{"title":"Clinical and Epidemiological Characteristics and Rotavirus Vaccination Status in Children Aged Under 2 Years Hospitalized with Intussusception in Kerala, India, 2019-2022: A Multicenter Observational Study - Correspondence.","authors":"Jianghao Yu, Pengcheng Liang, Tingting Zhou, Shuangyu Chen, Lu Xu, Jinwei Li, Nannan Qin","doi":"10.1007/s12098-025-05930-y","DOIUrl":"10.1007/s12098-025-05930-y","url":null,"abstract":"","PeriodicalId":13320,"journal":{"name":"Indian Journal of Pediatrics","volume":" ","pages":"222-223"},"PeriodicalIF":2.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145849921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-08DOI: 10.1007/s12098-025-05967-z
Pavneet Kaur, Deepika Kainth, Ankit Verma, M Jeeva Sankar, Ramesh Agarwal, Ashok K Deorari, Anu Thukral
The transition of preterm infants from hospital to caregiver-based care is challenging due to unpreparedness in newborn care. Caregiver training may facilitate transition, but evidence thereof is limited. This study assessed the safety and feasibility of transitioning stable preterm neonates from the NICU to the postnatal ward after implementing a NICU-based protocolized maternal training programme. 'Stable' 28-33 wk neonates transitioned to 'ready' mothers were followed for defined outcomes, which were compared with historical unit data. The mean gestation and birth weight (n = 73) were 31 wk and 1450 g, respectively. Seventy-one neonates (97.2%, 95% CI: 89.9-99.8) were transitioned successfully, with two (2.7%) requiring NICU readmission. The weekly weight gain was 16.5 (8) g/kg/d, with a hospital stay of 25 (17-36) d, and 100% maternal 'absolute satisfaction' at discharge. The mean weight-for-age Z-score was -1.23, and the exclusive breastfeeding proportion was 57.5% at follow-up. Outcomes compared favourably with comparators, concluding that it is safe and feasible to transition stable preterm neonates.
由于新生儿护理方面的准备不足，早产儿从医院向护理人员护理的过渡具有挑战性。护理人员培训可能促进过渡，但证据有限。本研究评估了在实施基于新生儿重症监护病房的协议化孕产妇培训计划后，将稳定的早产儿从新生儿重症监护病房转移到产后病房的安全性和可行性。“稳定”28-33周的新生儿过渡到“准备好”的母亲，对确定的结果进行跟踪，并与历史单位数据进行比较。平均妊娠31周，平均出生体重1450 g （n = 73）。71例新生儿（97.2%,95% CI: 89.9-99.8）成功过渡，2例（2.7%）需要再次入住新生儿重症监护病房。每周体重增加16.5 (8)g/kg/d，住院25 (17-36)d，出院时母亲100%“绝对满意”。平均年龄体重Z-score为-1.23，纯母乳喂养比例为57.5%。结果与比较组比较有利，结论是对稳定的早产儿进行过渡是安全可行的。
{"title":"Utility of Protocolized Maternal Training for Transitioning Stable Preterm Neonates: A Prospective Cohort Study.","authors":"Pavneet Kaur, Deepika Kainth, Ankit Verma, M Jeeva Sankar, Ramesh Agarwal, Ashok K Deorari, Anu Thukral","doi":"10.1007/s12098-025-05967-z","DOIUrl":"10.1007/s12098-025-05967-z","url":null,"abstract":"<p><p>The transition of preterm infants from hospital to caregiver-based care is challenging due to unpreparedness in newborn care. Caregiver training may facilitate transition, but evidence thereof is limited. This study assessed the safety and feasibility of transitioning stable preterm neonates from the NICU to the postnatal ward after implementing a NICU-based protocolized maternal training programme. 'Stable' 28-33 wk neonates transitioned to 'ready' mothers were followed for defined outcomes, which were compared with historical unit data. The mean gestation and birth weight (n = 73) were 31 wk and 1450 g, respectively. Seventy-one neonates (97.2%, 95% CI: 89.9-99.8) were transitioned successfully, with two (2.7%) requiring NICU readmission. The weekly weight gain was 16.5 (8) g/kg/d, with a hospital stay of 25 (17-36) d, and 100% maternal 'absolute satisfaction' at discharge. The mean weight-for-age Z-score was -1.23, and the exclusive breastfeeding proportion was 57.5% at follow-up. Outcomes compared favourably with comparators, concluding that it is safe and feasible to transition stable preterm neonates.</p>","PeriodicalId":13320,"journal":{"name":"Indian Journal of Pediatrics","volume":" ","pages":"188-190"},"PeriodicalIF":2.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145933111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-10DOI: 10.1007/s12098-025-05938-4
Amitoj Singh Chhina, Neha Hiremath
{"title":"Effect of Human Milk-Based Fortifier on Weight Gain and Morbidity Among Preterm Low Birth Weight Infants.","authors":"Amitoj Singh Chhina, Neha Hiremath","doi":"10.1007/s12098-025-05938-4","DOIUrl":"10.1007/s12098-025-05938-4","url":null,"abstract":"","PeriodicalId":13320,"journal":{"name":"Indian Journal of Pediatrics","volume":" ","pages":"196"},"PeriodicalIF":2.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145943417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objectives: To determine the accuracy of Face2Gene (F2G) app in the diagnosis of a genetic syndrome as a first correct response, after uploading the image of the patient in the app (top 1 accuracy), first 3 responses (top 3 accuracy), and first 10 responses (top 10 accuracy) out of 30 differential diagnoses given by the app. Also, to determine the accuracy of the app for rare and ultra-rare diagnoses given by the app.
Methods: Frontal facial images of individuals with the diagnosis of a genetic syndrome (established clinically or molecularly) were analysed with and without additional clinical features.
Results: In this study, a total of 118 children were recruited. Overall, the molecularly confirmed eventual diagnosis appeared in the "top 10" suggested syndromes by Face2Gene in 75/118 cases, providing a diagnostic yield of 63.6%. In this study, the top 1 accuracy for correct first diagnosis by the app and clinician's first diagnosis was 45.8% (n = 54). The Mcnemar test was examined for the clinician's accurate diagnosis as compared to top 1, top 3, and top 10 accuracy by the app and the p-value was statistically significant for top 10 accuracy (0.0005) and not for the top 1 and 3 diagnoses. The top 10 accuracy for the app in the rare cases was 21/30 cases (70%), and for ultra-rare cases was 28/64 (43.8%).
Conclusions: The Face2Gene app is useful as an assistant to clinicians in the diagnosis of rare and ultra-rare diseases. The top 10 accuracy is better than clinical diagnosis, and the yield is better for the ultra-rare cases and the single gene disease category, too.
{"title":"The Utility of Face2Gene App for Syndrome Recognition in Indian Children with Dysmorphism.","authors":"Mehak Malhotra, Suvarna Magar, Madhavi Shelke, Varsha Vaidya, Sandip Saraf, Ashka Prajapati, Udhaya Kotecha, Pratibha Pawal, Tushar Idhate, Avinash Sangle, Ghansham Magar, Anjali Kale, Gunjan Gandhi, Madhuri Engade, Saeed Siddique, Sachin Khambayate, Karthik Akunuri","doi":"10.1007/s12098-026-05992-6","DOIUrl":"https://doi.org/10.1007/s12098-026-05992-6","url":null,"abstract":"<p><strong>Objectives: </strong>To determine the accuracy of Face2Gene (F2G) app in the diagnosis of a genetic syndrome as a first correct response, after uploading the image of the patient in the app (top 1 accuracy), first 3 responses (top 3 accuracy), and first 10 responses (top 10 accuracy) out of 30 differential diagnoses given by the app. Also, to determine the accuracy of the app for rare and ultra-rare diagnoses given by the app.</p><p><strong>Methods: </strong>Frontal facial images of individuals with the diagnosis of a genetic syndrome (established clinically or molecularly) were analysed with and without additional clinical features.</p><p><strong>Results: </strong>In this study, a total of 118 children were recruited. Overall, the molecularly confirmed eventual diagnosis appeared in the \"top 10\" suggested syndromes by Face2Gene in 75/118 cases, providing a diagnostic yield of 63.6%. In this study, the top 1 accuracy for correct first diagnosis by the app and clinician's first diagnosis was 45.8% (n = 54). The Mcnemar test was examined for the clinician's accurate diagnosis as compared to top 1, top 3, and top 10 accuracy by the app and the p-value was statistically significant for top 10 accuracy (0.0005) and not for the top 1 and 3 diagnoses. The top 10 accuracy for the app in the rare cases was 21/30 cases (70%), and for ultra-rare cases was 28/64 (43.8%).</p><p><strong>Conclusions: </strong>The Face2Gene app is useful as an assistant to clinicians in the diagnosis of rare and ultra-rare diseases. The top 10 accuracy is better than clinical diagnosis, and the yield is better for the ultra-rare cases and the single gene disease category, too.</p>","PeriodicalId":13320,"journal":{"name":"Indian Journal of Pediatrics","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146062665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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