 25 (p = 0.042) of Scale B. After adjusting the significance level with the Bonferroni-Holm correction [The model selection resulted in the GRM being preferred over the GPCM for all subscales. A series of IRT models were then estimated to investigate the assumptions of one-dimensional scales, and an overarching one- or two-dimensional model within social competence and antisocial behavior, respectively. These results are presented in Table rrection , none ofThe estimated reliabilities for each scale are presented in Table Figure To illustrate the measurement precision of the scale scores based on the fitted two-dimensional model, we plotted the scale information functions for each of the subscales Fig. . Scale iWe conducted detailed analysis of the residual correlation matrix to identify sources of misfit in the model. Table In the present study, we applied IRT to investigate the psychometric properties of the social competence and Antisocial behavior scales in the HCSBS. To our knowledge this is the first study to use IRT to examine the HCSBS. Both social competence and antisocial behavior have received extensive attention in the literature on child development and adjustment, but to advance knowledge about these constructs, valid and reliable instruments are required. Our results showed acceptable model-fit for the two-dimensional structure of social competence, and Peer relations and Self-management/compliance appear to measure different but related aspects of social competence. Considering the Antisocial behavior scale, results showed a strong correlation between the Antisocial/aggressive and Defiant/disruptive scales, suggesting that the two concepts can not empirically be considered distinct from each other. Reliabilities for Social competence and Antisocial behavior subscales and total scale-scores were high. Furthermore, our analysis revealed that individual items varied in terms of how much information they contributed to the overall measurement precision of the scale. The scales also had different properties in terms of measurement precision. Peer relations showed higher test information across the latent spectrum than the Self-management/compliance scale, whereas the Defiant/disruptive scale had higher overall test information compared to the Antisocial/aggressive scale. All scales showed most information around the middle of the latent spectrum and can thus be viewed as well-matched with the intended target population. Inspections of residual correlations indicated that several items, in both scales, should be further evaluated and potentially revised in future versions of the scale.n = 157), which made it impossible to consider gender differences. Findings indicate gender differences in both social competence and antisocial behavior [The study has several implications for research and practice. First, the HCSBS is one of few scales that measures problem behavior and social comptence using the same rating scale. This makes it easier to use and interpret the relation between the two concepts. Our findings from a sub-clinical sample of Norwegian children indicate that interpretations based on the subscale scores of the HCSBS is supported, and that the sum scores and IRT scores of the subscales are highly reliable. However, practitioners should be aware that the HCSBS does not distinguish well between Antisocial/aggressive and Defiant/disruptive behaviors. Our item information analyses showed that the social competence and antisocial behaviors scales were most informative around the mean of the latent spectrum. As a result, the scales are well-matched with the target population, but do not very precisely assess respondents with very low or very high values. Thus, it seems most appropriate to measure antisocial behavior based on the combined scores from both subscales. The two scales measuring social competence do however provide distinct and separate scoring. It should be noted, that although there is broad consensus that social competence comprises interpersonal behaviors associated with a positive social outcome , 59, thebehavior , 62, thuThe findings of the present study add new knowledge about the psychometric properties of HCSBS. Our results indicate that the HCSBS has clinical utility when it comes to measure social competence and antisocial behavior in children. Thus, practitioners can rely on one instrument only instead of using different instruments to measure and monitor social competence and antisocial behavior in children with social and behavioral difficulties.Additional file 1: Table S1. Descriptive statistics for the social competence . Table S2. Descriptive statistics for the antisocial scale . Table S3. Item fit statistics for scale A. Table S4. Item fit statistics for scale B. Figure S1. Item category response functions for Scale A. Figure S2. Item category response functions for scale B. Figure S3. Item information functions for scale A. Figure S4. Item information functions for Scale B.


Studies have suggested some predictors for hamstring tendon (HT) autograft diameter based on anthropometric factors and preoperative magnetic resonance imaging (MRI) with variable results. Some authors have attributed the variability to gender differences. This prospective cohort reports the sensitivity and specificity of anthropometric and MRI predictors in males and females separately to determine the difference.Forty-two eligible patients who underwent anterior cruciate ligament reconstruction (ACLR) and MRI in our center were included. ACLR was performed by the senior surgeon using a 4-stranded HT autograft for all patients. A blinded musculoskeletal radiologist measured the cross-sectional area (CSA) of gracilis and semitendinosus tendons using the free-hand region of interest tool for all patients. An orthopaedic resident (PGY4) collected anthropometric factors and measured intraoperative autograft diameter.P < 0.001), smaller gracilis  and semitendinosus CSA  compared to males. ROC curve analysis resulted different cut-off values with high sensitivity and specificity for semitendinosus and combined CSA regarding gender.Mean intraoperative autograft diameter was 8.0 mm. Females had a significantly lower autograft diameter (7.4 vs. 8.2, Based on the results of this study, CSA of either isolated or combined HTs on preoperative axial MRI, height, and weight are the strongest predictors of intraoperative autograft diameter. It is suggested to consider different cut-offs for males and females to have a better clinical guide for surgeons.Level II. Hamstring tendon (HT) as an autograft for anterior cruciate ligament reconstruction (ACLR) has received considerable attention because of its good clinical and biomechanical results and low donor site morbidity , 24. StuStudies have shown a correlation between the diameter of tendons on preoperative magnetic resonance imaging (MRI) and the diameter of the autograft harvested during surgery , 12, 22.There are also studies that have investigated the role of anthropometric variables such as sex, height, and weight in predicting autograft diameter , 20, 21.Many studies have attributed the variability of anthropometric factors in predicting the intraoperative autograft diameter to gender differences , 21, 25.After receiving Institutional Review Board (IRB: IR.AJAUMS.REC.1400.196) approval and written informed consent, 42 patients were included in the study and underwent ACLR from February 2021 to July 2022 using a 4-stranded HT autograft. The inclusion criteria included patients older than 18 years who were candidates for ACLR based on clinical findings and MRI. Exclusion criteria included: Previous surgery on the same knee or the contralateral lower limb, multiligament injuries, and a history of hamstring injury. Patients who underwent MRI at another center were also excluded from the study. All patients were operated on by a senior surgeon in the same orthopaedic hospital. The MRI of all patients was performed at most 1 month before surgery using the same 3 T scanner  and a specific knee coil.Anthropometric factors were recorded during the week before surgery by an orthopaedic resident (PGY4) and included sex, age, height, weight, and body mass index (BMI). A musculoskeletal radiologist measured the cross-sectional area (CSA) of gracilis and semitendinosus tendons for all patients. Using the coronal sequence as a cross reference, he measured CSA on axial sequences at the level of the medial epicondyle of the distal femur since it has been proven to be the best location for CSA measurement of HTs  Fig. 1)1). CSA mBoth gracilis and semitendinosus tendons were harvested using the same method by the senior surgeon in all patients. A 3–4 cm oblique incision was placed medial to the tibial tuberosity, the sartorial fascia was incised, and each HT was isolated after the removal of excess fascial bands. After separating from the insertion site, gracilis and semitendinosus tendons were harvested by a closed-loop tendon stripper. Then the tendons were folded over to form a 4-stranded autograft. The diameter of the final HT autograft was determined using the sizing cylinder. All grafts were prepared and measured by the same orthopaedic resident (PGY4) under the supervision of the senior surgeon. Autograft measurement was performed when the routine diagnostic arthroscopy was finished and just before the autograft fixation for all patients, as Cruz et al.  found thSPSS version 19  software was used for data analysis. Mann-Whitney U test, and t-test were carried out for comparison of quantitative variables between groups and the Chi-square test was used for qualitative variables. The normality of the distribution of the quantitative data was investigated by the Kolmogorov-Smirnov statistic. Continuous variables were presented with mean ± standard deviation (SD). Spearman correlation coefficient was used to investigate the relationship between intraoperative autograft diameter and preoperative predictors. Receiver operating characteristic (ROC) analysis was performed to calculate the cut-off point in CSA measurement to reach an autograft thicker than 8 mm intraoperatively. A two-sided P-value of less than 0.05 was reported as statistically significant. Multiple regression analysis was done with selected preoperative predictors. We assessed the sensitivity and specificity of CSA measurement of MRI at the calculated cut-offs to predict adequate autograft (≥8 mm).Of the 42 eligible patients participating in this study 32 (76.2%) were male. The mean age of the patients was 32.8 years, ranging from 19 to 40 years. The mean interval between preoperative MRI and anthropometric measurements and ACLR was 18 (4–26) and 3 (1–6) days, respectively. The mean intraoperative HT autograft diameter was 8.0 mm. In 27 patients (64.3%), an HT autograft diameter of 8 mm or more was harvested during surgery. Anthropometric factors and preoperative measurements are reported in Table P < 0.001), smaller gracilis CSA , and smaller semitendinosus CSA  compared to males.Females had a significantly lower HT autograft diameter  and heavier in body weight (P = 0.036) with a greater gracilis (P < 0.001), semitendinosus (P < 0.001), and combined CSA (P < 0.001). Table Results of Mann-Whitney U and t-test analysis showed that patients with an HT autograft diameter ≥ 8 mm, were significantly taller  prediction, ROC curve analysis determined a cut-off value of 13.5mmr = 0.63), weight (r = 0.32), and the CSA of isolated and combined HTs, especially gracilis (r = 0.79) as the best predictors for the HT autograft diameter are. According to our results, a minimum gracilis CSA of 7.5mm2 at the level of the medial epicondyle on axial MRI can assure surgeons of an intraoperative autograft ≥8 mm with 88.9% sensitivity and 80% specificity. Interestingly, when the analysis was performed for males and females separately, the sensitivity increased to 91.7% for males and the specificity to 100% for females at the same cut-off. Regarding semitendinosus or combined HTs CSA measurements, a lower cut-off was obtained for females. This is in line with the hypothesis of this study, which states to have a more practical prediction of the HT autograft diameter, different cut-offs should be considered in males and females (Table r = 0.79 vs. 0.63). A multiple linear regression model showed that gracilis CSA (P < 0.001) and height (P = 0.004) are statistically important determinants of HT autograft diameter with the following linear regression equation:Based on the findings of this study, to make the use of preoperative MRI measurements more practical, it is better to assess the predictors in males and females separately. We found height (es Table . From a 2) + 0.037× Height (cm) - 1.35.HT autograft diameter = 0.373 × Gr CSA (mmFew studies have evaluated both MRI and anthropometric variables as predictors of HT autograft diameter simultaneously , 13, 22.In the study of Mr. Grawe et al.,  althoughThe study by Leiter et al.  and CoreHowever, this study also has shortcomings that can be controlled in other studies to obtain more reliable results. In this study, CSA was measured only at the level of the medial epicondyle, while studies  have shoPreoperative CSA of HTs, especially gracilis on MRI, length, and weight are most predictive for an adequate diameter of 4-stranded HT autograft harvested during ACLR.


To develop and validate a radiomic nomogram based on texture features from out-of-phase T1W images and clinical biomarkers in prediction of liver fibrosis.  Patients clinically diagnosed with chronic liver fibrosis who underwent liver biopsy and noncontrast MRI were enrolled. All patients were assigned to the nonsignificant fibrosis group with fibrosis stage <2 and the significant fibrosis group with stage ≥2. Texture parameters were extracted from out-of-phase T1-weighted (T1W) images and calculated using the Artificial Intelligent Kit (AK). Boruta and LASSO regressions were used for feature selection and a multivariable logistic regression was used for construction of a combinational model integrating radiomics and clinical biomarkers. The performance of the models was assessed by using the receiver operator curve (ROC) and decision curve.  ROC analysis of the radiomics model that included the most discriminative features showed AUCs of the training and test groups were 0.80 and 0.78. A combinational model integrating RADscore and fibrosis 4 index was established. ROC analysis of the training and test groups showed good to excellent performance with AUC of 0.93 and 0.86. Decision curves showed the combinational model added more net benefit than radiomic and clinical models alone.  The study presents a combinational model that incorporates RADscore and clinical biomarkers, which is promising in classification of liver fibrosis. Promising studies have shown that fibrosis can be eliminated or reversed in the early stage, while cirrhosis is difficult to be reversed [Liver disease accounts for approximately 2 million deaths per year and is the main public health crisis worldwide . Liver freversed . So, earAlthough biopsy is still the golden standard for liver fibrosis staging, it has some limitations, for instance, the invasive way, poor repeatability, sampling error, and hospitalization , 5. A noRadiomics analysis is a promising method in predicting liver fibrosis according to large amounts of studies. Texture features extracted from contrast MR images, T1 and T2 mapping images, and diffusion-weighted images all exhibited good to excellent diagnostic values –13. PrevThis retrospective study was approved by the institutional review board and local ethics committee (no. PJ2016-013-01). Written informed consent was obtained. All liver biopsies were clinically indicated.Participants who were clinically diagnosed with chronic hepatitis and underwent both noncontrast MRI scan and liver biopsy were screened for this study between July 2016 and September 2021. Inclusion criteria were as follows: adult patients 18 years of age or older, patients who underwent MRI scans before undergoing liver biopsies, patients' timeframe between MRI and biopsy should be six months, and patients who are willing to participate in this study and signed a written informed consent form. Exclusion criteria were as follows: patients with claustrophobia, MR images with large respiration or motion artifacts, decompensated cirrhosis, patients with splenectomy, and MRI exams performed 6 months or later than biopsy. A total of 145 participants were screened and 139 were included.All MRI scans were performed on the same 1.5 T clinical system  using a 4-channel body phased-array coil. All participants underwent the same abdominal MRI protocol, which consisted of the following sequences: in-phase and out-of-phase T1-weighted axial images. The imaging parameters of the T1W sequence were TR (repetition time) 200 ms, TE (time to echo) 2.2 ms/4.4 ms (in-phase/out-of-phase), averages of 1, concatenations 1, FoV (field of view) read 380 mm, FoV phase 78.1%, and slice thickness 6.0 mm.th rib. The fibrosis stages were assessed according to the METAVIR scoring system [A liver biopsy was performed under ultrasound guidance. Histopathologic features were evaluated by a pathologist with 10 years of experience who was blinded to patients' MRI diagnoses. The biopsy sampling area was selected in the liver at the level of the midaxillary line of the 8g system  and stan1/2).Laboratory results one week before biopsy were collected from the electronic medical record. Biomarkers included alanine aminotransferase (ALT), aspartate aminotransferase (AST), and platelet count (PLT). APRI was calculated using the following formula: , and FIB-4 was calculated using the following formula: (age × AST)/. Radiomics features include the first order, shape, gray-level co-occurrence matrix, gray-level run-length matrix, neighboring gray one-tone difference matrix, gray-level differential matrix, and wavelet transform. Overall, 851 texture features were extracted per ROI. Details are shown in Texture features were extracted from out-of-phase T1W images of all participants by two radiologists . All participants' images were exported in DICOMS format and then imported into an open-source software program   for manuThe intraclass correlation coefficient (ICC) , 24 was r-project.org)) software. In the training group, two feature selection methods, Boruta and Least absolute shrinkage and selection operator (LASSO) [All participants were randomly assigned into training group and test group with a ratio of 7 : 3. Considering the imbalance of the data, SMOTE was used for data augmentation of the minority group by increasing synthetic data points based on the original data points. All statistic data were performed by using R 3.5.1R  , were us (LASSO)  is an alt-test or Wilcoxon test. Categorical variables were analyzed by the chi-square test or Fisher's test. Univariable logistic regression was used to evaluate the association between clinical factors and the fibrosis grades. Finally, a clinical model was built by multivariable logistic regression. Meanwhile, collinearity was calculated based on the variance inflation factor (VIF) and a feature with VIF >10 was removed, and validation was applied by ROC analysis in the training and test groups.For clinical factors, continuous variables were analyzed by using the independent P < 0.05 was considered statistical significance.Significant clinical factors, as well as radiomics scores, were analyzed in multivariable regression to construct the combination model. The discriminative performance of the model was assessed using the ROC analysis and calibration curve. The Hosmer–Lemeshow test was used to test the goodness-of-fit of the model both in the training and test groups. The Delong test was applied to test the area under the ROC curve (AUC) of different models. A decision curve (DCA) was implemented to verify the clinical usefulness of the combination model, clinical model, and radiomic model, by calculating the standardization net benefits at different threshold probabilities. F = 1), 33 with stage 2 (F = 2), 32 with stage 3 (F = 3), and 32 with cirrhosis. The underlying diagnoses for liver biopsy were hepatitis B infection in 82 patients, hepatitis C infection in 4 patients, 15 patients with autoimmune hepatitis, 10 primary biliary hepatitis, 10 drug-induced hepatitis, and 18 others . All patients were assigned into nonsignificant fibrosis (F < 2) (age 47.5 ± 3.53) and significant fibrosis (F ≥ 2) (age 49.27 ± 19.79). Then patients' omics data were randomly divided into training and test groups with a ratio of 7 : 3.A total of 139 patients  were enrolled in this study, with 42 with fibrosis stage 1  and APRI 1.8 (95% CI: 1.16–3.40) (P=0.032). Then, the clinical model was constructed, and ROC analysis showed that the AUCs of the training and test groups were 0.80 (95% CI: 10.70–0.89) and 0.78 (95% CI: 10.61–0.94). Details are showned in Results of univariable logistic regression of the clinical factors are FIB-4 2.03 (95% CI: 1.43–3.29)  and 0.86 (95% CI: 0.74–0.99). The Delong test of AUC showed AUC of the combinational model and clinical model had statistical significance, while the others showed no statistical significance. The calibration curve and Hosmer–Lemeshow test exhibited acceptable goodness of fit with In this study, we developed and validated a noncontrast MRI radiomics nomogram for classification of liver fibrosis which incorporated the most predictive radiomics signatures and FIB-4 and had the potential to classify nonsignificant and significant fibrosis in a noninvasive way. Liver fibrosis is an important dynamic course during hepatitis processing to cirrhosis and is caused by the deposition of extracellular matrix. Liver fibrosis is difficult to diagnose because fibrosis is characterized by subtle changes and cannot be visible using CT or MRI examinations. Texture analysis is a new method that can extract features from images and transform them into visible variables. By analyzing these variables, more subtle changes inside the images can be obtained for further study.th percentile, and diff-entropy and reported an AUC of 0.902 in stratification of advanced fibrosis. Park et al. [F ≥ 2.For the construction of the radiomics model, the Boruta algorithm and LASSO regression were used for feature selection because of the redundancy of omics features. Boruta was developed to identify all relevant variables in a more efficient and stable way. It has been proved that Boruta was the most powerful approach for high-dimensional omics datasets in machine learning. LASSO regression is characterized by the simultaneous fitting of generalized linear models and variable selection based on the strength of their univariable outcomes and regularization. The AUC of the radiomics model of the training group is 0.87 0.80–0.94) and validated in the test group with an AUC of 0.82 (0.69–0.96). It revealed a radiomics model on the basis of out-of-phase MRI had the potential for classification of liver fibrosis. Large numbers of previous studies have proven that radiomics analysis of CT and MRI images could be a surrogate method for predicting liver fibrosis , 27–29. k et al.  calculat4 and valk et al. . RadiomiAPRI and FIB-4 are the most widely used clinical biomarkers for classification of liver fibrosis. Hu et al.  reportedThere are also some limitations in our study. First, the limited sample size in this study might decrease the statistical power and external validation should be required in another cohort. Second, the lack of fibrosis stage F0 may add some biases to the results. Third, considering the limited number of patients, we included all patients with different kinds of chronic liver fibrosis. A more detailed classification of patients may be needed in a further study. Fourth, as previous studies have shown that diagnostic performance of clinical biomarkers may be influenced by ASL level and necroinflammation activity, the nomogram integrating FIB-4 may add some error to the results. So, a further study with more details should be performed.In conclusion, radiomics based on noncontrast MRI have potential in stratification of liver fibrosis. A combinational model integrating radiomics and clinical biomarkers is promising in improving diagnostic values compared to the radiomic model and clinical model.


Prediction of susceptibility to Orthodontically Induced External Apical Root Resorption (OIEARR) has been hampered by the complex architecture of this multifactorial phenotype. The aim of this study was to analyze the impact of the interaction of multiple variables in the susceptibility to OIEARR.The study evaluated 195 patients requiring orthodontic treatment. Nine clinical and treatment variables, single nucleotide polymorphisms (SNPs) from five genes and variables interactions were analyzed as risk factors for OIEARR using a multiple linear regression model.p < 0.01). Duration of treatment was the most important predictor and gender was the second, closely followed by premolar extraction. For genes encoding osteoprotegerin (OPG), the receptor activator of nuclear factor κ B (RANK) and the IL1 receptor antagonist (IL1RN), the effect of analyzed variants changed from protective to deleterious depending on the duration of treatment and the age of the patient.The model explained 29% of OIEARR variability (ANOVA: This work shows that in OIEARR the impact of genetic susceptibility factors is dynamic changing according to clinical variables. Accurate phenotype prediction is essential for precision medicine. Unfortunately, for complex diseases this task has not been well succeeded. Apart from the difficulty in characterizing the genetic component of inter-individual variability, the complex interaction between genetic and non-genetic variables is a major challenge.IL1B) gene,  [%OIEARRmax was evaluated as a quantitative variable using a multiple linear regression approach . The valor (VIF) . The Haron 3.4.3  was usedon 3.4.3 . The dat1324556] .p > 0.05); for random error (Dahlberg formula), values varied between 0.5% and 1%, which is not statistically significant [Intraoperator error analysis revealed that for systematic error (t-test) there were no statistically significant differences between the two measurements . Data on OIEARR and %OIEARRmax distribution by tooth has already been described in previous work [p > 0.05).Clinical characterization of the patient sample is described in Table ous work . Frequenp < 0.001); B) duration of treatment and RANK gene SNP (p < 0.001); C) duration of treatment and OPG gene SNP (p < 0.001); D) patient age at the beginning of treatment and IL1RN genotype (p < 0.01). Besides these interactions, others have been tested but not used for further analysis (p > 0.05).Four “interactions” were identified by interaction plots and afterwards used in the model Fig. : A) durap < 0.01, n = 195, residual standard error = 8.00 on 182 degrees of freedom (df), adjusted R-squared = 0.29, coefficient of variance of the root mean square error (CV-RMSE) = 8.25). Table The regression model explains about 29% of %OIEARRmax variability (ANOVA: p.p.) (B = 3.93) more %OIEARRmax than females and that patients with genotype GG of P2RX7 SNP have, on average, 3p.p. (B = 2.87) more %OIEARRmax  B = .93 more p.p. (B = 15.86) more OIEARR, but are less affected by duration of treatment (2p.p. increase per year) than patients without premolar extraction (5p.p. increase per year). Therefore, for treatments up to 48 months, patients without premolar extraction remain less prone to OIEARR. Concerning the SNP of OPG gene, duration of treatment has less impact for patients with genotype TT than for patients with other genotypes (increase of 3p.p. vs. 8p.p. per year), so that for treatments up to 36 months TT is the risk genotype but for longer treatments it becomes protective. Similarly, genotypes CT and TT of RANK gene SNP are associated with a slower increase in OIEARR over time (3p.p. vs. 8p.p. per year) and though for treatments up to 36 months these are higher risk genotypes they become protective thereafter. Considering all the effects of interaction associated with the duration of treatment, the average effect of this variable is estimated to be 4p.p. per year. Analyzing the interaction between the “age at the beginning of treatment” and IL1RN SNP shows that after age 20, but not before, genotype TT becomes an increasing powerful risk factor . Regression lines on Fig. Based on non-standardized coefficients from Table In this work we explored not only clinical and genetic factors but also variables interaction effects determining susceptibility to OIEARR. Identified variables were used in a multiple linear regression model. The model explained 29% of inter-individual OIEARR variability, with an estimate for the test set RMSE (root mean squared error) of 8.25% OIEARR and a training set RMSE of 8% OIEARR, suggesting no overfitting of data.P2RX7, OPG encoding gene and IL1RN, independently contributed to OIEARR susceptibility, and RANK encoding gene showed a near significant result.Significant clinical contributors included duration of treatment, gender, age, and premolar extraction, all of them previously described in the literature, though with inconsistent results , 32, 33.IL1RN TT genotype, the interference with susceptibility to OIEARR varies with patient age, changing from a protective to a risk factor.The most interesting finding is the evidence of complex and dynamic variables interactions involving factors such as duration of treatment, premolar extraction, genetic profile, and age of patient. The harmful effect of long treatment duration has been described by many authors , 20, 25 P2RX7, TT for OPG gene, TT or CT for RANK gene and CT or CC for IL1RN. For these patients, OIEARR will vary between 17 and 23% (95%CI). Results also predict that lower risk patients, females with the opposite genotypes, will have between 3 and 13% of OIEARR (95%CI). So, higher risk patients have 2.5 times more OIEARR than lower risk patients. For other clinical profiles, higher and lower risk genotypes may be different.According to the model, for the average 17-year-old patient, without premolar extraction, for a 30-month course of treatment, these results predict that higher risk patients will be male, with a genotype profile of GG for These types of cross-over interactions involving genetic and non-genetic variables have been described in complex phenotypes , 36. In In a case/control study including sixty-seven patients and matched controls, Sharab et al. 2015) , who wer15 , who This study has some limitations. As revealed by the results of the multiple regression model, the size of the effect of variables is lower than predicted based on previous literature reports, meaning that a much larger sample size should be used in future work. Using %OIEARRmax as a dependent variable instead of data of all teeth improves the probability of identifying factors contributing to the phenotype, which is our main goal, but may overestimate the effects they have. Also, the exploratory approach used to select the two-way interactions to be included in the model may have introduced additional sources of noise. The method used for OIEARR diagnosis was based on panoramic films, known to be less accurate than periapical films. However, even periapical films show distortion because of error caused by variability in tooth shape and tooth angulation, and the literature review shows that independently of the methodology used, studies analyzing OIEARR etiology, severity, and distribution, give the same results , 15, 18.In summary, this work highlights the complex architecture of OIEARR and shows for the first time that the effect of variables and their interactions is dynamic and evolves over time. Currently, genetic testing cannot be recommended to predict this iatrogenic event. The impact of unmodifiable variables like genetic profile, seems to be dependent on clinically manageable factors such as the age at which treatment is started and the duration of treatment, thus stressing the importance of judicious clinical decisions.


Explosions can produce blast waves, high-speed medium, thermal radiation, and chemical spatter, leading to complex and compound eye injuries. However, few studies have comprehensively investigated the clinical features of different eye injury types or possible risk factors for poor prognosis.We retrospectively reviewed all consecutive records of explosive eye injuries (1449 eyes in 1115 inpatients) in 14 tertiary referral hospitals in China over 12 years (between January 2008 and December 2019). Data on demographics, eye injury types, ocular findings, treatments, and factors affecting visual prognosis were extracted from a standardized database of eye injuries and statistically analyzed.P < 0.01). However, no difference was observed between rupture and contusion. Ultimately, 9.59% of eyes were removed and the final vision was ≤ 4/200 in 45.82% of patients. Poor presenting vision [odds ratio (OR) = 5.789], full-thickness laceration of the eyeball ≥ 5 mm (OR = 3.665), vitreous hemorrhage (OR = 3.474), IOFB (OR = 3.510), non-mechanical eye injury , rupture (OR = 2.362), traumatic optic neuropathy (OR = 2.102), retinal detachment , endophthalmitis , contusion (OR = 1.679), ciliary body detachment (OR = 6.592), zone III OGI (OR = 1.940), and PVR  were significant negative predictors for poor visual outcomes.Mechanical ocular trauma accounted for 94.00% of explosion-related eye injuries, among which intraocular foreign bodies (IOFBs) resulted in 55.17% of open globe injuries (OGIs) and contusion caused 60.22% of close globe injuries (CGIs). Proliferative vitreous retinopathy (PVR) was more common in perforating (47.06%) and IOFB (26.84%) than in penetrating (8.79%) injuries, and more common with laceration (24.25%) than rupture (9.22%, Explosion ocular trauma has complex mechanisms, with multiple eyes involved and poor prognosis. In lethal level I explosion injuries, eyeball rupture is a serious condition, whereas contusion is more likely to improve. In level II injuries, IOFBs are more harmful than penetrating injuries, and level IV represents burn-related eye injuries. PVR is more associated with penetrating mechanisms than with OGI. Identifying the risk predictors for visual prognosis can guide clinicians in the evaluation and treatment of ocular blast injuries.The online version contains supplementary material available at 10.1186/s40779-022-00438-4. An explosive blast has sudden and devastating effects and usually causes great casualties . ExplosiThis retrospective study was conducted according to the tenets of the Declaration of Helsinki and approved by the ethics committee of the Chinese PLA General Hospital (S2002-074-01). Consecutive medical records of all patients with explosive eye injuries who were admitted to 14 tertiary referral hospitals in China between January 1, 2008 and December 31, 2019 were extracted and retrospectively reviewed. Each case was recorded using a standardized pre-formulated data sheet; the records were maintained in an eye injury database. Ultimately, 1449 eyes from 1115 patients with eye injuries caused by explosions were eligible for analysis.Detailed information regarding each eye that was injured from an explosion was collected using a standardized data sheet that included patient information , a thorough history (including the cause of explosion and timing and nature of the injury), clinical presentation , and treatments and outcomes . In addition, the mechanical globe injury zone and the wound length in the globe wall were recorded. Surgical findings and complete ophthalmological examination results were also retrieved for analysis. The VA data was either best-corrected or pinhole VA. The prognostic factors related to poor prognosis  were analyzed. The population was further divided into six groups according to age: 1–6 years (pre-schoolers), 7–12 years (juveniles), 13–18 years (teenagers), 19–39 years (youth adults), 40–59 years (middle-aged adults) and ≥ 60 years (old adults). Individuals ≤ 18 years of age were categorized as adolescents and individuals > 18 years old as adults.Classification and definition of mechanical eye injury (MEI) were based on the Birmingham Eye Trauma Terminology (BETT) . Open glThe globe injury zones were identified according to the Ocular Trauma Classification System (OTCS) . The OGINon-mechanical eye injury (NMEI) included thermal, alkali, and acid burns of the eye. Chronic hypotony was defined as intraocular pressure (IOP) < 8 mmHg after at least 6 months of follow-up. Snellen VA was converted to fractional VA and grouped according to the Ocular Trauma Score (OTS) study group (1 through 5) : no light-test. Further multiple logistic regression analysis was conducted to predict the independent factors affecting poor vision at the final assessment. P-values < 0.05 were considered statistically significant.All data were collected from an electronic database and crosschecked for errors. Statistical analyses were performed using SPSS software version 26.0 . Categorical variables were analyzed using the Chi-square test. Continuous variables were evaluated for normality, and means were compared using a two-tailed F = 0.107, P = 0.744]. Among all eye injuries, 72.91% occurred in adults, and the largest proportion was sustained by the 19–39-year-old group  . The proportion of men was highest in the 13–18-year-old group (92.31%) and the proportion of bilateral eye injuries was highest in the 40–59-year-old group (37.44%) . The mean age of all patients was (28.84 ± 14.52) years  and the ratio of men to women was 7.64:1. No significant age difference was observed between male and female patients , being classified as certain types of eye injury , some clinical characteristics , the wound of OGI was in zone III , complication with endophthalmitis  and development of secondary PVR  after explosive eye injuries.As shown in Table Explosions can result in various degrees of injuries distributed across a wide range due to different mechanisms initiated by the blast , 7. GeneThe ocular trauma classification can be analyzed and interpreted based on the mechanism of explosive injury. Primary (level I) explosion injuries develop when the explosive shockwaves produce pressure differences followed by an implosion effect in the eyeball. The maximum IOP during an explosion can reach a peak of 0.29 MPa 2175 mmHg) at 1.63 ms, which is two times larger than the physiological IOP in healthy eyes . Karimi  mmHg at The ocular injury zone location according to OTCS  is closely related to the prognosis of visual function. The ocular wall involved in the zone I can be repaired, whether the injury is an OGI or CGI. Because the cornea is a refractive medium, corneal damage affects VA, which can be improved by certain treatments, such as corneal transplantation. Zone II involves the iris, ciliary body tissue, and lens, which affect the pupil and IOP. Intraocular lenses can make up for the abnormal loss of function of the natural lens. The retina is the nerve layer responsible for eye visual perception and transmission, and is the key tissue involved in zone III injuries, which are difficult to repair. Low IOP caused by ciliary body injury and visual function damage caused by retinal injury are the most stubborn and difficult injuries to cure and improve. A poor prognosis is generally associated with zone III, followed by zones II and I . In our In our study, traumatic cataracts, VH, RD, and PVR all occurred more in OGI than in CGI, which indicates that, regardless of whether the sharp objects directly penetrate the eyeball or rupture it indirectly, the global structural integrity destructions indicate that the local or overall intraocular tissues undergo more severe, extensive, and diverse types of damage. No statistically significant difference was observed in the proportion of traumatic cataract in contusions and ruptures, which supports that zone II (where the lens is located) is equally involved in both types of ocular trauma by blunt force. Tears of the eyeball wall along with the adjacent uveal vascular networks can inevitably lead to intraocular hemorrhage including VH which, then, was more common in rupture than contusion. Among contusion injuries, RD only developed when the blunt impact from the shockwave produced a strain in the retina high enough to exceed the specified threshold for RD . ObviousAt the final follow-up, 9.59% of eyes had been removed following explosive injuries in our study. In previous reports, this percentage was only 0.61–10.00% for general or firework-related eye injuries , 33–36, As far as predictors of poor final VA, initial VA is generally acknowledged as a key factor that affects final vision status , 39–42, This multi-center review revealed that explosions cause high rates of bilateral ocular trauma, complex injury conditions and are associated with increased incidence of zone III (posterior segment) involvement and poor prognosis. Eyeball contusions and ruptures associated with primary (level I) explosion injuries, lacerations  secondary (level II) to explosion-related injuries, and NMEI related to grade IV explosive injury (burns) were the main mechanisms identified in our study. Rupture injuries tend to predict a worse prognosis and lower probability of recovery. Compared with pure penetrating injuries, the harm caused by IOFB and perforation is more severe. Moreover, we suggest that PVR caused by blunt force is not necessarily related to eyeball rupture, and the mechanism of penetration by a foreign object into the eyeball, especially by IOFBs or direct penetrating of the retinal/choroid, promotes the PVR occurrence and development. Worse presenting VA, larger-sized eyeball wall wound, clinical signs , injury type  and PVR development were associated with worse visual outcomes among injured eyes following an explosion. Future studies that include large and homogeneous case and control populations are required to evaluate the prognostic scoring system of eye blast injuries among different types of eye injuries caused by general causes.Additional file 1: Table S1. General features of the explosive eye injuries . Fig. S1. Distribution of the number of patients and the proportions of male patients and bilateral eye injuries in different age groups.


Staphylococcus pseudintermedius and Staphylococcus capitis have been identified on the mobile phones for the very first time. Interestingly, some soil microbes were also isolated and unfortunately found to have some antibiotic resistance like Raoultella ornithinolytica and Sphingomonas paucimobilis. The results revealed that mobiles were contaminated with multidrug-resistant (MDR) pathogens, and this study also showed that few of the saprophytic soil strains have antibiotic resistance, which can be an alarming situation that needs to be addressed.Mobile phones have become an indispensable part of human lives for communication, education, and entertainment activities. This study aims to evaluate the diversity pattern of bacterial contaminants on mobiles and to check antibiotic resistance profiles in 105 samples. The study revealed a contamination of 51% in men and 49% in women, the highest in the 21- to 30-year age group, evidencing the extreme use of mobiles by teenagers. The study observed Gram-negative bacteria (63%) versus Gram-positive bacteria (37%). Overall, Gram-negative bacterial isolates showed the highest sensitivity to antibiotic nitrofurantoin (90%) and the lowest in ampicillin (35%). Gram positive has highest incidence of sensitivity towards tigecycline (100%) and lowest in cefoxitin (20%). ES The mobile phone or smartphone have many attributes and characteristics that make it very attractive to both the young and the old. With the achievements in the field of technology, mobile phone, a portable electronic device for personal communication, has become an important part of one's life, and its benefits have made it user friendly. However, the disadvantage of overlooking the health hazard has been a concern because many users do not take care of personal hygiene while using these phones. The extensive usage of mobile devices, such as the touch screen, renders the highest possible transmission fomites of several pathogens across various age groups. Furthermore, different users handle them constantly exposing and acts as a good carrier to an array of microorganisms ,2. TheseStaphylococcus aureus, Escherichia coli, and Pseudomonas spp [In the current situation, there has been an incessant use and handling of mobile phones, and these devices have also been exposed to a variety of different pathogenic bacteria . These ponas spp . It has onas spp . These Monas spp .Antibiotic resistance has an imperative issue that is related with both nosocomial and hospital infections and that has been drastically increasing. This presents an obstacle in treating the MDR pathogens that cause infections ,9. Many The study was conducted from January to April 2021, in the campus of Dayananda Sagar University, Bengaluru, India. During the study period, a total of 100 mobile samples were collected from the individual mobiles. Sociodemographic characteristics of the participants were taken into account with a self-administered questionnaire to collect the information such as age, sex, profession, use of mobile phones, and the habit of cleaning their mobile phones were considered.The samples were collected by using a sterile cotton swab that was dipped in the nutrient broth and rolled on the keys, screen, and back of the mobile phones.Bacteria were isolated by inoculating swabs on MacConkey's agar, blood agar, and Mannitol salt agar . The inoculated plates were incubated at 37°C for 24 to 48 hours and observed for growth of the isolates. The primary bacterial identification was based on the morphological, cultural characteristics, and a series of biochemical tests. The test included Gram reaction, Indole test, MR and citrate test, Urease test, Mannitol motility, Triple sugar iron agar, Catalase, and Coagulase test .The isolates were subjected for AST according to Clinical Laboratory Standards Institute  using KiEscherichia coli ATCC 25922 and S. aureus ATCC25923 were used as quality control strains. Following antibiotics were procured and used for the AST, which included amikacin (30 mcg), ampicillin (10 mcg), piperacillin/tazobactam (100/10 mcg), cefuroxime (30 mcg), cefuroxime Axetil (30 mcg), ceftriaxone (30 mcg), cefoperazone/sulbactam (75/30 mcg), cefepime (30 mcg), imipenem (10 mcg), meropenem (10 mcg), gentamicin (10 mcg), nalidixic acid (30 mcg), ciprofloxacin (5 mcg), tigecycline (15 mcg), nitrofurantoin (300 mcg), colistin (10 mcg), trimethoprim/sulfamethoxazole (23.75/1.25 mcg), cefoxitin (300 mcg), benzylpenicillin (2 mcg), oxacillin (1 mcg), levofloxacin (10 mcg), inducible clindamycin (2 mcg), erythromycin (15 mcg), clindamycin (2 mcg), linezolid (30 mcg), daptomycin (10 mcg), teicoplanin (30 mcg), vancomycin (30 mcg), tetracycline (30 mcg), and rifampicin (5 mcg).βL producers were detected by performing Double Disc Synergy Test (DDST) as per the guidelines of CLSI . The test isolates suspension for each of the pure bacterial isolates were prepared according to 0.5 McFarland constant that were swabbed on MHA plates. After 15 min, antibiotic discs containing amoxycillin (100 mcg) and cefotaxime (30 mcg) with amoxycillin/clavulanic acid (100/10 mcg) and cefotaxime/chlorophyllin (30/10 mcg) were placed at a distance of 20 mm apart. The plates were incubated at 37°C for 24 hrs. The results were interpreted by measuring the diameter of the inhibition zone. According to CLSI, an increase in <5 mm in the zone diameter around the Clavulanic acid combination discs versus the same discs alone confirmed the presence of ESβL producers.ESData were entered and analysed using GraphPad Prism software and summarised frequencies and percentages has been presented in the tables and graphs.A total of 100 mobile samples were collected from the various participants in the study. The distribution on the basis of gender were 51% males and 49% were females . It has The study revealed that of the 100 mobiles that were used, 96 mobiles showed a contamination with bacteria. Four of the mobiles had been decontaminated with alcohol, and therefore, the incidence rate was found to be 96%. Five mobile phones had shown to have multiple contaminants of the bacteria. A total of 105 bacterial species were identified from the contaminant mobile phones. Of which Gram-negative bacteria had a highest incidence rate with 62.85% (66 isolates) while, Gram-positive were 37.14% (39 isolates) as in Staphylococci (CONS) were the most prevalent present with 15.38% followed by Staphylococcus citrus, Staphylococcus saprophyticus, Staphylococcus pseudintermedius, S. capitis, Staphylococcus hominis, Enterococcus faecalis, and the lowest was observed in Staphylococcus heamolyticus with 7.06% reviewed in K. oxytoca (18.18%) is the most frequently observed contaminant on the mobiles in Gram-negative bacteria, followed by E. coli (13.6%) and least was observed with Pseudomonas aeruginosa (4.5%). The study also observed the other contaminants like Citrobacter fraundii, Citrobacter koserii, and Aeromonas hydrophilia species each accounting for 7.5%. The other organisms observed in the study were R. ornithinolytica (6%) and S. paucimobilis (6%) as in In the study, Gram-positive bacteria, coagulase-negative The bacterial isolates showed a variable antibacterial susceptibility pattern, Gram-positive bacteria showed a maximum resistance to cefoxitin (79.4%) followed by, clindamycin (69.2%), and erythromycin (66.6%) The study revealed varying MIC results for the isolates that were isolated as interpreted in βL production by mobile contaminants was found to be highest in K. oxytoca (5.28%) followed by Klebsiella pneumoniae (4.62%) and the least in Erewina spp and Enterobacter spp (2.64%). The ESβL expressed by the bacteria has further increased resistance development to antibiotics such as ceftazidime, gentamycin, cefepime, and ceftriaxone. However, of the four ESβL producers other seven turned out to be non-ESβL.This study also aimed at the phenotypic detection of Gram-negative bacteria resistant to cephalosporins. The expression of ESK. pneumoniae) and 12.8% for 14 drugs (mostly in CONS) in Gram-negative and Gram-positive bacteria, respectively tabulated in Tables With the increase in the antimicrobials, there has been a drastic increase in the MDR strains ranging with the resistance among two drugs upto 18 antibiotics. Here, maximum of 4.5% to 16 antimicrobials  is observed in our study, compared to Gram-positive bacteria (37.14%). On the contrary, Karkee et al.  much hig workers ,22. Contis study ,18,27. HE. coli with 100%. However, Gram-negative isolates in this study had resistance to ampicillin [In this study, the isolated bacteria had variable sensitivities to the antibiotics tested. It had different variability patterns compared to the other studies with higher rates ,22,28. Apicillin  while ciStaphylococcus and Enterococcus species was found. Alongside, we could also observe S. pseudintermedius and S. capitis, these organisms are not been documented as contaminants amongst all studies done so far related in community on mobile phones. The study denoted a high resistance rate to cefoxitin 79.4% and 58.9% to penicillin group that includes benzylpenicillin and oxacillin. While, a recent study conducted by Campista-Leon et al. [Staphylococcus (84.6%), Bacillus, and Enterococcus species (7.7%). In addition, this study also showed erythromycin resistant with 92.3%, ampicillin and penicillin (76.9%), dicloxacillin (61.5%), cephalothin (38.5%), and cefotaxime and ceftriaxone (7.7%). In our studies, we used extensive antimicrobials, and varying results were observed with the resistance rates. The rising antibiotic resistance designates that in the near future, treating the patients with infectious diseases will be difficult, if we do not take proper measures to prevent their rate of contamination and safety measures to prevent and contained for their transmission.In our study, a remarkable increase in the incidence rate of n et al.  showed gR. ornithinolytica and S. paucimobilis, which are unfortunately found to have resistance to certain antibiotics. The presence of clinically significant MDR strains poses a potential risk to user health, further disseminating the antibiotic resistant mechanism in the community by these microbes, we recommend hand hygiene and disinfecting mobiles to prevent cross-infection by these microbes.Mobile phones have become a necessary need of every individual, irrespective of their profession with new breeding grounds for the multidrug pathogens leading to infections. With high antibiotic resistance rate that has been observed in our study, it shows that there is a need for the decontamination of the mobile phones. Increasing antibiotic resistance patterns is a huge challenge in the treatment of pathogenic infections. Based on our study, it appears crucial to make people aware about the possibility of MDR risk being transferred by mobile phones in workplace. With regular cleaning and sanitising, the implementation of appropriate infection prevention guidelines will help reduce possible risks. The study also noted some important saprophytic soil microbes, such as