Objective:To conduct a systematic review of risk prediction models for enteral feeding intolerance in ICU patients.Methods:Relevant literature was searched in China National Knowledge Infrastructure, Wanfang Data, China Biology Medicine disc, VIP, PubMed, Web of Science, Cochrane Library, Embase, CINAHL, and Scopus, with search limits from the establishment of the databases up to July 24, 2024. Two researchers independently screened the literature and extracted data, using Prediction model Risk Of Bias ASsessment Tool to evaluate the quality of the included studies.Results:A total of 12 studies were included, which included 20 prediction models. The area under the receiver operating characteristic curve or C-index for these models ranged from 0.70 to 0.94. The overall bias risk of the 12 studies was high, with three studies having good applicability. The bias risk primarily stemmed from issues such as measurement of prediction factors, variable handling, sample size, outcome definition, and model performance evaluation.Conclusions:Existing risk prediction models for enteral feeding intolerance in ICU patients exhibit a high risk of bias. Further validation, optimization, or development of new models is required in the future.

Objective:To conduct a systematic review of risk prediction models for enteral feeding intolerance in ICU patients.Methods:Relevant literature was searched in China National Knowledge Infrastructure, Wanfang Data, China Biology Medicine disc, VIP, PubMed, Web of Science, Cochrane Library, Embase, CINAHL, and Scopus, with search limits from the establishment of the databases up to July 24, 2024. Two researchers independently screened the literature and extracted data, using Prediction model Risk Of Bias ASsessment Tool to evaluate the quality of the included studies.Results:A total of 12 studies were included, which included 20 prediction models. The area under the receiver operating characteristic curve or C-index for these models ranged from 0.70 to 0.94. The overall bias risk of the 12 studies was high, with three studies having good applicability. The bias risk primarily stemmed from issues such as measurement of prediction factors, variable handling, sample size, outcome definition, and model performance evaluation.Conclusions:Existing risk prediction models for enteral feeding intolerance in ICU patients exhibit a high risk of bias. Further validation, optimization, or development of new models is required in the future.

OBJECTIVE: To explore the genetic basis for a child with facial dysmorphism and multiple malformations. METHODS: The child, born at 34⁺⁶ weeks' gestation due to premature rupture of amniotic membrane, dichorionic diamniotic twinning and gestational diabetes, was subjected to chromosomal karyotyping analysis and copy number variations sequencing (CNV-seq). RESULTS: The child was found to have facial dysmorphism, hypospadia, cryptorchidism and hypotonia. He was found to have a 46,XY,del(3)(p26) karyotype in addition with a 9.80 Mb deletion (chr3: 60 000-9 860 000) encompassing 33 protein coding genes. CONCLUSION The 3p26.3p25.3 deletion probably underlay the multiple malformations in this child. Continuous follow-up is required to improve his quality of life.
Humans ; Male ; Chromosome Deletion ; DNA Copy Number Variations ; Quality of Life ; Abnormalities, Multiple/genetics* ; Phenotype