Actual Risk Research Articles

A nomogram prediction model for the risk of intra-abdominal infection after endoscopic full-thick resection of gastric submucosal tumors

BackgroundThis study aimed to investigate the risk factors for complication of intra-abdominal infection (IAI) after endoscopic full-thickness resection of gastric submucosal tumors (GSMT) and to establish a nomogram prediction model for the occurrence of IAI. MethodsClinical data of patients with GSMT who underwent endoscopic full-thick resection (EFR) from January 2018 to July 2023 were retrospectively analyzed. The patients were divided into IAI and non-IAI groups according to whether IAI occurred during postoperative hospitalization. Univariate and multivariate logistic regression analyses were performed on the relevant clinical data of patients in the two groups to screen the independent influencing factors for the occurrence of IAI. The nomogram model was constructed based on the independent influencing factors. Model discrimination was assessed by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. The consistency of model-predicted risk with actual risk was evaluated using the Hosmer-Lemeshow goodness-of-fit test. The clinical performance of the nomogram model was evaluated using decision curve analysis. ResultsA total of 240 GSMT patients who underwent EFR procedures were finally included in this study, including 14 patients (5.83%) in the IAI group and 226 patients in the non-IAI group. Univariate and multivariate logistic regression analyses showed that age (OR=1.283, 95% CI=1.029∼1.600), preoperative albumin (OR= 0.575, 95% CI=0.395∼0.837), duration of operation (OR=1.222, 95% CI=1.060-1.409), and hospitalization time (OR=4.089, 95% CI=1.190-14.043) were independent influencing factors for the incidence of IAI in GSMT patients undergoing EFR surgery (P < 0.05). A Nomogram model was established based on the above factors. The Hosmer ⁃ Lemeshow test value of this model was 4.230 (P=0.836). The AUC value of the predictive model was 0.992 (95% CI: 0.983 to 1.000), with a C-index of 0.992 (95% CI: 0.983-1.000), indicating that the nomogram model had good accuracy and discrimination. Decision curve analysis showed that the nomogram model had a good predictive performance. ConclusionsAge, preoperative albumin, duration of operation, and hospitalization time were independent influences on the occurrence of IAI in GSMT patients undergoing EFR surgery. A nomogram model based on these factors had a high predictive efficacy and may provide a guiding intervention for the prevention of postoperative IAI in GSMT patients.

Characterization and potential toxicity of asbestiform erionite from Gawler Downs, New Zealand

Abstract Erionite is the name for a zeolite mineral series originating from diagenesis or hydrothermal alteration of volcanic rocks. The particular erionite “species” is based on the dominant extra-framework cation, erionite-Ca, erionite-K, or erionite Na. Irrespective of the species, erionite can display a fibrous/asbestiform morphology and has been linked with cases of malignant mesothelioma, a disease typically associated with asbestos exposure. Characterization of new discoveries of erionite is therefore important to assess any potential exposure hazards. This study describes a new asbestiform erionite from vesicles within the Upper Cretaceous Mt. Somers Volcanics Group (MSVG), Canterbury, New Zealand. The erionite is within the Hinds River Dacite, the youngest unit within the MSVG at Gawler Downs, ~100 km west of Christchurch, in the foothills of the Southern Alps. A multi-analytical approach was taken to analyze the sample which included micro-Raman spectroscopy, thermogravimetric analysis, electron microscopy, electron microprobe analysis, and X-ray powder diffraction with the Rietveld method. Results confirmed the mineral as fibrous erionite-K. The chemical composition of the mineral is unique due to the presence of higher levels of Mg. While Fe was also identified, this was due to smectite flakes occurring on the surface of the erionite fibers. According to the World Health Organization (WHO) respirable mineral fiber definition, where length ≥5 μm, width ≤3 μm, and aspect ratio (L/w) ≥3:1, the Gawler Downs erionite fibers are respirable, while the fibers themselves exceed respirable thickness. In addition to morphology, a value for the potential toxicity model was computed to be 2.28 for the Gawler Downs erionite. This is similar to those of other carcinogenic erionites from Karain, Turkey (2.33), and Nevada, U.S.A. (2.28). Taken together, results indicate Gawler Downs erionite represents an environmental hazard. Nevertheless, further investigation is required to determine potential environmental exposure pathways by which erionite may become airborne and assess the actual environmental risk in the Gawler Downs area.

An Assessment of Explosive and Fire Risks from Fighter Jet Collision with Aircraft Carrier

AbstractThis paper presents a framework for evaluating the risk of fire and explosion resulting from potential collisions between fighter jets and aircraft carriers. An event tree is a chronological order of risk issues that may arise from an initial event. This study creates an initial crash scenario based on actual accident cases and risk issues, which are event tree items. Using these scenarios, collision analysis is conducted utilizing finite element analysis to investigate the structural response. It allows us to identify potential fuel leakage and assess whether the collision impact is potent enough to activate the fuze of any onboard weaponry. Consequently, a series of fire analyses pertinent to the respective situations is executed. These analyses aim to discern whether hazardous conditions such as secondary fires or explosions will likely ensue post-collision. By simulating a possible collision scenario between a fighter jet and a flight deck, the proposed method systematically explores and understands the probability and consequences of fire and explosion events following such collisions.

Combined impact of heat and dust on diabetes hospitalization in Kuwait

IntroductionIn Kuwait, a severe diabetes and obesity epidemic coexists with intense dust storms and harsh summer heat. While, theoretically, this interplay between dust, heat, and diabetes presents a serious public...

Construction of a novel predictive model for hope level in patients with primary liver cancer from a positive psychology perspective

This study aimed to investigate the current hope levels in patients with primary liver cancer by analyzing the risk indicators of hope levels, constructing and validating a novel hope score-based predictive model. A total of 206 patients with primary liver cancer admitted to the hepato-pancreato-biliary surgery department of a tertiary hospital from October 2020 to June 2021 were included. The Herth Hope Index was utilized to assess hope levels, and based on the questionnaire results, the patients were categorized into low-hope (≤ 30 points) and high-hope (> 30 points) groups. Single-factor analysis and logistic multivariate regression analysis were conducted to explore the factors influencing hope levels in patients with primary liver cancer. A nomogram was plotted, and a risk prediction model for hope levels in these patients was developed. The predictive performance of the nomogram model was evaluated using calibration plots, the Hosmer–Lemeshow test, and other relevant assessments. Total of 206 patients participated in the questionnaire survey, with 82 patients (39.81%) categorized as belonging to the low-hope group. The results of the single-factor analysis showed statistically significant differences (all P < 0.05) in marriage status, education level, residence, occupation, family monthly income, reason for hospitalization or outpatient visit, pressure caused by the disease on the family, history of cirrhosis, and level of social support between the two groups. These variables were subsequently included in the logistic multivariate regression model. The results of the regression analysis indicated that marriage status, residence, family monthly income, and level of social support were independent risk factors. These four influencing factors were transformed into a visual predictive model, which yielded an area under the ROC curve of 0.931 (95% CI 0.899–0.963) and demonstrated model significance (Hosmer–Lemeshow test: χ2 = 4.008, P = 0.856, P > 0.05). The observed and expected values generated by the Hosmer–Lemeshow test were plotted as a scatter plot with a fitted linear trend, showing good consistency between the predictive model and actual risk. The constructed predictive model developed in this study exhibited good predictive capability for assessing the hope levels of patients with primary liver cancer. This model can assist clinical staff in rapidly identifying the psychological risk of low hope levels in patients, thereby providing valuable insights for the timely implementation of proactive management measures.

Establishment of predictive models and determinants of preoperative gastric retention in endoscopic retrograde cholangiopancreatography.

Study on influencing factors of gastric retention before endoscopic retrograde cholangiopancreatography (ERCP) background: With the wide application of ERCP, the risk of preoperative gastric retention affects the smooth progress of the operation. The study found that female, biliary and pancreatic malignant tumor, digestive tract obstruction and other factors are closely related to gastric retention, so the establishment of predictive model is very important to reduce the risk of operation. To analyze the factors influencing preoperative gastric retention in ERCP and establish a predictive model. A retrospective analysis was conducted on 190 patients admitted to our hospital for ERCP preparation between January 2020 and February 2024. Patient baseline clinical data were collected using an electronic medical record system. Patients were randomly matched in a 1:4 ratio with data from 190 patients during the same period to establish a validation group (n = 38) and a modeling group (n = 152). Patients in the modeling group were divided into the gastric retention group (n = 52) and non-gastric retention group (n = 100) based on whether gastric retention occurred preoperatively. General data of patients in the validation group and modeling group were compared. Univariate and multivariate logistic regression analyses were performed to identify factors influencing preoperative gastric retention in ERCP patients. A predictive model for preoperative gastric retention in ERCP patients was constructed, and calibration curves were used for validation. The receiver operating characteristic (ROC) curve was analyzed to evaluate the predictive value of the model. We found no statistically significant difference in general data between the validation group and modeling group (P > 0.05). The comparison of age, body mass index, hypertension, and diabetes between the two groups showed no statistically significant difference (P > 0.05). However, we noted statistically significant differences in gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction between the two groups (P < 0.05). Multivariate logistic regression analysis showed that gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction were independent factors influencing preoperative gastric retention in ERCP patients (P < 0.05). The results of logistic regression analysis revealed that gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction were included in the predictive model for preoperative gastric retention in ERCP patients. The calibration curves in the training set and validation set showed a slope close to 1, indicating good consistency between the predicted risk and actual risk. The ROC analysis results showed that the area under the curve (AUC) of the predictive model for preoperative gastric retention in ERCP patients in the training set was 0.901 with a standard error of 0.023 (95%CI: 0.8264-0.9567), and the optimal cutoff value was 0.71, with a sensitivity of 87.5 and specificity of 84.2. In the validation set, the AUC of the predictive model was 0.842 with a standard error of 0.013 (95%CI: 0.8061-0.9216), and the optimal cutoff value was 0.56, with a sensitivity of 56.2 and specificity of 100.0. Gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction are factors influencing preoperative gastric retention in ERCP patients. A predictive model established based on these factors has high predictive value.

Prediction model establishment and validation for enteral nutrition aspiration during hospitalization in patients with acute pancreatitis.

Acute pancreatitis (AP) is a disease caused by abnormal activation of pancreatic enzymes and can lead to self-digestion of pancreatic tissues and dysfunction of other organs. Enteral nutrition plays a vital role in the treatment of AP because it can meet the nutritional needs of patients, promote the recovery of intestinal function, and maintain the barrier and immune functions of the intestine. However, the risk of aspiration during enteral nutrition is high; once aspiration occurs, it may cause serious complications, such as aspiration pneumonia, and suffocation, posing a threat to the patient's life. This study aims to establish and validate a prediction model for enteral nutrition aspiration during hospitalization in patients with AP. To establish and validate a predictive model for enteral nutrition aspiration during hospitalization in patients with AP. A retrospective review was conducted on 200 patients with AP admitted to Chengdu Shangjin Nanfu Hospital, West China Hospital of Sichuan University from January 2020 to February 2024. Clinical data were collected from the electronic medical record system. Patients were randomly divided into a validation group (n = 40) and a modeling group (n = 160) in a 1:4 ratio, matched with 200 patients from the same time period. The modeling group was further categorized into an aspiration group (n = 25) and a non-aspiration group (n = 175) based on the occurrence of enteral nutrition aspiration during hospitalization. Univariate and multivariate logistic regression analyses were performed to identify factors influencing enteral nutrition aspiration in patients with AP during hospitalization. A prediction model for enteral nutrition aspiration during hospitalization was constructed, and calibration curves were used for validation. Receiver operating characteristic curve analysis was conducted to evaluate the predictive value of the model. There was no statistically significant difference in general data between the validation and modeling groups (P > 0.05). The comparison of age, gender, body mass index, smoking history, hypertension history, and diabetes history showed no statistically significant difference between the two groups (P > 0.05). However, patient position, consciousness status, nutritional risk, Acute Physiology and Chronic Health Evaluation (APACHE-II) score, and length of nasogastric tube placement showed statistically significant differences (P < 0.05) between the two groups. Multivariate logistic regression analysis showed that patient position, consciousness status, nutritional risk, APACHE-II score, and length of nasogastric tube placement were independent factors influencing enteral nutrition aspiration in patients with AP during hospitalization (P < 0.05). These factors were incorporated into the prediction model, which showed good consistency between the predicted and actual risks, as indicated by calibration curves with slopes close to 1 in the training and validation sets. Receiver operating characteristic analysis revealed an area under the curve (AUC) of 0.926 (95%CI: 0.8889-0.9675) in the training set. The optimal cutoff value is 0.73, with a sensitivity of 88.4 and specificity of 85.2. In the validation set, the AUC of the model for predicting enteral nutrition aspiration in patients with AP patients during hospitalization was 0.902, with a standard error of 0.040 (95%CI: 0.8284-0.9858), and the best cutoff value was 0.73, with a sensitivity of 91.9 and specificity of 81.8. A prediction model for enteral nutrition aspiration during hospitalization in patients with AP was established and demonstrated high predictive value. Further clinical application of the model is warranted.

Determinants of Hepatitis B Viral Infection among Pregnant Women in Greater Monrovia, Liberia

Background: The global prevalence of hepatitis B virus infection is estimated to affect over 2 billion individuals, with a notable proportion ranging from 6% to 25% residing in the Sub-Saharan African region. The prevalence of hepatitis B virus (HBV) in Liberia, Guinea, and Sierra Leone has been estimated to be approximately 2%. However, current understanding of the actual risk factors associated with HBV in the Greater Monrovia remains unclear. Consequently, this study aimed to identify the factors associated with hepatitis B viral infection among pregnant women residing in Greater Monrovia, Liberia. Methods: An unmatched case control study of 141 cases of HBV infected pregnant women and 141 controls was conducted. Data on socio-demographic characteristics, lifestyle activities and medical related risk factors were collected for both groups with a structured questionnaire. Bivariate and multivariate analyses established associations between the HBV infection and risk factors studied. Results: In all, 141 cases of HBV infected pregnant women and 141 controls participated in this study. The mean age of cases was 35.6 years (SD ±9.5) and 36.1 years (SD ±8.4) for controls. Low-income level &lt;100 dollars [aOR 13.0 (4.48-37.82, p&lt;0.001)], employment [aOR 0.04 (0.09-0.18) p&lt;0.001], STI history [aOR 5.19 (1.68-16.02, p=0.004)] and living with a HBV infected person [aOR 35.11 (4.24-58.90), p=0.001] were factors associated with HBV infection among pregnant women in Greater Monrovia. Conclusion: The risk factors of HBV infection among pregnant women in Greater Monrovia were engagement in formal employment, low-income level, history of sexually transmitted infections (STIs), and residing with an individual infected with hepatitis B virus (HBV). Control efforts by designated state institutions should include advocacy and awareness creation on HBV status identification, safe sex, and vaccination of uninfected individuals.

Single-center external validation and reconstruction of multiple predictive models for skip lateral lymph node metastasis in papillary thyroid carcinoma.

The unique metastatic pattern of skip lateral lymph node metastasis (SLLNM) in PTC patients may lead to missed diagnosis of lateral cervical metastatic lymph nodes. Therefore, many different SLLNM prediction models were constructed. In this study, partially eligible models (Hu 2020, Wang 2020, and Zhao 2023 nomograms) were selected for external validation, and then new variables were incorporated for model reconstruction to extend clinical applicability. 576 PTC patients from our center were selected to evaluate the performance of the three nomograms using the receiver operating characteristic curve (ROC), calibration curves, and decision curve analyses (DCA). Three new variables were added to calibrate the model, including assessment of LN status on ultrasound (US-SLLNM), the distance from the tumor to the capsule (Capsular distance), and the number of central lymph node dissections (CLND number). Univariate and multivariate logistic regression analyses were used to screen independent predictors to reconstruct the model, and 1000 Bootstrap internal validations were performed. SLLNM were present in 69/576 patients (12.0%). In external validation, the area under the ROC curves (AUCs) for Hu 2020, Wang 2020, and Zhao 2023 nomograms were 0.695 (95% CI:0.633-0.766), 0.792 (95% CI=0.73-0.845), and 0.769 (95% CI:0.713-0.824), respectively. The calibration curves for the three models were overall poorly fitted; DCA showed some net clinical benefit. Model differentiation and net clinical benefit improved by adding three new variables. Based on multivariate analysis, female, age, and maximum tumor diameter ≤ 10 mm, located at the upper pole, Capsular distance < 0mm, US-SLLNM, CLND number ≤ 5 were identified as independent predictors of SLLNM and were used to construct the new model. After 1000 Bootstrap internal validations, the mean AUC of the model was 0.870 (95% CI:0.839-0.901), the calibration curve was close to the ideal curve, and the net clinical benefit was significant. Overall, these nomograms were well differentiated and provided some net clinical benefit, but with varying degrees of underestimation or overestimation of the actual risk and high false-negative rates. New dynamic nomogram was constructed based on the addition of new variables and larger samples, showing better performance.

Total arsenic and arsenic species in selected seafoods: Analysis using high-performance liquid chromatography- inductively coupled plasma mass spectrometry and health risk assessment

The objective of the present study was to determine the inorganic and organic arsenic species and assess the actual risk of selected seafood produced in Sri Lanka in terms of inorganic arsenic species. A total of 80 samples, comprising 75 seafood samples and 5 freshwater samples, including mollusks, echinoderms, and crustaceans, were analyzed for their total arsenic (TA) levels and arsenic species. TA levels in seafood were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) after microwave digestion. Arsenic species, including arsenobetaine (AsB), arsenite (AsIII), arsenate (AsV), monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA), were selectively separated and quantified using High-Performance Liquid Chromatography (HPLC) coupled to ICP-MS, following water bath extraction with 30 mmol/L nitric acid. The TA levels in seafood ranged from 0.036 to 11.686 mg kg-1. The spike recovery values for the five arsenic species lay within 80 % to 120 %, and the chromatographic recovery percentages ranged from 85.5 % to 123.6 %. In most samples, 100 % AsB was detected. Sea cucumber and both marine and freshwater giant river prawns showed AsB percentages of the total arsenicals at 83.2 %, 39.7 %, and 21.3 %, respectively. DMA was found in sea cucumber and marine giant river prawn at levels of 0.065 mg kg-1 and 0.048 mg kg-1, respectively, while MMA was not detected in any samples. AsIII was found in marine water giant river prawn and freshwater giant river prawn at levels of 0.010 mg kg-1 and 0.044 mg kg-1, respectively. AsV was only found in marine giant river prawn at a concentration of 0.193 mg kg-1. No other samples contained detectable levels of inorganic arsenicals. The Target Hazard Quotient (THQ) values for marine and freshwater giant river prawn were 0.90 and 0.2, respectively, indicating no significant health risks since the THQ values were <1. Therefore, our study suggests that consuming the studied seafood does not pose any health risks in terms of arsenic.

Dynamic and probabilistic safety zones for autonomous mobile robots operating near humans

The inefficiency of maintaining static and long-lasting safety zones in environments where actual risks are limited is likely to increase in the coming decades, as autonomous systems become more common and human workers fewer in numbers. Nevertheless, an uncompromising approach to safety remains paramount, requiring the introduction of novel methods that are simultaneously more flexible and capable of delivering the same level of protection against potentially hazardous situations. We present such a method to create dynamic safety zones, the boundaries of which can be redrawn in real-time, taking into account explicit positioning data when available and using conservative extrapolation from last known location when information is missing or unreliable. Simulation and statistical methods were used to investigate performance gains compared to static safety zones. The use of a more advanced probabilistic framework to further improve flexibility is also discussed, although its implementation would not offer the same level of protection and is currently not recommended.

Soil erosion risk in the Mocache Canton applying multicriteria analysis and geographic information systems

Soil erosion is one of the main and most widespread types of soil degradation, determined by environmental and anthropogenic factors, which significantly impact the physical, chemical and biological properties of the soil, favoring its degradation. Consequently, through this research we sought to evaluate the risk of soil erosion in the canton of Mocache through the application of multicriteria analysis techniques and the use of geographic information systems (GIS). The CORINE model included several criteria for the zoning of potential and actual erosion risk, including erosivity, defined by the Modified Fournier Index (MFI) and the Bagnouls-Gaussen Aridity Index (BGI); erodibility, composed of soil texture, stoniness and depth; soil occupation; slope-orientation; and vegetation cover, through the estimation of the Normalized Difference Vegetation Index (NDVI). An expert consultation supported by Analytic Hierarchy Process (AHP) was applied to define the contribution of each criterion to erosion risk. The resulting layers were combined using a weighted relationship (map algebra) within the GIS environment. It was obtained that slope-orientation and erosivity explain a large part of the erosion risk, with a weighting of 42.46% and 27.48% in order, according to the expert evaluation and the AHP. The high erosivity was contributed by the predominant climatic factors: intense precipitation and high temperatures. In addition, it was found that the potentialand current erosion risk represent 13.1% (7,244 ha) and 10.7% (5,905 ha) of the territorial extension. It is concluded that physical-natural, meteorological factors and anthropogenic activities contribute to the risk of potential and current soil erosion in Mocache canton

Design and Implementation of a Generalized Safety Fault Diagnosis System for China Space Station Scientific Experimental Rack.

As astronauts stay in the China Space Station for a long time during the operation phase, how to ensure the long-term safety of the scientific experimental rack (SER) in the field of space application is a problem that needs to be solved urgently. Each SER in the field of space station applications is a complex system that faces risks from different hazards. At present, there is no generalized monitoring and diagnosis system for the common risks faced by the SER. In this paper, a generalized safety fault diagnosis system is proposed to ensure the long-term safe and stable work of SERs in orbit, considering the actual risks faced by the SER. With the design of a generalized main control board, a measurement and control board, and an SSPC (solid-state power controller) board, the software and hardware cooperate to realize the acquisition of various physical quantities, data processing, power supply and distribution management, and other functions. Combined with relevant fault detection algorithms, the real-time detection and diagnosis of the relevant risks, abnormality warnings, and fault disposal operations are realized, which can effectively ensure the safety of the payloads in the field of space application, astronauts, and the space-station system.

A nomogram for predicting colorectal cancer liver metastasis using circulating tumor cells from the first drainage vein

PurposeTo use circulating tumor cells (CTC) from the first drainage vein (FDV) of the primary lesion and other clinically relevant parameters to construct a nomogram for predicting liver metastasis in colorectal cancer (CRC) patients, and to provide a theoretical basis for clinical diagnosis and treatment. MethodsInformation from 343 CRC patients was collected and a database was established. Multivariate logistic analysis was used to identify independent factors for colorectal cancer liver metastasis(mCRC) and nomograms were constructed. Receiver operating characteristic curves(ROC), calibration plots, and decision curve analysis (DCA) were used to assess discrimination, agreement with actual risk, and the clinical utility of the prediction model, respectively. ResultCTC levels in FDV were significantly higher in patients with liver metastasis than in those without liver metastasis. Logistic multivariate analysis showed that vascular invasion, T stage, carcinoembryonic antigen (CEA), CA19-9, and CTC could be used as predictors to construct nomograms. The nomograms showed good discriminatory ability in predicting mCRC, with area under the curve (AUC) values of 0.871 [95 % CI: 0.817–0.924) and 0.891 (95 % CI: 0.817–0.964) for the training and validation sets, respectively.] The calibration curves of both the training and validation sets showed that the model was effective in predicting the probability of mCRC. DCA was used to evaluate this predictive model and showed good net clinical benefit. ConclusionWe developed and validated a nomogram model based on the combination of CTC in the FDV with other clinical parameters to better predict the occurrence of mCRC.

Clinical Trial Data-Driven Risk Assessment of Drug-Drug Interactions: A Rapid and Accurate Decision-Making Tool.

In clinical practice, the vast array of potential drug combinations necessitates swift and accurate assessments of pharmacokinetic drug-drug interactions (DDIs), along with recommendations for adjustments. Current methodologies for clinical DDI evaluations primarily rely on basic extrapolations from clinical trial data. However, these methods are limited in accuracy owing to their lack of a comprehensive consideration of various critical factors, including the inhibitory potency, dosage, and type of the inhibitor, as well as the metabolic fraction and intestinal availability of the substrate. This study aims to propose an efficient and accurate clinical pharmacokinetic-mediated DDI assessment tool, which comprehensively considers the effects of inhibitory potency and dosage of inhibitors, intestinal availability and fraction metabolized of substrates on DDI outcomes. This study focuses on DDIs caused by cytochrome P450 3A4 enzyme inhibition, utilizing extensive clinical trial data to establish a methodology to calculate the metabolic fraction and intestinal availability for substrates, as well as the concentration and inhibitory potency for inhibitors ( or ). These parameters were then used to predict the outcomes of DDIs involving 33 substrates and 20 inhibitors. We also defined the risk index for substrates and the potency index for inhibitors to establish a clinical DDI risk scale. The training set for parameter calculation consisted of 73 clinical trials. The validation set comprised 89 clinical DDI trials involving 53 drugs. which was used to evaluate the reliability of in vivo values of and , the accuracy of DDI predictions, and the false-negative rate of risk scale. First, the reliability of the in vivo and values calculated in this study was assessed using a basic static model. Compared with values obtained from other methods, this study values showed a lower geometric mean fold error and root mean square error. Additionally, incorporating these values into the physiologically based pharmacokinetic-DDI model facilitated a good fitting of the C-t curves when the substrate's metabolic enzymes are inhibited. Second, area under the curve ratio predictions of studied drugs were within a 1.5× margin of error in 81% of cases compared with clinical observations in the validation set. Last, the clinical DDI risk scale developed in this study predicted the actual risks in the validation set with only a 5.6% incidence of serious false negatives. This study offers a rapid and accurate approach for assessing the risk of pharmacokinetic-mediated DDIs in clinical practice, providing a foundation for rational combination drug use and dosage adjustments.

Assessing radon hazard in drinking water: A comprehensive approach integrating deterministic and probabilistic methods with water consumption routines

The research aimed to determine the spatiotemporal distribution patterns of radon activity concentrations in tap water of Yerevan city and assess radon-associated hazards using both deterministic and probabilistic approaches. This was accomplished by integrating one-year monitoring data of radon in water with water consumption habits among adult population clusters, which were identified through food frequency questionnaire in Yerevan.The study findings indicated variations in radon activity levels across administrative districts. The highest average activity concentrations were detected in Davtashen (7.07 Bq/L), while the lowest average was observed in Kanaker-Zeytun (1.57 Bq/L). The overall pattern of spatiotemporal variation during monitoring period revealed higher prevalence of radon in water in the northern and western parts of the city compared to the east and south, indicating different sources of drinking water. The radon-associated hazard assessment from water, using a deterministic approach (e.g., inhalation, ingestion, radon dissolution in blood, total effective dose), revealed values below the individual dose criterion (IDC) of 0.1 mSv/y. Monte Carlo simulation revealed a probability of exceeding IDC in specific water consumption-based groups. Residents of Yerevan who drink more than 3 L water daily with the highest observed activity concentration of 11.4 Bq/L, have an 86.26 % chance of exceeding IDC. Residents consuming 2.1 L water daily have a 7.02 % chance of exceeding IDC.The study highlights the importance of applied principles and methodologies for radon monitoring, particularly considering actual water consumption data and different risk assessment approaches. Considering the worst-case scenario results, it is recommended to keep tap water consumption up to 3 L per day, keeping the tap open longer to reduce radon levels. It also emphasizes the need for continued monitoring, given the variations in radon activity. The study provides valuable insights into radon exposure assessment, mitigation, and action plans in terms of water safety and public health.

Calculated PRA and PIRCHE Algorithm in Kidney Transplant Recipients

Abstract Introduction Calculated PRA testing in kidney transplantation has revolutionized the field by enabling a more accurate assessment of compatibility and risk prediction for AMR. On the other hand, The PIRCHE algorithm aims to identify the potentially immunogenic human leukocyte antigens (HLA) epitopes on the donor graft that are recognized by the recipient's HLA antibodies. The aim of this analysis was to compare the actual immunological risk at the time of transplantation with the hypothetical risk that would be determined by cPRA and PIRCHE. Another aim was to compare this hypothetical risk also in the context of the development of DSA and the protocol graft biopsy at month 3. Material and methods In a group of 20 patients we recorded the real immunological risk determined at the time of transplantation according to the induction immunosuppression protocol of the Transplant-Nephrology Department of the University Hospital Martin and compared it with the hypothetical calculated risk according to cPRA and PIRCHE. We then compared the hypothetical risk with the protocol biopsy result and with any evidence of donor-specific antibodies at month 3 after the kidney transplantation. Results Under cPRA, the two patients we assessed as medium risk in real time would be classified as low risk. Both of these patients did not have DSA identified at month 3 and did not have rejection changes in the protocol biopsy. According to PIRCHE, the immunological risk would change from moderate to low in two patients, and even from very high to low in one patient. In none of these patients did we subsequently observe DSA formation at month 3 post-transplantation, and also all three protocol biopsies were free of rejection changes in these patients. Conclusion In our analysis we confirmed the importance of both immunological and non-immunological parameters for determining risk at the time of transplantation. For using PIRCHE score larger studies are required to confirm this strategy.

Perceived versus actual HIV risk among PrEP indicated persons with criminal legal involvement

ABSTRACT Individuals involved with community supervision experience multi-level obstacles impacting health outcomes. This is a high-risk period for HIV acquisition due to potential reengagement in unprotected sex and/or unsafe injection drug practices. This study aimed to assess the congruence between actual and perceived HIV risk and the degree to which individual, social, and behavioral factors impact risk perception among individuals on community supervision. While all participants were clinically indicated for PrEP, most participants (81.5%) did not consider themselves at risk for HIV (69.5%) or were not sure of their risk (12.0%). Among those with no or unsure perceived risk, 94% engaged in sexual behaviors that put them at-risk of HIV. Perceived HIV risk was associated with sharing injection equipment (aPR = 1.8, 95% CI [1.02, 3.3]), identifying as a sexual minority (aPR = 2.3, 95% CI [1.3, 3.9]), and having sex with a partner living with HIV (aPR = 2.4, 95% CI [1.3, 4.3]). Having sex with a partner living with HIV was the only sexual risk behavior associated with a perceived risk of HIV. These findings indicate a substantial discrepancy between actual and perceived HIV risk, highlighting the need for targeted interventions to improve risk perception accuracy and enhance risk prevention among individuals on community supervision.

Prognostic factors of patients with human epidermal growth factor receptor 2-positive breast cancer following neoadjuvant therapy: Development and validation of a predictive nomogram

ObjectiveHuman epidermal growth factor receptor 2 (HER2)–positive breast cancer exhibits an aggressive phenotype and poor prognosis. The application of neoadjuvant therapy (NAT) in patients with breast cancer can significantly reduce the risks of disease recurrence and improve survival. By integrating different clinicopathological factors, nomograms are valuable tools for prognosis prediction. This study aimed to assess the prognostic value of clinicopathological factors in patients with HER2-positive breast cancer and construct a nomogram for outcome prediction. MethodsWe retrospectively analyzed the clinicopathological data from 374 patients with breast cancer admitted to the Fourth Hospital of Hebei Medical University between January 2009 and December 2017, who were diagnosed with invasive breast cancer through preoperative core needle biopsy pathology, underwent surgical resection after NAT, and were HER2-positive. Patients were randomly divided into a training and validation set at a ratio of 7:3. Univariate and multivariate survival analyses were performed using Kaplan-Meier and Cox proportional hazards regression models. Results of the multivariate analysis were used to create nomograms predicting 3-, 5-, and 8-year overall survival (OS) rates. Calibration curves were plotted to test concordance between the predicted and actual risks. Harrell C-index and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the discriminability of the nomogram prediction model. ResultsAll included patients were women, with a mean age of 50 ± 10.4 years (range: 26–72 years). In the training set, both univariate and multivariate analyses identified residual cancer burden (RCB) class, tumor-infiltrating lymphocytes(TILs), and clinical stage as independent prognostic factors for OS, and these factors were combined to construct a nomogram. The calibration curves demonstrated good concordance between the predicted and actual risks, and the C-index of the nomogram was 0.882 (95 % CI 0.863–0.901). The 3-, 5-, and 8-year areas under the ROC curve (AUCs) were 0.909, 0.893, and 0.918, respectively, indicating good accuracy of the nomogram. The calibration curves also demonstrated good concordance in the validation set, with a C-index of 0.850 (95 % CI 0.804–0.896) and 3-, 5-, and 8-year AUCs of 0.909, 0.815, and 0.834, respectively, which also indicated good accuracy. ConclusionThe nomogram prediction model accurately predicted the prognostic status of post-NAT patients with breast cancer and was more accurate than clinical stage and RCB class. Therefore, it can serve as a reliable guide for selecting clinical treatment measures for breast cancer.

Abnormal CSR Performance and Auditor Litigation Risk

Recent studies provide evidence that corporate social responsibility (CSR) conscious firms are less likely to engage in high-profile corporate misconduct and be subject to SEC investigations, suggesting that auditor litigation risk may be lower for better CSR performers. However, we argue that the association between CSR performance and auditor litigation risk may not be linear for two reasons. First, for a given level of audit risk, the lower the perceived risk of material misstatement, the higher the actual detection risk. Second, ceteris paribus, an incorrectly assessed low audit risk acceptable for abnormally high CSR performance would also increase auditor’s actual detection risk. Using a matched sample analysis for the period of 2004 to 2013, this study finds that the propensity for auditors to be sued first decreases as CSR performance improves, but then increases with excessively high abnormal CSR performance. Further analyses indicate that the convexity of CSR performance on auditor detection risk arises from the inherent risk channel (client business risk, financial misreporting, and earnings management), but not from the control risk channel (internal control material weaknesses). This study provides new insights on the signaling value of CSR performance on an auditor’s litigation risk.