Giant angioleiomyoma of uterus masquerading as ovarian tumour: a case report

Angioleiomyoma is a rare benign tumour of uterus. We are presenting an unusual case of 45-year-old female with 11 kg giant angioleiomyoma of uterus which was masquerading as ovarian tumour on imaging. Exploratory laparotomy was done which was suggestive of huge lobulated mass arising from the uterus. Hysterectomy with bilateral salpingo-oophorectomy was done. Histopathological examination of specimen was suggestive of uterine subserosal and broad ligament angioleiomyoma of cavernous type. This case is being reported because of its rarity and challenges in diagnosis and management.

INCLEN Diagnostic Tool for Neuromotor Impairments (INDT-NMI) for Primary Care Physician: Development and Validation.

Objectives: To develop and validate a diagnostic tool for use by primary care physicians for diagnosing neuro-motor impairment among 2-9 year old children in primary care settings. Study design: Modified Delphi technique involving national (n=49) and international (n=6) experts was used for development of INDT-NMI. The tool was then validated through a cross sectional study. Setting: Neurology specialty clinics of three tertiary care pediatric centers in New Delhi, India. Participants: 454 children aged 2-9 years [mean (SD) age: 60.4 (23.7) mo], selected through systematic random sampling, underwent assessment for identification and classification of neuromotor impairments (NMI). Intervention: All study subjects were first administered INDTNMI (candidate test) by a trained physician followed by expert assessment for NMI and other neurodevelopment disorders (NDD) by team of two pediatric neurologists (Gold standard). Results: According to expert evaluation, 171 (37.8%) children had neuromotor impairments. There were four categories of subjects: NMI alone (n=66); NMI+other NDDs (n=105); Other NDDs without NMI (n=225) and ‘Normal’ group (n=58). Using expert evaluation as gold standard, overall sensitivity of the INDTNMI was 75.4% and specificity was 86.8%. INDT-NMI helped graduate physicians to correctly classify 86.6% (112/129) children with NMI into different types (cerebral palsy, neuromotor diseases and other NMI). Graduate physicians assigned 40 children (8.8%) as ‘indeterminate’, 38 (95%) of whom had either NDD and/or NMI and thus merited referral. Misclassification of NMI occurred in those with mild changes in muscle tone, dystonia, or ataxia and associated NDDs. Conclusion: Graduate primary care physicians with a structured short training can administer the new tool and diagnose NMI in 2-9 year old children with high validity. INDT-NMI requires further evaluation in actual primary care settings.

INCLEN Diagnostic Tool for Epilepsy (INDT-EPI) for Primary Care Physicians: Development and Validation.

Objective: To evaluate the diagnostic accuracy of a new diagnostic instrument for epilepsy – INCLEN Diagnostic Tool for Epilepsy (INDT-EPI) – with evaluation by expert pediatric neurologists. Study design: Evaluation of diagnostic test. Setting: Tertiary care pediatric referral centers in India. Methods: Children aged 2-9 years, enrolled by systematic random sampling at pediatric neurology out-patient clinics of three tertiary care centers were independently evaluated in a blinded manner by primary care physicians trained to administer the test, and by teams of two pediatric neurologists. Outcomes: A 13-item questionnaire administered by trained primary care physicians (candidate test) and comprehensive subject evaluation by pediatric neurologists (gold standard). Results: There were 240 children with epilepsy and 274 without epilepsy. The candidate test for epilepsy had sensitivity and specificity of 85.8% and 95.3%; positive and negative predictive values of 94.0% and 88.5%; and positive and negative likelihood ratios of 18.25 and 0.15, respectively. Conclusion: The INDT-EPI has high validity to identify children with epilepsy when used by primary care physicians.

INCLEN Diagnostic Tool for Attention Deficit Hyperactivity Disorder (INDT-ADHD): Development and Validation.

Objective: To develop and validate INCLEN Diagnostic Tool for Attention Deficit Hyperactivity Disorder (INDT-ADHD). Design: Diagnostic test evaluation by cross sectional design. Setting: Tertiary care pediatric centers. Participants: 156 children aged 65-117 months. Methods: After randomization, INDT-ADHD and Connor’s 3 Parent Rating Scale (C3PS) were administered, followed by an expert evaluation by DSM-IV-TR diagnostic criteria. Main outcome measures: Psychometric evaluation of diagnostic accuracy, validity (construct, criterion and convergent) and internal consistency. Results: INDT-ADHD had 18 items that quantified symptoms and impairment. Attention deficit hyperactivity disorder was identified in 57, 87 and 116 children by expert evaluation, INDT-ADHD and C3PS, respectively. Psychometric parameters of INDT-ADHD for differentiating attention deficit hyperactivity disorder and normal children were: sensitivity 87.7%, specificity 97.2%, positive predictive value 98.0% and negative predictive value 83.3%, whereas for differentiating from other neuro-developmental disorders were 87.7%, 42.9%, 58.1% and 79.4%, respectively. Internal consistency was 0.91. INDT-ADHD has a 4-factor structure explaining 60.4% of the variance. Convergent validity with Conner’s Parents Rating Scale was moderate (r =0.73, P= 0.001). Conclusions: INDT-ADHD is suitable for diagnosing attention deficit hyperactivity disorder in Indian children between the ages of 6 to 9 years.

INCLEN Diagnostic Tool for Autism Spectrum Disorder (INDT-ASD): Development and Validation.

Objective: To develop and validate INCLEN Diagnostic Tool for Autism Spectrum Disorder (INDT-ASD). Design: Diagnostic test evaluation by cross sectional design Setting: Four tertiary pediatric neurology centers in Delhi and Thiruvanthapuram, India. Methods: Children aged 2-9 years were enrolled in the study. INDT-ASD and Childhood Autism Rating Scale (CARS) were administered in a randomly decided sequence by trained psychologist, followed by an expert evaluation by DSM-IV TR diagnostic criteria (gold standard). Main outcome measures: Psychometric parameters of diagnostic accuracy, validity (construct, criterion and convergent) and internal consistency. Results: 154 children (110 boys, mean age 64.2 mo) were enrolled. The overall diagnostic accuracy (AUC=0.97, 95% CI 0.93, 0.99; P<0.001) and validity (sensitivity 98%, specificity 95%, positive predictive value 91%, negative predictive value 99%) of INDT-ASD for Autism spectrum disorder were high, taking expert diagnosis using DSM-IV-TR as gold standard. The concordance rate between the INDT-ASD and expert diagnosis for ‘ASD group’ was 82.52% [Cohen’s κ=0.89; 95% CI (0.82, 0.97); P=0.001]. The internal consistency of INDT-ASD was 0.96. The convergent validity with CARS (r = 0.73, P= 0.001) and divergent validity with Binet-Kamat Test of intelligence (r = -0.37; P=0.004) were significantly high. INDT-ASD has a 4-factor structure explaining 85.3% of the variance. Conclusion: INDT-ASD has high diagnostic accuracy, adequate content validity, good internal consistency high criterion validity and high to moderate convergent validity and 4-factor construct validity for diagnosis of Autistm spectrum disorder.