OBJECTIVE: When patients administered 177Lu-DOTATATE are released or discharged from rooms where radiopharmaceuticals are used, the time required for release or discharge varies across patients. This study investigated whether the amount of radioactivity accumulated on 111In-somatostatine receptor scintigraphy (111In-SRS) performed prior to treatment can predict the 1 cm dose-equivalent rate at a distance of 1 m from the patient on the day after 177Lu-DOTATATE administration.
METHODS: Whole-body planar 111In-SRS images were acquired for 21 patients. Pixel values within whole-body and abdominal (35 × 25 cm) regions of interest (ROIs) were converted to radioactivity dose (MBq). The 1 cm dose-equivalent rate (µSv/h) at a distance of 1 m from the patient 18.3 ± 0.5 h after administration of 177Lu-DOTATATE was measured using an ionization survey meter.
RESULTS: The following relationships were observed between the radioactivity on 111In-SRS and the 1 cm dose-equivalent rate on the day after administration of 177Lu-DOTATATE: whole-body ROI: y = 0.16x + 5.01 (r = 0.56, p = 0.009), abdominal ROI: y = 0.27x + 5.13 (r = 0.63, p = 0.002). The regression equations indicate that patients cannot be released or discharged from the radiopharmaceutical room the day after 177Lu-DOTATATE administration if the whole-body and abdominal ROI doses are greater than 81 and 48 MBq, respectively, on 111In-SRS.
CONCLUSIONS: The amount of radioactivity accumulated on 111In-SRS may be a predictor of release criteria for patients receiving 177Lu-DOTATATE.

Background Pneumonia is a major concern among the elderly, with high readmission rates after hospitalization. These readmissions increase medical costs and reflect the quality of hospital care. This study aimed to explore the predictive factors associated with readmission within 30 days among elderly patients with pneumonia. Methodology This retrospective cohort study utilized the existing medical records. We included patients with pneumonia aged 75 and above who were discharged from a community hospital between April 2016 and March 2022. Patients who died during hospitalization or were transferred to other hospitals were excluded. Sex, age, length of hospital stay, Barthel Index (BI) at discharge, height, weight, body mass index, blood test findings, presence of tube feeding, Charlson Comorbidity Index, neutrophil-to-lymphocyte ratio (NLR), and Geriatric Nutritional Risk Index were used as predictive factors. The primary outcome was readmission within 30 days of discharge. A logistic regression analysis was performed. Results We included 337 patients: 50 (15%) in the readmission group and 287 (85%) in the control group. Univariate logistic regression analysis indicated low BI at discharge, and the odds ratio (OR) for readmission was 0.99 (95% confidence interval (CI) = 0.98-1.00). In patients with hemoglobin 10.0 g/dL or less, the OR for readmission was 2.18 (95% CI = 1.08-4.28). In patients with an NLR of 5 points or more, the OR for readmission was 2.64 (95% CI = 1.30 -5.24). In patients with aspartate transaminase of 38 U/L or more, the OR for readmission was 2.99 (95% CI = 1.07-7.68). Multivariate logistic regression revealed that an NLR of 5 points or more (adjusted OR = 2.42, 95% CI = 1.12-5.14) was correlated with readmission in elderly pneumonia patients. Conclusions In elderly patients with pneumonia, a high NLR at discharge may be a potential predictor of readmission within 30 days. This could be a new finding of our study. By sharing these findings during patient discharge conferences, there is potential to assist the medical team, patients, and caregivers in predicting unforeseen short-term readmissions. Further high-quality research is required to verify the reproducibility of these findings.

The post-operative course after Liver Transplantation (LT) can be complicated by early allograft dysfunction (EAD), primary nonfunction (PNF) and death. A lactate concentration at the end of transplant of ≥5 mmol/L was recently proposed as a predictive marker of PNF, EAD, and mortality; this study aimed to validate these previous reports in a large single center cohort.
This retrospective cohort study included adult liver transplant recipients who received grafts from deceased donors at our center between June 2012 and May 2021. Receiver operating characteristic (ROC) curves for the lactate concentration at the end of transplantation were computed to determine the AUC for PNF, EAD and mortality at 90 days.
In our cohort of 1137 cases, the AUCs for lactate to predict EAD, PNF and mortality were respectively .56 (95% confidence interval [CI]: .53-.60), .69 (95% CI: .52-.85), and .74 (95% CI: .63-.84).
The clinical value of lactate concentration at the end of transplantation to predict PNF, EAD and mortality at 90 days was, at best, modest, as shown by the relatively low AUCs. Our findings cannot validate previous reports that the lactate level alone is a good predictor of poor outcomes after liver transplantation.

Severe bleeding is the leading cause of early death in patients with newly diagnosed acute promyelocytic leukemia (APL). However, there are no means for hemorrhagic risk stratification in APL. This study aimed to identify optimized predictors of severe bleeding events related to APL. A total of 109 consecutive patients with newly diagnosed APL from January 2015 to April 2022 were retrospectively investigated. A systematic review of computer-based patient medical records was conducted to obtain clinical date, including baseline characteristics, routine blood examination findings, coagulation and fibrinolysis indexes, and bleeding events. Among the 109 patients, 89 were classified into the no-severe bleeding group, while 20 had severe bleeding. Compared with the patients with no severe bleeding, the patients with severe bleeding had significantly higher circulating leukemic cell percentages, disseminated intravascular coagulation (DIC) scores, D-dimer (D-D) levels, and fibrin degradation product (FDP) levels. They also had lower fibrinogen (FIB) levels and a longer prothrombin time. Multivariate analysis revealed that the circulating leukemic cell percentage (OR = 1.040, CI = 1.008-1.072, P = 0.012), FIB level (OR = 0.101, CI = 0.011-0.896, P = 0.040), and FDP level (OR = 1.012, CI = 1.000-1.024, P = 0.047) were independent risk factors for severe bleeding. FDP/FIB, D-D/FIB, and seven meaningful indicators in the single-factor analysis were included in the receiver operating characteristic (ROC) curve analysis. The results showed that FDP/FIB was the best indicator for predicting severe bleeding related to newly diagnosed APL. The area under the ROC curve of FDP/FIB was 0.915, and the best cutoff value was 61.77, with 100% sensitivity and 74.2% specificity. Statistical analysis showed a higher incidence of severe bleeding and higher DIC scores when FDP/FIB was >61.77 in APL patients. FDP/FIB has obvious advantages in predicting the degree of bleeding associated with primary promyelocytic leukemia; the greater the FDP/FIB value, the more severe the bleeding. The risk of severe bleeding was the highest when FDP/FIB > 61.77.

OBJECTIVE: This study was proposed to evaluate factors predicting a successful vaginal delivery following labor induction and develop induction prediction model in term pregnancy among Thai pregnant women.
METHODS: We conducted a retrospective cohort study using electronic medical records of 23,833 deliveries from April 2010 to July 2021 at tertiary care university hospital in Bangkok, Thailand. Univariate regression was performed to identify the association of individual parameters to successful vaginal delivery. Multiple logistic regression analysis of all possible variables from univariate analysis was performed to develop a prediction model with statistically significant of p value <0.05.
RESULTS: Of the total 809 labor-induced pregnancies, the vaginal delivery rate was 56.6%. Among predicting variables, history of previous vaginal delivery (aOR 5.75, 95% CI 3.701-8.961), maternal delivery BMI <25 kg/m2 (aOR 2.010, 95% CI 1.303-3.286), estimated fetal weight <3500 g (aOR 2.193, 95% CI 1.246-3.860), and gestational age ≤39 weeks (aOR 1.501, 95% CI 1.038-2.173) significantly increased the probability of a successful vaginal delivery following labor induction. The final prediction model has been internally validated. Model calibration and discrimination were satisfactory with Hosmer-Lemeshow test P = 0.21 and with AUC of 0.756 (95% CI 0.695-0.816).
CONCLUSIONS: This study determined the pragmatic predictors for successful vaginal delivery following labor induction comprised history of previous vaginal delivery, maternal delivery BMI <25 kg/m2, estimated fetal weight <3500 g, and gestational age ≤39 weeks. The final induction prediction model was well-performing internally validated prediction model to estimate individual probability when undergoing induction of labor. Despite restricted population, the predicting factors and model could be useful for further prospective study and clinical practice to improve induction outcomes.

Periodontal diseases and dental caries are the most common diseases of humans and the main cause of tooth loss. Both diseases can lead to nutritional compromise and negative impacts upon self-esteem and quality of life. As complex chronic diseases, they share common risk factors, such as a requirement for a pathogenic plaque biofilm, yet they exhibit distinct pathophysiologies. Multiple exposures contribute to their causal pathways, and susceptibility involves risk factors that are inherited (e.g. genetic variants), and those that are acquired (e.g. socio-economic factors, biofilm load or composition, smoking, carbohydrate intake). Identification of these factors is crucial in the prevention of both diseases as well as in their management.
OBJECTIVE: To systematically appraise the scientific literature to identify potential risk factors for caries and periodontal diseases.
METHODS: One systematic review (genetic risk factors), one narrative review (role of diet and nutrition) and reference documentation for modifiable acquired risk factors common to both disease groups, formed the basis of the report.
CONCLUSIONS: There is moderately strong evidence for a genetic contribution to periodontal diseases and caries susceptibility, with an attributable risk estimated to be up to 50%. The genetics literature for periodontal disease is more substantial than for caries and genes associated with chronic periodontitis are the vitamin D receptor (VDR), Fc gamma receptor IIA (Fc-γRIIA) and Interleukin 10 (IL10) genes. For caries, genes involved in enamel formation (AMELX, AMBN, ENAM, TUFT, MMP20, and KLK4), salivary characteristics (AQP5), immune regulation and dietary preferences had the largest impact. No common genetic variants were found. Fermentable carbohydrates (sugars and starches) were the most relevant common dietary risk factor for both diseases, but associated mechanisms differed. In caries, the fermentation process leads to acid production and the generation of biofilm components such as Glucans. In periodontitis, glycaemia drives oxidative stress and advanced glycation end-products may also trigger a hyper inflammatory state. Micronutrient deficiencies, such as for vitamin C, vitamin D or vitamin B12, may be related to the onset and progression of both diseases. Functional foods or probiotics could be helpful in caries prevention and periodontal disease management, although evidence is limited and biological mechanisms not fully elucidated. Hyposalivation, rheumatoid arthritis, smoking/tobacco use, undiagnosed or sub-optimally controlled diabetes and obesity are common acquired risk factors for both caries and periodontal diseases.

BACKGROUND: Hypoalbuminaemia at admission is a common finding in patients admitted to the Paediatric Intensive Care Unit (PICU) and it is thought that this may predict morbidity and mortality.
METHODS: A retrospective study was conducted in the tertiary hospital. The medical records of critically ill children were reviewed. The data were analyzed for the prevalence of hypoalbuminaemia and outcomes.
RESULTS: Two hundred and two patients were included in the analysis. The incidence of hypoalbuminaemia at admission was 57.9%. These patients had a mortality rate 4 times greater (adjusted odds ratio 3.8; 95% CI: 1.4-10.0), a longer length of PICU stay (8.6 vs. 6.7 days, P = 0.04) and a longer period on a ventilator (5.9 vs. 3.9 days, P = 0.04) than patients with normal albumin levels.
CONCLUSIONS: Hypoalbuminaemia at admission was a predictive factor of poor outcome in critically ill children. It is associated with a higher mortality, a longer length of stay in the PICU, as well as longer ventilator use.