Development of a Novel Scoring System for Predicting the Risk of Colorectal Neoplasia: A Retrospective Study

Early Identification of Post-Traumatic Stress Disorder in Trauma Patients: Development of a Multivariable Risk Prediction Model

BACKGROUND

The purpose of this study was to build a risk prediction model to identify trauma patients at the time of injury who are at high risk for post-traumatic stress disorder (PTSD) 1 year later.

METHODS

Patients 18+ with operative orthopedic trauma injuries were enrolled in prospective social determinants of health cohort. Data were collected through initial surveys, medical records at time of injury, and 1-year follow-up phone screenings. Univariate analysis examined associations between factors and PTSD at 1 year. The best fit multivariable logistic regression model led to a novel PTSD risk prediction tool based on weights assigned similar to the Charlson index methods.

RESULTS

Of 329 enrolled patients, 87 (26%) completed follow-up surveys; 58% screened positive for chronic PTSD. The best fit model predicting PTSD included age, insurance, violent mechanism, and 2 acute stress screening questions (AUC .89). Using these parameters, the maximum possible TIPPS index was 19. Those with PTSD at 1 year had a mean TIPPS index of 12.9 ± 4.0, compared to 5.9 ± 4.2 for those who did not (P < .001).

DISCUSSION

Traumatic injury often leads to PTSD, which can be predicted by a novel risk score incorporating age, insurance status, violent injury mechanism, and acute stress reaction symptoms. Stability in life and relationships with primary care physicians may be protective of PTSD.

LEVEL OF EVIDENCE

Diagnostic level II.

Risk Factors for Failure of Closed Forearm Fracture Reduction in the Pediatric Emergency Department

OBJECTIVES

This study aimed to explore risk factors for failure of forearm fracture closed reduction in the pediatric emergency department (ED) and to suggest indications for initial surgery.

METHODS

This retrospective cohort study included all patients aged 0 to 18 years who presented to our pediatric ED with an extraarticular forearm fracture treated with closed reduction between May 2017 and April 2021. We explored risk factors for procedural failure, defined as a need for surgical intervention within 6 weeks of the closed reduction attempt.

RESULTS

Of 375 patients (median age 8.1 years, 294 [78.2%] boys), 44 (11.7%) patients sustained a reduction failure, of whom 42 (95.5%) had both radius and ulna fractures. Of the 259 patients with fractures of both bones, the following parameters were independent predictors for reduction failure: refracture (adjusted odds ratio [aOR] 17.6, P < 0.001), open fracture (aOR 10.1, P = 0.007), midshaft fracture (aOR 2.6, P = 0.004), radial translation rate 37% and higher in either plane (aOR 5.1, P = 0.004), and age of 10 years and older (aOR 2.9, P = 0.01).

CONCLUSIONS

Most pediatric forearm fractures can be successfully managed by closed reduction in the ED. Two-bone fractures had the strongest association with reduction failure. Refracture, open fracture, midshaft location, initial radius bone translation of 37% and higher (and not initial angulation), and patient age of 10 years and older are independent risk factors for reduction failure in two-bone fractures. We propose a risk score for reduction failure that can serve as a decision-making tool.

Risk factors of progression from discoid lupus to severe systemic lupus erythematosus: a registry-based cohort study of 164 patients

BACKGROUND

No study has assessed the risk factors of progression from discoid lupus erythematosus (DLE) to severe systemic lupus erythematosus (sSLE) (defined as requiring hospitalization and specific treatment).

OBJECTIVE

To identify the risks factors of and generate a predicting score for progression to sSLE among patients with isolated DLE or associated with systemic lupus erythematosus with mild biological abnormalities.

METHODS

In this registry-based cohort study, multivariable analysis was performed using risk factors identified from literature and pruned by backward selection to identify relevant variables. The number of points was weighted proportionally to the odds ratio (OR).

RESULTS

We included 30 patients with DLE who developed sSLE and 134 patients who did not. In multivariable analysis, among 12 selected variables, an age of <25 years at the time of DLE diagnosis (OR, 2.8; 95% CI, 1.1-7.0; 1 point), phototype V to VI (OR, 2.7; 95% CI, 1.1-7.0; 1 point), and antinuclear antibody titers of ≥1:320 (OR, 15; 95% CI, 3.3-67.3; 5 points) were selected to generate the score. Among the 54 patients with a score of 0 at baseline, none progressed to sSLE, whereas a score of ≥6 was associated with a risk of approximately 40%.

LIMITATIONS

Retrospective design.

CONCLUSION

In our cohort, an age of <25 years at the time of DLE diagnosis, phototype V to VI, and antinuclear antibody titers of ≥1:320 were risk factors for developing sSLE.

Exploring aflatoxin contamination and household-level exposure risk in diverse Indian food systems

The present study sought to identify household risk factors associated with aflatoxin contamination within and across diverse Indian food systems and to evaluate their utility in risk modeling. Samples (n = 595) of cereals, pulses, and oil seeds were collected from 160 households across four diverse districts of India and analyzed for aflatoxin B1 using enzyme-linked immunosorbent assay (ELISA). Demographic information, food and cropping systems, food management behaviors, and storage environments were profiled for each household. An aflatoxin detection risk index was developed based on household-level features and validated using a repeated 5-fold cross-validation approach. Across districts, between 30–80% of households yielded at least one contaminated sample. Aflatoxin B1 detection rates and mean contamination levels were highest in groundnut and maize, respectively, and lower in other crops. Landholding had a positive univariate effect on household aflatoxin detection, while storage conditions, product source, and the number of protective behaviors used by households did not show significant effects. Presence of groundnut, post-harvest grain washing, use of sack-based storage systems, and cultivation status (farming or non-farming) were identified as the most contributive variables in stepwise logistic regression and were used to generate a household-level risk index. The index had moderate classification accuracy (68% sensitivity and 62% specificity) and significantly correlated with village-wise aflatoxin detection rates. Spatial analysis revealed utility of the index for identifying at-risk localities and households. This study identified several key features associated with aflatoxin contamination in Indian food systems and demonstrated that household characteristics are substantially predictive of aflatoxin risk.

Association between Hemoglobin Levels and Colorectal Polyps in Asymptomatic Chinese Adults

Methods

A cross-sectional analysis was performed among 1633 asymptomatic adults who underwent colonoscopy examinations during routine health check-ups at the First Affiliated Hospital, College of Medicine, Zhejiang University, between 2015 and 2018.

Results

A total of 449 (27.50%) participants were diagnosed with colorectal polyps, and those with colorectal polyps had significantly higher hemoglobin levels than did those without colorectal polyps. Hemoglobin levels were positively associated with the prevalence of colorectal polyps, with rates of 16.43%, 26.20%, 32.17%, and 35.87% among participants with hemoglobin levels in the first, second, third, and fourth quartiles, respectively (P for trend < 0.001). Stepwise multiple regression analysis showed that elevated hemoglobin levels independently increased the risk of colorectal polyps (odd ratio = 1.017; 95% confidence interval: 1.008–1.026).

Conclusion

Elevated hemoglobin levels were significantly and independently associated with the prevalence and risk of colorectal polyps in asymptomatic adults.

Alpha-glucosidase inhibitor use is associated with decreased colorectal neoplasia risk in patients with type 2 diabetes mellitus receiving colonoscopy: a retrospective study

Purpose

The purpose of this study was to clarify the factors that influence the incidence of colorectal neoplasia in patients with type 2 diabetes mellitus (DM).

Study Design and Setting

Among a total of 1176 patients who underwent total colonoscopy at our hospital, we retrospectively analyzed 168 patients with type 2 DM. Univariate and multivariate logistic regression analyses were then performed to identify the risk factors associated with colorectal neoplasia.

Results

A multivariate analysis of these patients demonstrated that male gender (odds ratio [OR] = 4.04, 95% confidence interval [CI] = 1.67-10.37, p = 0.002), taking statins (OR = 4.59, 95% CI = 1.69-13.43, p = 0.003), taking alpha glucosidase inhibitor (α-GI) (OR = 0.35, 95% CI = 0.13-0.87, p = 0.023) and taking low-dose aspirin (LDA) (OR = 0.32, 95% CI = 0.10-0.95, p = 0.040) were independent factors associated with an increased (male gender and statins) or decreased (α-GI and LDA) risk of colorectal neoplasia.

Conclusions

While male gender and taking statins are risk factors, taking α-GI as well as LDA may reduce the risk of colorectal neoplasia in patients with type2 DM.

Molecular pathological epidemiology: new developing frontiers of big data science to study etiologies and pathogenesis

Molecular pathological epidemiology (MPE) is an integrative field that utilizes molecular pathology to incorporate interpersonal heterogeneity of a disease process into epidemiology. In each individual, the development and progression of a disease are determined by a unique combination of exogenous and endogenous factors, resulting in different molecular and pathological subtypes of the disease. Based on "the unique disease principle," the primary aim of MPE is to uncover an interactive relationship between a specific environmental exposure and disease subtypes in determining disease incidence and mortality. This MPE approach can provide etiologic and pathogenic insights, potentially contributing to precision medicine for personalized prevention and treatment. Although breast, prostate, lung, and colorectal cancers have been among the most commonly studied diseases, the MPE approach can be used to study any disease. In addition to molecular features, host immune status and microbiome profile likely affect a disease process, and thus serve as informative biomarkers. As such, further integration of several disciplines into MPE has been achieved (e.g., pharmaco-MPE, immuno-MPE, and microbial MPE), to provide novel insights into underlying etiologic mechanisms. With the advent of high-throughput sequencing technologies, available genomic and epigenomic data have expanded dramatically. The MPE approach can also provide a specific risk estimate for each disease subgroup, thereby enhancing the impact of genome-wide association studies on public health. In this article, we present recent progress of MPE, and discuss the importance of accounting for the disease heterogeneity in the era of big-data health science and precision medicine.

Risk Model for Colorectal Cancer in Spanish Population Using Environmental and Genetic Factors: Results from the MCC-Spain study

Colorectal cancer (CRC) screening of the average risk population is only indicated according to age. We aim to elaborate a model to stratify the risk of CRC by incorporating environmental data and single nucleotide polymorphisms (SNP). The MCC-Spain case-control study included 1336 CRC cases and 2744 controls. Subjects were interviewed on lifestyle factors, family and medical history. Twenty-one CRC susceptibility SNPs were genotyped. The environmental risk model, which included alcohol consumption, obesity, physical activity, red meat and vegetable consumption, and nonsteroidal anti-inflammatory drug use, contributed to CRC with an average per factor OR of 1.36 (95% CI 1.27 to 1.45). Family history of CRC contributed an OR of 2.25 (95% CI 1.87 to 2.72), and each additional SNP contributed an OR of 1.07 (95% CI 1.04 to 1.10). The risk of subjects with more than 25 risk alleles (5^th quintile) was 82% higher (OR 1.82, 95% CI 1.11 to 2.98) than subjects with less than 19 alleles (1^st quintile). This risk model, with an AUROC curve of 0.63 (95% CI 0.60 to 0.66), could be useful to stratify individuals. Environmental factors had more weight than the genetic score, which should be considered to encourage patients to achieve a healthier lifestyle.