Total Risk Score Research Articles

Risk-Based Completion Cost Overrun Ratio Estimation in Construction Projects Using Machine Learning Classification Algorithms: A Case Study

Estimating the completion cost accurately in the early phases of construction projects is critical to their success. However, cost overruns are almost inevitable due to the risks inherent in construction projects. Hence, the completion cost fluctuates throughout the execution phase and requires periodic updates. There is a need for a prompt and user-friendly completion cost estimation model that accounts for fluctuating risk scores and their impacts on the total cost during the execution phase. Machine learning (ML) techniques could address these requirements by providing effective methods for tackling dynamic systems. The proposed approach aims to predict the cost overrun ratio classes of the completion cost according to the changes in the total risk scores at any time of the project. Six classification algorithms were utilized and validated by employing 110 data points from a globally operating construction company. The performances of the algorithms were evaluated with validation and performance indices. The decision tree classifier surpassed other algorithms. Although there are some research limitations, including risk perception, data gathering restrictions, and selecting proper ML algorithms upon data properties, this research improves the planning abilities of construction executives by providing a cost overrun ratio based on changing total risk scores, facilitating swift and simple assessments at any stage of a construction project’s execution.

A Risk Tool for Evaluating Overuse Injury and Return-to-Play Time Periods in Youth and Collegiate Athletes: Preliminary Study.

Overuse injuries in youth athletes are associated with risks, including sports specialization, biological maturation, female sex, and workload measures. As no assessment tool exists to evaluate risk accumulation, we developed a novel risk factor scoring system (Sport Training Assessment of Risk [STAR]) to assess participants' risk of overuse injury and explore association with return-to-play (RTP) time periods. (1) STAR will reach an acceptable predictive threshold in the assessment of overuse injury in youth athletes. (2) Higher STAR scores will be associated with increased RTP time periods after injury. Longitudinal cohort study. Level 3. Youth athletes with an injury sustained during competitive sport completed questionnaires. Association of questionnaire variables with injury risk type was evaluated via logistic regression analyses, and unweighted and weighted versions of a total risk score were developed. RTP was defined by physician clearance per electronic medical record review. Mantel-Haenszel chi-square tests and Kendall's rank correlation coefficients were used to assess the relationship between weighted total risk score and RTP time periods. The weighted STAR model was analyzed with receiver operating characteristic (ROC) curves. The weighted STAR model trended toward an acceptable level of prediction for overuse (nonserious + serious) injury (area under the ROC curve [AUC], 0.66; 95% CI, 0.61-0.71), but was less predictive for serious overuse injury (AUC, 0.63; 95% CI, 0.55-0.71). Weighted total risk score was weakly associated with return to full play (ρ = 0.11; P < 0.01), and potentially with return to modified play (ρ = -0.08; P = 0.04). STAR may be a feasible tool for assessing overuse injury risk and RTP time periods in youth athletes but requires further development, as it did not reach an acceptable predictive threshold in this preliminary study. Clinicians can use STAR to assess overuse injury risk in youth athletes.

6967 Simple Prediction Model for Vitamin D Deficiency in Women with Osteoporosis or Risk Factors for Osteoporosis

Abstract Disclosure: T. Mullikapipat: None. N. Dumrongwongsuwinai: None. O. Vallibhakara: None. S. Rattanasiri: None. S. Vallibhakara: None. W. Wajanavisit: None. B. Ongphiphadhanakul: None. H. Nimitphong: None. Background: People at high risk of vitamin D deficiency, such as those at risk of osteoporosis, should have their 25-hydroxyvitamin D [25(OH)D] levels assessed. The availability and cost of 25(OH)D measurement in Thailand are both restricted. The objective of this study was to create a model for predicting vitamin D deficiency in women with osteoporosis or risk factors for osteoporosis. Methods: This was a cross-sectional study of women with or at risk of osteoporosis who visited Ramathibodi Hospital's outpatient clinics (medicine, obstetrics and gynecology, and orthopedic) between August 2016 and August 2019. All participants were assessed their 25(OH)D using a chemiluminescent assay (Liaison, DiaSorin Inc.; Stillwater, MN). Each participant completed a questionnaire to determine vitamin D intake through supplementation and sun exposure, as well as the existence of factors impacting vitamin D status. Vitamin D deficiency was defined as 25(OH)D levels less than 30 ng/mL. Logistic regression analyses were used to examine the predictors of vitamin D deficiency. In the vitamin D deficiency prediction model, odds ratios (OR) were converted into simple scores. The sensitivity, specificity, and positive and negative predictive values of the different cutoffs in the total risk score were calculated and used to establish the optimum cutoff for those at high risk of vitamin D deficiency. Internal validation on this model was carried out using a bootstrap resampling method of 1000. Results: Sixty percent of participants had vitamin D deficiency. The final model (n=488) for the prediction of vitamin D deficiency consisted of BMI ≥ 25 kg/m2 [OR 1.15, 95% confidence interval(CI) 0.99-2.30), no exercise (OR 1.59, 95% CI 1.02-2.49), exercise 1-2 times/week (OR 1.40, 95% CI 0.79-2.46), sunlight exposure &amp;lt; 15 minutes/day (OR 1.70, 95% CI 1.04-2.78), no vitamin D supplementation (OR 8.76, 95% CI 5.02-15.28), and vitamin D supplementation ≤ 20,000 IU/day (OR 2.31, 95% CI 1.34-3.96). The area under the curve was 0.747. At a cutoff of 6.6 in total risk score (range 4-13.6), the model predicted vitamin D deficiency with a sensitivity of 71.9 and a specificity of 65.3. The internal validation by Bootstrap revealed a ROC of 0.752 (95%CI 0.751-0.754). Conclusions: In women at risk of osteoporosis, a simple questionnaire can uncover variables related to vitamin D deficiency. The risk score might be used in clinical practice to identify individuals who could benefit from vitamin D supplementation without requiring 25(OH)D levels to be measured. However, external validation in a different cohort is required before implementation. Presentation: 6/2/2024

B-136 From Result to Response: The Development of Laboratory-Based Scoring Models to Predict COVID-19 Patient Outcomes

Abstract Background Patient characteristics relating to increased risk for COVID-19 severity are well-documented, including older age and pre-existing health concerns; however, methods to accurately predict patients’ acute reaction to SARS-CoV-2 infections remain lacking. Identification of specific laboratory tests informative of patient outcomes could effectively screen incoming patients and better inform physicians regarding optimal treatment plans. The aim of this study was to examine associations between frequently ordered laboratory markers and COVID-19 patient mortality to develop an objective laboratory-based scoring system that estimates patients’ risk of mortality. Methods Study participants included inpatients from 3 hospitals recruited into the GENCOV project based in Ontario, Canada. Participants (n=325) were at least 18 years of age, provided consent, and were hospitalized within 1 month of having a PCR confirmed COVID-19 infection between January 2020 and February 2022. Extensive clinical data including patient demographics, laboratory results, and treatment outcomes were extracted from patient’s electronic medical records (EMR). Results for 32 biochemical and hematological tests including complete blood cell counts, coagulation (activated partial thromboplastin time, D-dimer, fibrinogen, prothrombin time), general chemistry (albumin, blood gases, creatine kinase, electrolytes, glucose, triglycerides), inflammatory (lactate dehydrogenase, ferritin, C-reactive protein), liver (alanine aminotransferase, aspartate aminotransferase, total bilirubin), renal (creatinine, urea) and cardiac (troponin, NT-proBNP, BNP) markers were collected from each chart. Univariable logistic regression with nested likelihood ratio tests were used to determine significant associations between laboratory results and patient outcomes. Significant markers were incorporated into multivariable models and variable risk values were assigned. Total calculated risk scores for each participant were compared using univariable and multivariable risk values. Validation of each scoring method was performed on a 20% subset of inpatients. Receiver operating characteristic (ROC) curves evaluated model performance. Results Six laboratory markers were associated with COVID-19 patient mortality when controlling for age and sex. Univariable regression showed that elevated creatinine, elevated lactate, elevated white blood cell, low base excess, low bicarbonate, or low pH results upon admission were significantly associated with increased odds of mortality, in comparison to test results within the reference range for these same markers. Multivariable regression revealed fewer markers (only low bicarbonate and low base excess) showing significant associations with COVID-19 mortality. Area under the ROC curves (AUC) determined that risk scores derived from univariable values performed similarly to multivariable values in validation (0.800 vs 0.802) and development cohorts (0.821 vs 0.829). Total risk scores calculated from the univariable vs multivariable models suggest higher sensitivity (90% vs 85%) than specificity (58% vs 67%) in the validation cohort, whereas the development cohort had higher sensitivity (88%) than specificity (66%) with univariable scores, and higher specificity (81%) than sensitivity (74%) with multivariable scores. Conclusions Laboratory results associated with COVID-19 mortality following both univariable and multivariable analyses suggest hospitalized patients infected with SARS-CoV-2 may present with acidosis. Total risk scores derived from univariable and multivariable values performed similarly in predicting mortality; however, differences in marker significance between models indicate discrepancies with risk interpretation. Further comparison of the created risk score assessments with equivalent models in other populations is warranted.

A new quantitative method for determining patient risk for reusable medical device categorization based on using and interpreting Kremer’s cleaning classification system

The cleaning of reusable medical devices involves inherent challenges that can impact on the effectiveness of the cleaning process; consequently, the subsequent safety of patients. Fluid dynamics play a critical role in determining the flow and distribution of cleaning agents where the design of the device can either facilitate or hinder this important process. Complex geometries, narrow channels, or irregular surfaces can impede effective flushing of contaminants leading to incomplete cleaning that creates a greater likelihood for patient contamination risks. Device features (n =23) were exposed to the most challenging cleaning conditions to find the point of failure in both fluid dynamics and soil retention. Experimental results obtained from the aforementioned along with associated compound risks were used to assign a risk value. Using the "hardest to clean" device feature approach as the base risk value, the total quantitative risk score was calculated for different reusable medical devices from numerical values obtained from addressing 14 questions focusing on variability in geometry, material use, types of cleaning, and intended patient use. Patient risk values for devices with different features were calculated from using Kremer's cleaning categories based on position within value ranges. Occurrences less than 18 correspond to minimal risk devices while a total risk score between the values of 18-39 are moderate and equal to or above 40 scores corresponds to the maximal category. Application of this quantitative assessment approach will facilitate appropriate mitigation of risk for cleaning reusable medical devices by informing use of targeted effective interventions. Future use of this Kremer cleaning classification will complement and augment disinfection and sterilization modalities.

Abstract A027: Ethnic variations in breast cancer risk factors distribution in Guam, HIPIMR study

Abstract Background: Guam has significant ethnic disparities in breast cancer incidence, with rates varying from 46.7 per 100,000 among Asian women to 137.5 per 100,000 among Micronesian women. Incidence rates for Filipino, CHamoru (indigenous people), and White women are 59.8, 94.0, and 121.9 per 100,000, respectively (2013-2017). The Hawai‘i and Pacific Island Mammography Registry (HIPIMR), a collaborative effort between the University of Hawai‘i Cancer Center and the University of Guam Cancer Research Center, collects health and breast imaging data to enhance early cancer detection tailored to the unique ethnic profiles of women in Hawai‘i and Guam. This study aims to identify the distribution of breast cancer risk factors among different ethnic groups in women undergoing screening in Guam. Differences in the prevalence of risk factors may explain variations in incidence patterns. Methods: This study included 1,413 women undergoing mammography screening at FHP Health Center in Guam, from November 2023 to May 2024. The risk factors were classified as follows: BMI (≥25), age of menarche (≤13), age of first pregnancy (≥30), number of live births (≤1), age of menopause (≥55), and family history of first-degree relatives. The robust Poisson method was used to estimate prevalence ratios (PR) of risk factors among ethnic groups, adjusted for age and education. Asians were used as the reference group due to their lowest incidence rates. Furthermore, the total risk score was calculated by summing all the risk factors. ANOVA was used to test the differences in average risk scores among different ethnic groups. Results: All ethnic groups had significantly higher prevalence of being overweight or obese compared to Asian women. The prevalence ratios were highest for Micronesians (PR=1.73, 95% CI: 1.40, 2.13) and CHamoru (PR=1.55, 95% CI: 1.27, 1.90). CHamoru women had the highest rates of breast cancer family history (PR=1.74, 95% CI: 1.19, 2.54). However, CHamoru women had a lower prevalence of having a small number of live births (PR=0.39, 95% CI: 0.24, 0.65) and an older age at first birth (PR=0.83, 95% CI: 0.71, 0.96) when compared to Asian women. There was a significant difference in average score among ethnic groups (P&amp;lt;.001). CHamoru women had significantly higher score (2.35) than Filipino (2.08) and Asian (2.00) women. Conclusion: Our study reveals disparities in risk factors across ethnic groups, consistent with the Guam Cancer Registry's reports of high breast cancer rates among Micronesian and CHamoru women. This project is ongoing, with the aim of linking our data with the Guam Cancer Registry. This linkage will enable us to identify breast cancer cases among participants and compare risk factors across different ethnic groups for women with and without breast cancer. Acknowledgement: This research was funded by the National Cancer Institute: The University of Guam/University of Hawaii Cancer Center Partnership to Advance Cancer Health Equity, Grant U54CA143728 (University of Guam, YCP)/Grant U54CA143727 (University of Hawaii Cancer Center). Citation Format: Gian Paras, Su Bin Jin, Rose Grino, Cabrini Aguon, John Shepherd, Grazyna Badowski. Ethnic variations in breast cancer risk factors distribution in Guam, HIPIMR study [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A027.

Impulsivity, trauma history, and interoceptive awareness contribute to completion of a criminal diversion substance use treatment program for women.

In the US, women are one of the fastest-growing segments of the prison population and more than a quarter of women in state prison are incarcerated for drug offenses. Substance use criminal diversion programs can be effective. It may be beneficial to identify individuals who are most likely to complete the program versus terminate early as this can provide information regarding who may need additional or unique programming to improve the likelihood of successful program completion. Prior research investigating prediction of success in these programs has primarily focused on demographic factors in male samples. The current study used machine learning (ML) to examine other non-demographic factors related to the likelihood of completing a substance use criminal diversion program for women. A total of 179 women who were enrolled in a criminal diversion program consented and completed neuropsychological, self-report symptom measures, criminal history and demographic surveys at baseline. Model one entered 145 variables into a machine learning (ML) ensemble model, using repeated, nested cross-validation, predicting subsequent graduation versus termination from the program. An identical ML analysis was conducted for model two, in which 34 variables were entered, including the Women's Risk/Needs Assessment (WRNA). ML models were unable to predict graduation at an individual level better than chance (AUC = 0.59 [SE = 0.08] and 0.54 [SE = 0.13]). Post-hoc analyses indicated measures of impulsivity, trauma history, interoceptive awareness, employment/financial risk, housing safety, antisocial friends, anger/hostility, and WRNA total score and risk scores exhibited medium to large effect sizes in predicting treatment completion (p < 0.05; ds = 0.29 to 0.81). Results point towards the complexity involved in attempting to predict treatment completion at the individual level but also provide potential targets to inform future research aiming to reduce recidivism.

Genetic Risk, Health-Associated Lifestyle, and Risk of Early-onset Total Cancer and Breast Cancer.

Early-onset cancer (diagnosed under age 50) generally manifests as an aggressive disease phenotype. The association between healthy lifestyle and early-onset cancer and whether it varies by common genetic variants remains unclear. We analyzed a prospective cohort of 66,308 participants who were under age 50 and free of cancer at baseline in the UK Biobank. Using Cox regression, we estimated Hazard ratios (HRs) and 95% confidence intervals (CIs) for early-onset total and breast cancer based on sex-specific composite total cancer polygenic risk scores (PRSs), a breast cancer-specific PRS, and sex-specific health-associated lifestyle scores (HLSs). In multivariable-adjusted analyses with 2-year latency, higher genetic risk (highest vs lowest tertile of PRS) was associated with significantly increased risks of early-onset total cancer in females (HR, 95% CI: 1.83, 1.49-2.26) and males (2.03, 1.51-2.73) as well as early-onset breast cancer in females (3.06, 2.20-4.26). An unfavorable lifestyle (highest vs lowest category of HLS) was associated with higher risk of total cancer and breast cancer in females across genetic risk categories; the association with total cancer and breast cancer was stronger in the highest genetic risk category than the lowest: HRs (95% CIs) were 1.55 (1.12, 2.14) and 1.69 (1.11, 2.57) in the highest genetic risk category and 1.03 (0.64, 1.67) and 0.81 (0.36, 1.85) in the lowest. Genetic and lifestyle factors were independently associated with early-onset total and breast cancer risk. Individuals with a high genetic risk may benefit more from adopting a healthy lifestyle in preventing early-onset cancer.

Comparing Static-99R and STABLE-2007 profiles of people convicted of sexual offences in Hong Kong to Western normative data

ABSTRACT This study investigates cross-cultural applications of Static-99R and STABLE-2007 in assessing sexual recidivism risk in Hong Kong. Comparing scores of 249 incarcerated individuals convicted of sexual offences in Hong Kong with Western norms, results show greater cultural similarities in STABLE-2007 than Static-99R items. Hong Kong offenders exhibit higher total risk scores than those reported in Western validation samples. Notably, they appeared to ‘specialise’ in non-contact offences like taking up-skirt pictures, were less criminally involved, and had more non-male strangers or non-family members victims compared to Western validation samples. These findings underscore the importance of culturally sensitive risk assessment tools in diverse contexts. PRACTICE IMPACT STATEMENT In response to recent calls to examine the cross-cultural application of western-developed risk assessment tools, the present study examined the applicability of the Static-99R and STABLE-2007 among a sample of persons who had sexually offended in Hong Kong (HK). The research supported the Evaluation and Treatment Unit’s recent attempts to strengthen seamless continuation of care from custody and community, as the sentences of these individuals typically last for only a few weeks.

A pilot clinical risk model to predict polymyxin-induced nephrotoxicity: a real-world, retrospective cohort study.

Polymyxin-induced nephrotoxicity (PIN) is a major safety concern and challenge in clinical practice, which limits the clinical use of polymyxins. This study aims to investigate the risk factors and to develop a scoring tool for the early prediction of PIN. Data on critically ill patients who received intravenous polymyxin B or colistin sulfate for over 24 h were collected. Logistic regression with the least absolute shrinkage and selection operator (LASSO) was used to identify variables that are associated with outcomes. The eXtreme Gradient Boosting (XGB) classifier algorithm was used to further visualize factors with significant differences. A prediction model for PIN was developed through binary logistic regression analysis and the model was assessed by temporal validation and external validation. Finally, a risk-scoring system was developed based on the prediction model. Of 508 patients, 161 (31.6%) patients developed PIN. Polymyxin type, loading dose, septic shock, concomitant vasopressors and baseline blood urea nitrogen (BUN) level were identified as significant predictors of PIN. All validation exhibited great discrimination, with the AUC of 0.742 (95% CI: 0.696-0.787) for internal validation, of 0.708 (95% CI: 0.605-0.810) for temporal validation and of 0.874 (95% CI: 0.759-0.989) for external validation, respectively. A simple risk-scoring tool was developed with a total risk score ranging from -3 to 4, corresponding to a risk of PIN from 0.79% to 81.24%. This study established a prediction model for PIN. Before using polymyxins, the simple risk-scoring tool can effectively identify patients at risk of developing PIN within a range of 7% to 65%.

Risk predictive score and cord morphology classification for intraoperative neuromonitoring alerts in kyphosis surgery

BACKGROUNDIntraoperative neuromonitoring (IONM) alert is one of the worrying events of kyphosis corrective surgery, which can result in a postoperative neurological deficit. To our knowledge, there is no risk prediction score to predict such events in patients undergoing kyphosis surgery. PURPOSETo develop a new preoperative MRI-based cord morphology classification (CMC) and risk prediction score for predicting IONM alerts in patients with kyphotic deformity. STUDY DESIGNRetrospective analysis of prospectively collected data. PATIENT SAMPLEAbout 114 patients undergoing surgical correction for kyphotic deformity. OUTCOME MEASURESIntraoperative neuromonitoring alerts and postoperative neurological status using AIS grading. METHODSKyphotic deformity patients undergoing posterior spinal fusion were retrospectively reviewed. Based on the morphology of the spinal cord and surrounding CSF in MRI, there are 5 types of cord. Type 1 (normal cord): circular cord with surrounding visible CSF between the cord and the apex, Type 2 (flattened cord): cord with <50% distortion at the apex with obliteration of the anterior CSF; Type 3 (deformed cord): cord with >50% distortion at the apex with complete obliteration of the surrounding CSF; Type 4 (stretched cord): the cord is stretched and atrophied over the apex of the curve. Type 5 (translated cord): horizontal translation of the cord at the apex with buckling collapse of the vertebral column. Preoperative radiographs were used to measure the preoperative sagittal cobbs angle, sagittal deformity angular ratio (S-DAR), sagittal vertical axis (SVA), apex of the curve, and type of kyphosis. Clinical data like the duration of symptoms, clinical signs of myelopathy, neurological status (AIS grade), grade of myelopathy using the mJOA score, and type of osteotomy were documented. Multivariate logistic regression was used to determine the risk factors for IONM alerts and the risk prediction score was developed which was validated with new cohort of 30 patients. RESULTSA total of 114 patients met the inclusion criteria. IONM alerts were documented in 33 patients (28.9%), with full recovery of the signal in 25 patients and a postoperative deficit in 8 patients. Rate of IONM alerts was significantly higher in Type 5 (66%), followed by Type 4 (50%), Type 3 (21.1%), Type 2 (11.1%), and Type 1 (11.1%) (p-value<.001). Based on multiple logistic regression, 7 factors, namely preoperative neurological status, mJOA score≤6, presence of signs of myelopathy, apex of the curve above T5, preoperative sagittal cobbs, S-DAR, and MRI-based CMC, were identified as risk predictors. The value for the risk factors varies from 0 to 4, and the maximum total risk score was 13. The cut-off value of 6 had good sensitivity (84.9%) and specificity (77.8%) indicating a high risk for IONM alerts. The AUC of the predictive model was 0.92, indicating excellent discriminative ability. CONCLUSIONWe developed and validated a risk predictive score that identifies patients at risk of IONM alerts during kyphosis surgery. Identification of such high-risk patients (risk score≥6) helps in proper evaluation and preoperative counselling and helps in providing a proper evidence-based reference for treatment strategies.

Long-term endoscopic gastric mucosal changes up to 20 years after Helicobacter pylori eradication therapy

Helicobacter pylori eradication therapy reduces the risk of gastric cancer. However, it is unclear whether the severity of risk factors for gastric cancer such as atrophy and intestinal metaplasia are reduced after eradication in the long term. We aimed to study long-term changes in endoscopic risk factors for gastric cancer up to 20 years post-eradication. The endoscopic severity of gastritis according to the Kyoto Classification of Gastritis in 167 patients was retrospectively evaluated over an average follow-up 15.7 years. A significant improvement in mean total gastric cancer risk score (4.36 ± 1.66 to 2.69 ± 1.07, p < 0.001), atrophy (1.73 ± 0.44 to 1.61 ± 0.49, p = 0.004), and diffuse redness (1.22 ± 0.79 to 0.02 ± 0.13, p < 0.001) was observed compared to baseline in the Eradication group. However, there was no change in the never infection and current infection groups. The frequency of map-like redness increased over time until 15 years (3.6% to 18.7%, p = 0.03). The Cancer group had significantly higher risk scores at all time points. Endoscopic atrophy significantly improved in eradicated patients over long-term, suggested that eradication is one of the key elements in gastric cancer prevention. Individualized surveillance strategies based on endoscopic gastritis severity before eradication may be important for those at risk of gastric cancer.

Sex Differences, Age, and Burn Size Contribute to Risk of PTSD and Depression After Burn Injury.

The prevalence of psychological symptoms in burn survivors has been well documented; however, the role of biological sex requires further investigation. This study explored sex differences among burn survivors and examined the impact of sex, age, and total body surface area (TBSA) of the burn injury on (1) the risk of developing PTSD and depression and, subsequently, (2) the influence of initial risk on symptom outcomes 30 days post-injury. Participants included 374 adult patients enrolled in the Burn Behavioral Health program at a regional Burn Center. T-tests and chi-square tests were conducted to determine differences between sexes on outcome measures. A path analysis was conducted to evaluate relationships between variables of interest. Findings revealed significant sex discrepancies in risk and symptom outcomes. Compared to men, women reported greater total risk scores of developing PTSD and depression (p = .005) early after their burn injury. A subscale analysis showed that women reported greater risk scores on depression (p < .001), but not on PTSD. Women did not report higher depression scores 30 days post-injury compared to men but did report higher PTSD scores than men (p = .020). When sex, age, and TBSA were included in a path analysis, female sex (p=.001), younger age (p<.001), and larger TBSA of the burn injury (p=.024) were associated with greater risk. Additionally, risk scores significantly predicted PTSD (p<.001) and depression (p<.001) symptoms 30 days post-injury. Our research shows how sex, age, and TBSA affect the risk of PTSD and depression among burn survivors. It underscores the importance of accounting for sex and age differences in mental health risk, especially in women and younger patients. This emphasizes the urgency of early screening and intervention.

Construction of a prognostic model for extensive-stage small cell lung cancer patients undergoing immune therapy in northernmost China and prediction of treatment efficacy based on response status at different time points

Background and purposeRecently, the emergence of immune checkpoint inhibitors has significantly improved the survival of patients with extensive-stage small cell lung cancer. However, not all patients can benefit from immunotherapy; therefore, there is an urgent need for precise predictive markers to screen the population for the benefit of immunotherapy. However, single markers have limited predictive accuracy, so a comprehensive predictive model is needed to better enable precision immunotherapy. The aim of this study was to establish a prognostic model for immunotherapy in ES-SCLC patients using basic clinical characteristics and peripheral hematological indices of the patients, which would provide a strategy for the clinical realization of precision immunotherapy and improve the prognosis of small cell lung cancer patients.MethodsThis research retrospectively collected data from ES-SCLC patients treated with PD-1/PD-L1 inhibitors between March 1, 2019, and October 31, 2022, at Harbin Medical University Cancer Hospital. The study data was randomly split into training and validation sets in a 7:3 ratio. Variables associated with patients’ overall survival were screened and modeled by univariate and multivariate Cox regression analyses. Models were presented visually via Nomogram plots. Model discrimination was evaluated by Harrell’s C index, tROC, and tAUC. The calibration of the model was assessed by calibration curves. In addition, the clinical utility of the model was assessed using a DCA curve. After calculating the total risk score of patients in the training set, patients were stratified by risk using percentile partitioning. The Kaplan–Meier method was used to plot OS and PFS survival curves for different risk groups and response statuses at different milestone time points. Differences in survival time groups were compared using the chi-square test. Statistical analysis software included R 4.1.2 and SPSS 26.ResultsThis study included a total of 113 ES-SCLC patients who received immunotherapy, including 79 in the training set and 34 in the validation set. Six variables associated with poorer OS in patients were screened by Cox regression analysis: liver metastasis (P = 0.001), bone metastasis (P = 0.013), NLR < 2.14 (P = 0.005), LIPI assessed as poor (P < 0.001), PNI < 51.03 (P = 0.002), and LDH ≥ 146.5 (P = 0.037). A prognostic model for immunotherapy in ES-SCLC patients was constructed based on the above variables. The Harrell’s C-index in the training and validation sets of the model was 0.85 (95% CI 0.76–0.93) and 0.88 (95% CI 0.76–0.99), respectively; the AUC values corresponding to 12, 18, and 24 months in the tROC curves of the training set were 0.745, 0.848, and 0.819 in the training set and 0.858, 0.904 and 0.828 in the validation set; the tAUC curves show that the overall tAUC is > 0.7 and does not fluctuate much over time in both the training and validation sets. The calibration plot demonstrated the good calibration of the model, and the DCA curve indicated that the model had practical clinical applications. Patients in the training set were categorized into low, intermediate, and high risk groups based on their predicted risk scores in the Nomogram graphs. In the training set, 52 patients (66%) died with a median OS of 15.0 months and a median PFS of 7.8 months. Compared with the high-risk group (median OS: 12.3 months), the median OS was significantly longer in the intermediate-risk group (median OS: 24.5 months, HR = 0.47, P = 0.038) and the low-risk group (median OS not reached, HR = 0.14, P = 0.007). And, the median PFS was also significantly prolonged in the intermediate-risk group (median PFS: 12.7 months, HR = 0.45, P = 0.026) and low-risk group (median PFS not reached, HR = 0.12, P = 0.004) compared with the high-risk group (median PFS: 6.2 months). Similar results were obtained in the validation set. In addition, we observed that in real-world ES-SCLC patients, at 6 weeks after immunotherapy, the median OS was significantly longer in responders than in non-responders (median OS: 19.5 months vs. 11.9 months, P = 0.033). Similar results were obtained at 12 weeks (median OS: 20.7 months vs 11.9 months, P = 0.044) and 20 weeks (median OS: 20.7 months vs 11.7 months, P = 0.015). Finally, we found that in the real world, ES-SCLC patients without liver metastasis (P = 0.002), bone metastasis (P = 0.001) and a total number of metastatic organs < 2 (P = 0.002) are more likely to become long-term survivors after receiving immunotherapy.ConclusionThis study constructed a new prognostic model based on basic patient clinical characteristics and peripheral blood indices, which can be a good predictor of the prognosis of immunotherapy in ES-SCLC patients; in the real world, the response status at milestone time points (6, 12, and 20 weeks) can be a good indicator of long-term survival in ES-SCLC patients receiving immunotherapy.

Maternal Risk Factors for Respiratory Syncytial Virus Lower Respiratory Tract Infection in Otherwise Healthy Preterm and Term Infants: A Systematic Review and Meta-analysis.

To date, there is no published, formal assessment of all maternal risk factors for respiratory syncytial virus lower respiratory tract infection (RSV-LRTI) in infants. A systematic literature review and meta-analysis were undertaken to ascertain: What maternal risk factors are associated with an increased risk of RSV-LRTI in infants? The systematic literature review used explicit methods to identify, select and analyze relevant data. PubMed, Embase and the Cochrane Library were searched (November 2022) using terms regarding: (1) RSV/LRTI; (2) risk factors; (3) pregnant/postpartum population. Bayesian meta-analysis compared RSV hospitalization (RSVH) risk in infants born to mothers with or without certain risk factors. A total of 2353 citations were assessed and 20 were included in the final review (10 individual studies; 10 pooled analyses). In 10 studies examining infants (<1 year) without comorbidities (primary outcome), 10 maternal risk factors were associated with RSV-LRTI/RSVH in multivariate analyses. Meta-analysis revealed smoking while pregnant increased infant RSVH risk by 2.01 (95% credible interval: 1.52-2.64) times, while breast-feeding was protective (0.73, 95% credible interval: 0.58-0.90). Risk scoring tools have reported that maternal risk factors contribute between 9% and 21% of an infant's total risk score for RSVH. A greater understanding of maternal risk factors and their relative contribution to infant RSV-LRTI will enable more accurate assessments of the impact of preventive strategies.

A Predefined Rule-Based Multi-Factor Risk Stratification Is Associated With Improved Outcomes at a Rural Primary Care Practice.

This study built a predefined rule-based risk stratification paradigm using 19 factors in a primary care setting that works with rural communities. The factors include medical and nonmedical variables. The nonmedical variables represent 3 demographic attributes and one other factor represents transportation availability. Medical variables represent major clinical variables such as blood pressure and BMI. Many risk stratification models are found in the literature but few integrate medical and nonmedical variables, and to our knowledge, no such model is designed specifically for rural communities. The data used in this study contain the associated variables of all medical visits in 2021. Data from 2022 were used to evaluate the model. After our risk stratification model and several interventions were adopted in 2022, the percentage of patients with high or medium risk of deteriorating health outcomes dropped from 34.9% to 24.4%, which is a reduction of 30%. The medium-complex patient population size, which had been 29% of all patients, decreased by about 4% to 5.7%. According to the analysis, the total risk score showed a strong correlation with 3 risk factors: dual diagnoses, the number of seen providers, and PHQ9 (0.63, 0.54, and 0.45 correlation coefficients, respectively).

Development and internal validation of a dynamic fall risk prediction and monitoring tool in aged care using routinely collected electronic health data: a landmarking approach.

Falls pose a significant challenge in residential aged care facilities (RACFs). Existing falls prediction tools perform poorly and fail to capture evolving risk factors. We aimed to develop and internally validate dynamic fall risk prediction models and create point-based scoring systems for residents with and without dementia. A longitudinal cohort study using electronic data from 27 RACFs in Sydney, Australia. The study included 5492 permanent residents, with a 70%-30% split for training and validation. The outcome measure was the incidence of falls. We tracked residents for 60 months, using monthly landmarks with 1-month prediction windows. We employed landmarking dynamic prediction for model development, a time-dependent area under receiver operating characteristics curve (AUROCC) for model evaluations, and a regression coefficient approach to create point-based scoring systems. The model identified 15 independent predictors of falls in dementia and 12 in nondementia cohorts. Falls history was the key predictor of subsequent falls in both dementia (HR 4.75, 95% CI, 4.45-5.06) and nondementia cohorts (HR 4.20, 95% CI, 3.87-4.57). The AUROCC across landmarks ranged from 0.67 to 0.87 for dementia and from 0.66 to 0.86 for nondementia cohorts but generally remained between 0.75 and 0.85 in both cohorts. The total point risk score ranged from -2 to 57 for dementia and 0 to 52 for nondementia cohorts. Our novel risk prediction models and scoring systems provide timely person-centered information for continuous monitoring of fall risk in RACFs. Embedding these tools within electronic health records could facilitate the implementation of targeted proactive interventions to prevent falls.

Outcomes of Patients with Normal LDL-Cholesterol at Admission for Acute Coronary Syndromes: Lower Is Not Always Better.

There are few prospective data on the prognostic value of normal admission low-density lipoprotein cholesterol (LDL-C) in statin-naïve patients with acute coronary syndromes (ACS) who are treated with a preemptive invasive strategy. We aimed to analyze the proportion of patients with normal LDL-C at admission for ACS in our practice, and their characteristics and clinical outcomes in comparison to patients with high admission LDL-C. Two institutions' prospective registries of patients with confirmed ACS from Jan 2017 to Jan 2023 were used to identify 1579 statin-naïve patients with no history of prior coronary artery disease (CAD), and with available LDL-C admission results, relevant clinical and procedural data, and short- and long-term follow-up data. Normal LDL-C at admission was defined as lower than 2.6 mmol/L. All demographic, clinical, procedural, and follow-up data were compared between patients with normal LDL-C and patients with a high LDL-C level (≥2.6 mmol/L) at admission. There were 242 (15%) patients with normal LDL-C at admission. In comparison to patients with high LDL-cholesterol at admission, they were significantly older (median 67 vs. 62 years) with worse renal function, had significantly more cases of diabetes mellitus (DM) (26% vs. 17%), peripheral artery disease (PAD) (14% vs. 9%), chronic obstructive pulmonary disease (COPD) (8% vs. 2%), and psychological disorders requiring medical attention (19% vs. 10%). There were no significant differences in clinical type of ACS. Complexity of CAD estimated by coronary angiography was similar between the two groups (median Syntax score 12 for both groups). There were no significant differences in rates of complete revascularization (67% vs. 72%). Patients with normal LDL-C had significantly lower left ventricular ejection fraction (LVEF) at discharge (median LVEF 52% vs. 55%). Patients with normal LDL-C at admission had both significantly higher in-hospital mortality (5% vs. 2%, RR 2.07, 95% CI 1.08-3.96) and overall mortality during a median follow-up of 43 months (27% vs. 14%, RR 1.86, 95% CI 1.45-2.37). After adjusting for age, renal function, presence of diabetes mellitus, PAD, COPD, psychological disorders, BMI, and LVEF at discharge in a multivariate Cox regression analysis, normal LDL-C at admission remained significantly and independently associated with higher long-term mortality during follow-up (RR 1.48, 95% CI 1.05-2.09). A spontaneously normal LDL-C level at admission for ACS in statin-naïve patients was not rare and it was an independent risk factor for both substantially higher in-hospital mortality and mortality during long-term follow-up. Patients with normal LDL-C and otherwise high total cardiovascular risk scores should be detected early and treated with optimal medical therapy. However, additional research is needed to reveal all the missing pieces in their survival puzzle after ACS-beyond coronary anatomy, PCI optimization, numerical LDL-C levels, and statin therapy.

Abstract 6141: Genetic risk, health-associated lifestyle, and risk of early-onset total cancer and breast cancer: A prospective cohort study

Abstract Background Early-onset cancer (diagnosed under 50 years of age) is generally more aggressive. Its rising incidence is a global concern. The associations between genetic risk, lifestyle, and the risk of early-onset cancer may inform preventive strategies. Methods We studied the association between genetic risk, lifestyle and early-onset cancers among 66308 white British participants enrolled in the UK Biobank before age 50. Genetic risk was assessed using sex-specific composite total cancer polygenic risk scores (PRSs). We calculated composite PRSs as weighted sums of previously-developed cancer site-specific PRSs using weights obtained from lasso regression. We considered a breast cancer-specific PRS for analyses on breast cancer among women. A health-associated lifestyle score (HLS) was calculated based on baseline smoking, BMI (men only), physical activity, alcohol intake, and diet. Cox models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of early-onset total cancer and breast cancer across genetic risk and HLS groups in women and men. Results A total of 1247 incident invasive early-onset cancer cases (820 in women, 427 in men) were documented, including 386 cases of early-onset breast cancer. In multivariable-adjusted analyses with 2-year latency, higher genetic risk (highest vs. lowest tertile of PRS) was associated with significantly increased risks of early-onset total cancer in women (composite PRS HR=1.85; 95% CI, 1.50-2.29), early onset total cancer in men (composite PRS HR=1.94; 95% CI, 1.45-2.59), and early-onset breast cancer in women (breast-cancer PRS HR=3.06; 95% CI, 2.20-4.25). The HRs (95% CI) of early-onset total cancer in women and men, and early-onset breast cancer in women associated with adopting an unfavorable lifestyle (highest vs. lowest tertile of HLS) were 1.49 (0.99, 2.25), 1.14 (0.67, 1.95), and 1.78 (0.97, 3.24), respectively, in the total study population; 1.85 (1.02, 3.36), 3.27 (0.78, 13.72), and 1.67 (0.71, 3.90), respectively, in those with high genetic risk; 1.25 (0.60, 2.57), 1.11 (0.42, 2.89), and 1.66 (0.54, 5.11), respectively, in those with intermediate genetic risk; and 1.15 (0.44, 2.98), 1.16 (0.39, 3.40), and 2.10 (0.57, 7.75), respectively, in those with low genetic risk. Compared to individuals with both low genetic risk and a favorable lifestyle, those with high genetic risk and an unfavorable lifestyle had substantially increased risks of early-onset total cancer in women (3.07; 1.64-5.78) and men (2.18; 0.78-6.11), and significantly higher early-onset breast cancer risk in women (4.11; 1.56-10.85). Conclusion Genetic and lifestyle factors were independently associated with risks of early-onset total cancer and breast cancer. Compared to those with low genetic risk, individuals with a high genetic risk may benefit more from adopting a healthy lifestyle in preventing early-onset cancer. Citation Format: Yin Zhang, Yuxi Liu, Kathryn L. Penney, Sara Lindström, Peter Kraft. Genetic risk, health-associated lifestyle, and risk of early-onset total cancer and breast cancer: A prospective cohort study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6141.

Criminogenic Risk Assessment Beyond Juvenile Justice: Exploring the Predictive Ability of the Youth Level of Service/Case Management Inventory (YLS/CMI) in Norway

This study evaluated the predictive properties of the Youth Level of Service/Case Management Inventory (YLS/CMI) in 646 Norwegian adolescents (63% males) placed in non-secure, community-based residential care. Using receiver operating characteristics and logistic regression, the study explored the YLS/CMI’s efficacy in predicting various recidivism outcomes across subgroups. The inventory demonstrated to be a significant predictor for all categories of offending behavior (area under the curve ranged from .62 to .77). Although the YLS/CMI total risk score showed a robust association with offending across subgroups, there were discernible variations in predictive ability between males and females. This pattern extended to analyses of subdomains and have implications for clinical use. Overall, the findings support the YLS/CMI as a useful tool for predicting delinquency in a Norwegian residential setting and contribute to the expanding body of literature supporting the instrument’s utility across various cultures and contexts.