OBJECTIVES: To study the clinical and microbiological characteristics of children with drowning-associated aspiration pneumonia, so as to provide a reference for empirical selection of antibacterial agents. METHODS: A retrospective analysis was performed on the medical data of 185 children with drowning-associated aspiration pneumonia who were admitted to Children's Hospital of Chongqing Medical University from January 2010 to October 2020. According to the drowning environment, these children were divided into four groups: fecal group (n=44), freshwater group (n=69), swimming pool group (n=41), and contaminant water group (n=31). The clinical characteristics and pathogen detection results were reviewed and compared among the four groups. RESULTS: The 185 children had an age of 4 months to 17 years (median 34 months). Sputum cultures were performed on 157 children, and 103 were tested positive (65.6%), with 87 strains of Gram-negative bacteria (68.5%), 37 strains of Gram-positive bacteria (29.1%), and 3 strains of fungi (2.4%). Gram-negative bacteria were the main pathogen in the fecal group and the contaminant water group, accounting for 88.2% (30/34) and 78.3% (18/23), respectively. The freshwater group had a significantly higher detection rate of Gram-positive bacteria than the fecal group (P<0.008), and the swimming pool group had an equal detection rate of Gram-negative bacteria and Gram-positive bacteria. CONCLUSIONS For pulmonary bacterial infection in children with drowning in feces or contaminant water, antibiotics against Gram-negative bacteria may be applied empirically, while for children with drowning in a swimming pool or freshwater, broad-spectrum antibiotics may be used as initial treatment, and subsequently the application of antibiotics may be adjusted according to the results of the drug sensitivity test.
Anti-Bacterial Agents/therapeutic use* ; Child ; Drowning ; Gram-Negative Bacteria ; Humans ; Pneumonia, Aspiration/drug therapy* ; Retrospective Studies ; Water

OBJECTIVE: To analyze the mortality of injuries among children and adolescents aged 5 to 24 in China from 1990 to 2019, and to provide the theoretical basis for the formulation of policies related to injury prevention. METHODS: The mortality data of children and adolescents aged 5 to 24 years in China between 1990 and 2019 were obtained from Global Burden of Disease (GBD) 2019, and the change in mortality between 1990 and 2019 was described. Age-period-cohort analysis was utilized to determine the age effect, period effect and cohort effect for road injuries, drowning and self-harm. RESULTS: Injury mortality of Chinese children and adolescents aged 5 to 24 years decreased from 46.22 [95% uncertainty interval (UI): 40.88-52.12] per 100 000 to 20.36 (95%UI: 17.58-23.38) per 100 000 between 1990 and 2019. Sub-group analysis revealed a pattern that was basically consistent with the overall trend. From 1990 to 2019, drowning declined from the first leading cause of injury death among children and adolescents aged 5 to 24 years in China to the second while road injuries became the one which caused the most death among them, and self-harm was the third leading cause of injury death. The top three causes of injury death in each subgroup were basically the same as the overall, but the order was different in each subgroup. Age-period-cohort analysis showed that the death risk of road injuries, drowning, and self-harm all decreased with period and cohort. Aside from that, the death risk of road injuries showed a U-shape trend, which decreased at first but increased soon afterwards, with the increase of age, while the death risk of drowning decreased with age and the death risk of self-harm increased with age. CONCLUSION In China, the injuries mortality among children and adolescents aged 5 to 24 years has decreased over the last three decades. However, specific cause-related injury deaths, manifested differently in different sub-groups. Targeted policies and intervention should be proposed to reduce the mortality of children and adolescents in accordance with the characteristics of injuries death in different genders and age groups.
Adolescent ; Asians ; Cause of Death ; Child ; China/epidemiology* ; Drowning ; Female ; Global Burden of Disease ; Humans ; Infant ; Male ; Wounds and Injuries

Objective: To analyze the trajectory of drowning and road traffic injury mortality among children aged 5-14 years in China from 2008 to 2019. Methods: Mortality data of unintentional injuries were from the Mortality Surveillance Data Set of National Disease Surveillance System from 2009 to 2018 and grouped by regions, urban and rural areas, genders, and age groups. The trajectory model was used to analyze the trend of drowning and road traffic injury mortality with years. Results: The mortality of drowning and road traffic injury showed a similar trend. In the trajectory model of drowning mortality, east, middle and west rural boys and western urban boys of all ages belonged to the high mortality group. The moderate mortality group included eastern urban boys and western girls aged 5-9 years and also contained eastern and middle urban boys and western urban girls aged 10-14 years. The other combinations belonged to the low mortality group. In the trajectory model of road traffic injury mortality, western urban boys, all rural boys and western rural girls aged 5-9 years, middle and western rural boys and western urban boys aged 10-14 years belonged to the high mortality group. Eastern urban girls aged 5-9 years and 10-14 years belonged to the low mortality group. The other combinations belonged to the moderate mortality group. Conclusion: There are different groups in the trajectory model of drowning and road traffic injury mortality among children in China. Identifying the trajectory of injury mortality is helpful to carry out more targeted prevention in China.
Accidental Injuries ; Accidents, Traffic ; Child ; China/epidemiology* ; Drowning ; Female ; Humans ; Male ; Rural Population ; Urban Population ; Wounds and Injuries

Autopsy ; Drowning/diagnosis* ; Forensic Pathology ; Humans ; Lung ; Postmortem Changes ; Water

Drowning is the death caused by asphyxiation due to fluid blocking the airway. In the practice of forensic medicine, it is the key to determine whether the corpse was drowned or entered the water after death. At the same time, the drowning site inference and postmortem submersion interval (PMSI) play an important role in the investigating the identity of the deceased, narrowing the investigation scope, and solving the case. Based on diatoms testing, molecular biology, imaging and artificial intelligence and other technologies, domestic and foreign forensic scientists have done relative research in the identification of the cause of death, drowning site inference and PMSI, and achieved certain results in forensic medicine application. In order to provide a reference for future study of bodies in the water, this paper summarizes the above research contents.
Artificial Intelligence ; Diatoms ; Drowning/diagnosis* ; Forensic Pathology ; Humans ; Lung ; Water

Diatom test is the main laboratory test method in the diagnosis of drowning in forensic medicine. It plays an important role in differentiating the antemortem drowning from the postmortem drowning and inferring drowning site. Artificial intelligence (AI) automatic diatom test is a technological innovation in forensic drowning diagnosis which is based on morphological characteristics of diatom, the application of AI algorithm to automatic identification and classification of diatom in tissues and organs. This paper discusses the morphological diatom test methods and reviews the research progress of automatic diatom recognition and classification involving AI algorithms. AI deep learning algorithm can assist diatom testing to obtain objective, accurate, and efficient qualitative and quantitative analysis results, which is expected to become a new direction of diatom testing research in the drowning of forensic medicine in the future.
Artificial Intelligence ; Autopsy ; Diatoms ; Drowning/diagnosis* ; Humans ; Lung

Diatom detection is an important method for identifying drowning and throwing corpses after death and inferring the drowning sites in forensic examination of corpses in water. In recent years,high-throughput sequencing technology has achieved rapid development and has been widely used in research related to diatom taxonomic investigations. This paper reviews the research status and prospects of high-throughput sequencing technology and its application in forensic diatom detection.
Cadaver ; Diatoms/genetics* ; Drowning/diagnosis* ; Forensic Pathology/methods* ; High-Throughput Nucleotide Sequencing ; Humans ; Lung ; Technology

OBJECTIVES: To explore the application values of diatom artificial intelligence (AI) search system in the diagnosis of drowning. METHODS: The liver and kidney tissues of 12 drowned corpses were taken and were performed with the diatom test, the view images were obtained by scanning electron microscopy (SEM). Diatom detection and forensic expert manual identification were carried out under the thresholds of 0.5, 0.7 and 0.9 of the diatom AI search system, respectively. Diatom recall rate, precision rate and image exclusion rate were used to detect and compare the efficiency of diatom AI search system. RESULTS: There was no statistical difference between the number of diatoms detected in the target marked by the diatom AI search system and the number of diatoms identified manually (P>0.05); the recall rates of the diatom AI search system were statistically different under different thresholds (P<0.05); the precision rates of the diatom AI system were statistically different under different thresholds(P<0.05), and the highest precision rate was 53.15%; the image exclusion rates of the diatom AI search system were statistically different under different thresholds (P<0.05), and the highest image exclusion rate was 99.72%. For the same sample, the time taken by the diatom AI search system to identify diatoms was only 1/7 of that of manual identification. CONCLUSIONS Diatom AI search system has a good application prospect in drowning cases. Its automatic diatom search ability is equal to that of experienced forensic experts, and it can greatly reduce the workload of manual observation of images.
Artificial Intelligence ; Diatoms ; Drowning/diagnosis* ; Humans ; Liver ; Lung ; Microscopy, Electron, Scanning

OBJECTIVES: To construct a YOLOv3-based model for diatom identification in scanning electron microscope images, explore the application performance in practical cases and discuss the advantages of this model. METHODS: A total of 25 000 scanning electron microscopy images were collected at 1 500× as an initial image set, and input into the YOLOv3 network to train the identification model after experts' annotation and image processing. Diatom scanning electron microscopy images of lung, liver and kidney tissues taken from 8 drowning cases were identified by this model under the threshold of 0.4, 0.6 and 0.8 respectively, and were also identified by experts manually. The application performance of this model was evaluated through the recognition speed, recall rate and precision rate. RESULTS: The mean average precision of the model in the validation set and test set was 94.8% and 94.3%, respectively, and the average recall rate was 81.2% and 81.5%, respectively. The recognition speed of the model is more than 9 times faster than that of manual recognition. Under the threshold of 0.4, the mean recall rate and precision rate of diatoms in lung tissues were 89.6% and 87.8%, respectively. The overall recall rate in liver and kidney tissues was 100% and the precision rate was less than 5%. As the threshold increased, the recall rate in all tissues decreased and the precision rate increased. The F1 score of the model in lung tissues decreased with the increase of threshold, while the F1 score in liver and kidney tissues with the increase of threshold. CONCLUSIONS The YOLOv3-based diatom electron microscope images automatic identification model works at a rapid speed and shows high recall rates in all tissues and high precision rates in lung tissues under an appropriate threshold. The identification model greatly reduces the workload of manual recognition, and has a good application prospect.
Diatoms ; Drowning/diagnosis* ; Humans ; Liver/diagnostic imaging* ; Lung/diagnostic imaging* ; Microscopy, Electron, Scanning

OBJECTIVES: To explore the application value of virtual autopsy to obtain key evidence information on drowned corpses and its application value of virtual autopsy in the diagnosis of drowning. METHODS: In this study, 7 corpses were selected as the research objects. The image data of corpses were collected by computed tomography (CT) before conventional autopsy. The characteristics of corpses were observed through image reading, combined with virtual measurement indexes, and compared with 15 non-drowned corpses. RESULTS: The postmortem CT of drowning showed the more fluid in respiratory tract than the non-drowning, and ground-glass opacities in the lung. The statistical volume of fluid in the sinus (maxillary sinus and sphenoid sinus) was (10.24±4.70) mL in drowning cases and (2.02±2.45) mL in non-drowning cases. The average CT value of fluid in the sinus, left atrial blood and gastric contents in drowning cases were (15.91±17.20), (52.57±9.24) and (10.33±12.81) HU, respectively, which were lower than those in non-drowning cases (P<0.05). CONCLUSIONS The comprehensive consideration of multiple characteristic image manifestations and the virtual measurement indexes are helpful to the forensic pathological diagnosis of drowning. Virtual autopsy can be used as an auxiliary method in the forensic diagnosis of drowning.
Autopsy/methods* ; Cadaver ; Drowning/diagnostic imaging* ; Forensic Pathology/methods* ; Humans ; Tomography, X-Ray Computed/methods*