Abstract Background: Post-Intensive Care Syndrome (PICS) encompasses cognitive, motor, and mental impairments persisting for years in ICU survivors. Despite its significance, the prevalence of PICS in Indonesia remains uncertain due to limited research and a lack of validated measurement tools. This study aims to translate and validate the PICS Questionnaire for use among ICU survivors in Indonesia. Methods: The study followed a two-phase approach: translation and evaluation. The translation phase adhered to the 10-step process of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) guidelines. The analysis phase involved 184 subjects, using Confirmatory Factor Analysis (CFA) for validation and Cronbach's α and Intraclass Correlation Coefficient (ICC) for reliability testing. Results: The CFA reported factor loadings (λ >0.40) for each item in its relevant domain. Fit index values indicated a good-to-acceptable fit. Internal reliability was high for the mental, physical, and cognitive domains (0.812 vs. 0.779 vs. 0.855), with Cronbach's α of > 0.70. Test-retest reliability and ICC demonstrated dependable results (>0.70) for each domain. Conclusion: The translated and validated Indonesian PICS Questionnaire demonstrates good validity and reliability. This tool will enable healthcare professionals to assess PICS among ICU survivors in Indonesia and facilitate further research on its prevalence and impact on quality of life.
Intensive Care Unit ; Quality of Life ; Surveys and Questionnaires ; Factor Analysis ; Statistical ; Indonesia

Objective To explore the application value of multi-model adaptive statistical iterative reconstruction-Veo (ASiR-V) in ultra-low dose chest CT examination of children in the plateau area. Methods The children who underwent chest CT examination in Xizang Autonomous Region People's Hospital were enrolled in this study and assigned into two groups according to the scanning conditions.Group A underwent scanning at a tube voltage of 100 kV and ASiR-V 50% reconstruction,and group B underwent scanning at a tube voltage of 80 kV and ASiR-V 0 (Group B1) and ASiR-V 50% (Group B2) reconstruction.The image quality of each group was evaluated objectively and subjectively.The radiation dose and image quality were compared between groups. Results Groups A and B showed the volume CT dose indexes of (2.33±0.62) mGy and (0.86±0.01) mGy and the dose length products of (65.01±25.12) mGy·cm and (23.55±3.38) mGy·cm,respectively,which presented differences between groups (both P<0.001).The image noise in the bilateral upper and middle lung areas in group B2 was lower than that in group B1 but higher than that in group A (all P<0.001).There was no significant difference in image quality score of the lung window among groups (all P>0.05).Groups A,B1,and B2 had no significant differences in ascending aorta (P=0.538) or liver CT value (P=0.175) in the mediastinal window.The signal-to-noise ratios and contrast-to-noise ratios of ascending aorta and liver in group B2 were higher than those in group B1 (all P<0.001) and lower than those in group A (all P<0.05).The image quality score of the mediastinal window followed a descending order of group A>group B2>group B1 (all P<0.001)。Conclusion ASiR-V combined with low tube voltage can effectively reduce the radiation dose and guarantee the image quality of chest CT of children in the plateau area.
Humans ; Radiation Dosage ; Tomography, X-Ray Computed/methods* ; Child ; Male ; Female ; Child, Preschool ; Radiography, Thoracic/methods* ; Infant ; Models, Statistical ; Image Processing, Computer-Assisted/methods*

OBJECTIVES: This study aims to describe the clinical characteristics, treatment received and outcome of patients diagnosed with HLH at the Philippine Children’s Medical Center from 2004 to 2017.

MATERIALS AND METHODS: This cross-sectional analytical study was conducted from June 10, 2023 to June 1, 2024 at the Philippine Children's Medical Center. Detailed information was obtained for each case according to protocol. A complete history was taken from the accompanying caretakers. Children aged 0 to 7 years and 11 months, recently diagnosed with focal epilepsy, were evaluated using the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5-TR) criteria. The level of early child development was determined based on the total Battelle Developmental Inventory-2 developmental quotient score.

RESULTS: The study examined 246 children with focal epilepsy. Significant findings included those children with NDD had a higher median age (4.67 years) compared to those without NDD (3.37 years) (p < .001). A higher proportion of non-NDD children were under one year old. Children without NDD had mothers with higher educational attainment (p = .015) and came from families with higher incomes (p = .003). Neonatal complications such as hypoxic-ischemic encephalopathy (HIE) and sepsis were more common in children with NDD (p = .005 and p = .006). Phenobarbital use was more frequent in children with NDD (p = .001), who also had more abnormal EEG and neuroimaging findings (p < .001). Neurodevelopmental evaluations were conducted later for children with NDD (p < .001). A significant number (75.20%) of children exhibited neurodevelopmental problems, with global developmental delay being most prevalent. Crude analysis showed associations between age, number of antiseizure medications, and delays in evaluation with increased odds of NDD.

CONCLUSIONS: The study offers insights into children with focal epilepsy at a tertiary hospital in the Philippines, emphasizing the impact of low socioeconomic status, age, birth complications and multiple anti-seizure medications. These findings are vital for clinicians to modify care plans through a multidisciplinary approach to enhance outcomes and improve quality of life in this high-risk population.

Human ; Male ; Female ; Infant Newborn: First 28 Days After Birth ; Infant: 1-23 Months ; Child Preschool: 2-5 Yrs Old ; Child: 6-12 Yrs Old ; Neurodevelopmental Disorders ; Sepsis ; Hypoxia-ischemia, Brain ; Epilepsies, Partial ; Educational Status ; Diagnostic And Statistical Manual Of Mental Disorders ; Child Development

INTRODUCTION: Medical errors commonly occur in medical imaging departments. These errors are frequently influenced by patient safety culture. This study aimed to develop a suitable patient safety culture assessment tool for medical imaging departments. METHODS: Staff members of a teaching hospital medical imaging department were invited to complete the generic short version of the Safety Attitude Questionnaire (SAQ). Internal consistency and reliability were evaluated using Cronbach's α. Confirmatory factor analysis (CFA) was conducted to examine model fit. A cut-off of 60% was used to define the percentage positive responses (PPR). PPR values were compared between occupational groups. RESULTS: A total of 300 complete responses were received and the response rate was 75.4%. In reliability analysis, the Cronbach's α for the original 32-item SAQ was 0.941. Six subscales did not demonstrate good fit with CFA. A modified five-subscale, 22-item model (SAQ-MI) showed better fit (goodness-to-fit index ≥0.9, comparative fit index ≥ 0.9, Tucker-Lewis index ≥0.9 and root mean square error of approximation ≤0.08). The Cronbach's α for the 22 items was 0.921. The final five subscales were safety and teamwork climate, job satisfaction, stress recognition, perception of management and working condition, with PPR of 62%, 68%, 57%, 61% and 60%, respectively. Statistically significant differences in PPR were observed between radiographers, doctors and others occupational groups. CONCLUSION The modified five-factor, 22-item SAQ-MI is a suitable tool for the evaluation of patient safety culture in a medical imaging department. Differences in patient safety culture exist between occupation groups, which will inform future intervention studies.
Humans ; Surveys and Questionnaires ; Patient Safety ; Attitude of Health Personnel ; Diagnostic Imaging ; Reproducibility of Results ; Male ; Female ; Adult ; Job Satisfaction ; Factor Analysis, Statistical ; Middle Aged ; Hospitals, Teaching ; Safety Management ; Organizational Culture ; Medical Errors/prevention & control*

Computer Simulation ; Models, Statistical

To develop a caregiver parenting behavior scale for children aged 2 to 6 years, and to verify its reliability and validity. This study recruited 1 350 caregivers of children aged 2 to 6 years. The item discrimination analysis and exploratory factor analysis were used to analyze the structure, dimensions and items of the scale. Homogeneity reliability, split-half reliability and test-retest reliability were used to analyze the reliability of the scale. Content validity and construct validity were used to analyze the validity of the scale. The results showed that the final scale contained 7 dimensions and 45 items. Cronbach's α coefficient of the total scale was 0.945; the coefficient of split half was 0.899; the test-retest reliability analysis showed that the correlation coefficients between the two tests were 0.893 (total score), 0.854 (social), 0.832 (language), 0.871 (gross motor), 0.893 (fine motor), 0.862 (cognitive), 0.832 (self-care), and 0.872 (sensory). The content validity analysis was carried out by two rounds of expert argumentation using Delphi expert consultation method. The Kendall coefficient of the items score in two rounds of Delphi expert consultation was 0.813 (P<0.01). The structure validity analysis showed that there were significant correlations between each dimension and the total scale, also between each dimension of the scale, and the extracted average variance values of each dimension was greater than the correlation coefficients between this dimension and other dimensions. In conclusion, the reliability and validity of the scale are qualified. It can be used as a tool to evaluate and guide the parenting behavior of caregivers of children aged 2 to 6 years.
Humans ; Child ; Caregivers/psychology* ; Reproducibility of Results ; Parenting ; Surveys and Questionnaires ; Factor Analysis, Statistical ; Psychometrics/methods*

Objective To analyze the risk factors and build a clinical prediction model for hemodynamic depression (HD) after carotid artery stenting (CAS). Methods A total of 116 patients who received CAS in the Department of Vascular Surgery,Drum Tower Clinical College of Nanjing Medical University and the Department of Vascular Surgery,the Affiliated Suqian First People's Hospital of Nanjing Medical University from January 1,2016 to January 1,2022 were included in this study.The patients were assigned into a HD group and a non-HD group.The clinical baseline data and vascular disease characteristics of each group were collected,and multivariate Logistic regression was employed to identify the independent predictors of HD after CAS and build a clinical prediction model.The receiver operating characteristic (ROC) curve was drawn,and the area under the ROC curve (AUC) was calculated to evaluate the predictive performance of the model. Results The HD group had lower proportions of diabetes (P=0.014) and smoking (P=0.037) and higher proportions of hypertension (P=0.031),bilateral CAS (P=0.018),calcified plaque (P=0.001),eccentric plaque (P=0.003),and the distance<1 cm from the minimum lumen level to the carotid bifurcation (P=0.009) than the non-HD group.The age,sex,coronary heart disease,symptomatic carotid artery stenosis,degree of stenosis,and length of lesions had no statistically significant differences between the HD group and the non-HD group (all P>0.05).Based on the above predictive factors,a clinical prediction model was established,which showed the AUC of 0.807 and the 95% CI of 0.730-0.885 (P<0.001).The model demonstrated the sensitivity of 62.7% and the specificity of 87.7% when the best cut-off value of the model score reached 12.5 points. Conclusions Diabetes,smoking,calcified plaque,eccentric plaque,and the distance<1 cm from the minimum lumen level to the carotid bifurcation are independent predictors of HD after CAS.The clinical prediction model built based on the above factors has good performance in predicting the occurrence of HD after CAS.
Humans ; Carotid Stenosis ; Depression ; Models, Statistical ; Prognosis ; Stents ; Hemodynamics ; Plaque, Amyloid

OBJECTIVE: To establish a predictive model for severe swallowing disorder after acute ischemic stroke based on nomogram model, and evaluate its effectiveness. METHODS: A prospective study was conducted. The patients with acute ischemic stroke admitted to Mianyang Central Hospital from October 2018 to October 2021 were enrolled. Patients were divided into severe swallowing disorder group and non-severe swallowing disorder group according to whether severe swallowing disorder occurred within 72 hours after admission. The differences in general information, personal history, past medical history, and clinical characteristics of patients between the two groups were compared. The risk factors of severe swallowing disorder were analyzed by multivariate Logistic regression analysis, and the relevant nomogram model was established. The bootstrap method was used to perform self-sampling internal validation on the model, and consistency index, calibration curve, receiver operator characteristic curve (ROC curve), and decision curve were used to evaluate the predictive performance of the model. RESULTS: A total of 264 patients with acute ischemic stroke were enrolled, and the incidence of severe swallowing disorder within 72 hours after admission was 19.3% (51/264). Compared with the non-severe swallowing disorder group, the severe swallowing disorder group had a higher proportion of patients aged of ≥ 60 years old, with severe neurological deficits [National Institutes of Health stroke scale (NIHSS) score ≥ 7], severe functional impairments [Barthel index, an activity of daily living functional status assessment index, < 40], brainstem infarction and lesions ≥ 40 mm (78.43% vs. 56.81%, 52.94% vs. 28.64%, 39.22% vs. 12.21%, 31.37% vs. 13.62%, 54.90% vs. 24.41%), and the differences were statistically significant (all P < 0.01). Multivariate Logistic regression analysis showed that age ≥ 60 years old [odds ratio (OR) = 3.542, 95% confidence interval (95%CI) was 1.527-8.215], NIHSS score ≥ 7 (OR = 2.741, 95%CI was 1.337-5.619), Barthel index < 40 (OR = 4.517, 95%CI was 2.013-10.136), brain stem infarction (OR = 2.498, 95%CI was 1.078-5.790) and lesion ≥ 40 mm (OR = 2.283, 95%CI was 1.485-3.508) were independent risk factors for severe swallowing disorder after acute ischemic stroke (all P < 0.05). The results of model validation showed that the consistency index was 0.805, and the trend of the calibration curve was basically consistent with the ideal curve, indicating that the model had good prediction accuracy. ROC curve analysis showed that the area under the ROC curve (AUC) predicted by nomogram model for severe swallowing disorder after acute ischemic stroke was 0.817 (95%CI was 0.788-0.852), indicating that the model had good discrimination. The decision curve showed that within the range of 5% to 90%, the nomogram model had a higher net benefit value for predicting the risk of severe swallowing disorder after acute ischemic stroke, indicating that the model had good clinical predictive performance. CONCLUSIONS The independent risk factors of severe swallowing disorder after acute ischemic stroke include age ≥ 60 years old, NIHSS score ≥ 7, Barthel index < 40, brainstem infarction and lesion size ≥ 40 mm. The nomogram model established based on these factors can effectively predict the occurrence of severe swallowing disorder after acute ischemic stroke.
United States ; Humans ; Aged ; Middle Aged ; Ischemic Stroke ; Deglutition Disorders ; Models, Statistical ; Nomograms ; Prognosis ; Prospective Studies ; Brain Stem Infarctions

UNLABELLED: AbstractObjective: To analysis the clinical data of patients after single-center hematopoietic stem cell transplantation (HSCT) and construct a predictive model for metabolic syndrome (MS) diagnosis. METHODS: Ninety-three hematology patients who underwent HSCT at the First Hospital of Lanzhou University from July 2015 to September 2022 were selected to collect basic data, transplantation status and postoperative data, the clinical characteristics of patients with and without MS after transplantation were compared and analyzed. Logistic regression model was used to analyze the influence fators of MS after transplantation, and a predictive model of HSCT-MS diagnosis was constructed under the influence of independent influence factors. The model was evaluated using the ceceiver operating characteristic curve (ROC curve). RESULTS: Metabolic syndrome occurred in 36 of 93 HSCT patients and did not occur in 57. Compared with non-HSCT-MS group, HSCT-MS had significantly higher fasting blood glucose (FBG) levels before transplantation, shorter course before transplantation, and higher bilirubin levels after transplantation (P<0.05). The statistically significant clinical indicators were subjected to multi-factor logistic regression analysis, and the results showed that pre-transplant high FBG, pre-transplant short disease course and post-transplant high bilirubin were independent influence factors for HSCT-MS. The standard error of predicting the occurrence of HSCT-MS based on the clinical model was 0.048, the area under the curve AUC=0.776, 95% CI :0.683-0.869, the optimal threshold was 0.58 based on the Jorden index at maximum, the sensitivity was 0.694, and the specificity was 0.772, which has certain accuracy. CONCLUSION A clinical prediction model for HSCT-MS based on logistic regression analysis is constructed through the analysis of clinical data, which has certain clinical value.
Humans ; Metabolic Syndrome ; Prognosis ; Models, Statistical ; Hematopoietic Stem Cell Transplantation ; ROC Curve ; Retrospective Studies

OBJECTIVES: To construct a clinical prediction model for the impact of acupuncture on pregnancy outcomes in poor ovarian response (POR) patients, providing insights and methods for predicting pregnancy outcomes in POR patients undergoing acupuncture treatment. METHODS: Clinical data of 268 POR patients (2 cases were eliminated) primarily treated with "thirteen needle acupuncture for Tiaojing Cuyun (regulating menstruation and promoting pregnancy)" was collected from the international patient registry platform of acupuncture moxibustion (IPRPAM) from September 19, 2017 to April 30, 2023, involving 24 clinical centers including Acupuncture-Moxibustion Hospital of China Academy of Chinese Medical Sciences. LASSO and univariate Cox regression were used to screen factors influencing pregnancy outcomes, and a multivariate Cox regression model was established based on the screening results. The best model was selected using the Akaike information criterion (AIC), and a nomogram for clinical pregnancy prediction was constructed. The prediction model was evaluated using receiver operating characteristic (ROC) curves and calibration curves, and internal validation was performed using the Bootstrap method. RESULTS: (1) Age, level of anti-Müllerian hormone (AMH), and total treatment numbers of acupuncture were independent predictors of pregnancy outcomes in POR patients receiving acupuncture (P<0.05). (2) The AIC value of the best subset-Cox multivariate model (560.6) was the smallest, indicating it as the optimal model. (3) The areas under curve (AUCs) of the clinical prediction model after 6, 12, 24, and 36 months treatment were 0.627, 0.719, 0.770, and 0.766, respectively, and in the validation group, they were 0.620, 0.704, 0.759, and 0.765, indicating good discrimination and repeatability of the prediction model. (4) The calibration curve showed that the prediction curve of the clinical prediction model was close to the ideal model's prediction curve, indicating good calibration of the prediction model. CONCLUSIONS The clinical prediction model for the impact of acupuncture on pregnancy outcomes in POR patients based on the IPRPAM platform has good clinical application value and provides insights into predicting pregnancy outcomes in POR patients undergoing acupuncture treatment.
Pregnancy ; Female ; Humans ; Pregnancy Outcome ; Models, Statistical ; Prognosis ; Acupuncture Therapy ; Registries