Change in vital parameters at first methylphenidate administration as a predictor of clinical response at six-months follow-up

Change in vital parameters at first methylphenidate administration as a predictor of clinical response at six-months follow-up | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Change in vital parameters at first methylphenidate administration as a predictor of clinical response at six-months follow-up Barbara D’Aiello, Deny Menghini, Giorgia Cordaro, Stefano Vicari, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6451904/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Aug, 2025 Read the published version in European Child & Adolescent Psychiatry → Version 1 posted 9 You are reading this latest preprint version Abstract ADHD is a neurodevelopmental disorder characterized by inappropriate levels of attention, hyperactivity and impulsivity affecting with social, personal and educational functioning. Structural, functional, and neurobiological abnormalities underlie ADHD symptoms and should be considered in therapeutic interventions. International guidelines recommend cognitive behavioral therapy, parent training, and pharmacological treatment, primarily methylphenidate. While methylphenidate enhances treatment efficacy, about 30% of patients show poor response, and no reliable biomarkers for treatment prediction exist. Evidence suggests that methylphenidate increases blood pressure, correlating with attentional improvements and neurobiological changes in ADHD. Blood pressure could thus serve as a low-cost, accessible predictor of methylphenidate response. The aim of this study was to explore whether a change in basic vital parameters like heart rate and blood pressure after a single methylphenidate administration can predict methylphenidate response in children and adolescents with ADHD after 6 months of drug treatment. In this context, data on vital parameters and severity of symptoms made during the first single-dose methylphenidate administration and at 6-month methylphenidate monotherapy were retrieved from patients' medical records. Our results showed that greater blood pressure increases during methylphenidate single dose administration were associated with a greater reduction in ADHD-symptoms after six-months methylphenidate treatment. Our results could help in manage the risk-benefit ratio in pharmacological treatment of ADHD, thus improving tailored-to-patients drug indications. MPH response predictors Vital parameters heart rate Blood pressure Clinical biomarkers Systolic pressure Introduction Attention-Deficit\Hyperactivity Disorder (ADHD) is a lifelong neurodevelopmental disorder with a prevalence of ~ 6–16% in children and adolescents that interferes with social, personal and educational functioning [ 1 ]. Persistent ADHD is associated with several adverse outcomes, such as scholastic underachievement, earlier/riskier sexual activity, dysfunctional interpersonal relationships, and lower overall socioeconomic status [ 2 ]. One of the most influential theories regarding the neural basis of ADHD suggests deficient inhibitory control mechanisms [ 3 ], imputed to the fronto-striatal pathway [ 4 ]. This network links the prefrontal cortex to the dorsal neo-striatum via excitatory glutaminergic cells, the basal ganglia to the dorsomedial thalamus via inhibitory projections, and the thalamus back to the prefrontal cortex via excitatory projections [ 5 ]. International guidelines [ 6 ] recommend intervening by drug treatments as first choice in case of severe or moderate symptoms, in addition to cognitive behavioral therapy and parent training, in order to ensure that people with ADHD have a comprehensive treatment that addresses psychological, behavioral and occupational/educational needs. According to the most recent evidence, methylphenidate (MPH) represents the first-choice treatment for children and adolescents with ADHD taking into account both efficacy and tolerability profile [ 7 ]. Although the specific mechanism of action is not fully defined, MPH is thought to inhibit the protein responsible for dopamine reuptake into the synaptic space, DAT-1, thereby increasing dopaminergic levels in frontotemporal, thalamic [ 8 ] and cortical regions [ 9 – 12 ]. The efficacy of MPH is supported by more than 150 randomized, controlled studies in school-age children [ 13 ]. More specifically, there is evidence that when MPH dosage was optimized the majority of patients with ADHD achieved a remission of symptoms and showed functional improvement attaining to the level of non-ADHD peers [ 12 ]. Furthermore, MPH proved effective in reducing anxiety symptoms [ 14 ], aggression [ 15 ], and suicide risk [ 16 , 17 ] in patients with ADHD. Despite the great benefits described above, about 30% of patients do not respond well to medication [ 7 ], have no long-term benefits, experience side effects and, especially in adolescence, adhere poorly to treatment. It has been shown that age, the severity of ADHD and comorbid symptoms such as conduct problems, oppositional defiant behaviors, depression and substance use can interfere with the effect of MPH [ 18 – 23 ]. However, no reliable markers of treatment response have been identified and managing the variability in treatment response still represents a big challenge. Potential predictors of MPH treatment response include neurobiological markers and correlates of neural activity observed with neuroimaging and neurophysiological techniques, but these have high costs and are not applicable to individual cases in daily clinical practice. Affordable and accessible markers to identify patients who will benefit from MPH treatment are needed. A single dose of 0.25-mg/kg MPH significantly increases heart rate (HR) and blood pressure (BP), mainly via central and peripheral adrenergic mechanisms [ 24 ]. Specifically, for HR, sBP and dBP the increases were about the same magnitude and significant for the 0.5-mg/ kg and 0.25-mg/kg MPH doses, smaller and not statistically significant for the 0.1- mg/kg, and negligible for the 0.025-mg/kg doses. Evidence shows that MPH increases HR on average by 3–10 beats/min, systolic (sBP) by 3–8 mmHg and diastolic (dBP) by 2–14 mmHg [ 25 ]. A positron emission tomography (PET) study showed that the MPH-induced increase in sBP is significantly associated with a surge in striatal dopamine [ 9 ]. In particular, subjects who did not show an increase in striatal dopamine following a high dose (0.25/0.50 mg/kg) of MPH did not show an increase in sBP either [ 24 ]. Thus, there is a potential association between a variation in sBP and MPH response, as a change in dopaminergic transmission is crucial to ADHD symptoms’ improvement driven by MPH administration. In fact, it has been shown that PET-detected increased dopamine transmission in the striatum after a single dose of MPH is associated with MPH treatment response at one-year follow-up in adults with ADHD [ 26 ]. Consistently, a recent study [ 27 ] investigated the hypothesis that changes in sBP after acute MPH administration were associated with performance change in a neuropsychological test of sustained attention in children with ADHD. Larger increases in sBP after MPH administration were associated with greater improvements in attentional performance. However, this has not been studied in association with long-term outcomes in developmental age. In this context, it could be assumed that sBP could be a low-cost and easily accessible marker to use in routinely clinical practice as a predictor of MPH response. Since HR is increased by MPH through the same mechanisms, it could represent an additional predictor. The overarching goal of the present project was to provide a scientific foundation for a rapid, low-cost method to identify MPH responders. We therefore explored, in our study, whether a change in basic vital parameters like HR and BP after a single dose MPH administration could predict MPH response in children and adolescents with ADHD after 6 months of drug therapy. For this purpose, data on vital parameters (sBP, dBP, and HR) and severity of symptoms previously collected in routine clinical practice during the first single-dose MPH administration and at 6-month MPH monotherapy were retrieved from patients' medical records. The aims were to evaluate MPH clinical efficacy (significant reduction of inattentive and impulsive/hyperactive symptomatology) at six-months follow-up and to derive highly accessible and affordable biological markers of treatment response, by testing the potential association between sBP/HR changes and MPH treatment-associated behavioral changes at six-months follow-up. Our main hypothesis was that greater sBP/HR increases during MPH single dose administration could be associated with greater reductions in ADHD-symptoms after six-month MPH treatment. Method 2.1 Participants One hundred seventy-one, consecutive, drug-naïve Italian children and adolescents with ADHD Combined Presentation (see Table 1 ), assessed and followed up at the Child and Adolescent Neuropsychiatry Unit of the Bambino Gesù Children's Hospital in Rome, received their first dose of MPH and were treated with MPH monotherapy for a duration of 6 months. The inclusion criteria for the study were as follows: (a) a primary diagnosis of ADHD according to the DSM-5 criteria, (b) the absence of neurological disorders. Only patients who consistently continued therapy throughout the mentioned 6-month period were included. After conducting neuropsychiatric and psychopathological assessment, each participant received a single dose of MPH Immediate Release (0.3 mg/kg), based on their age and weight. Vital parameters as systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate (HR) were collected before the administration, after 45’ (T1) and after 180’ minutes (T2). Moreover, the parents of participants completed the ADHD severity (SNAP-IV, [ 28 ]) questionnaires at baseline (Time 0) and after 6 month of MPH treatment (Time 1). The aim was to determine if there was a significant difference between T0 and T1 in the parameters of SNAP-IV. All participants and their parents or legal guardians were provided with information regarding the assessment instruments and treatment options. Written informed consent was obtained from the parents or legal guardians of each participant included in the study. The study was conducted in accordance with the principles outlined in the Declaration of Helsinki. Table 1 Demographic information of participants with ADHD. Characteristics Data Gender Males 148 Females 23 Age (mean ± SD) 10.54 ± 9.25 IQ (mean ± SD) 99.16 ± 18.96 Comorbid diagnosis (n) Autism Spectrum disorder Oppositional defiant disorder 11 63 Specific learning disorder 61 Anxiety disorder 25 Mood disorder 5 Language disorder Intellectual disability 15 22 2.2 Materials Psychiatric diagnoses were based on developmental history, extensive clinical examination, and a semi-structured interview, Kiddie-Sads Present and Lifetime Version Diagnostic and Statistical Manual of Mental Disorders 5 [ 29 ]. The severity of ADHD symptoms was controlled with SNAP-IV [ 28 ] a parent-report rating scale used to evaluate comorbidity with Oppositional Defiant Disorder. It consists of 26 items rated on a 4-point scale (0 = no symptoms to 3 = severe symptoms). The items are divided into three subscales: Inattention, Hyperactivity/Impulsivity, and Oppositional Behaviors. Subscale scores are calculated by taking the average. Higher scores indicate a higher number of problem symptoms. T-scores will be used for statistical analyses. Non-verbal Intelligence Quotient was assessed with the Perceptual Reasoning Index of the Wechsler Intelligence Scale for Children Fourth Edition or Colored Progressive Matrices or Standard Progressive Matrices (CPM/SPM; [ 30 , 31 ]). 2.3. Treatments and monitoring All 171 patients were drug-naïve at baseline and received monotherapy throughout the follow-up period. At baseline (T0), patients were administered a dose-test of MPH Immediate Release (0.3 mg/kg), based on their age and weight. After ten days, the starting dose of MPH was increased, with subsequent titrations of 5–10 mg given twice a day (8 am and 2 pm). The dosage adjustments were made no more frequently than every 5 days and were flexible, considering factors such as age, weight, clinical response, and side effects. Monitoring visits were conducted every three months. At the end of the 6-month period, the MPH dosage reached 0.6 mg/day. 2.4. Statistical analysis The Shapiro-Wilk test was employed to assess the normality of the data, while Levene's test was used to examine the homogeneity of variances. If applicable, Mauchly's sphericity test was conducted to confirm sphericity. Categorical data were presented as counts and proportions, whereas continuous data were reported as means and standard deviations or medians and ranges. To compare vital parameters (SBP, DBP, HR) at T0, 45’ (T1) and 180’ minutes (T2) after single dose administration, 3 different repeated measures analysis of variance (RM-ANOVA) was employed. Post hoc comparisons were conducted using Tukey's honest significance test. Effect sizes were measured using partial eta-squared (ηp2). To compare ADHD severity (SNAP-IV scores) at Time 0 and after 6 month of treatment, repeated measures analysis of variance (RM-ANOVA) was employed. Post hoc comparisons were conducted using Tukey's honest significance test. Effect sizes were measured using partial eta-squared (ηp2). Four different hierarchical linear regression model with two blocks were employed. The dependent variable were the improvement in SNAP-IV Scales after 6 months of treatment. Predictors in block 1 included age and IQ at baseline. In block 2, predictors included were Δ DBP T1-T0, Δ DBP T2-T0, Δ SBP T1-T0, Δ SBP T2-T0, Δ HR T1-T0, Δ HR T2-T0. The statistical software SPSS Version 22 (IBM Corporation, Armonk, NY, USA, 2017) was used for analyses. Results Concerning vital parameters, a RM-ANOVA on SBP demonstrated a significant Time effect (F 2,312 = 10.43, p < 0.00001, η 2 p = .06) with lower values obtained at T0 (109.02 ± 10.87) than T1 (111.51 ± 10.65, p = 0.007) and T2 (112.71 ± 10.46, p < 0.0001). The values between T1 and T2 did not differed (p = 0.31) as reported in Table 2 . RM-ANOVA on DBP demonstrated a significant Time effect (F 2,312 = 4.47, p = 0.012, η 2 p = 0.02) with lower values obtained at T0 (62.41 ± 8.39) than T2 (64.55 ± 8.08, p = 0.008). The values between T0 and T1 (63.25 ± 8.92, p = 0.46) and the values between T1 and T2 (p = 0.17) did non differed. RM-ANOVA on HR demonstrated the Time effect (F 2,310 = 15.83, p < 0.0001, η 2 p = 0.09) with lower values obtained at T0 (79.67 ± 12.60) than T1 (83.36 ± 13.72, p = 0.0001) and T2 (84.45 ± 14.51, p < 0.0001). The values between T1 and T2 did not differed (p = 0.343). Table 2 Mean and standard deviation of vital parameters at T0-T1-T2. Measures T0 Mean (SD) T1 Mean (SD) T2 Mean (SD) SBP 109.00 (10.85) 111.62 (10.67) 112.60 (10.44) DBP 62.27 (8.43) 63.39 (9.11) 64.44 (8.04) HR 79.61 (12.65) 83.83 (14.01) 84.46 (14.44) As for ADHD severity, we found that patients reduced SNAP-IV scores T1 as reported in Table 3 . The Time effect was significant (F 1,169 = 253.98, p < 0.0001, η 2 p = 0.60) with higher scores for T0 (2.32 ± 0.04) than T1 (1.50 ± 0.04). The SNAP-IV effect (F 3,507 = 27.92, p < 0.0001, η 2 p = 0.14) was significant with lower scores in Oppositional Behaviours (1.76 ± 0.04) than Inattention (2.04 ± 0.03), Hyperactivity/Impulsivity (1.86 ± 0.03) and Combined (1.96 ± 0.03). The SNAP-IV scores X Time interaction was significant (F 3,507 = 16.56, p < 0.0001, η 2 p = 0.09). Table 3 Comparisons between T0-T1 on SNAP-IV from RM-ANOVA. Measures T0 Mean (SD) T1 Mean (SD) p Inattention 2.50 (0.04) 1.59 (0.05) < 0.0001 Hyperactivity/Impulsivity 2.29 (0.05) 1.44 (0.05) < 0.0001 Combined 2.40 (0.04) 1.52 (0.04) < 0.0001 Oppositional Behaviors 2.08 (0.06) 1.44 (0.05) < 0.0001 In the forward hierarchical regression model to predict improvement in SNAP-IV Inattention, age and IQ at time 0 were entered at step 1, Δ DBP T1-T0, Δ DBP T2-T0, Δ SBP T1-T0, Δ SBP T2-T0, Δ HR T1-T0, Δ HR T2-T0were entered at step 2 as predictors. Overall, the regression model accounted for 20.6% of the variance. As reported in Table 4 – 5 , Δ SBP T1-T0 accounted for 4.2% of the unique variance (suggesting that higher changes in SBP were associated with improved inattention. No interaction effect was found between any of the predictive variables. Table 4 Hierarchical linear regression model predicting improvement in SNAP-IV Inattention after MPH administration. Model R 2 R 2 adjusted R 2 change F p 1 0.001 -0.013 0.001 0.106 0.899 2 0.042 0.22 0.041 6.013 0.015 Predictors Model 1: IQ, age Predictors Model 2: IQ, age, Δ SBP Table 5 Coefficients of Hierarchical linear regression model predicting improvement in SNAP-IV Inattention after MPH administration Standardized coefficients Model Variables B t p 1 age IQ 0.037 0.008 0.443 0.094 0.658 0.926 2 age IQ Δ SBP 0.046 0.003 0.202 0.555 0.032 2.45 0.580 0.975 0.015 In the forward hierarchical regression model to predict improvement in SNAP-IV Hyperactivity/Impulsivity, age and IQ at time 0 were entered at step 1, Δ DBP T1-T0, Δ DBP T2-T0, Δ SBP T1-T0, Δ SBP T2-T0, Δ HR T1-T0, Δ HR T2-T0were entered at step 2 as predictors. Overall, the regression model accounted for 22.7% of the variance. As reported in Table 6 – 7 , Δ DBP T1-T0 accounted for 5.2% of the unique variance (indicating that a greater increase in DBP was associated with improved hyperactivity/impulsivity symptoms). No interaction effect was found between any of the predictive variables. Table 6 Hierarchical linear regression model predicting improvement in SNAP-IV Hyperactivity/Impulsivity after MPH administration. Model R 2 R 2 adjusted R 2 change F p 1 0.001 -0.013 0.001 0.066 0.937 2 0.052 0.031 0.051 7.524 0.007 Predictors Model 1: IQ, age Predictors Model 2: IQ, age, Δ DBP Table 7 Coefficients of Hierarchical linear regression model predicting improvement in SNAP-IV Hyperactivity/Impulsivity after MPH administration Standardized coefficients Model Variables B t p 1 age IQ 0.028 0.015 0.329 0.176 0.743 0.861 2 age IQ Δ DBP 0.038 0.009 0.011 0.463 0.113 0.225 0.644 0.910 0.007 In the forward hierarchical regression model to predict improvement in SNAPIV Combined, age and IQ at time 0 were entered at step 1, Δ DBP T1-T0, Δ DBP T2-T0, Δ SBP T1-T0, Δ SBP T2-T0, Δ HR T1-T0, Δ HR T2-T0were entered at step 2 as predictors. Overall, the regression model accounted for 23.5% of the variance. As reported in Table 8 – 9 , Δ SBP T1T0 accounted for 5.5% of the unique variance (suggesting that greater changes in SBP were associated with greater improvement in symptoms). No interaction effect was found between any of the predictive variables. Table 8 Hierarchical linear regression model predicting improvement in SNAPIV Combined after MPH administration. Model R 2 R 2 adjusted R 2 change F p 1 0.001 -0.013 0.001 0.097 0.908 2 0.055 0.035 0.054 8.051 0.005 Predictors Model 1: IQ, age Predictors Model 2: IQ, age, Δ SBP Table 9 Coefficients of Hierarchical linear regression model predicting improvement in SNAPIV Combined after MPH administration Standardized coefficients Model Variables B t p 1 age IQ 0.034 0.012 0.406 0.138 0.685 0.891 2 age IQ Δ SBP 0.044 0.006 0.233 0.536 0.068 2.837 0.593 0.946 0.005 In the forward hierarchical regression model to predict improvement in SNAPIV Oppositional Behaviors, age and IQ at time 0 were entered at step 1, Δ DBP T1-T0, Δ DBP T2-T0, Δ SBP T1-T0, Δ SBP T2-T0, Δ HR T1-T0, Δ HR T2-T0were entered at step 2 as predictors. Overall, the regression model was not significant (See Table 10 – 11 ). . Table 10 Hierarchical linear regression model predicting improvement in SNAPIV Oppositional Behaviors after MPH administration. Model R 2 R 2 adjusted R 2 change F p 1 0.002 0.012 0.002 0.130 0.878 Predictors Model 1: IQ, age Table 11 Coefficients of Hierarchical linear regression model predicting improvement in Oppositional Behaviors after MPH administration Standardized coefficients Model Variables B t p 1 age IQ 0.004 0.043 0.043 0.509 0.966 0.611 Discussion In this study we examined whether variations in vital parameters during MPH first administration could serve as indicators of therapeutic efficacy. Our findings indicate a significant reduction in ADHD symptomatology after six months of continuous treatment, supporting the effectiveness of MPH as demonstrated in previous studies [ 10 , 12 ], along with a notable variation in vital parameters following MPH administration. In particular, we observed that systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) values were all significantly lower at baseline (T0) compared to the values recorded at 45 minutes (T1) and 180 minutes (T2) post drug administration. This suggests an increase in vital parameters corresponding to the absorption of MPH, confirming that the drug begins to exhibit its clinical effects within 45 minutes and maintains a therapeutic action for approximately 3–4 hours, as highlighted in earlier research [ 32 ]. Therefore, our data indicate that MPH induces an increase in BP, consistent with the well documented side effects MPH are its cardiovascular impacts [ 17 , 24 – 26 , 33 , 34 ]. Coherently, recent metanalysis [ 17 ] included 46.107 participants both children/adolescents and adults treated with MPH showing that MPH significantly increases FC and of SBP. Meta regression identified the mean dose and duration of treatment with MPH as significant moderators of heterogeneity. However, these increases remain modest and do not pose significant issues for patients taking psychostimulants. Coherently, a recent metanalysis on the therapeutic response to long-acting psychostimulants found that the most frequently reported side effects included decreased appetite (28.6%), headache (14.5%), and insomnia (12.3%), while changes in heart rate and BP were not statistically significant [ 35 ]. The mechanisms through which MPH induces a variation in BP, however, remain inadequately defined. The most plausible hypotheses include the activation of norepinephrine (NE) resulting from the inhibition of the norepinephrine transporter, and the role of dopamine (DA) both in the central nervous system and peripherally. In the central nervous system, DA acts on the ventral tegmental area and the striatum, while peripherally, it influences the adrenal glands by binding to D2 receptors, which inhibits the release of both norepinephrine and epinephrine [ 24 ](17). The DA is a peripheral vasostimulant in that adrenergic receptors also bind DA by increasing arterial smooth muscle contraction and cardiac sinoatrial node conductivity, which explains its cardiac effects. The increase in striatal DA, in turn, is foundational to these cardiovascular responses. Notably, a PET study has shown that this increase is observable at the cerebral level, associated with alterations in dopaminergic transmission within the striatum [ 26 ]. Those who did not have increased sBP did not show striatal activation. This clearly has implications for ADHD symptomatology since the reduction in symptoms is associated precisely with increased dopamine in the prefrontal cortex. In line, overall, our hierarchical regression analyses indicate that changes in systolic and diastolic blood pressure significantly predict improvements in ADHD symptoms following MPH administration. Specifically, Δ SBP was a significant predictor of inattention and combined scores, while Δ DBP was associated with hyperactivity/impulsivity improvements. No significant predictors were identified for changes in oppositional behaviors. These findings suggest a potential physiological mechanism linking cardiovascular responses to MPH efficacy in ADHD symptomatology, warranting further investigation. A recent study [ 27 ] aimed to determine whether changes in sBP following acute administration of MPH are associated with neurocognitive responses to MPH, as measured by the Conners Continuous Performance Test (CPT), in a sample of 513 children with ADHD aged 6 to 12 years. Participants received 0.25 mg/kg of MPH twice daily for one week, followed by a placebo for another week, with a randomized, counterbalanced treatment assignment. On the third day of each treatment week, participants completed the CPT twice: before and after receiving the study drug (1 hour post administration), coinciding with peak MPH blood levels. Results indicated that greater increases in sBP were associated with greater improvements in CPT performance following MPH administration. In conclusion, significant increases in sBP after MPH administration were correlated with enhanced performance on the CPT. Our study has generalized these findings, indicating that higher levels of BP following MPH administration can predict improvements in ADHD symptoms after six months of treatment. Understanding the relationship between vital parameter changes and therapeutic outcomes may enable clinicians to tailor MPH dosages more effectively. By considering individual responses in vital signs, healthcare providers can optimize treatment plans for better symptom management. Educating parents and patients about the potential cardiovascular effects of MPH, alongside its cognitive benefits, can foster informed decision making and enhance adherence to treatment. Awareness of normal BP fluctuations can help alleviate concerns regarding medication side effects. Identifying that increases in BP are generally modest and do not pose significant risks can reassure clinicians when prescribing MPH. However, it also highlights the importance of evaluating patients with preexisting cardiovascular conditions more closely. Given the study's findings of ADHD symptom reduction over six months, clinicians may feel more confident in recommending long-term MPH treatment, particularly if they monitor and manage any cardiovascular effects effectively. The need to understand the underlying mechanisms of MPH's cardiovascular effects can guide future research, leading to more targeted interventions and the development of safer medication alternatives or adjunct therapies. In conclusion, BP increase during test dose with MPH could prove to be a predictive factor for response to drug therapy and thus these findings can help improve clinical outcomes by promoting safer and more effective management strategies for children with ADHD. This study presents several limitations that must be considered when interpreting its results. Firstly, it is crucial to acknowledge that this is not a clinical trial; consequently, there was no rigorous monitoring of participants' adherence to pharmacological therapy. Secondly, the study's participant pool exhibited a lack of gender diversity, which may limit the generalizability of the findings to a broader population. Additionally, the nonblind design of the study introduces potential bias, as the participants were aware of the treatment being administered. Furthermore, there exists a risk of parent report treatment bias, wherein parents may perceive and report clinical improvements merely due to the initiation of the treatment, thereby potentially skewing the perceived effectiveness of the intervention. These limitations highlight the necessity for further research to validate and expand upon the findings of this study. Declarations Repository data: DOI 10.17605/OSF.IO/GJZ9A Conflict of Interest The authors have no financial or proprietary interests in any material discussed in this article. Institutional Review Board Statement All participants and parents were informed about assessment tools and treatment options. Written informed consent was obtained from parents. All procedures were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Ethics Committee of the Bambino Gesù Children Hospital (2541_OPBG_2021). Data were retrospectively selected and completely de-identified at the time of the study. The privacy rights of human subjects were always observed. Author Contributions Conceptualization, B.D., P.D.R., and S.V.; methodology, B.D., D.M., P.D.R. and S.V.; supervision, S.V. and P.D.R.; writing original draft, B.D., G.C., D.M., and P.D.R.; writing review and editing, B.D., P.D.R, and S.V. All authors have read and agreed to the published version of the manuscript. Funding: This work was supported by the Italian Ministry of Health with Current Research funds. 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IJERPH 15:1789 D’Aiello B, Di Vara S, De Rossi P, Pretelli I, Vicari S, Menghini D (2022) Moderators and Other Predictors of Methylphenidate Response in Children and Adolescents with ADHD. IJERPH 19:1640 De Rossi P, Pretelli I, Menghini D, D’Aiello B, Di Vara S, Vicari S (2022) Clinical characteristics of children and adolescents with ADHD with or without methylphenidate prescription at their first diagnostic assessment. Eur Arch Psychiatry Clin Neurosci [Internet]. [cited 2022 Aug 12]; Available from: https://link.springer.com/ 10.1007/s00406-022-01386-9 D’Aiello B, Battisti A, Lazzaro G, Pani P, De Rossi P, Di Vara S et al (2022) Comparing the Effect of Methylphenidate and Anodal tDCS on Inhibitory Control and Working-Memory in Children and Adolescents with Attention Deficit/Hyperactivity Disorder: A Study Protocol for a Randomized, within-Subject Trial. IJERPH 19:4575 D’Aiello B, Di Vara S, De Rossi P, Vicari S, Menghini D (2024) The effect of a single dose of methylphenidate on attention in children and adolescents with ADHD and comorbid Oppositional Defiant Disorder. De Luca V, editor. PLoS ONE. ;19:e0299449 D’Aiello B, Menghini D, Di Vara S, De Rossi P, Vicari S (2024) Predictors of Methylphenidate response in children and adolescents with ADHD: the role of sleep disturbances. Eur Arch Psychiatry Clin Neurosci [Internet]. [cited 2025 Mar 31]; Available from: https://link.springer.com/ 10.1007/s00406-024-01932-7 Vallejo-Valdivielso M, de Castro-Manglano P, Díez-Suárez A, Marín-Méndez JJ, Soutullo CA (2019) Clinical and Neuropsychological Predictors of Methylphenidate Response in Children and Adolescents with ADHD: A Naturalistic Follow-up Study in a Spanish Sample. CPEMH 15:160–171 Volkow ND, Wang G-J, Fowler JS, Molina PE, Logan J, Gatley SJ et al (2003) Cardiovascular effects of methylphenidate in humans are associated with increases of dopamine in brain and of epinephrine in plasma. Psychopharmacology 166:264–270 Fay TB, Alpert MA (2019) Cardiovascular Effects of Drugs Used to Treat Attention-Deficit/Hyperactivity Disorder: Part 1: Epidemiology, Pharmacology, and Impact on Hemodynamics and Ventricular Repolarization. Cardiol Rev 27:113–121 Volkow ND, Wang G-J, Tomasi D, Kollins SH, Wigal TL, Newcorn JH et al (2012) Methylphenidate-Elicited Dopamine Increases in Ventral Striatum Are Associated with Long-Term Symptom Improvement in Adults with Attention Deficit Hyperactivity Disorder. J Neurosci 32:841–849 Traicu A, Grizenko N, Fortier M-È, Fageera W, Sengupta SM, Joober R (2020) Acute blood pressure change with methylphenidate is associated with improvement in attention performance in children with ADHD. Prog Neuropsychopharmacol Biol Psychiatry 96:109732 Swanson J, Nolan W, Pelham WE (1981) The SNAP rating scale for the diagnosis of attention deficit disorder. Paper presented at the meeting of the American Psychological Association; Los Angeles. Aug Kaufman J, K-SADS-PL (2019) DSM-5®: intervista diagnostica per la valutazione dei disturbi psicopatologici in bambini e adolescenti. Erickson, Trento Orsini A, Pezzuti L, Picone L (2012) WISC-IV. Contributo alla taratura italiana. Giunti O.S., Firenze Raven JC, John Hugh Court (1998) Raven’s progressive matrices and vocabulary scales. Oxford Psychologists, Oxford, pp 223–237 Swanson JM, Volkow ND (2002) Pharmacokinetic and pharmacodynamic properties of stimulants: implications for the design of new treatments for ADHD. Behav Brain Res 130:73–78 Stiefel G, Besag FMC (2010) Cardiovascular Effects of Methylphenidate, Amphetamines and Atomoxetine in the Treatment of Attention-Deficit Hyperactivity Disorder. Drug Saf 33:821–842 The ADDUCE consortium, Hennissen L, Bakker MJ, Banaschewski T, Carucci S, Coghill D et al (2017) Cardiovascular Effects of Stimulant and Non-Stimulant Medication for Children and Adolescents with ADHD: A Systematic Review and Meta-Analysis of Trials of Methylphenidate, Amphetamines and Atomoxetine. CNS Drugs. ;31:199–215 Cerrillo-Urbina AJ, García-Hermoso A, Pardo-Guijarro MJ, Sánchez-López M, Santos-Gómez JL, Martínez-Vizcaíno V (2018) The Effects of Long-Acting Stimulant and Nonstimulant Medications in Children and Adolescents with Attention-Deficit/Hyperactivity Disorder: A Meta-Analysis of Randomized Controlled Trials. J Child Adolesc Psychopharmacol 28:494–507 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Aug, 2025 Read the published version in European Child & Adolescent Psychiatry → Version 1 posted Editorial decision: Revision requested 09 Jul, 2025 Reviews received at journal 09 Jul, 2025 Reviews received at journal 02 Jul, 2025 Reviewers agreed at journal 06 May, 2025 Reviewers agreed at journal 28 Apr, 2025 Reviewers invited by journal 25 Apr, 2025 Editor assigned by journal 15 Apr, 2025 Submission checks completed at journal 15 Apr, 2025 First submitted to journal 15 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6451904","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":448909721,"identity":"314814a3-83d8-48d2-bcfb-b472a2e9b0c6","order_by":0,"name":"Barbara D’Aiello","email":"","orcid":"","institution":"Bambino Gesù Children’s Hospital, IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Barbara","middleName":"","lastName":"D’Aiello","suffix":""},{"id":448909722,"identity":"2d68dbd0-9726-4c73-860a-27a2ad40ce44","order_by":1,"name":"Deny Menghini","email":"","orcid":"","institution":"Bambino Gesù Children’s Hospital, IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Deny","middleName":"","lastName":"Menghini","suffix":""},{"id":448909723,"identity":"04e4a922-9e3b-47dc-a46e-1d064b1a15f0","order_by":2,"name":"Giorgia Cordaro","email":"","orcid":"","institution":"Azienda Unità Sanitaria Locale Modena","correspondingAuthor":false,"prefix":"","firstName":"Giorgia","middleName":"","lastName":"Cordaro","suffix":""},{"id":448909726,"identity":"540c4590-b574-4e16-8c6f-186bdd16a6a3","order_by":3,"name":"Stefano Vicari","email":"","orcid":"","institution":"Università Cattolica del Sacro Cuore","correspondingAuthor":false,"prefix":"","firstName":"Stefano","middleName":"","lastName":"Vicari","suffix":""},{"id":448909729,"identity":"d601d063-db56-4f0a-9ab6-70d9ce035685","order_by":4,"name":"Pietro Rossi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYDACZgjF2ACmDGwYGCQIawGrhmlJg2kxwKcJWQvDYcJazNmZjz+uqGCQ7Zc+fPjjj4LzcubS7ReYCyr+4NRi2cyW2HjmDIPxzL60NGkeg9vGlnPOFDDPOIPbFoPDPIaNjW0MiRvO8JgxMxjcTtxwIyeBmbcNnxb+j2At+8/wGH/8YXAOquUfXlsYIbbw8BhI8BgcAGpJP8DM24BbC9AvhjMbzkgYzzjDBvJLMsgvDId5jhnj1GLOf/jBx4YKG9n+HmZgiP2xA4XYw8c8NXK4HQahJJBFgM7DqZ4BW4wZMLA/wKdjFIyCUTAKRh4AACU7Up/FE104AAAAAElFTkSuQmCC","orcid":"","institution":"Bambino Gesù Children’s Hospital, IRCCS","correspondingAuthor":true,"prefix":"","firstName":"Pietro","middleName":"","lastName":"Rossi","suffix":""}],"badges":[],"createdAt":"2025-04-15 07:08:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6451904/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6451904/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00787-025-02845-z","type":"published","date":"2025-08-29T15:57:47+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90344919,"identity":"6d11f30d-c4e5-4c6b-ba57-fac230e7fc29","added_by":"auto","created_at":"2025-09-01 16:07:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":726551,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6451904/v1/b8079763-b253-4605-b287-739b913c128a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Change in vital parameters at first methylphenidate administration as a predictor of clinical response at six-months follow-up","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAttention-Deficit\\Hyperactivity Disorder (ADHD) is a lifelong neurodevelopmental disorder with a prevalence of ~\u0026thinsp;6\u0026ndash;16% in children and adolescents that interferes with social, personal and educational functioning [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Persistent ADHD is associated with several adverse outcomes, such as scholastic underachievement, earlier/riskier sexual activity, dysfunctional interpersonal relationships, and lower overall socioeconomic status [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. One of the most influential theories regarding the neural basis of ADHD suggests deficient inhibitory control mechanisms [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], imputed to the fronto-striatal pathway [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This network links the prefrontal cortex to the dorsal neo-striatum via excitatory glutaminergic cells, the basal ganglia to the dorsomedial thalamus via inhibitory projections, and the thalamus back to the prefrontal cortex via excitatory projections [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. International guidelines [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] recommend intervening by drug treatments as first choice in case of severe or moderate symptoms, in addition to cognitive behavioral therapy and parent training, in order to ensure that people with ADHD have a comprehensive treatment that addresses psychological, behavioral and occupational/educational needs.\u003c/p\u003e \u003cp\u003eAccording to the most recent evidence, methylphenidate (MPH) represents the first-choice treatment for children and adolescents with ADHD taking into account both efficacy and tolerability profile [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Although the specific mechanism of action is not fully defined, MPH is thought to inhibit the protein responsible for dopamine reuptake into the synaptic space, DAT-1, thereby increasing dopaminergic levels in frontotemporal, thalamic [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and cortical regions [\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe efficacy of MPH is supported by more than 150 randomized, controlled studies in school-age children [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. More specifically, there is evidence that when MPH dosage was optimized the majority of patients with ADHD achieved a remission of symptoms and showed functional improvement attaining to the level of non-ADHD peers [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Furthermore, MPH proved effective in reducing anxiety symptoms [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], aggression [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], and suicide risk [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] in patients with ADHD.\u003c/p\u003e \u003cp\u003eDespite the great benefits described above, about 30% of patients do not respond well to medication [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], have no long-term benefits, experience side effects and, especially in adolescence, adhere poorly to treatment. It has been shown that age, the severity of ADHD and comorbid symptoms such as conduct problems, oppositional defiant behaviors, depression and substance use can interfere with the effect of MPH [\u003cspan additionalcitationids=\"CR19 CR20 CR21 CR22\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, no reliable markers of treatment response have been identified and managing the variability in treatment response still represents a big challenge. Potential predictors of MPH treatment response include neurobiological markers and correlates of neural activity observed with neuroimaging and neurophysiological techniques, but these have high costs and are not applicable to individual cases in daily clinical practice. Affordable and accessible markers to identify patients who will benefit from MPH treatment are needed.\u003c/p\u003e \u003cp\u003eA single dose of 0.25-mg/kg MPH significantly increases heart rate (HR) and blood pressure (BP), mainly via central and peripheral adrenergic mechanisms [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Specifically, for HR, sBP and dBP the increases were about the same magnitude and significant for the 0.5-mg/ kg and 0.25-mg/kg MPH doses, smaller and not statistically significant for the 0.1- mg/kg, and negligible for the 0.025-mg/kg doses. Evidence shows that MPH increases HR on average by 3\u0026ndash;10 beats/min, systolic (sBP) by 3\u0026ndash;8 mmHg and diastolic (dBP) by 2\u0026ndash;14 mmHg [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA positron emission tomography (PET) study showed that the MPH-induced increase in sBP is significantly associated with a surge in striatal dopamine [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In particular, subjects who did not show an increase in striatal dopamine following a high dose (0.25/0.50 mg/kg) of MPH did not show an increase in sBP either [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThus, there is a potential association between a variation in sBP and MPH response, as a change in dopaminergic transmission is crucial to ADHD symptoms\u0026rsquo; improvement driven by MPH administration.\u003c/p\u003e \u003cp\u003eIn fact, it has been shown that PET-detected increased dopamine transmission in the striatum after a single dose of MPH is associated with MPH treatment response at one-year follow-up in adults with ADHD [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsistently, a recent study [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] investigated the hypothesis that changes in sBP after acute MPH administration were associated with performance change in a neuropsychological test of sustained attention in children with ADHD. Larger increases in sBP after MPH administration were associated with greater improvements in attentional performance. However, this has not been studied in association with long-term outcomes in developmental age.\u003c/p\u003e \u003cp\u003eIn this context, it could be assumed that sBP could be a low-cost and easily accessible marker to use in routinely clinical practice as a predictor of MPH response.\u003c/p\u003e \u003cp\u003eSince HR is increased by MPH through the same mechanisms, it could represent an additional predictor.\u003c/p\u003e \u003cp\u003eThe overarching goal of the present project was to provide a scientific foundation for a rapid, low-cost method to identify MPH responders.\u003c/p\u003e \u003cp\u003eWe therefore explored, in our study, whether a change in basic vital parameters like HR and BP after a single dose MPH administration could predict MPH response in children and adolescents with ADHD after 6 months of drug therapy. For this purpose, data on vital parameters (sBP, dBP, and HR) and severity of symptoms previously collected in routine clinical practice during the first single-dose MPH administration and at 6-month MPH monotherapy were retrieved from patients' medical records.\u003c/p\u003e \u003cp\u003eThe aims were to evaluate MPH clinical efficacy (significant reduction of inattentive and impulsive/hyperactive symptomatology) at six-months follow-up and to derive highly accessible and affordable biological markers of treatment response, by testing the potential association between sBP/HR changes and MPH treatment-associated behavioral changes at six-months follow-up. Our main hypothesis was that greater sBP/HR increases during MPH single dose administration could be associated with greater reductions in ADHD-symptoms after six-month MPH treatment.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Participants\u003c/h2\u003e \u003cp\u003eOne hundred seventy-one, consecutive, drug-na\u0026iuml;ve Italian children and adolescents with ADHD Combined Presentation (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), assessed and followed up at the Child and Adolescent Neuropsychiatry Unit of the Bambino Ges\u0026ugrave; Children's Hospital in Rome, received their first dose of MPH and were treated with MPH monotherapy for a duration of 6 months. The inclusion criteria for the study were as follows: (a) a primary diagnosis of ADHD according to the DSM-5 criteria, (b) the absence of neurological disorders. Only patients who consistently continued therapy throughout the mentioned 6-month period were included.\u003c/p\u003e \u003cp\u003eAfter conducting neuropsychiatric and psychopathological assessment, each participant received a single dose of MPH Immediate Release (0.3 mg/kg), based on their age and weight. Vital parameters as systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate (HR) were collected before the administration, after 45\u0026rsquo; (T1) and after 180\u0026rsquo; minutes (T2).\u003c/p\u003e \u003cp\u003eMoreover, the parents of participants completed the ADHD severity (SNAP-IV, [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]) questionnaires at baseline (Time 0) and after 6 month of MPH treatment (Time 1). The aim was to determine if there was a significant difference between T0 and T1 in the parameters of SNAP-IV.\u003c/p\u003e \u003cp\u003e All participants and their parents or legal guardians were provided with information regarding the assessment instruments and treatment options. Written informed consent was obtained from the parents or legal guardians of each participant included in the study. The study was conducted in accordance with the principles outlined in the Declaration of Helsinki.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic information of participants with ADHD.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eData\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.54\u0026thinsp;\u0026plusmn;\u0026thinsp;9.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIQ (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99.16\u0026thinsp;\u0026plusmn;\u0026thinsp;18.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbid diagnosis (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAutism Spectrum disorder\u003c/p\u003e \u003cp\u003eOppositional defiant disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecific learning disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMood disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLanguage disorder\u003c/p\u003e \u003cp\u003eIntellectual disability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Materials\u003c/h2\u003e \u003cp\u003ePsychiatric diagnoses were based on developmental history, extensive clinical examination, and a semi-structured interview, Kiddie-Sads Present and Lifetime Version Diagnostic and Statistical Manual of Mental Disorders 5 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe severity of ADHD symptoms was controlled with SNAP-IV [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] a parent-report rating scale used to evaluate comorbidity with Oppositional Defiant Disorder. It consists of 26 items rated on a 4-point scale (0\u0026thinsp;=\u0026thinsp;no symptoms to 3\u0026thinsp;=\u0026thinsp;severe symptoms). The items are divided into three subscales: Inattention, Hyperactivity/Impulsivity, and Oppositional Behaviors. Subscale scores are calculated by taking the average. Higher scores indicate a higher number of problem symptoms. T-scores will be used for statistical analyses.\u003c/p\u003e \u003cp\u003eNon-verbal Intelligence Quotient was assessed with the Perceptual Reasoning Index of the Wechsler Intelligence Scale for Children Fourth Edition or Colored Progressive Matrices or Standard Progressive Matrices (CPM/SPM; [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Treatments and monitoring\u003c/h2\u003e \u003cp\u003eAll 171 patients were drug-na\u0026iuml;ve at baseline and received monotherapy throughout the follow-up period. At baseline (T0), patients were administered a dose-test of MPH Immediate Release (0.3 mg/kg), based on their age and weight. After ten days, the starting dose of MPH was increased, with subsequent titrations of 5\u0026ndash;10 mg given twice a day (8 am and 2 pm). The dosage adjustments were made no more frequently than every 5 days and were flexible, considering factors such as age, weight, clinical response, and side effects. Monitoring visits were conducted every three months. At the end of the 6-month period, the MPH dosage reached 0.6 mg/day.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical analysis\u003c/h2\u003e \u003cp\u003eThe Shapiro-Wilk test was employed to assess the normality of the data, while Levene's test was used to examine the homogeneity of variances. If applicable, Mauchly's sphericity test was conducted to confirm sphericity. Categorical data were presented as counts and proportions, whereas continuous data were reported as means and standard deviations or medians and ranges.\u003c/p\u003e \u003cp\u003eTo compare vital parameters (SBP, DBP, HR) at T0, 45\u0026rsquo; (T1) and 180\u0026rsquo; minutes (T2) after single dose administration, 3 different repeated measures analysis of variance (RM-ANOVA) was employed. Post hoc comparisons were conducted using Tukey's honest significance test. Effect sizes were measured using partial eta-squared (ηp2).\u003c/p\u003e \u003cp\u003eTo compare ADHD severity (SNAP-IV scores) at Time 0 and after 6 month of treatment, repeated measures analysis of variance (RM-ANOVA) was employed. Post hoc comparisons were conducted using Tukey's honest significance test. Effect sizes were measured using partial eta-squared (ηp2).\u003c/p\u003e \u003cp\u003eFour different hierarchical linear regression model with two blocks were employed. The dependent variable were the improvement in SNAP-IV Scales after 6 months of treatment. Predictors in block 1 included age and IQ at baseline. In block 2, predictors included were Δ DBP T1-T0, Δ DBP T2-T0, Δ SBP T1-T0, Δ SBP T2-T0, Δ HR T1-T0, Δ HR T2-T0.\u003c/p\u003e \u003cp\u003eThe statistical software SPSS Version 22 (IBM Corporation, Armonk, NY, USA, 2017) was used for analyses.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003cp\u003eConcerning vital parameters, a RM-ANOVA on SBP demonstrated a significant Time effect (F\u003csub\u003e2,312\u003c/sub\u003e = 10.43, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;.06) with lower values obtained at T0 (109.02\u0026thinsp;\u0026plusmn;\u0026thinsp;10.87) than T1 (111.51\u0026thinsp;\u0026plusmn;\u0026thinsp;10.65, p\u0026thinsp;=\u0026thinsp;0.007) and T2 (112.71\u0026thinsp;\u0026plusmn;\u0026thinsp;10.46, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The values between T1 and T2 did not differed (p\u0026thinsp;=\u0026thinsp;0.31) as reported in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eRM-ANOVA on DBP demonstrated a significant Time effect (F\u003csub\u003e2,312\u003c/sub\u003e = 4.47, p\u0026thinsp;=\u0026thinsp;0.012, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.02) with lower values obtained at T0 (62.41\u0026thinsp;\u0026plusmn;\u0026thinsp;8.39) than T2 (64.55\u0026thinsp;\u0026plusmn;\u0026thinsp;8.08, p\u0026thinsp;=\u0026thinsp;0.008). The values between T0 and T1 (63.25\u0026thinsp;\u0026plusmn;\u0026thinsp;8.92, p\u0026thinsp;=\u0026thinsp;0.46) and the values between T1 and T2 (p\u0026thinsp;=\u0026thinsp;0.17) did non differed.\u003c/p\u003e \u003cp\u003eRM-ANOVA on HR demonstrated the Time effect (F\u003csub\u003e2,310\u003c/sub\u003e = 15.83, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.09) with lower values obtained at T0 (79.67\u0026thinsp;\u0026plusmn;\u0026thinsp;12.60) than T1 (83.36\u0026thinsp;\u0026plusmn;\u0026thinsp;13.72, p\u0026thinsp;=\u0026thinsp;0.0001) and T2 (84.45\u0026thinsp;\u0026plusmn;\u0026thinsp;14.51, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The values between T1 and T2 did not differed (p\u0026thinsp;=\u0026thinsp;0.343).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean and standard deviation of vital parameters at T0-T1-T2.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasures\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT0 Mean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT1 Mean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT2 Mean (SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e109.00 (10.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e111.62 (10.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e112.60 (10.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62.27 (8.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63.39 (9.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64.44 (8.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e79.61 (12.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83.83 (14.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e84.46 (14.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs for ADHD severity, we found that patients reduced SNAP-IV scores T1 as reported in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The Time effect was significant (F\u003csub\u003e1,169\u003c/sub\u003e = 253.98, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.60) with higher scores for T0 (2.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04) than T1 (1.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04). The SNAP-IV effect (F\u003csub\u003e3,507\u003c/sub\u003e = 27.92, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.14) was significant with lower scores in Oppositional Behaviours (1.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04) than Inattention (2.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03), Hyperactivity/Impulsivity (1.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03) and Combined (1.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03). The SNAP-IV scores X Time interaction was significant (F\u003csub\u003e3,507\u003c/sub\u003e = 16.56, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.09).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparisons between T0-T1 on SNAP-IV from RM-ANOVA.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasures\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT0 Mean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT1 Mean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInattention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.50 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.59 (0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperactivity/Impulsivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.29 (0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.44 (0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombined\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.40 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.52 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOppositional Behaviors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.08 (0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.44 (0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the forward hierarchical regression model to predict improvement in SNAP-IV Inattention, age and IQ at time 0 were entered at step 1, Δ DBP T1-T0, Δ DBP T2-T0, Δ SBP T1-T0, Δ SBP T2-T0, Δ HR T1-T0, Δ HR T2-T0were entered at step 2 as predictors.\u003c/p\u003e \u003cp\u003eOverall, the regression model accounted for 20.6% of the variance. As reported in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Δ SBP T1-T0 accounted for 4.2% of the unique variance (suggesting that higher changes in SBP were associated with improved inattention.\u003c/p\u003e \u003cp\u003eNo interaction effect was found between any of the predictive variables.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHierarchical linear regression model predicting improvement in SNAP-IV Inattention after MPH administration.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadjusted\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003echange\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.899\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003ePredictors Model 1: IQ, age\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003ePredictors Model 2: IQ, age, Δ SBP\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCoefficients of Hierarchical linear regression model predicting improvement in SNAP-IV Inattention after MPH administration\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStandardized coefficients\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eVariables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003et\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage\u003c/p\u003e \u003cp\u003eIQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003cp\u003e0.926\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage\u003c/p\u003e \u003cp\u003eIQ\u003c/p\u003e \u003cp\u003eΔ SBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003cp\u003e0.003\u003c/p\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.555\u003c/p\u003e \u003cp\u003e0.032\u003c/p\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.580\u003c/p\u003e \u003cp\u003e0.975\u003c/p\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the forward hierarchical regression model to predict improvement in SNAP-IV Hyperactivity/Impulsivity, age and IQ at time 0 were entered at step 1, Δ DBP T1-T0, Δ DBP T2-T0, Δ SBP T1-T0, Δ SBP T2-T0, Δ HR T1-T0, Δ HR T2-T0were entered at step 2 as predictors.\u003c/p\u003e \u003cp\u003eOverall, the regression model accounted for 22.7% of the variance. As reported in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, Δ DBP T1-T0 accounted for 5.2% of the unique variance (indicating that a greater increase in DBP was associated with improved hyperactivity/impulsivity symptoms).\u003c/p\u003e \u003cp\u003eNo interaction effect was found between any of the predictive variables.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHierarchical linear regression model predicting improvement in SNAP-IV Hyperactivity/Impulsivity after MPH administration.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadjusted\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003echange\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003ePredictors Model 1: IQ, age\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003ePredictors Model 2: IQ, age, Δ DBP\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCoefficients of Hierarchical linear regression model predicting improvement in SNAP-IV Hyperactivity/Impulsivity after MPH administration\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStandardized coefficients\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eVariables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003et\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage\u003c/p\u003e \u003cp\u003eIQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.743\u003c/p\u003e \u003cp\u003e0.861\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage\u003c/p\u003e \u003cp\u003eIQ\u003c/p\u003e \u003cp\u003eΔ DBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003cp\u003e0.009\u003c/p\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.463\u003c/p\u003e \u003cp\u003e0.113\u003c/p\u003e \u003cp\u003e0.225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003cp\u003e0.910\u003c/p\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the forward hierarchical regression model to predict improvement in SNAPIV Combined, age and IQ at time 0 were entered at step 1, Δ DBP T1-T0, Δ DBP T2-T0, Δ SBP T1-T0, Δ SBP T2-T0, Δ HR T1-T0, Δ HR T2-T0were entered at step 2 as predictors.\u003c/p\u003e \u003cp\u003eOverall, the regression model accounted for 23.5% of the variance. As reported in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, Δ SBP T1T0 accounted for 5.5% of the unique variance (suggesting that greater changes in SBP were associated with greater improvement in symptoms).\u003c/p\u003e \u003cp\u003eNo interaction effect was found between any of the predictive variables.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHierarchical linear regression model predicting improvement in SNAPIV Combined after MPH administration.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadjusted\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003echange\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003ePredictors Model 1: IQ, age\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003ePredictors Model 2: IQ, age, Δ SBP\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCoefficients of Hierarchical linear regression model predicting improvement in SNAPIV Combined after MPH administration\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStandardized coefficients\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eVariables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003et\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage\u003c/p\u003e \u003cp\u003eIQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.406\u003c/p\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003cp\u003e0.891\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage\u003c/p\u003e \u003cp\u003eIQ\u003c/p\u003e \u003cp\u003eΔ SBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003cp\u003e0.006\u003c/p\u003e \u003cp\u003e0.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003cp\u003e0.068\u003c/p\u003e \u003cp\u003e2.837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003cp\u003e0.946\u003c/p\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the forward hierarchical regression model to predict improvement in SNAPIV Oppositional Behaviors, age and IQ at time 0 were entered at step 1, Δ DBP T1-T0, Δ DBP T2-T0, Δ SBP T1-T0, Δ SBP T2-T0, Δ HR T1-T0, Δ HR T2-T0were entered at step 2 as predictors.\u003c/p\u003e \u003cp\u003eOverall, the regression model was not significant (See Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHierarchical linear regression model predicting improvement in SNAPIV Oppositional Behaviors after MPH administration.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadjusted\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003echange\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003ePredictors Model 1: IQ, age\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCoefficients of Hierarchical linear regression model predicting improvement in Oppositional Behaviors after MPH administration\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStandardized coefficients\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eVariables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003et\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage\u003c/p\u003e \u003cp\u003eIQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.966\u003c/p\u003e \u003cp\u003e0.611\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eIn this study we examined whether variations in vital parameters during MPH first administration could serve as indicators of therapeutic efficacy. Our findings indicate a significant reduction in ADHD symptomatology after six months of continuous treatment, supporting the effectiveness of MPH as demonstrated in previous studies [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], along with a notable variation in vital parameters following MPH administration. In particular, we observed that systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) values were all significantly lower at baseline (T0) compared to the values recorded at 45 minutes (T1) and 180 minutes (T2) post drug administration. This suggests an increase in vital parameters corresponding to the absorption of MPH, confirming that the drug begins to exhibit its clinical effects within 45 minutes and maintains a therapeutic action for approximately 3\u0026ndash;4 hours, as highlighted in earlier research [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTherefore, our data indicate that MPH induces an increase in BP, consistent with the well documented side effects MPH are its cardiovascular impacts [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Coherently, recent metanalysis [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] included 46.107 participants both children/adolescents and adults treated with MPH showing that MPH significantly increases FC and of SBP. Meta regression identified the mean dose and duration of treatment with MPH as significant moderators of heterogeneity.\u003c/p\u003e \u003cp\u003eHowever, these increases remain modest and do not pose significant issues for patients taking psychostimulants. Coherently, a recent metanalysis on the therapeutic response to long-acting psychostimulants found that the most frequently reported side effects included decreased appetite (28.6%), headache (14.5%), and insomnia (12.3%), while changes in heart rate and BP were not statistically significant [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe mechanisms through which MPH induces a variation in BP, however, remain inadequately defined.\u003c/p\u003e \u003cp\u003eThe most plausible hypotheses include the activation of norepinephrine (NE) resulting from the inhibition of the norepinephrine transporter, and the role of dopamine (DA) both in the central nervous system and peripherally. In the central nervous system, DA acts on the ventral tegmental area and the striatum, while peripherally, it influences the adrenal glands by binding to D2 receptors, which inhibits the release of both norepinephrine and epinephrine [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e](17).\u003c/p\u003e \u003cp\u003eThe DA is a peripheral vasostimulant in that adrenergic receptors also bind DA by increasing arterial smooth muscle contraction and cardiac sinoatrial node conductivity, which explains its cardiac effects. The increase in striatal DA, in turn, is foundational to these cardiovascular responses.\u003c/p\u003e \u003cp\u003eNotably, a PET study has shown that this increase is observable at the cerebral level, associated with alterations in dopaminergic transmission within the striatum [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThose who did not have increased sBP did not show striatal activation. This clearly has implications for ADHD symptomatology since the reduction in symptoms is associated precisely with increased dopamine in the prefrontal cortex.\u003c/p\u003e \u003cp\u003eIn line, overall, our hierarchical regression analyses indicate that changes in systolic and diastolic blood pressure significantly predict improvements in ADHD symptoms following MPH administration. Specifically, Δ SBP was a significant predictor of inattention and combined scores, while Δ DBP was associated with hyperactivity/impulsivity improvements. No significant predictors were identified for changes in oppositional behaviors. These findings suggest a potential physiological mechanism linking cardiovascular responses to MPH efficacy in ADHD symptomatology, warranting further investigation.\u003c/p\u003e \u003cp\u003eA recent study [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] aimed to determine whether changes in sBP following acute administration of MPH are associated with neurocognitive responses to MPH, as measured by the Conners Continuous Performance Test (CPT), in a sample of 513 children with ADHD aged 6 to 12 years. Participants received 0.25 mg/kg of MPH twice daily for one week, followed by a placebo for another week, with a randomized, counterbalanced treatment assignment. On the third day of each treatment week, participants completed the CPT twice: before and after receiving the study drug (1 hour post administration), coinciding with peak MPH blood levels. Results indicated that greater increases in sBP were associated with greater improvements in CPT performance following MPH administration. In conclusion, significant increases in sBP after MPH administration were correlated with enhanced performance on the CPT.\u003c/p\u003e \u003cp\u003eOur study has generalized these findings, indicating that higher levels of BP following MPH administration can predict improvements in ADHD symptoms after six months of treatment.\u003c/p\u003e \u003cp\u003eUnderstanding the relationship between vital parameter changes and therapeutic outcomes may enable clinicians to tailor MPH dosages more effectively. By considering individual responses in vital signs, healthcare providers can optimize treatment plans for better symptom management. Educating parents and patients about the potential cardiovascular effects of MPH, alongside its cognitive benefits, can foster informed decision making and enhance adherence to treatment. Awareness of normal BP fluctuations can help alleviate concerns regarding medication side effects. Identifying that increases in BP are generally modest and do not pose significant risks can reassure clinicians when prescribing MPH. However, it also highlights the importance of evaluating patients with preexisting cardiovascular conditions more closely. Given the study's findings of ADHD symptom reduction over six months, clinicians may feel more confident in recommending long-term MPH treatment, particularly if they monitor and manage any cardiovascular effects effectively.\u003c/p\u003e \u003cp\u003eThe need to understand the underlying mechanisms of MPH's cardiovascular effects can guide future research, leading to more targeted interventions and the development of safer medication alternatives or adjunct therapies.\u003c/p\u003e \u003cp\u003eIn conclusion, BP increase during test dose with MPH could prove to be a predictive factor for response to drug therapy and thus these findings can help improve clinical outcomes by promoting safer and more effective management strategies for children with ADHD.\u003c/p\u003e \u003cp\u003eThis study presents several limitations that must be considered when interpreting its results. Firstly, it is crucial to acknowledge that this is not a clinical trial; consequently, there was no rigorous monitoring of participants' adherence to pharmacological therapy. Secondly, the study's participant pool exhibited a lack of gender diversity, which may limit the generalizability of the findings to a broader population. Additionally, the nonblind design of the study introduces potential bias, as the participants were aware of the treatment being administered. Furthermore, there exists a risk of parent report treatment bias, wherein parents may perceive and report clinical improvements merely due to the initiation of the treatment, thereby potentially skewing the perceived effectiveness of the intervention. These limitations highlight the necessity for further research to validate and expand upon the findings of this study.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eRepository data:\u003c/p\u003e\n\u003cp\u003eDOI 10.17605/OSF.IO/GJZ9A\u003c/p\u003e\n\u003cp\u003eConflict of Interest\u003c/p\u003e\n\u003cp\u003eThe authors have no financial or proprietary interests in any material discussed in this article.\u003c/p\u003e\n\u003cp\u003eInstitutional Review Board Statement\u003c/p\u003e\n\u003cp\u003eAll participants and parents were informed about assessment tools and treatment options. Written informed consent was obtained from parents. All procedures were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Ethics Committee of the Bambino Gesù Children Hospital (2541_OPBG_2021). Data were retrospectively selected and completely de-identified at the time of the study. The privacy rights of human subjects were always observed.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003eConceptualization, B.D., P.D.R., and S.V.; methodology, B.D., D.M., P.D.R. and S.V.; supervision, S.V. and P.D.R.; writing original draft, B.D., G.C., D.M., and P.D.R.; writing review and editing, B.D., P.D.R, and S.V.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003eFunding:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Italian Ministry of Health with Current Research funds.\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eWe would like to thank in advance all of the children and adolescents who will take part in the study and their parents.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmerican Psychiatric Association (2013) Diagnostic and Statistical Manual of Mental Disorders (5th Ed.)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarkley RA, Fischer M (2011) Predicting Impairment in Major Life Activities and Occupational Functioning in Hyperactive Children as Adults: Self-Reported Executive Function (EF) Deficits Versus EF Tests. 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Drug Saf 33:821\u0026ndash;842\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThe ADDUCE consortium, Hennissen L, Bakker MJ, Banaschewski T, Carucci S, Coghill D et al (2017) Cardiovascular Effects of Stimulant and Non-Stimulant Medication for Children and Adolescents with ADHD: A Systematic Review and Meta-Analysis of Trials of Methylphenidate, Amphetamines and Atomoxetine. CNS Drugs. ;31:199\u0026ndash;215\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCerrillo-Urbina AJ, Garc\u0026iacute;a-Hermoso A, Pardo-Guijarro MJ, S\u0026aacute;nchez-L\u0026oacute;pez M, Santos-G\u0026oacute;mez JL, Mart\u0026iacute;nez-Vizca\u0026iacute;no V (2018) The Effects of Long-Acting Stimulant and Nonstimulant Medications in Children and Adolescents with Attention-Deficit/Hyperactivity Disorder: A Meta-Analysis of Randomized Controlled Trials. J Child Adolesc Psychopharmacol 28:494\u0026ndash;507\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-child-and-adolescent-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ecap","sideBox":"Learn more about [European Child \u0026 Adolescent Psychiatry](http://link.springer.com/journal/787)","snPcode":"787","submissionUrl":"https://submission.nature.com/new-submission/787/3","title":"European Child \u0026 Adolescent Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"MPH response predictors, Vital parameters, heart rate, Blood pressure, Clinical biomarkers, Systolic pressure","lastPublishedDoi":"10.21203/rs.3.rs-6451904/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6451904/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eADHD is a neurodevelopmental disorder characterized by inappropriate levels of attention, hyperactivity and impulsivity affecting with social, personal and educational functioning. Structural, functional, and neurobiological abnormalities underlie ADHD symptoms and should be considered in therapeutic interventions. International guidelines recommend cognitive behavioral therapy, parent training, and pharmacological treatment, primarily methylphenidate. While methylphenidate enhances treatment efficacy, about 30% of patients show poor response, and no reliable biomarkers for treatment prediction exist. Evidence suggests that methylphenidate increases blood pressure, correlating with attentional improvements and neurobiological changes in ADHD. Blood pressure could thus serve as a low-cost, accessible predictor of methylphenidate response. The aim of this study was to explore whether a change in basic vital parameters like heart rate and blood pressure after a single methylphenidate administration can predict methylphenidate response in children and adolescents with ADHD after 6 months of drug treatment. In this context, data on vital parameters and severity of symptoms made during the first single-dose methylphenidate administration and at 6-month methylphenidate monotherapy were retrieved from patients' medical records. Our results showed that greater blood pressure increases during methylphenidate single dose administration were associated with a greater reduction in ADHD-symptoms after six-months methylphenidate treatment. Our results could help in manage the risk-benefit ratio in pharmacological treatment of ADHD, thus improving tailored-to-patients drug indications.\u003c/p\u003e","manuscriptTitle":"Change in vital parameters at first methylphenidate administration as a predictor of clinical response at six-months follow-up","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-29 17:11:05","doi":"10.21203/rs.3.rs-6451904/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-09T12:37:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-09T12:22:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-02T12:37:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"258577341639234282169091664744103987838","date":"2025-05-06T20:40:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"50384026432369372254108720040667956535","date":"2025-04-28T06:09:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-25T17:17:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-15T14:09:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-15T14:06:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Child \u0026 Adolescent Psychiatry","date":"2025-04-15T07:05:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-child-and-adolescent-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ecap","sideBox":"Learn more about [European Child \u0026 Adolescent Psychiatry](http://link.springer.com/journal/787)","snPcode":"787","submissionUrl":"https://submission.nature.com/new-submission/787/3","title":"European Child \u0026 Adolescent Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"2ae9ee22-85a3-4f09-9f44-e0d471bd3771","owner":[],"postedDate":"April 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-01T16:02:15+00:00","versionOfRecord":{"articleIdentity":"rs-6451904","link":"https://doi.org/10.1007/s00787-025-02845-z","journal":{"identity":"european-child-and-adolescent-psychiatry","isVorOnly":false,"title":"European Child \u0026 Adolescent Psychiatry"},"publishedOn":"2025-08-29 15:57:47","publishedOnDateReadable":"August 29th, 2025"},"versionCreatedAt":"2025-04-29 17:11:05","video":"","vorDoi":"10.1007/s00787-025-02845-z","vorDoiUrl":"https://doi.org/10.1007/s00787-025-02845-z","workflowStages":[]},"version":"v1","identity":"rs-6451904","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6451904","identity":"rs-6451904","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}