Four minutes registration of HRV has been shown to have intra-individual stability over 6 months in this age group (19). In conclusion, adolescent females with AD, MDD and comorbidity of AD/MDD show a decrease HRV compared with healthy controls, which is partly explained by the effect of SSRI. = 0.55, SDNN = 0.60). This was not explained by body mass index, blood pressure or physical activity. Medication with SSRI explained 15.5% of the total variance of HF, 3.0% of LF and 6.5% of SDNN. Conclusions: Adolescent female psychiatric patients with AD and/or MDD show reduced HRV compared with healthy controls. Medication with SSRI explained a part of this difference. were calculated as effect sizes using the pooled standard deviations (of 0.20 represents a small effect size, 0.50 represents a medium effect size and 0.80 represents a large effect size. The three diagnostic subgroups of the clinical sample were analysed with one-way ANOVA and compared by contrast analysis. The ANOVA was executed by the method of variance components with diagnosis and SSRI used as random factors. This method has the advantage of revealing the relative influence of diagnosis and SSRI on the residual variation, when the effects of the fixed factors have been removed. The variables HR, BMI, SBP, DBP, p-glucose and physical activity served as fixed factors. Results Sample characteristics From the original medical sample (n = 73), one subject was excluded because of pregnancy and three because of somatic disorders (diabetes and hypothyreosis). Another seven individuals were excluded as a result of 5% missing or distorted HRV data and two subjects dropped out. The final medical sample included 60 subjects, (AD n = 20, MDD n = 11, comorbidity of AD and MDD n = 29). The medical sample contained 23 individuals with anti depressant medication of which 22 experienced SRRI medication (citalopram, fluoxetin and sertralin) and one experienced a tricyclic antidepressant (tryptizol). No individuals were taking Seretonin Noradrenalin Reuptake Inhibitors. From the original control sample (n = 66) 1 subject was excluded as a result of thyrotoxicosis and twelve were excluded because of 5% missing or distorted HRV data, rendering a final control sample of 53 subjects (Fig. 2a,b). Open in a separate window Number 2 (a) Exclusion process of the medical sample. (b) Exclusion process of the nonclinical sample. Background factors such as parent unemployment or solitary parent household did not differ between the medical sample and the settings. The control sample contained a higher ratio of subjects with parents of non-Swedish source. Use of tobacco, SBP, DBP and self-reported physical activity showed no significant variations between the medical sample and the settings, but BMI was lower and p-glucose higher in the medical sample (Table 1). The difference of p-glucose between the samples was partly explained by four subjects in the medical sample with high p-glucose ( 12 mmol/L) but no decrease of HRV compared with the rest of the subjects with this sample (data not shown). Table 1 Assessment of back ground characteristics in the medical sample and in the settings thead th align=”center” rowspan=”1″ colspan=”1″ /th th align=”center” rowspan=”1″ colspan=”1″ Clinical sample n = 601 hr / /th th align=”center” rowspan=”1″ colspan=”1″ Settings n = 53 hr / /th th align=”center” rowspan=”1″ colspan=”1″ /th th align=”center” rowspan=”1″ colspan=”1″ /th th align=”remaining” rowspan=”1″ colspan=”1″ N/imply (SD) /th th align=”center” rowspan=”1″ colspan=”1″ N/imply (SD) /th th align=”center” rowspan=”1″ colspan=”1″ X2/z-value/t-value /th /thead Parents occupational status (n = 58)2Both parents used44390.96 nsAt least one parent unemployed1014Family situation (n = 56)2Living with two parents39380.06 nsLiving with sole parent1715Parents ethnical background (n = 58)2At least one parent Swedish55444.01*Both parents of foreign origin39Daily smoking of cigarettes (n = 58)2No4946Yes970.12 nsPhysical Activity Temanogrel Index (n = 58)3.113.47Z = 1.56 nsBody Mass Index (n = Temanogrel 57)20.8 (2.2)22.3(3.7)t = 2.63*p-glucose (n = 59)6.7 (2.2)5.5 (0.7)Z = ?3.41**Systolic blood pressure (n = 58)109.7 (11.6)111.4 (9.3)t = 0.85 nsDiastolic blood pressure (n = 57)68.5 (9.7)67.2 (7.5)t = ?0.76 nsBDI (n = 53)25.4 (12.0)9.2 (8.6)t = ?8.1***BAI (n = 53)22.3 (10.9)12.0 (9.0)t = ?5.5***SDQ-em (n = 53)7.2 (1.6)3.5 (2.3)Z = ?7.3*** Open in a separate window 1The medical sample consisted of 60 subjects but each subject has not delivered full data units. 2Parents occupational, family scenario, ethnicity, snuff and cigarette usage are used only to describe the representativity of the samples and are not launched as covariates in the calculations. ***t- and z-values were significant at p 0.001 **p 0.01 *p 0.05, ns = non-significant. Linear regression models applied on HF, LF and SDNN in both samples showed significant contributions from physical activity and DBP only in the non-clinical sample. BMI, p-glucose and SBP showed no contributions in any of the samples (Table 2). Table 2 Linear Regression Models showing the effect of BMI, p-glucose, SBP, DBP and physical activity on each HRV parameter (a).Another seven patients were excluded as a result of 5% missing or distorted HRV data and two subject matter dropped out. blood pressure or physical activity. Medication with SSRI explained 15.5% of the total variance of HF, 3.0% of LF and 6.5% of SDNN. Conclusions: Adolescent female psychiatric individuals with AD and/or MDD display reduced HRV compared with healthy settings. Medication with SSRI explained a part of this difference. were calculated as effect sizes using the pooled standard deviations (of 0.20 represents a small effect size, 0.50 represents a medium effect size and 0.80 represents a large effect size. The three diagnostic subgroups of the medical sample were analysed with one-way ANOVA and compared by contrast analysis. The ANOVA Temanogrel was carried out by the method of variance parts with analysis and SSRI used as random factors. This method has the advantage of exposing the relative influence of analysis and SSRI on the residual variation, when the effects of the fixed factors have been eliminated. The variables HR, BMI, SBP, DBP, p-glucose and physical activity served as fixed factors. Results Sample characteristics From the original medical sample (n = 73), one subject was excluded because of pregnancy and three because of somatic disorders (diabetes and hypothyreosis). Another seven individuals were excluded as a result of 5% missing or distorted HRV data and two subjects dropped out. The final medical sample included 60 subjects, (AD n = 20, MDD n = 11, comorbidity of AD and MDD n = 29). The medical sample contained 23 individuals with anti depressant medication of which 22 experienced SRRI medication (citalopram, fluoxetin and sertralin) and one experienced a tricyclic antidepressant (tryptizol). No individuals were taking Seretonin Noradrenalin Reuptake Inhibitors. From the original control sample (n = 66) 1 subject was excluded as a result of thyrotoxicosis and twelve were excluded because of 5% missing or distorted HRV data, rendering a final control sample of 53 subjects (Fig. 2a,b). Open in a separate window Number 2 (a) Exclusion process of the medical sample. (b) Exclusion process of the nonclinical sample. Background factors such as parent unemployment or solitary parent household did not differ between the medical sample and the settings. The control sample contained a higher ratio of subjects with parents of non-Swedish source. CDC25B Use of tobacco, SBP, DBP and self-reported physical activity showed no significant variations between the medical sample and the settings, but BMI was lower and p-glucose higher in the medical sample (Table 1). The difference of p-glucose between the samples was partly explained by four subjects in the medical Temanogrel sample with high p-glucose ( 12 mmol/L) but no decrease of HRV compared with the rest of the subjects with this sample (data not shown). Table 1 Assessment of back ground characteristics in the medical sample and in the settings thead th align=”center” rowspan=”1″ colspan=”1″ /th th align=”center” rowspan=”1″ colspan=”1″ Clinical sample n = 601 hr / /th th align=”center” rowspan=”1″ colspan=”1″ Settings n = 53 hr / /th th align=”center” rowspan=”1″ colspan=”1″ /th th align=”center” rowspan=”1″ colspan=”1″ /th th align=”remaining” rowspan=”1″ colspan=”1″ N/imply (SD) /th th align=”center” rowspan=”1″ colspan=”1″ N/imply (SD) /th th align=”center” rowspan=”1″ colspan=”1″ X2/z-value/t-value /th /thead Parents occupational status (n = 58)2Both parents used44390.96 nsAt least one parent unemployed1014Family situation (n = 56)2Living with two parents39380.06 nsLiving with sole parent1715Parents ethnical background (n = 58)2At least one parent Swedish55444.01*Both parents of foreign origin39Daily smoking of cigarettes (n = 58)2No4946Yes970.12 nsPhysical Activity Index (n = 58)3.113.47Z = 1.56 nsBody Mass Index (n = 57)20.8 (2.2)22.3(3.7)t = 2.63*p-glucose (n = 59)6.7 (2.2)5.5 (0.7)Z = ?3.41**Systolic blood circulation pressure (n = 58)109.7 (11.6)111.4 (9.3)t = 0.85 nsDiastolic blood circulation pressure (n = 57)68.5 (9.7)67.2 (7.5)t = ?0.76 nsBDI (n = 53)25.4 (12.0)9.2 (8.6)t = ?8.1***BAI (n = 53)22.3 (10.9)12.0 (9.0)t = ?5.5***SDQ-em (n = 53)7.2 (1.6)3.5 (2.3)Z = ?7.3*** Open up in another window 1The scientific sample contains 60 topics but each subject matter hasn’t delivered complete data models. 2Parents occupational, family members circumstance, ethnicity, snuff and cigarette intake are used and then explain the representativity from the examples and are not really released as covariates in the computations. ***t- and z-values had been significant at p 0.001 **p 0.01 *p 0.05, ns = nonsignificant. Temanogrel Linear regression versions used on HF, LF and SDNN in both examples showed significant efforts from exercise and DBP just in the nonclinical test. BMI, p-glucose and SBP demonstrated no contributions in virtually any from the examples (Table.