IOS has shown a highly significant association with spirometric indices and reversibility testing. It may be a substitute for spirometry in children who fail to perform forced expiratory maneuvers.

The aim of our study was to assess the diagnostic value of neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and red blood cell distribution width (RDW) in children with lymphadenopathy (LAP). METHODS: Between January, 2009 and December, 2018, 190 children who underwent excisional lymph node biopsy due to enlarged lymph nodes were included. The clinical and laboratory features of pediatric patients with lymph node enlargement, histopathological examination of the lymph node, and the role of complete blood count parameters in the differentiation of reactive and malignant LAP were analyzed retrospectively. RESULTS: In total, 139 (73.2 %) children had pathologically confi rmed reactive LAP and 51 (26.8 %) were diagnosed with lymphoma. Compared with the reactive LAP group, median values for NLR, MLR, PLR, and RDW were signifi cantly higher in children with lymphoma (p < 0.01). According to receiver operating characteristic curve analysis performed for distinguishing between reactive LAP and lymphomas, the area under curves of NLR, MLR, PLR, and RDW were 0.75, 0.76, 0.71, and 0.61, respectively. CONCLUSIONS: Children with histologically proven lymphoma have higher NLR, MLR, PLR, and RDW values than children with reactive LAP. NLR, MLR, PLR, and RDW tests, which can be performed even in primary health care centers, may be useful markers to determine which patients with LAP should be referred to the advanced center at an early stage for biopsy (Tab. 4, Fig. 2, Ref. 26).

Background Screen media exposure has been increasing in the preschool years. Risky aspects of screen exposure have many potential negative effects on children’s health. We aimed to evaluate problematic screen exposure in Turkish preschool children by using a unique tool called the “Seven-in-Seven Screen Exposure Questionnaire” and to investigate factors associated with problematic screen exposure. Methods A questionnaire form was designed including general descriptive questions in the first part. In the second part, a questionnaire we designed called the “Seven-in-Seven Screen Exposure Questionnaire” was conducted to evaluate problematic screen exposure characteristics. The questionnaire included seven items: daily screen time, viewing with parent(s), setting screen limits, screen exposure during meals and in the hour before bedtime, age of onset of screen exposure, and viewing low-quality content. The total problematic screen exposure score (range 0–13) was generated by summing scores from the seven items. Total scores are classified into two categories: low (< 7) and high (≥ 7). Logistic regression was performed to search for independent parameters associated with problematic screen exposure. Results One thousand two hundred forty-five mother-child pairs participated in this study. The median age of the children was 3.9 (IQR: 2.9–4.7) years and 51% were males. Overall, 280 children (22.5%) had a problematic screen exposure score of ≥7 (high). The median problematic screen exposure score was 4 (IQR: 3–6). Maternal age of < 30 years; paternal age of ≥30 years; maternal educational level of ≤12 years; the age of 24–48 months; home-based daycare; postponing eating, toileting, or sleeping while using a screen; and using touchscreen devices were found to be associated with an increased risk of having a high problematic screen exposure score. Conclusion Developing national scales to monitor problematic screen use in children would be more effective than monitoring screen time alone. All of the screen use characteristics not recommended in children would be evaluated using problematic screen exposure scales. The “Seven-in-Seven Screen Exposure Questionnaire” may serve as an example for further studies.

AimEarly childhood screen exposure leads to multiple adverse health events and parents have a major influence on their children's screen time. Our aim was to determine the association between maternal acceptance–rejection/control behaviours and excessive screen exposure in pre‐school children.MethodsIn this cross‐sectional descriptive study, children aged 2–5 years who had daily screen time <1 h (n = 76) and >4 h (n = 62) were enrolled. A structured survey form and Parental Acceptance–Rejection/Control Questionnaire were completed by mothers.ResultsTotal rejection scores were found to be lower in those with screen time <1 h than cases with >4 h (82.7 ± 13.2, 89.3 ± 17.2; P = 0.015). In addition, higher hostility, neglect and reverse‐affection scores were detected in excessive screen‐exposed group (P = 0.033, P = 0.003, P = 0.047, respectively). Multivariate logistic regression analyses revealed that mothers' low acceptance of their children and high neglect score were associated with excessive screen exposure after adjusting possible confounding factors. The undifferentiated rejection and control behaviours of the mothers had no association with excessive screen exposure.ConclusionChildren with excessive screen time may have a problematic relationship with their mothers. The relationship between parent and child should be examined and corrective actions should be taken.

Background and Objectives. The comparison of Positron emission tomography- computed tomography (PETCT) and bone marrow biopsy (BMB) modalities in detecting bone marrow disease is an up to date research topic. In this study, we aimed to compare the results of PET-CT and BMB procedures in detecting bone marrow involvement in pediatric malignancies. Method. At the time of diagnosis, PET-CT imaging and BMB performed patients` data were evaluated, retrospectively. Malign diagnoses were Hodgkin's lymphoma in 23 (30.7%), non-Hodgkin's lymphoma in 20 (26.7%), neuroblastoma in 11 (14.7%), Ewing sarcoma in 10 (13.7%), Langerhans cell histiocytosis in 6 (8%), and rhabdomyosarcoma in 5 (6.6%) patients. Results. Bone marrow involvement was detected in 39 (52%) of 75 patients. Bone marrow involvement was identified by both PET-CT and BMB in 18 (46.1%) patients, by only PET-CT in 12 (30.7%) patients, by only BMB in 9 (23%) patients. The sensitivity of PET-CT was 66%, specificity was 75%, positive predictive value was 60%, and negative predictive value was 80%. Sensitivity, spesificity, positive and negative predictive values of PETCT were different in before mentioned malignancy groups. Conclusion. PET-CT may not have high sensitivity and specificity to identify bone marrow involvement for each type of cancer. The approach of using bone marrow biopsy and PET-CT as complementary modalities seems reliable.

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