Despite a limited sample size, the strong AUROC values highlight the robustness of the binary classifiers in detecting ADHD—as such, with additional data, sensitivity and specificity metrics can be substantially augmented. This study is the first to apply machine learning based methods for the detection of ADHD using solely pupillometrics, and highlights its strength as a potential discriminative biomarker, paving the path for the development of novel diagnostic applications to aid in the detection of ADHD using oculometric paradigms and machine learning.Accurate and efficient detection of attention-deficit/hyperactivity disorder (ADHD) is critical to ensure proper treatment for affected individuals. Current clinical examinations, however, are inefficient and prone to misdiagnosis, as they rely on qualitative observations of perceived behavior. We propose a robust machine learning based framework that analyzes pupil-size dynamics as an objective biomarker for the automated detection of ADHD. Our framework integrates a comprehensive pupillometric feature engineering and visualization pipeline with state-of-the-art binary classification algorithms and univariate feature selection. The support vector machine classifier achieved an average 85.6% area under the receiver operating characteristic (AUROC), 77.3% sensitivity, and 75.3% specificity using ten-fold nested cross-validation (CV) on a declassified dataset of 50 patients. 218 of the 783 engineered features, including fourier transform metrics, absolute energy, consecutive quantile changes, approximate entropy, aggregated linear trends, as well as pupil-size dilation velocity, were found to be statistically significant differentiators ( Its overall prevalence among children and adolescents is 5–8%, affecting upwards of 1 million children per year in the US alone2. The long-term effects of untreated ADHD are detrimental for individuals and their families. Children and adults with untreated ADHD suffer from poor educational outcomes and familial relationships3, as well as increased economic burdens. Moreover, untreated ADHD during childhood is a risk factor for later adult mental health issues4. Lack of treatment impairs social and occupational functioning and increases the likelihood of developing comorbid disorders such as heightened anxiety, depression, personality disorders, and antisocial behaviors5. Additionally, inaccurate clinical evaluations can lead to inappropriate treatment interventions, such as incorrectly administering stimulant drug medications that have side effects on healthy children7. Accurate and efficient diagnosis of ADHD, thus, is crucial to effectively administer treatments and prevent subsequent complications for a child’s socioemotional development, academic and occupational achievement, and overall welfare.Attention-deficit/hyperactivity disorder (ADHD) is a clinically heterogeneous neurobehavioral disorder characterized by inattention, impulsivity, and hyperactivity9, as diagnosis is based solely on observed behavior and reported symptoms, creating a risk of over and under-diagnosis10. Evaluations are based on a checklist of eighteen symptoms, nine related to inattention and nine related to hyperactivity and impulsivity11. These subjective clinical assessments often last multiple hours6. Moreover, the demand for these examinations greatly exceeds the maximum capacity of available developmental pediatric clinics6. As a result, children are often waitlisted for over a year, preventing timely diagnosis and delaying the start of necessary treatment6. Wait times can extend beyond 13 months for minorities or socioeconomically disadvantaged groups6. Other assessment methods such as computerized performance tests have been criticized due to poor clinical utility12. Medical experts collectively agree that the lack of an objective and efficient mechanism to characterize ADHD remains a pervasive and detrimental problem, precluding effective treatment regimens3.Current clinical diagnosis is subjective, inefficient, and inaccurate. There is no reliable objective test to diagnose ADHD16. Pupillometric-based analyses have been applied to a number of psychiatric disorders, such as obsessive compulsive disorder, autism, dyslexia, and Tourette syndrome, in order to gain behavioral insights into correlations between eye movements and behavior18. In particular, one promising biomarker for ADHD in humans is pupil-size dynamics—the ways in which the pupil responds to certain visual stimuli9. Pupil-size dynamics have been shown to be associated with the brain norepinephrine system, an area which controls executive functioning19 and is impaired by ADHD. In accordance with this, Wainstein et al. showed in an experimental study that pupil-size dynamics were strong differentiators between ADHD positive and negative subjects after performing statistical analysis; moreover pupil-size was also shown to be strongly correlated with attentional performance in subjects9. Geng et al. showed that pupil size reflects uncertainty in users who completed a visuospatial working memory task20. Wahn et al. additionally showed that pupil-size dynamics can be utilized as a reliable metric to assess attentional load in patients21. Given the vast literature highlighting associations between pupil-size dynamics and attentional performance in neurobehavioral disorders, we hypothesized that pupillometric features could be utilized as objective biomarkers to effectively characterize ADHD using a machine learning based and time series analysis methodology.Due to the currently deficient methods for diagnosing ADHD, a reliable objective mechanism to characterize the disorder is necessary to ensure accurate and efficient diagnosis. Oculomotor paradigms are particularly adept in analyzing abnormalities in brains affected by neurodevelopmental disorders22. Similarly, Qian et al. devised a machine learning-based model to classify visual responses based on pupillometrics23. Baltaci et al. also incorporated a machine learning-based model to to classify user’s stress response and mental state based on pupillometrics, extracting a variety of statistical features based on pupillary movement24.Babiker et al. developed a machine learning model to predict a user’s emotional state using pupillometrics, engineering a set of features based on pupil-size dilation velocity and acceleration; their method achieved overall 96.5% accuracy, 97.93% sensitivity, and 98% specificityAs such, we sought to develop a machine learning-based framework to analyze pupillometric variation in subjects, hypothesizing that it would accurately discriminate between ADHD positive patients and control subjects. Using the engineered features, we also sought to extract valuable oculometric patterns to advance current understandings of pupillometry regarding the presence of ADHD using various feature visualization techniques and statistical validation.26. The subjects were elementary school children aged 10–12, recruited from local schools in Chile25. Three specific groups of subjects are included: Off-ADHD, On-ADHD and Ctrl9. Off-ADHD corresponds to positively diagnosed subjects not taking any medication, while On-ADHD corresponds to those taking medication. Ctrl represents a control group of healthy subjects. The 28 Off-ADHD subjects consisted of 4 girls, 24 boys, and the 22 Ctrl subjects consisted of 4 girls, 18 boys25. The medication administered was methylphenidate. The Eyelink 1000 device was used to record oculometrics at a sampling frequency of 1 kHz25. More specific experiment details are outlined extensively in Wainstein et al.’s publication25.The preprocessed time series dataset evaluated in this study was released by Wainstein et al., conducted under Universidad Católica de ChileOff-ADHD ground truth labels included. We note that the inclusion of on- and off-medication subjects introduces a bias in the ADHD Positive class through a confounding variable of receiving medication; this bias would not accurately reflect the population of patients with ADHD, as medication regulates the symptoms of ADHD and potentially impacts pupillometric patterns. This would degrade the validity of the machine learning algorithms if they were to be trained and tested on biased data. As such, the ADHD Positive class comprised of only Off-ADHD subjects, amounting to a full dataset of 50 instances.We assess model performance for binary classification by considering the ADHD Positive Group with only On-ADHD and Off-ADHD subjects, respectively25.A group of 50 subjects participated in the study. 28 subjects were patients diagnosed with ADHD, and 22 were healthy control patients. A subgroup of 17 ADHD patients performed the task twice, on and off medication, denoted as 25.All subjects were required to complete a visuospatial working memory task, which consisted of multiple 8 s trials, during which pupil-sizes were measured. In the first five seconds, three dot arrays were presented, followed by a distractor image. In the last three seconds, subjects were presented with a random dot array and asked to determine if the dot had been presented to them beforeDue to the high dimensional nature of the time-series data—each patient consisted of 160 trials, each containing 8000 timestamps of data—in order to reduce computational costs and ensure time-efficient analysis for feature extraction, for each trial, the time-series data was reduced to 500 timestamps by taking a moving average window of size 16ms and concatenating the results. We found that the overall structure of the time-series data was retained from the average sliding window approach. A side-by-side figure of original and reduced time series is provided in the A total of 783 features were engineered using time series analysis software—we engineered 22 custom features using garnered intuition on the pupillometric data. Engineered features obtained from software include aggregated linear trends, fourier transform metrics, energy spectral density, approximate entropy, as well as standard statistical values such as the mean, median, standard deviation, and variance of pupil-sizes during various intervals across the time-series. Features were calculated per-trial and then averaged across all trials, grouped by patient ID, in order to provide a thorough and encompassing feature space for each patient. Missing values were estimated using cubic spline interpolation prior to analysis, and trials with more than 80% of the data missing were excluded from analysis.For custom feature extraction, further building off of Wainstein et al.’s original visualizations, pupil-sizes for each group were averaged and visualized in Fig. We engineered custom features based on pupil-size dilation velocity and acceleration using garnered intuition on pupil-size dynamics between ADHD Positive and Negative groups. Let mentclass2pt{minimThe following binary classification algorithms were trained using the engineered features: Logistic Regression, KNN Neighbors, Naive Bayes, Decision Tree Classifier, and a Random Forest Classifier. Since over-complex algorithms tend to overfit on small datasets, evaluation was limited to the aforementioned classifiers.28. Nested CV is a reliable alternative to K-fold CV when estimates of the underlying hyperparameter search is desired—for the nested CV pipeline, an inner CV loop is used to tune hyperparameters for various models; the optimized model is then applied to a separate outer CV loop that assesses model performance without producing overly optimistic estimates. For feature selection per-fold, 9 optimal features were filtered using a standard univariate correlation-based one-way ANOVA F-test for feature ranking, which analyzes numerical input in conjunction with class labels. Since an excess of features can cause overfitting, especially for small datasets, a fixed value of 9 was arbitrarily established for selecting features in each fold for nested CV. Features were selected using only the train data in each fold in order to prevent overfitting and leaking of information into the test set. The nested CV procedure was repeated for a total of 30–50 times for each model, enabling the construction of confidence intervals for binary classification metrics.A comprehensive evaluation of each algorithm was conducted: due to the small dataset size, training and evaluating using a holdout set would not accurately reflect the generalization ability of a model and unnecessarily degrade predictive power by reducing training set size. As such, nested ten-fold cross-validation (CV) was employed to assess the performance of the models. Nested CV provides a robust and approximately unbiased estimate of test error: it addresses problems in traditional K-fold CV and leave-one-out CV, which have been shown to yield overly optimistic and biased test error estimatesStandard medical diagnostic metrics—sensitivity (true positive rate), specificity (true negative rate), area under the receiver operating characteristic (AUROC), as well as accuracy— were taken into account for analysis of model performance based on nested CV.29. The top 15 out of the 783 ranking features were selected and visualized in order to examine their strengths in differentiating between ADHD positive and negative subjects. We present class separability visualizations using the RadViz multivariate visualization algorithm, which projects a feature space onto a 2D plane in order to observe class separability among various features, grouped by ADHD diagnosis30. Features are placed uniformly around the circumference of a circle, with data points placed in the interior of the circle—the position of a given data point gravitates proportionally in the direction towards the corresponding features based on its values, as shown in Figs. In order to garner intuition on discriminative pupillometric characteristics for ADHD Positive and Negative subjects, a number of features were ranked using a nonparametric Mann–Whitney U TestOff-ADHD ground truth labels. We present a list of p-values and feature names in a supplemental file.For each engineered feature, a nonparametric Mann–Whitney U test was used to to quantitatively assess how effective the generated features were in differentiating between ADHD positive and negative groups, where ADHD positive represents only 31. Feature extraction was implemented using the tsfresh 0.16.0 library32.All the machine learning algorithms were implemented in Scikit-learn 0.22.2Figures Figures Figure In Fig. Among the custom engineered features, the mean velocity after the presentation of a stimulus, max accumulated velocity before the stimulus, and the difference in max velocities before and after probe presentation had p-values of 4.2e−02, 4.2e−02, and 4.9e−02, respectively. The additional significant features are listed in the RadViz visualization in Fig. ith coefficient. The quantile change is recorded from quantile 0.4–0.8, where the variance of absolute changes in pupil-size at consecutive intervals was calculated. The number of peaks is calculated by counting the number of occurrences in which a given pupil-size is greater than its 10 neighboring values on the left and right side.For the rest of the engineered features, we present names of features and p-values in a supplemental file, and report a select few of the filtered features that were statistically significant, which are showed in Table As shown in Table State-of-the-art machine learning algorithms were evaluated based on three key medical diagnostic classification metrics: sensitivity, specificity, and AUROC. An evaluation of the models is shown in Table Figure 7. Additional data, however, is needed to adequately assess sensitivity, specificity, and accuracy using a holdout test dataset. Overall, howeover, the strong AUROC values indicate the potential to achieve very strong metrics for the detection of ADHD with additional data, and provide a proof-of-concept that highlights the potential to use pupillometrics to effectively differentiate between ADHD Positive and Negative subjects.This study utilized a small dataset of 50 instances for machine learning model evaluation—for this reason, ten-fold nested CV was applied to the data to best assess how well each of the models could generalize to unseen data. Bayesian methods and simple classifiers like Logistic Regression tend to perform well on small datasets, which is reflected in our results. The support vector machine classifier, howeover, seems most promising given the strong balance in sensitivity and specificity, as well as an excellent AUROC of 0.856 (± 0.16). We note that the small dataset size significantly skews the sensitivity and specificity metrics, but the overall excellent AUROC metrics indicate that the classifiers are robust in detecting ADHD—as such, with additional clinical data, sensitivity and specificity metrics can be substantially augmented, enabling high-accuracy and efficient detection of ADHD. In small datasets, AUROC can assist in providing a more comprehensive assessment of binary classification ability by measuring accuracy at varying thresholds and taking into account probabilistic scores rather than class label predictions. The excellent AUROC values of the classifiers presented improve upon the reported misdiagnosis rate to be approximately 80% in 2010—approximately 20 percent of 4.5 million children using stimulant prescription medication were found to be misdiagnosed from a research studyMoreover, the statistically significant features provide a strong foundation for the binary classifiers and a new lens to view relationships in pupil-size dynamics and the presence of ADHD, reflected in our statistical validation and class separability visualizations. The features overall exhibited strong class separability between ADHD Positive and Negative groups, which is reflected in the AUROC values of the classifiers.We note that one drawback of our study lies in the small sample size, which can reasonably be only generalized to the encompassing city in Chile from which the data was collected. Additional data would help in creating a sample representative of the true population.33. The statistical significance of the engineered features in this study further illustrate its validity and strength in differentiating between ADHD positive and negative groups. Our results also show that local maxima and minima in pupil-size are also strong differentiators between positive and negative subjects. Moreover, standard deviation in pupil-size across a time-series was found to be a strong discriminator between the two groups, with control subjects exhibiting greater variation in pupil-size, indicating that ADHD positive subjects potentially suffer from lack of overall mobility in pupillary responses, which could further inform the use of pupillometrics as a biomarker to characterize ADHD.Insights into the pupil-size dynamics of ADHD positive and negative subjects were uncovered. In particular, variation, specifically standard deviation, in pupil-size dilation velocity, previously not studied within the scope of ADHD, were found to be strong discriminators between ADHD positive and negative subjects. Control subjects visually exhibited greater pupil dilation velocity and acceleration compared to ADHD positive subjects, indicative of heightened neural activity and decision making. ADHD positive subjects exhibit lower dilation speeds and pupil sizes most likely because of uncertainty and inattentiveness—Van de Brink et al. highlighted that smaller relative pupil size linearly correlates with greater lapses in attention, while greater pupil sizes correlate with increased attentional effort33. ADHD Positive subjects, however, exhibit greater variance in consecutive changes in pupil-size, measured in absolute value, from quantile 0.4 to 0.8, which includes the presentation of a stimulus. This suggests that their pupillometric patterns are more erratic when measured at consecutive timestamps, especially during the presentation of a probe, as opposed to more fluid changes in pupil-size exhibited by control subjects at consecutive timestamps. In accordance with this, approximate entropy, which measures regularity and unpredictability across a time-series34, is higher for ADHD positive subjects, further suggesting that their pupillary movements are more erratic than healthy subjects. The larger number of peak sizes also concurs this observation among ADHD Positive subjects.Additionally, absolute energy values, consecutive quantile changes, approximate entropy metrics, and peak numbers provide informative metrics for potentially differentiating between ADHD Positive and Negative subjects. Healthy subjects exhibit greater overall energy, or sum of squares, across a time-series, which indicates that they generally exhibit greater pupil-sizes across a trial than ADHD positive subjects, which concurs with the notion that larger pupil-sizes represent increased attentional effort6. Our findings can streamline clinical diagnosis and serve as a novel lens to view associations between pupillometrics and the presence of ADHD using machine learning. Moreover, they can enable medical professionals to make more informed decisions for diagnosing ADHD accurately. We provide a proof-of-concept, showing that pupillometrics can be used to effectively differentiate between ADHD Positive and Negative groups using machine learning. Future work to increase model performance and robustness revolve around attaining additional clinical and data and potentially integrating eye gaze directions with pupillometrics to provide a comprehensive and more accurate risk score of having ADHD. In conjunction with this, deep learning based models could enable more scalable and powerful analysis of this oculometric data for ADHD detection in the future with additional data. Moreover, potentially employing a multi-classification model that takes into account On-ADHD, Off-ADHD, and Ctrl subjects could enable a more robust framework.Our machine learning based framework offers a novel and reliable technical approach to diagnose ADHD that is time-efficient and reliant on an objective biomarker, rather than inaccurate, subjective clinical evaluations. Evaluations currently last multiple hours and rely on loose qualitative observationsSupplementary Information.


The association patterns of attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) with educational attainment (EA) are complex; children with ADHD and ASD are at risk of poor academic outcomes, and parental EA has been associated with risk of ADHD/ASD in the offspring. Little is known on the causal links between ADHD, ASD, EA and the potential contribution of cognitive ability.Using the latest genome-wide association studies (GWAS) summary data on ADHD, ASD and EA, we applied two-sample Mendelian randomization (MR) to assess the effects of genetic liability to ADHD and ASD on EA. Reverse direction analyses were additionally performed. Multivariable MR was performed to estimate any effects independent of cognitive ability.MVMRIVW: -1.7 months of education per doubling of genetic liability to ADHD; 95% CI: -2.8 to -0.7), whereas genetic liability to ASD a positive effect . Reverse direction analyses suggested that genetic liability to higher EA had an effect on lower risk of ADHD, independently of cognitive ability  and increased risk of ASD , which was partly explained by cognitive ability .Genetic liability to ADHD had a negative effect on EA, independently of cognitive ability (Genetic liability to ADHD and ASD is likely to affect educational attainment, independently of underlying cognitive ability. Key MessagesThere is increasing evidence suggesting that children with attention deficit hyperactivity disorder (ADHD) are at risk of lower school performance and poor academic outcomes, and that adolescents with autism spectrum disorder (ASD) are less likely to transition to higher education compared with their typically developing peers.Additionally, cohort- and registry-based studies suggest an association between parental educational attainment and risk of ADHD and ASD in the offspring.The observational evidence seems to be in line with studies using whole-genome association findings. Specifically, genetic liability to ADHD shows negative genetic correlations and associations with educational attainment, whereas ASD presents positive associations.However, there is an absence of evidence from Mendelian randomization (MR) approaches on whether the associations are causal in nature, and on the possible contribution of cognitive ability.The present study uses a range of MR methods to assess whether there is a bidirectional causal link between genetic liability to ADHD, ASD and educational attainment and the possible role of cognitive ability.We found evidence of effects of genetic liability to ADHD on educational attainment, and evidence of effects of genetic liability to higher educational attainment on risk of ADHD which was independent of cognitive ability. Genetic liability to higher educational attainment was found to causally influence ASD in a positive direction although most of the effect was due to cognitive ability.The present study adds to the existing literature on ADHD, ASD and educational attainment by highlighting two main points: (i) the influence of genetic liability to ADHD and ASD on educational attainment, independently of cognitive ability; and (ii) the distinct contribution of genetic liability to higher educational attainment and cognitive ability on risk of ADHD and ASD.,,Attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are neurodevelopmental conditions that typically first manifest early in childhood and often persist into adulthood.,,Observational research evidence suggests that children with ADHD show lower academic performance compared with their typically developing peers,,The pattern of association of ADHD and ASD with educational outcomes is further complicated by parental educational attainment. Specifically, higher parental educational attainment has been found to be associated with increased risk of ASD in the offspring, whereas lower parental educational attainment with increased risk of ADHD.Observational evidence has been recently corroborated by studies using whole-genome approaches  summary statistics and MR to investigate the causal links between genetic liability to ADHD, ASD and educational attainment . In MR s,,,The study was conducted using publicly available GWAS summary data. Ethics declarations for each dataset used in the present study can be found in the original publications.MR allows the estimation of causal links between an exposure and an outcome by utsing common genetic variants as instruments for the exposure of interest. The robustness of the method relies on assumptions that the genetic instruments should satisfy the following: (i) there must be a robust association between the implicated genetic variants and the exposure; (ii) the variants should not be associated with any confounders of the associations between the exposure and the outcome; and (iii) the variants should operate on the outcome entirely via the exposure.We used the latest publicly available GWAS summary statistics on ADHD,P-value <= 5 x 10-8. The identified variants were clumped using an r2 <0.01, within a 10 000 kb window, based on the 1000 Genomes European phase 3 reference panel. This resulted in 11 single nucleotide polymorphisms (SNPs) for ADHD, two SNPs for ASD, 481 SNPs for educational attainment and 212 SNPs for cognitive ability.In each GWAS dataset, we extracted all variants with a P-value threshold to 5 x 10-7. After clumping, we identified 10 independent (r2 <0.01) SNPs. A similar threshold (P <= 5 x 10-6) for instrument definition has been used in previous studies.,,P-values of the instruments can be found in IJE online).In order to increase the power of the ASD analyses, we relaxed the 2 >0.9).For each analysis, instruments were extracted from the outcome GWASs. LD link online suite [LDlink: An Interactive Web Tool for Exploring Linkage Disequilibrium in Population Groups (nih.gov)]IJE online). The full process followed and the final number of instruments used for each analysis are visualized in IJE online). Two-sample MR analyses were performed using the TwoSampleMR R package.Finally, the alleles of the outcome variants were harmonized on the exposure so that the effect estimates of both exposure and outcome variants were expressed per effect allele increase. As the effect allele frequencies for the ADHD and ASD GWASs were not provided, when the harmonization of the exposure-outcome alleles was not possible, variants were excluded from the analyses as being palindromic. Detailed information on the harmonized datasets used in the present MR analyses can be found in The primary MR method used in this study was the inverse variance weighted (IVW) regression. It is a weighted generalized linear regression of the SNP-outcome coefficients on the SNP-exposure coefficients with a constrained to zero intercept term, giving an overall effect estimate of the exposure on the outcome.We assessed the strength of the instruments by calculating their F-statistic. As a rule of thumb, if the F >10, then the IVW is unlikely to suffer from weak instrument bias.IJE online).We tested for the presence of horizontal pleiotropy and assessed the robustness of the causal effect estimates using a series of sensitivity analyses, including: MR-Egger regression,Where multiple exposures are suspected to have effects on an outcome, and the exposures are genetically and phenotypically correlated, univariable MR can yield biased effect estimates.2 <0.01, 10 000 kb-window) instruments for cognitive ability were added to the models. The full list of primary exposure instruments and cognitive ability instruments was clumped (r2 = 0.01), to ensure the absence of LD among the included SNPs, and then harmonized. The process followed and the number of instruments used in the MVMR analyses are visualized in IJE online. We performed an inverse variance weighted (IVW) regression of the SNP-outcome coefficients on the SNP-exposure coefficients, entering the two exposures in the regression model simultaneously. Details on the effect sizes, standard errors and P-values of the cognitive ability instruments used can be found in For each MVMR analysis, 212 genome-wide significant and independent   .Pval = 0.41). Steiger filtering suggested that the direction of the effect was correct for all the ADHD instruments. IJE online) shows the effect estimates, standard errors and P-values derived from the primary and sensitivity analyses.The effect estimates were directionally consistent across the sensitivity analyses performed. There was limited evidence of horizontal pleiotropy in the analyses, as suggested by the MR-Egger intercept  . IJE online) contains the direct effect estimates of genetic liability to ADHD and cognitive ability on educational attainment, and the robust to weak instruments direct effect estimates and corresponding confidence intervals, as well as the conditional F statistics of the instruments.For the MVMR, the direct effect of genetic liability to ADHD on educational attainment (i.e. not via cognitive ability) was approximately 50% smaller than the total effect ( x 10-4) . There wMRIVW: 3 days, per doubling of genetic liability to ASD; 95% CI: -2.1 months to 2.4 months; Pval = 0.9)  (IJE online) contains detailed information on the effect estimates, standard errors and P-values across primary and sensitivity analyses.For the univariable MR, the F statistic of the ASD instruments ranged from 26 to 36. There was little evidence of an effect of genetic liability to ASD on educational attainment (l = 0.9) . The con = 0.42) . SteigerMVMRIVW: 1 month per doubling of genetic liability to ASD; 95% CI: 3 days to 1.7 months; Pval = 0.03) . The direct effect estimates of genetic liability to ASD and cognitive ability on educational attainment and the robust to weak instruments direct effect estimates and corresponding confidence intervals, , the conditional F statistics of the instruments, can be found in IJE online).When including cognitive ability in the MVMR models, there was some evidence suggesting that a doubling in the genetic liability to ASD had a small positive direct effect on educational attainment, approximately 29 days ( = 0.03) . There wOR: 0.30; 95% CI: 0.26 to 0.36; Pval = 6 x 10-51) . Both MR-Egger and SIMEX-adjusted MR-Egger estimates, accounting for these pleiotropic effects, were directionally in agreement with the IVW, and the confidence intervals across the methods were largely overlapping (IJE online). Steiger filtering identified 81 instruments explaining more variation in ADHD than in educational attainment. Removing those attenuated the identified effect estimate, which was still suggestive of a strong effect of genetic liability to higher educational attainment on risk of ADHD  was associated with approximately 70% lower risk of ADHD (IVWx 10-51) . There w of ADHD .OR: 0.33; 95% CI: 0.26 to 0.43; Pval = 6 x 10-17) . A direct effect was identified even after removing the instruments identified through Steiger filtering (IJE online). In the MVMR, the estimated effect of genetic liability to higher educational attainment on risk of ADHD, independent of cognitive ability, was largely comparable to the total effect (IVWx 10-17) . There wOR: 1.51 per SD increase; 95% CI: 1.29 to 1.77; Pval = 4 x 10-7) (IJE online) and there was limited evidence to indicate the presence of unbalanced horizontal pleiotropy . Steiger filtering suggested that 62 SNPs associated with educational attainment explained more variation in ASD and these were removed. The exclusion of these SNPs, despite attenuating the primary analysis effect estimate, was suggestive of an effect of genetic liability to higher educational attainment on ASD  . The estt on ASD .OR: 1.24 per SD increase; 95% CI: 0.96 to 1.6; Pval = 0.09) . After removing SNPs identified through Steiger filtering which explain more variation in the outcome, the effect estimate attenuated further, providing limited evidence of a direct effect of genetic liability to higher educational attainment on risk of ASD (IJE online). In the MVMR, the direct effect of genetic liability to higher educational attainment on risk of ASD, not mediated through cognitive ability, was smaller than the total effect (IVW = 0.09) . There wThis is the first study to investigate the bidirectional associations between genetic liability to ADHD, ASD and educational attainment and explore the possible role of cognitive ability in the identified effects using two-sample MR. Despite the genetic and phenotypic overlap of ADHD and ASD, we found distinct associations of ADHD and ASD genetic liability with educational attainment.,,We found evidence consistent with a negative effect of genetic liability to ADHD on educational attainment, which was only partly attributed to the effects of cognitive ability. This implies that it is ADHD genetic liability itself, not just cognitive ability, which causally influences lower educational attainment. This is in line with a large body of observational evidence suggesting that beyond cognitive ability, ADHD traits and disorder are associated with poor academic outcomes.,,,We also found that genetic liability to higher educational attainment, over and above cognitive ability, was associated with lower risk of ADHD. This could be explained in the context of educational attainment being associated with several socioeconomic position and lifestyle indicators.,Another possible explanation could be dynastic effects .In the case of ASD, we found little evidence suggesting a positive effect of genetic liability to ASD on educational attainment. The effect was identified only after the direct, independent of cognitive ability, effects were estimated. In order for this finding to be interpreted, the observational associations of ASD with educational attainment and cognitive ability need to be considered. Observational evidence suggests that academic performance in ASD is highly variable and dependent on several factors including cognitive ability, learning disabilities and executive functioning, as well as family socioeconomic indicators.We also identified a positive total effect of genetic liability to higher educational attainment on risk of ASD, which MVMR analyses revealed was attributed, at least partially, to the effects of cognitive ability. This is in line with a recent study using the polygenic transmission disequilibrium test (pTDT) in families of children with ASD, suggesting that parental polygenic risk for higher educational attainment is associated with autism risk in the proband, and these probands tend to inherit more alleles associated with higher cognitive ability compared with their siblings without ASD.Before reaching conclusions, it is worth considering the extent to which the identified bidirectional relationships, between genetic liability to ASD and educational attainment, reflect selection bias. Evidence from the USA, as well as the UK, seem to suggest an association between parental socioeconomic position indicators and autism diagnosis in the offspring, possibly due to better access to health care.Overall, in both ADHD and ASD findings, alternative explanations including diagnostic masking and selection bias cannot be rejected. Little is currently known on the sociodemographic, socioeconomic and educational factors that might influence ADHD and ASD diagnosis. Specifically, availability and access to health care services, family income and educational background, even perceived societal stigma, might be defining factors of which children will end up having a diagnosis and therefore being included in current GWASs.Our study benefited from using the latest and largest publicly available GWAS data on all the phenotypes of interest. We performed thorough sensitivity analyses to assess the effect of pleiotropic variants used as instruments for each phenotype. We were also able to model the effects of each exposure along with cognitive ability, so that direct and indirect effects were quantified.Pval <5 x 10-7). This might have made the ASD analyses prone to weak instrument bias, biasing the estimated effect towards the null. However, F statistic and MR Raps analyses do not support this interpretation. Second, there was sample overlap between the educational attainment and cognitive ability GWASs, as both studies included participants from UK Biobank (overlapping participants n = 195 653). This overlap represented approximately 27% of the educational attainment GWAS participants. Overlap between the exposure and outcome GWASs  can lead to bias towards the observational estimate.,One of the limitations of the study is the use of instruments for ASD below the genome-wide significance threshold  and the University of Bristol support the MRC Integrative Epidemiology Unit . The Economics and Social Research Council (ESRC) support N.M.D. via a Future Research Leaders grant [ES/N000757/1] and the Norwegian Research Council support N.M.D. via grant number 295989. This research was funded in whole, or in part, by the Wellcome Trust. C.D. is funded by the Wellcome Trust [108902/B/15/Z]. B.L. and L.R. are supported by the Wellcome Trust (grant ref: 204895/Z/16/Z) awarded to A.T., G.D.S., E.S. and K.T. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. L.D.H. is supported by a Career Development Award from the UK Medical Research Council [MR/M020894/1] and project entitled ‘social and economic value of health’, which is part of the Health Foundation’s Efficiency Research Programme (grant id: 807293). The Health Foundation is an independent charity committed to bringing about better health and health care for people in the UK. No funding body has influenced data collection, analysis or interpretation. This publication is the work of the authors, who serve as the guarantors for the contents of this paper.dyab107_Supplementary_DataClick here for additional data file.


ABSTRACT IMPACT: This study has implications for understanding early developmental mechanisms of ADHD and for guidelines regarding safe use of acetaminophen during pregnancy. OBJECTIVES/GOALS: Prenatal acetaminophen exposure has been associated with childhood attention-deficit hyperactivity disorder (ADHD), but the underlying mechanism is unknown. This prospective birth cohort study aims to identify linkages between specific metabolites in umbilical cord plasma and the association of prenatal acetaminophen exposure and ADHD. METHODS/STUDY POPULATION: The sample was a subset of the Boston Birth Cohort that included 583 mother-newborn dyads followed at Boston Medical Center from 1998 to 2018. Metabolites were measured from cord plasma collected at birth. Based on existing literature, the analyses focused on candidate metabolites involved in neuroendocrine, inflammation, and oxidative stress pathways. The outcome was physician-diagnosed ADHD between the ages of 3 and 16 years. Exploratory analyses and multiple logistic regressions were used to examine the association of these candidate metabolites with both unmetabolized cord plasma acetaminophen levels and with incident risk of ADHD, adjusting for covariates of maternal and child characteristics. RESULTS/ANTICIPATED RESULTS: Of the 583 children, 257 had ADHD and 326 had neurotypical development. Two promising results have been found thus far. 5-methoxytryptophol (5-MTX), a neuroendocrine molecule which also has antioxidant and immunomodulatory properties, was inversely associated with acetaminophen and ADHD risk. For children below the median cord 5-MTX level, the odds of ADHD were 3.29  for the third tertile of acetaminophen compared to the first tertile. This association attenuated among those above the median 5-MTX level: 2.23 , suggesting a protective effect. Tryptophan, an essential amino acid and precursor of serotonin, was positively associated with acetaminophen and ADHD. Next steps include mediation analysis with tryptophan and analyses for other metabolites. DISCUSSION/SIGNIFICANCE OF FINDINGS: This study identifies cord plasma metabolites as possible modifiers or mediators linking prenatal acetaminophen exposure and childhood ADHD, which may offer insight into a mechanistic pathway. The study findings have implications for FDA, clinical, and public health guidelines regarding safe use of acetaminophen during pregnancy.


The study evaluated the socio-demographic characteristics, obstetric variables and foeto-maternal complications associated with low birth weight (LBW) in order to provide better treatment and management options.The prospective study conducted from February, 2019 to June, 2020 recruited 312 primigravid pregnant women who reported for antenatal care in three tertiary referral hospitals in northern Ghana. Their socio-demographic, obstetric and adverse foeto-maternal outcome information were obtained with a well-structured questionnaire according to the World Health Organisation (WHO) guidelines. Participants’ blood samples were collected for haematological tests. Odds ratio  for the association between socio-demographic, obstetric characteristics, foeto-maternal complications and haematological tests in relation to LBW were assessed using logistic regression model.st visit, before and after delivery significantly increased the odds of LBW. Preterm delivery (PTD<37 weeks) , p<0.001), preeclampsia (PE) , p<0.001), blood transfusion , p = 0.003), caesarian delivery , p<0.001) and male sex neonates , P = 0.020) presented with increased odds of LBW. Increasing gestational age at delivery presented with 28% reduced odds of LBW , P = 0.023). Upon controlling for potential confounders in multivariate logistic regression, only gestational age at delivery , P = 0.030) remained significantly associated with reduced odds of LBW.This study reported a LBW prevalence of 13.5%. Increasing maternal systolic blood pressure (SBP) and diastolic blood pressure (DBP) at 1This study found that high blood pressure at 1st visit, before and after delivery results in increased chances of delivering a baby with LBW. Furthermore, PTD<37 weeks, having PE in current pregnancy, and male sex potentiate the risk of LBW. On the other hand, increasing gestational age reduces the risk of LBW. Thus, we recommend that midwives should intensify education to pregnant women on the benefits of regular ANC visits to aid in the early detection of adverse foeto-maternal complications. We also recommend proper clinical management of pregnancies associated with an elevated blood pressure at registration. Also, maternal intrapartum blood pressure measurement could be used to predict LBW in low resourced settings. Low birth weight (LBW) is defined by the World Health Organization (WHO) as weight at birth less than 2500 g (5.5 lb). LBW is a significant public health problem globally and it is associated with a range of short and long-term consequences. Overall, it is estimated that 15% to 20% of all births worldwide are LBW, representing more than 20 million births per year [In sub-Saharan Africa, risk factors such as high risk pregnancies, younger and advanced maternal age, anaemia during pregnancy as well as hypertensive disorders of pregnancy including gestational hypertension, preeclampsia (PE), eclampsia and poor nutritional status of mother are widely reported to be associated with LBW , 4. ProgIn 2013, 16.5% of the 11,647 neonates born in the major tertiary referral hospital in Ghana  had LBW . AdditioSeveral studies evaluating factors associated with LBW have been conducted in some African countries –15. HoweTable 1 shows the antenatal and delivery information for the three study sites for the year 2019.The study was conducted in three major referral (tertiary) hospitals in northern Ghana. The hospitals were the Tamale Teaching Hospital (TTH) in Tamale (Northern Region), the Bolgatanga Regional Hospital (RHB) in Bolgatanga (Upper East Region) and the Bawku Presbyterian Hospital (BPH) in Bawku (Upper East Region). n = z2pq/d2; where n = minimum sample size, z = confidence limit at 95% = 1.96, p = prevalence of LBW = 0.0969, q = complimentary probability = 1-p, d = precision = 0.05, the minimum sample size required for the study was 134 participants. In this study, 312 pregnant women were recruited. The women included did not have deliveries with birth defect, gestational diabetes, still births, had singleton gestations and did not have a history of LBW .The study was a prospective multicenter study conducted following the STROBE checklist  from FebFig 1).The obstetric characteristics evaluated were maternal age, gestational age at delivery and parity. Delivery characteristics such as mode of delivery, maternal blood pressure at booking, before delivery and after delivery were recorded. Adverse maternal outcomes were blood transfusion, labour induction, sickle cell disease (SCD) crisis, preterm delivery (PTD) <37 weeks, PE and eclampsia. Perinatal outcome indicators associated with LBW were sex of new born, birth weight and intrauterine growth retardation (IUGR) .Adhering to WHO standard procedure, a hospital grade electronic weighing scale (China) of capacity 150kg weight and 70~190cm height was used to measure body weight and height respectively, as previously described . Body mast visit and glucose-6-phosphate dehydrogenase (G6PD) quantitative test. ABO and Rh blood grouping was conducted by utilizing commercially prepared monoclonal anti-A, anti-B, and anti-D antisera  according to Cheesbrough protocol [Haematological tests were performed by drawing 5ml of blood from veins located within the antecubital fossa. Assays conducted include ABO/Rh blood grouping, sickling test, haemoglobin electrophoresis, haemoglobin concentration at 1protocol . HaemoglG6PD status was determined quantitatively . Study participants were classified as: G6PD Normal if G6PD activity was ≥ 4000 mU/gHb (≥4.00 U/gHb), G6PD Partial Defect if G6PD activity was 1000 to 3999 mU/gHb (1.00–3.99 U/gHb) and G6PD full defect if G6PD activity was <1000 mU/gHb (<1.00 U/gHb) .Participant antenatal and delivery information outlining socio-demographic, obstetric characteristics and perinatal outcomes were obtained by trained interviewers (midwives) through structured questionnaires at time of study inclusion, at delivery and 48 hours postpartum.Birth weight in grams (g) was measured within 24 hours after birth and LBW was diagnosed if a neonate weighed less than 2500g .Categorical variables were presented as frequencies and percentages. Continuous data were presented as mean ± SD. Logistic regression analysis was used to evaluate the risk factors associated with LBW. To determine potential factors associated with birth weight, we first performed univariate logistic regression analysis. This was followed by multivariate logistic regression analysis using the enter method for variables with p-values <0.05 after univariate analysis to identify independent risk factors. Statistical analysis was performed using Stata version 14.2, GraphPad Prism 8 and MedCalc statistical software version 19.8. The receiver operating characteristics (ROC) curve was computed at an estimated prevalence of LBW, 9.69% and confidence interval (CI) of 95%. All tests were two-sided and p-value < 0.05 was considered statistically significant.Ethical approval for this study was obtained from the institutional review board of the Navrongo Health Research Centre of the Ghana Health Service with approval number NHRCIRB326. Written informed consent was obtained from all participants who opted to participate after the aims and objectives of the study had been explained to them. Consent for minors were obtained from the parents/guardians. Participation was voluntary, and respondents were assured that the information obtained was strictly for research and academic purposes only and were guaranteed the liberty to opt out from the study at their own convenience.Table 1.Antenatal and delivery information for the three sites for the year 2019 is represented in 2 respectively, were enrolled in the study. A higher proportion of the women enrolled in the study were of Northern ethnicity (278/312 vs. 34/312), were married (91.67%) and nulliparous (38.46%), had O positive blood group (33.94%), were of haemoglobin genotype AA (82.69%) and anaemic defined by haemoglobin level <11 g/dl at 1st ANC visit (53.85%). Majority of the participants did not deliver prematurely (96.15%), did not have PE (92.31%) and eclampsia (96.89%) in the current pregnancy. Majority of neonates had an appearance, grimace, activity and respiration (APGAR) score >7 at 1 minute (87.82%) and 5 minutes (94.23%), respectively (Table 2).A total of 312 pregnant women with average age and BMI of 27.22 ± 6.08 years old and 25.44 ± 6.79 kg/mFig 2).Among the 312 participants, the prevalence of Normal birth weight (NBW) and Low birth weight (LBW) were 86.5% (270/312) and 13.5% (42/312), respectively , p = 0.030) remained significantly associated with reduced odds of LBW (Table 3).Pregnant women with PTD <37 weeks , p<0.001), PE in current pregnancy , p<0.001), participants who had blood transfusion , p = 0.003), male sex neonates , p = 0.020) and caesarian section , p<0.001) presented with significantly higher odds of LBW. Increasing gestational age at delivery presented with 28% reduced odds of LBW , p<0.001). Additionally, a unit increase in systolic blood pressure (SBP) and diastolic blood pressure (DBP) at 1st ANC visit, and at delivery and SBP at 48 hours post-delivery presented with excellent sensitivities  and a good to moderate Area under the curve (AUC) (0.715(0.660–0.765), 0.767(0.709–0.817) and 0.671 (0.604–0.734), respectively), in predicting LBW. SBP at 1st visit had the lowest sensitivity (33.33%) but the highest specificity (90.91%) followed by SBP at delivery (78.38%). DBP at 1st visit was the least specific (45.00%) in predicting LBW .DBP at 1The prevalence of LBW in this study was 13.5%. This prevalence is not very different from previously reported prevalence from similar studies conducted in southern part of Ghana by the United Nations Children’s Fund (UNICEF) and in northern Ghana by Agoringya et al. who correspondingly reported 13.0% and 13.8% prevalence, respectively , 21. Const visit and delivery could serve as an inexpensive predictor of LBW. In contrast, Hovi et al. in Finland and Taylor et al. in Great Britain found no significant association between maternal high blood pressure and LBW [In Ghana and sub-Saharan Africa, there is paucity of data on the association between birth weight and maternal blood pressure. The blood pressure measurements presented with a good predictive power for LBW. Our finding suggests that in low resourced settings, elevation in maternal blood pressure measurements at 1 and LBW , 26. TheIn this study, PE was associated with increased odds of LBW. This finding could be due to the mechanistic relationship PE has with birth weight. An abnormally implanted placenta which predisposes a woman to PE is also implicated in hypo-perfusion culminating in hypoxia which restricts fetal growth leading to low birth weight , 28. TheFirst trimester haemoglobin concentration of pregnant women who delivered LBW babies were not significantly different from those who delivered NBW babies in this study. This is because the anaemic condition at this stage of pregnancy is often resolved with the administration of haematinics or by dietary modifications. This finding is in variance with the findings of Vanek and his colleagues in Israel who outlined an association between hypertensive disorders of pregnancy and several risk factors such as blood transfusions, labour induction, hydramnios and gestational diabetes resulting in low birth weight .We also found caesarian delivery and PTD<37 as risk factors for LBW. Our study agrees with Chen et al., who found LBW to be associated with maternal and fetal complications necessitating caesarian delivery in avoidance of intrauterine foetal demise, still birth and neonatal death at term . ChronicOur study found the male sex to be associated with higher odds of LBW. On the contrary, Tshotetsi et al., in South Africa and Ayuurebobi et al., in Ghana could not find an association between male sex and LBW , 37. SimThe study included several risk factors for LBW; socio-demographic, obstetric characteristics, haematological tests and foeto-maternal complications of pregnancy in one study. Additionally, the relationship between foeto-maternal complications of pregnancies such as PE, PTD<37 weeks, blood transfusion, caesarian deliveries and LBW were evaluated. Our study is limited due to the small sample size. Additionally, a substantial number of pregnant women who deliver in the 3 tertiary hospitals used for the study typically register for antenatal care elsewhere and are referred to tertiary hospitals to deliver when there is any suspicion of possible complications. Hence, care should be taken when interpreting the data since the results may not be generalizable to the entire populationst visit, before and after delivery results in increased chances of delivering a baby with LBW. Furthermore, PTD<37 weeks, having PE in current pregnancy, male sex and blood transfusion potentiate the risk of LBW. On the other hand, increasing gestational age reduces the risk of LBW. Thus, we recommend that midwives should intensify education to pregnant women on the benefits of regular ANC visits to aid in the early detection of adverse foeto-maternal complications. We further recommend proper clinical management of pregnancies associated with an elevated blood pressure at registration. Also, maternal intrapartum blood pressure measurement could be used to predict LBW in low resourced settings.This study found that high blood pressure at 1


The aim of the present study was to investigate the differences in ADHD symptomatology between healthy controls and children who underwent cardiac surgery at different ages.Altogether, 133 children  were examined. Patients completed the Youth Self Report (YSR), while their parents completed the Child Behaviour Checklist (CBCL) and the ADHD Rating Scale-IV.Children receiving surgery for the first time under the age of 3 years were more likely diagnosed with cyanotic type malformation and have undergone to a greater number of operations. However, ADHD symptoms of those treated surgically at or above 3 years of age were more severe than that of the control group or those who were treated surgically at a younger age. The control group and those treated surgically below the age of three did not differ across any of the ADHD symptom severity indicators.The age at the time of cardiac surgery might be associated with later ADHD symptom severity – with lower age at operation associated with better outcomes. Further, adequately powered studies are needed to confirm these exploratory findings and investigate the moderators of this relationship.The online version contains supplementary material available at 10.1186/s12888-021-03324-w. In recent years, improvements in medical treatments, non-invasive imaging, surgical techniques, as well as advances in cardiopulmonary bypass surgery and pediatric intensive care have allowed more than 90% of children born with congenital heart disease (CHD) to reach adulthood. The overall mortality of this patient population has decreased by 31% over the last 20 years .Even though the etiology of ADHD is multifactorial, several studies reported a significantly higher morbidity for this disorder among cardiac surgery patients, especially after aortic arch repairs and corrections of great artery transposition , 6. ChilStudies have shown, that adolescents with different cardiac anomalies  have a threefold inreased risk for higher psychiatric morbidity, including attention deficit and hyperactivity disorder, compared to the healthy population . ChildrePrevious studies have shown that the risk of developing ADHD in adolescence is significantly higher in cardiac surgery patients compared to healthy individuals. The symptoms may worsen by repeated exposure to anesthetics and surgery-induced stress and inflammatory responses . The litRecently, it was also suggested that single or repeated anesthesia itself could be a risk factor for the development of ADHD symptoms independently of the surgery performed , 15. StuUnfortunately, there is no clear medical protocol regarding intraoperative cerebral protection. Different neuroprotective operative management strategies, such as the use of deep hypothermic circulatory arrest, may have less influence on behavioral outcomes than had been assumed previously. Studies suggest that the prevalence of ADHD in pediatric cardiac populations remains higher than in the normal population even if operations are conducted in deep hypothermic circulatory arrest, a finding which may point to the role of non-operation-related factors in the development of ADHD . In lineTo date, studies examining the association between ADHD symptomatology and cardiac surgery in children have largely ignored the age of patients at operation and / or did not include healthy individuals as a control group. The primary aim of this study, therefore, was to investigate the potential relationship between later ADHD symptoms and the timing of first cardiac surgery in relation to the age of children . FurtheAll procedures performed in this study were in accordance with institutional guidelines and the 1964 Helsinki declaration and its later amendments. The study protocol was approved by the Hungarian Medical Research Council  and was performed upon participants and parents giving informed consent. Altogether, 133 children were examined: 54 patients with congenital heart disease undergoing first cardiac surgery under 3 years of age, 26 operated at the age of 3 or later, and 53 healthy controls. Detailed demographic data about the study groups are reported in Table n = 2), cerebral palsy (n = 3), severe hypoxic-injury during peripartum periods (n = 2), genetic syndromes (Down or DiGeorge syndrome) associated with cognitive deficits (n = 2), lack of parental or children consent (n = 1), the incapability of completing questionnaires (n = 1), premature birth (n = 2), lack of perioperative data (n = 2), and missing ADHD questionnaire data (n = 2) – resulting in a sample size of 80. In the first subgroup of patients undergoing cardiac surgery, 54 children were enrolled if having the first surgery under 3 years of age, while the second subgroup included 26 patients who received the first operation at or above 3 years of age. Patients underwent 174 operations in total: 130 operations in the subgroup operated below the age of 3 for the first time and 44 operations in the other subgroup  who underwent an ambulatory investigation in 2013 and 2014 at the same center because of accidentally detected heart murmurs but later were identified as healthy. No study participants were born with extreme low weight (< 2500 g) or had known intrauterine growth retardation either in the control or the two intervention groups. In the control group, a single patient had a formal diagnosis of ADHD and treated by psychotherapy. In the surgery subgroups, no patients were formally diagnosed with ADHD. No participants of the study received pharmacotherapy for ADHD symptoms.The demographic and perioperative medical data were retrieved retrospectively from the institutional medical record. Medical variables included the length of the cardiac intensive care unit- (ICU) and overall hospital stay; length of the surgery; and length of extracorporeal circulation (ECC) needed while surgical interventions were made. Further, length of aortic cross-clamp use and the risk adjustment system for congenital heart surgery (RACHS) score were also reported. The former is a surgical instrument used during interventions without extracorporeal circulation, which separates the aorta from the outflow deriving from the heart excluding it from the systemic circulation, while the latter refers to the complexity of the operation  .AD and YSRAD) was used in the present study. Internal consistency for scores on the CBCLAD was good , while that of scores on the YSRAD was suboptimal but acceptable  in the present sample. In both cases, higher scores indicate more severe ADHD symptomatology. Diagnostic cut off scores for the CBCLAD were used considering T scores of 65 (94th percentile) based on gender- and age specific norms [The Hungarian version –24 of thic norms . Using tTOT), the 18-item ADHD Rating Scale–IV [IA) and hyperactivity-impulsivity (ADHD RSHI) symptoms. This assessment tool is appropriate for use regarding children aged 4–20. In this study, the ‘home version’ of the instrument was used as parents were the raters (in contrast to the ‘school version’ where teachers report on the children), who characterized their child’s behavior considering the 6 months prior to assessment. Internal consistency in the present sample was very high both for the two subscales  and the total  scores. Higher scores indicate more severe symptomatology in this case as well. To provide an approximate prevalence of ADHD in the sample (Table TOT were used corresponding to T scores of 64.5 (93th percentile) based on gender- and age specific norms [Beyond the total score . On the univariate level, chi square tests , F-tests , and t-tests  were used to compare participants across surgery status .AD, CBCLAD, ADHD RSIA, ADHD RSHI, ADHD RSTOT), used as separate dependent variables. In addition to the omnibus tests, post-hoc pairwise comparisons were also performed to provide a more nuanced picture of the differences among the study groups. All multivariate analyses (including the post hoc tests) were controlled for sex and age at survey completion. To estimate statistical power of the multivariate models, post hoc power analysis was also carried for the main independent variable of interest (surgery status).On the multivariate level, analysis of covariance (ANCOVA) was used to investigate the relationship between surgery status and the five indictors of ADHD symptom severity  or moderate . In terms of the prevalence of diagnosable ADHD symptom severity, those undergoing surgery later in life had higher prevalence rates than the other two subgroups. The difference did not reach statistical significance in case of the CBCLAD , while in the case of the ADHD RSTOT, the difference was statistically significant and the effect size was large  to 0.75 (YSRAD).Results of the omnibus tests from the multivariate analyses indicated that surgery status was significantly associated with most indicators of ADHD symptomatology even after controlling for sex and age at survey completion, with effect sizes in the small to medium range Table . SimilarAD Table . ObserveRegarding all ADHD symptom severity indicators, the post hoc tests indicated that the symptoms of those treated surgically at or above 3 years of age were more severe than not only the control group but also of those who were treated surgically at a younger age; and with some exceptions, these differences were statistically significant  but not with the other four ADHD symptomatology indicators .Considering the non-trivial differences in standard deviation of some ADHD indicators across study groups Table , the mulAD (p = 0.031) and the CBCLAD (p = 0.036); while non-significant for the model for ADHD RSIA (p = 0.073), ADHD RSHI (p = 0.355), and the ADHD RSTOT (p = 0.284). Considering the significant interactions, sex-stratified analyses were also conducted for scores on the YSRAD and the CBCLAD. These analyses indicated that surgery status was significantly associated with YSRAD  and CBCLAD  scores in girls but not in boys .Given the importance of sex differences in the phenomenology of ADHD, further multivariate analyses were completed (in the untrimmed data set) to test the moderator role of sex: an interaction term of sex and surgery status was added to the default models. This interaction term was significant in the model for the YSRThe worldwide prevalence of ADHD in pediatric populations is approximately 5.29% . ADHD islarger number of operations and was more frequently diagnosed with a cyanotic malformation, which suggests that factors other than cyanotic malformation or number of operations (cf. repeated anesthetic exposure) should explain the more severe ADHD symptomatology observed in the subgroup operated later in life.The aim of this study was to shed light on the long-term consequences of pediatric cardiac surgery in terms of attention-deficit and hyperactivity symptoms. To the best of our knowledge, this is the first study reporting an age-related comparison of patients with congenital heart disease undergoing cardiac surgery and a healthy population. The results indicated a significantly higher severity of attention deficit and hyperactivity symptoms in children who underwent cardiac surgery at or above the age of three compared to non-operated individuals or even children operated at a younger age, an outcome which was largely consistent across assessment tools and data providers (patient- vs. parent-report). Interestingly, the subgroup operated at a younger age underwent a A potential explanation for our findings is that repair mechanisms and neuronal plasticity in newborns and younger children are more efficient than in children of older ages. Brain development consists of a cascade of different stages composing of cell birth, cell migration, differentiation, maturation (dendrite and axon growth), synaptogenesis, cell death, synaptic pruning, and myelogenesis – all following an age-dependent pattern . Due to It is also worthy of note though that the results of the primary analyses of this study were not particularly robust: the sensitivity analyses indicated that the trends observed in the primary analyses emerge more consistently among females than males and that outliers might be responsible for a disproportionately large amount of variance. These considerations suggest that further investigations with a more explicit focus on sex differences and larger samples need to confirm the findings of this exploratory study and investigate potential moderators of the relationship between age at cardiac surgery and ADHD symptomatology.A major strength of this study was the consideration of both self- and collateral reports on the same construct (ADHD symptomatology) using multiple, parallel assessment tools. While overall the findings were homogeneous, certain differences did emerge across assessment tools , which indicates that future studies with a similar focus should carefully select which measure(s) to use considering, for instance, the goals of the study  or the statistical power intended to achieve.Limitations of this study need to be acknowledged as well. First, the sample was relatively small limiting our ability to reliably detect small differences among the study groups or conduct adequately powered sex-stratified analyses. This shortcoming of the study was also highlighted by the suboptimally low (< 0.80) post hoc power values. Further, the convenience nature of the sampling procedure limits the generalizability of the findings and reduces the strength of our hypothesis regarding neural plasticity. For example, it is possible that the subsample of those treated surgically at a younger age had a more favorable ADHD symptom profile in our study compared to those operated on later not because of more effective neural repair mechanisms but because only the most resilient individuals from the first group survived their early years  raising the possibility of selection bias.2Another sampling-related limitation of the study design was the heterogeneity of the sample, that is, congenital heart disease was conceptualized as a homogenous disease despite the quite diverse conditions this umbrella term covers. The large variability in medical procedures used to correct this diverse group of medical conditions makes it challenging to design studies with adequate sample size while focusing on a single condition or surgical procedure. Most likely not independently of this fact, the omnibus approach used in the present study is not unique and was also used in other studies investigating the psychological aspects of congenital heart diseases or their treatment , 38.Yet another limitation of the present study is that certain surgical interventions – from surgical technology to treatment guidelines for surgery and postoperative clinical management – have evolved considerably since the study period; and therefore, our findings might be less generalizable to clients receiving treatment according to these more recent protocols. Further studies following the most recent treatment guidelines and focusing on a single or smaller group of congenital heart diseases and their treatment could contribute to a more nuanced understanding of how congenital heart diseases and the surgical procedures aiming to correct them influence neurocognitive development.A further limitation of the study was the lack of access to detailed medical information on the prenatal and the peripartum periods , which could also have influenced the cognitive and behavioral development of the offspring –41. DataThe results of the present study raise the possibility that the age of children at cardiac surgery has a prognostic role in the emergence of a future attention disorder. The clinical relevance of routine ADHD screening and early diagnosis in pediatric cardiac rehabilitation could help both patients and their social environment to recognize early signs and prevent severe consequences of ADHD such as poorer school performance, social isolation, depression, or substance abuse. Our study also calls attention to the importance of the large variety of factors potentially influencing behavioral outcomes in pediatric cardiac populations , which variables should be made easily accessible to health care providers in (electronic) health records to facilitate both high-quality clinical service delivery and research.The results of the present study suggest that the negative psychological effects of pediatric cardiac surgery might not be equally salient in different ages and thus certain age groups might be more at risk to develop ADHD symptoms after cardiac surgery. This notion, on the one hand, could help better target ADHD screening, assessment, and treatment procedures in pediatric populations, while on the other hand, it raises the possibility that other cardiac-surgery-related psychological outcomes are also dependent on the timing of cardiac interventions, which possibility deserves further investigations.Additional file 1: Table S1. Diagnoses and surgical procedures in the sample, stratified by age at first operation (below vs. at or above 3 years of age).


Bartonella spp. are Gram-negative, facultative, intracellular bacteria transmitted by hematophagous insects. Several species cause zoonotic diseases such as cat-scratch disease. Bartonella henselae and Bartonella clarridgeiae are the main species found in Thailand, however, there have been few studies on Bartonella spp. In addition, the hematological evaluation of Bartonella-infected animals is limited in Thailand. The aims of this study were prevalence investigation and hematological evaluation of Bartonella-infected dogs and cats residing in Bangkok, Thailand. (2) Methods: In total, 295 dogs and 513 cats were molecularly evaluated to detect Bartonella spp. using PCR with primers targeting the partial gltA, rpoB, ftsZ, ribC, and groEL genes. In total, 651 domestic animals were evaluated for hematological parameters compared between Bartonella-positive and Bartonella-negative animals. (3) Results: Overall, the prevalence of Bartonella spp. was 1.61% which was found only in free-ranging cats (2.83%). Bartonella henselae and B. clarridgeiae were confirmed from a concatenated phylogenetic tree of partial gltA and ribC genes, with 100% bootstrapping replication. For other housekeeping gene sequences, mixed infection was expected from the amplicons of rpoB, ftsZ, and groEL. Importantly, the mean corpuscular volume (MCV) was significantly increased in Bartonella-positive cats. (4) Conclusions: We suggest that B. henselae and B. clarridgeiae are important species and are still circulating in domestic animals, especially cats. The evaluation of blood parameters, especially a raised MCV, should be of concern in Bartonella infection in asymptomatic cats. Additionally, the knowledge of how to prevent Bartonella-related diseases should be promoted with people in at-risk situations.(1) Background:  Bartonella spp. are Gram-negative, facultative, fastidious intracellular bacteria causing various pathological changes and bacteremia in their natural and accidental hosts. Several bloodsucking arthropods have been confirmed as vectors transmitting these pathogens including cat fleas  [Pulex irritans) [Pediculus humanus) [Luztomyia verrucarum) [Bartonella spp. such as the brown dog tick  [Ixodes spp. [Dermacentor spp. [Bartonella and candidatus Bartonella have been described and more than 35 species have revealed their whole genome.s felis) , human frritans) , human lhumanus) , and sanrucarum) . Additioguineus)  and the des spp.  and Dermtor spp. ). Up to B. henselae (cat-scratch disease), B. bacilliformis (Carrion’s disease and verruga peruana), and B. quintana (trench fever) [Bartonella spp. from various animal hosts, both companion and wild animals [B. henselae, which can cause an asymptomatic infection among the hosts, such as carnivores, rodents, and ruminants [Human bartonelloses are caused by h fever) . Humans  animals . Bartone animals . At leasuminants ,11,12.Bartonella spp. [Bartonella-infected animals, particularly cats and dogs, is still unclear. Several studies in other countries have evaluated the blood parameters in Bartonella-infected animals. Importantly, blood parameters are frequently used to diagnose and monitor animal health. Even if domestic cats and dogs are popular in Thailand, there has been little hematological study comparing uninfected- and infected-Bartonella animals.Dogs and cats are defined as family members sharing household environments with humans in both urban and rural areas, and they are considered as a source of zoonotic infection, especially of bartonellosis . In addilla spp.  and are lla spp. , but doglla spp. . The clilla spp. . The evaBartonella-contaminated vector feces, and blood-sucking arthropod bite [Bartonella in domestic animals in Thailand. The objectives of this study were to investigate the prevalence of Bartonella spp. in domestic dogs and cats and to evaluate the hematological parameters of Bartonella-infected dogs and cats in Bangkok, Thailand.In Thailand, dogs and cats that are both free-ranging and owned cohabit human communities. Bangkok is a province where the density of temples and household are considered high. Free-ranging animals were frequently found in temples which were a place for cultural activities and festivals, and owned animals were also found in the household. Significantly, the pattern of familiarity between humans and their belonging animals might induce zoonotic infection, particularly bartonellosis. The main proven modes of transmission in the human are animal scratch or bite with pod bite . Howevern = 513) and dogs (n = 295) residing in Bangkok, Thailand, consisting of 634 free-ranging (from temples) and 174 owned animals (from KUVTH). The ratio of males to females in the animals was 1.26:1 in the owned and 0.83:1 in the free-ranging animals. The mean ± standard deviation age of studied animals was 3.03 ± 2.01 years in the free-ranging animals (2.83 ± 1.71 years in cats and 3.29 ± 2.33 years in dogs), and in the owned animals was 3.47 ± 1.75 years (3.22 ± 1.71 years in cats and 3.58 ± 1.77 years in dogs). The numbers for related factors  are presented in In total, 808 blood samples were collected from domestic cats (Bartonella spp. in the domestic dogs and cats was 1.61% (13/808). Only domestic cats presented Bartonella DNA in extracted blood samples, however, there was an evidence only in free-ranging cats (2.83%) residing in temples  in the current study. Bartonella spp. were detected in animals residing in 10/54 (18.52%) temple clusters that were located in three zones of Bangkok (p = 0.35). Additionally, there were no significant differences for gender (p = 0.34), age group (p = 0.51), and ectoparasite infestation (p = 0.22) in the examined animals.The overall prevalence of  temples . Notably Bangkok . The posgltA-positive amplicons showed a similar direction with matched species of ribC gene results. However, rpoB, ftsZ, and groEL revealed different species (Bartonella. Amplicons of gltA and ribC matched with two species of Bartonella consisting of B. henselae (%identity = 97.01–100% of gltA and 86.62–100% of ribC) and B. clarridgeiae (%identity = 94.59–100% of gltA and 99.54–100% of ribC). Additionally, the similarity was up to 100% for rpoB, ftsZ, and groEL in all sequences, and details of sequencing data are revealed in gltA and ribC sequences showed two lineages of Bartonella that were identical to B. henselae and B. clarridgeiae, with 100% bootstrapping replication  in Bartonella-infected free-ranging cats (p < 0.05). Moreover, more than 36% of positive cats had low PCV, HGB, and MCHC. The reference of blood parameters was included in In total, 650 examined animals (80.45%) were evaluated for blood parameters. The hematological results of the examined animal population were presented in Bartonella spp. in domestic dogs and cats in Bangkok, Thailand. The results indicated that the prevalence of Bartonella in the total cat population evaluated was 2.53%, however, Bartonella spp. was observed only in free-ranging cats. The current study found two species of Bartonella (B. henselae and B. clarridgeiae) which was similar with another study in Thailand that also reported that B. henselae and B. clarridgeiae as the main species in this region [Bartonella bacteremia was found in 13 cats, however, all dogs were negative to Bartonella in this study. In cats, this positive proportion contrasted with other Bartonella prevalence reported in Brazil [Bartonella spp. in dogs was not significantly different from studies in China [Bartonella spp. were detected in cardiac tissues [Bartonella was positive only in cardiac tissue but no evidence in blood [Bartonella DNA in their blood samples. Comparisons of prevalence differences between recent and previous studies are presented in Bartonella [Bartonella than owned animals [Bartonella was the main factor causing a false negative. For the detection method, sensitivity was the impacted factor that caused the different prevalence. Moreover, the concentration of Bartonella DNA might not match with the sensitivity of the test [Bartonella detection [This study detected evidence of s region . Evidencn Brazil ,19, Green Brazil , Italy [n Brazil ,22, Germn Brazil , New Caln Brazil , USA [25n Brazil ,27,28,29n Brazil , Israel n Brazil , Portugan Brazil , France n Brazil ,34, and n Brazil , but wasn Brazil ,36, Spain Brazil , Scotlann Brazil , Irelandn Brazil , and Chiin China , Spain [in China , Cape Vein China , and Grein China , but con tissues ,43 and b tissues ,44,45,46in blood . Conversin blood  and catsin blood . This exrtonella . Strayed animals  and thesthe test  and causBartonella spp. in the current study is quite low. The low prevalence in this study was suspected to be caused by direct pathogen detection from the bacteremia level in blood samples [Bartonella spp. [Bartonella spp. detection in clinical samples, e.g., blood, other body fluids, and tissues [Bartonella diagnosis in humans and experimental cats [Bartonella spp. were quite more abundant. Due to the phylogenetic study, the longest sequence product of cPCR was more useful than the nested PCR for analysis. Additionally, the Bartonella Alphaproteobacteria growth medium (BAPGM) pre-enrichment was suggested for the specimen culture in Bartonella spp. to increase the sensitivity rate of PCR detection compared with the direct DNA extraction from pure samples [Bartonella spp. had been also co-isolated with Bartonella spp. especially environmental bacteria, non-pathogenic commensal organism, and skin normal flora [The prevalence of  samples ,50,51 anlla spp.  at the s tissues . Comparetal cats . Althoug samples . Even ifal flora ,56, and Bartonella DNA. Additionally, some studies concluded that the prevalence of Bartonella infection in stray animals was higher than in pet animals [Bartonella-positive animals. This was consistent with other studies that found no difference in prevalence based on gender, residing location, living pattern, age, and ectoparasitic appearance [Bartonella spp [Only free-ranging cats were found with  animals ,49. Howepearance . A contrella spp . We founBartonella henselae and B. clarridgeiae were the major species detected in cats [B. henselae [B. vinsonii subsp. arupensis [Bartonella infection in Thailand. Bartonella henselae was reported as the main species causing zoonotic infection, especially via cat-scratch disease. In Southeast Asia, it has been suggested that B. henselae and B. clarridgeiae are the species affecting human health and of veterinary importance [B. henselae and B. clarridgeiae are transmitted to humans via cat fleas (C. felis) [C. felis is the major vector as the pathogen-transmissible insect for feline bartonellosis [ in cats . These s in cats ,58,59,60henselae  and B. vrupensis . Of thesportance . In the . felis)  which ar. felis)  and C. fnellosis .gltA gene of Bartonella spp. for screening. Using gltA detection, this gene had a high specificity for Bartonella detection in extracted DNA samples from blood [gltA and ribC-amplified amplicons revealed a similar species of Bartonella. Additionally, other studies mentioned that positive Bartonella samples targeting the ribC gene were also positive to gltA in all samples due to the higher detection power of gltA [rpoB, ftsZ, and groEL) in the current study. This might have been due to the low discriminatory power of some genes, except for rpoB, for species differentiation in the Bartonella genus [Bartonella spp. in individual cats. From the results, it was difficult to make any conclusions regarding the mixed infection at this time. Nevertheless, co-infection should be investigated using other more sensitive techniques.The current study used primers targeting the om blood . The cur of gltA ,69,70. Hla genus . On the Bartonella-positive free-ranging cats had raised values for MCV. Over 36% of bacteremic cats had low values for HGB and MCHC. Another study in dogs mentioned that Bartonella-infected blood was significantly low in hemoglobin (HGB), erythrocytic mass (RBC), and hematocrit (HCT) [Bartonella-positive animals were significantly low in HGB, MCH, and MCHC [B. bacilliformis and were described in various ways [Bartonella-positive animals frequently showed anemia, eosinophilia, neutrophilia, and thrombocytopenia in [Bartonella-infected cats mostly showed mild or no abnormality of blood panels [Bartonella spp. were rarely described in naturally infected cats presented as healthy carriers [Bartonella in red blood cells in the replication stage [B. henselae growth and hemoglobin was a potential source of heme in vivo [Bartonella-positive cats in this study. Nevertheless, there are some limitations including the criteria for owned animals’ inclusion. A significant inclusion criterion for blood donors of studied samples that might affect Bartonella detection in owned animals required an ectoparasite control. Flea- and tick-controlled animals were possibly a chance of negative Bartonella detection. Due to the ectoparasite infestation, there was a risk factor for Bartonella infection in dogs and cats [Bartonella detection in ectoparasite was not included in this study. For further study, Bartonella spp. in animal-infesting ectoparasites should be examined to describe the dynamics of pathogen transmission.it (HCT) . The samand MCHC . The mecous ways . Bartonepenia in ,74. Addid panels . Howeverd panels . Interescarriers ,76. For on stage , and (2)on stage . In addi in vivo  which exand cats . HoweverBlood samples were collected by veterinarians and involved the gentle restraint technique. This animal research study was approved by the Kasetsart University Institutional Animal Care and Use Committee under the Ethical Review Board of the Office of National Research Council of Thailand (NRCT). All the laboratories used in this study met the standards followed by verification of the Institutional Biosafety Committee (IBC), Faculty of Veterinary Medicine, Kasetsart University .In this study, we surveyed both free-ranging and owned animals. Free-ranging animals were dogs and cats residing in temples of Bangkok. These animals were fed by animal care takers of each temple. Moreover, the ectoparasite control history of free-ranging animals was unknown. Owned animals were dogs and cats registered at the Blood Bank (BB) unit of Kasetsart University Veterinary Teaching Hospital (KUVTH) for blood donors. Owned animals lived only in the household and they roamed only in the area around their houses. The criteria for blood donors at BB of KUVTH included a limited age (1–7 years), flea and tick continue control, no blood receive history, no drug usage, and required body weight (dogs ≥ 17 kg and cats ≥ 4 kg).Bartonella spp. and the remaining volume was used for hematological evaluation.This cross-sectional study was conducted in the Bangkok metropolis of Thailand. The animal caretakers and owners of animals that resided in temples and registered with the BB at KUVTH, respectively were invited to participate in this study. Animal that had resided in temples were defined as free-ranging animals and animals that had donated blood at the BB of KUVTH were defined as owned animals. The temples that consented in this study were in three zones of Bangkok . Thirty-General data were collected for both free-ranging and owned animals including gender, living area, breed, age, and ectoparasite presentation at the surveyed time. Data of free-ranging animals were interviewed from the animal caretaker, however, data of owned animals were brought from the KUVTH record database and BB unit logbook. For ectoparasite presentation, they were examined at the time of blood collection and type of ectoparasite was recorded.TM Blood DNA Extraction Mini Kit, Favorgen Biotech Corporation, Pingtung, Taiwan) following the manufacturer’s instructions. The final volume of eluted solution (100 µL) was stored at −20 °C until the PCR-based detection.The separated blood samples were extracted for genomic DNA using commercial kits  gene . The 25 µL of PCR mixture contained 0.5 µL of dNTPs solution (0.2 mM each), 1X of Taq Reaction buffer (mixed with MgSO4), 4 pmol/µL of each primer, 0.04 U/µL of Taq DNA polymerase  Inc., Richmond, BC, Canada), 0.8% of dimethyl sulfoxide, and 3 µL of DNA template. The amplified products were kept at 4 °C until electrophoresis. Electrophoresis was conducted using agarose gel under a 0.5X TAE buffer. The process of electrophoresis was run at 100 V for 40–60 min depending on the expected amplicon size. The sample bands which were suspected as being positive for the Bartonella amplicon size were purified using a DNA purification kit , according to the manufacturer’s instructions.Conventional PCR was performed to detect tA) gene . The ampBartonella-suspected samples were amplified for other housekeeping gene fragments (rpoB), cell division protein (ftsZ), 60 kDa chaperonin (groEL), and riboflavin synthase (ribC). The amplification cycles for each housekeeping gene are shown in gltA.The ragments  consisti®, Seoul, Korea). The obtained DNA sequences were edited using the SnapGene ® Viewer software version 5.2.4  and the phylogenetic relationship was analyzed using the MEGA-X software . Concatenated sequences were used to establish a phylogenetic tree under the fitted parameter model of the maximum likelihood method with 500 bootstrapping replications. All amplicon sequences were submitted to GenBank (accession numbers MW575344–MW575394).The purified amplicons were analyzed using Sanger’s sequencing technology by a commercial company . Additionally, a manual differential count from the Diff-Quick stained blood smear was also performed in all of the samples. Common blood panels were analyzed based on the leukocyte count (WBC) and the proportions of neutrophils (NEU), lymphocytes (LYM), eosinophils (EOS), monocytes (MON), and by the numbers of basophils (BAS), the erythrocytic count (RBC), hemoglobin concentration (HGB), packed cell volume (PCV), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and platelet count (PLT).The remaining blood samples were sent to the Hematological Unit of KUVTH and to a private hematological company. All of the blood samples were analyzed using the laser flow cytometry technique by an automated hematology analyzer . There was no evidence of Bartonella in domestic dogs. Two zoonotic species were identified in this study (B. henselae and B. clarridgeiae). There was a high proportion detected in temple clusters located in the inner zone of Bangkok, however, there were no significant differences for other associated factors. The 100% bootstrapping replication of the concatenated phylogenetic tree based on the gltA and ribC genes confirmed the two species of Bartonella spp. in this study. Nevertheless, other genes  revealed different species from the same individual sample and mixed infection was expected. Bartonella-positive, free-ranging cats had raised MCV values compared to negative cats, additionally, there were low values of HGB and MCHC in over 36% of the Bartonella-positive cats. Based on these results, we suggest that zoonotic Bartonella spp., especially B. henselae and B. clarridgeiae, are important in Thailand and a prevention program, such as routine health checks of animals and humans, should be implemented. Importantly, abnormal red blood cell parameters such as a high corpuscular volume or low hemoglobin-related parameters in healthy cats should also be considered as indicators of feline subclinical bartonellosis in Thailand. Moreover, the knowledge of Bartonella-related diseases protection should be intervened in the risk person.Overall, the prevalence of