Analysis of factors affecting nonalcoholic fatty liver disease in Chinese steel workers and risk assessment studies

BACKGROUND

The global incidence of nonalcoholic fatty liver disease (NAFLD) is rapidly escalating, positioning it as a principal public health challenge with significant implications for population well-being. Given its status as a cornerstone of China's economic structure, the steel industry employs a substantial workforce, consequently bringing associated health issues under increasing scrutiny. Establishing a risk assessment model for NAFLD within steelworkers aids in disease risk stratification among this demographic, thereby facilitating early intervention measures to protect the health of this significant populace.

METHODS

Use of cross-sectional studies. A total of 3328 steelworkers who underwent occupational health evaluations between January and September 2017 were included in this study. Hepatic steatosis was uniformly diagnosed via abdominal ultrasound. Influential factors were pinpointed using chi-square (χ2) tests and unconditional logistic regression analysis, with model inclusion variables identified by pertinent literature. Assessment models encompassing logistic regression, random forest, and XGBoost were constructed, and their effectiveness was juxtaposed in terms of accuracy, area under the curve (AUC), and F1 score. Subsequently, a scoring system for NAFLD risk was established, premised on the optimal model.

RESULTS

The findings indicated that sex, overweight, obesity, hyperuricemia, dyslipidemia, occupational dust exposure, and ALT serve as risk factors for NAFLD in steelworkers, with corresponding odds ratios (OR, 95% confidence interval (CI)) of 0.672 (0.487-0.928), 4.971 (3.981-6.207), 16.887 (12.99-21.953), 2.124 (1.77-2.548), 2.315 (1.63-3.288), 1.254 (1.014-1.551), and 3.629 (2.705-4.869), respectively. The sensitivity of the three models was reported as 0.607, 0.680 and 0.564, respectively, while the precision was 0.708, 0.643, and 0.701, respectively. The AUC measurements were 0.839, 0.839, and 0.832, and the Brier scores were 0.150, 0.153, and 0.155, respectively. The F1 score results were 0.654, 0.661, and 0.625, with log loss measures at 0.460, 0.661, and 0.564, respectively. R2 values were reported as 0.789, 0.771, and 0.778, respectively. Performance was comparable across all three models, with no significant differences observed. The NAFLD risk score system exhibited exceptional risk detection capabilities with an established cutoff value of 86.

CONCLUSIONS

The study identified sex, BMI, dyslipidemia, hyperuricemia, occupational dust exposure, and ALT as significant risk factors for NAFLD among steelworkers. The traditional logistic regression model proved equally effective as the random forest and XGBoost models in assessing NAFLD risk. The optimal cutoff value for risk assessment was determined to be 86. This study provides clinicians with a visually accessible risk stratification approach to gauge the propensity for NAFLD in steelworkers, thereby aiding early identification and intervention among those at risk.

Prediction of Catheter-Associated Urinary Tract Infections Among Neurosurgical Intensive Care Patients: A Decision Tree Analysis

BACKGROUND

Catheter-associated urinary tract infections (CAUTIs) are the most common device-associated infections in hospitals and can be prevented. To identify the risk factors and develop a risk prediction model for CAUTIs among neurosurgical intensive care unit (NICU) patients.

METHODS

All patients admitted to the NICU of a tertiary hospital between January 2019 and January 2020 were enrolled. Two decision tree models were applied to analyze the risk factors associated with CAUTIs in NICU patients. The performance of the decision tree model was evaluated.

RESULTS

A total of 537 patients admitted to the NICU with indwelling catheters were recruited for this study. The rate of CAUTIs was 4.44 per 1000 catheter days, and Escherichia coli was the predominant pathogen causing CAUTIs among indwelling catheter patients. The classification and regression tree model displayed good power of prediction (area under the curve : 0.920). Nine CAUTI risk factors (age ≥60 years (P = 0.004), Glasgow Coma Scale score ≤8 (P = 0.009), epilepsy at admission (P = 0.007), admission to the hospital during the summer (P < 0.001), ventilators use (P = 0.007), receiving less than 2 types of antibiotics (P < 0.001), albumin level <35 g/L (P = 0.002), female gender (P = 0.002), and having an indwelling catheter for 7-14 days (P = 0.001) were also identified.

CONCLUSION

We developed a novel scoring model for predicting the risk of CAUTIs in patients with neuro-critical illness in daily clinical practice. This model identified several risk factors for CAUTI among NICU patients, novel factors including epilepsy and admission during the summer, can be used to help providers prevent and reduce the risk of CAUTI among vulnerable groups.

Role of risk scoring systems in predicting life expectancy after carotid endarterectomy in asymptomatic patients

OBJECTIVE

The aim of this study is to compare and to test the performance of all available risk scoring systems (RSSs) designed to predict long-term survival rate in asymptomatic candidate patients for carotid endarterectomy (CEA) for significant carotid artery stenosis.

METHODS

Data on asymptomatic patients who underwent CEA in three high-volume centers were prospectively recorded. Through literature research using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations, six RSSs were identified for the intent of the study. Primary endpoints were 3- and 5-year survival rates after CEA. All items used as variables to compose multiple RSSs were applied to every patient in the study population. The 3- and 5-year mortality prediction rates for each score were assessed by sensitivity, specificity, and predictive negative and positive value calculation, as well as univariable Cox proportional hazard models with the Harrell C index.

RESULTS

During the study period, 825 CEAs in 825 asymptomatic patients were analyzed. All items used in RSSs were available in the dataset, with some concerns regarding their definition and application among RSSs. The 3- and 5-year survival rates of the study cohort were 94.5% and 90.3%, respectively. Among the six RSSs analyzed, no RSS demonstrated optimal results in terms of mortality rate prediction accuracy, although some scores had good diagnostic and risk of death precision.

CONCLUSIONS

RSSs, when used alone, fail to optimally detect postoperative life expectancy in asymptomatic CEA patient candidates. Further prospective controlled studies are needed to compose and validate RSSs with better calibration to predict outcomes.

Development of a risk scoring system for prognostication in HIV-related toxoplasma encephalitis

BACKGROUND

This study aims to evaluate specific risk factors influencing prognosis of HIV-infected patients with toxoplasma encephalitis (TE) in order to develop a prognostic risk scoring system for them.

METHODS

This is a six-center retrospective study of hospitalized HIV/TE patients. Data including six-week mortality after diagnosis, baseline characteristics, clinical features, laboratory tests and radiological characteristics of eligible patients were assimilated for risk model establishing.

RESULTS

In this study, the six-week mortality among 94 retrospective cases was 11.7% (11/94). Seven specific risk factors, viz. time from symptom onset to presentation, fever, dizziness, CD4+ T-cell counts, memory deficits, patchy brain lesions, and disorders of consciousness were calculated to be statistically associated with mortality. A criterion value of '9' was selected as the optimal cut-off value of the established model. The AUC of the ROC curve of this scoring model was 0.976 (p < 0.001). The sensitivity and specificity of the risk scoring model was 100.0 and 86.9%, respectively, which were 81.8 and 94.1% of this scoring model in the verification cohort, respectively.

CONCLUSIONS

The developed scoring system was established with simple risk factors, which also allows expeditious implementation of accurate prognostication, and appropriate therapeutic interventions in HIV-infected patients with TE.

Novel Risk Scoring System for Patients with Metastatic Renal Cell Carcinoma Treated with Immune Checkpoint Inhibitors

BACKGROUND

The International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) criteria are the gold standard for risk-stratifying patients with metastatic renal cell cancer (mRCC). We developed a novel risk scoring system for patients with mRCC treated with immune checkpoint inhibitors (ICIs).

METHODS

We performed a retrospective analysis of 100 ICI-treated patients with mRCC at Winship Cancer Institute from 2015 to 2018. Several baseline variables were collected, including markers of inflammation, body mass index (BMI), and sites of metastatic disease, and all were considered for inclusion in our risk scoring system. Upon variable selection in multivariable model, monocyte-to-lymphocyte ratio (MLR), BMI, and number and sites of metastases at baseline were used for risk score calculation. Patients were categorized using four-level risk groups as good (risk score = 0), intermediate (risk score = 1), poor (risk score = 2), or very poor (risk score = 3-4). Cox's proportional hazard model and the Kaplan-Meier method were implemented for survival outcomes.

RESULTS

Most patients were male (66%) with clear cell renal cell carcinoma (72%). The majority (71%) received anti-programmed cell death protein-1 monotherapy. Our risk scoring criteria had higher Uno's concordance statistics than IMDC in predicting overall survival (OS; 0.71 vs. 0.57) and progression-free survival (0.61 vs. 0.58). Setting good risk (MLR <0.93, BMI ≥24, and D_Met = 0) as the reference, the OS hazard ratios were 29.5 (95% confidence interval [CI], 3.64-238.9), 6.58 (95% CI, 0.84-51.68), and 3.75 (95% CI, 0.49-28.57) for very poor, poor, and intermediate risk groups, respectively.

CONCLUSION

Risk scoring using MLR, BMI, and number and sites of metastases may be an effective way to predict survival in patients with mRCC receiving ICI. These results should be validated in a larger, prospective study.

IMPLICATIONS FOR PRACTICE

A risk scoring system was created for patients with metastatic renal cell carcinoma treated with immune checkpoint inhibitors. The results of this study have significant implications for practicing oncologists in the community and academic setting. Importantly, these results identify readily available risk factors that can be used clinically to risk-stratify patients with metastatic renal cell carcinoma who are treated with immune checkpoint inhibitors.

Validation of POSSUM, P-POSSUM and the surgical risk scale in major general surgical operations in Harare: A prospective observational study

BACKGROUND

Raw mortality and morbidity, though commonly studied in surgical audit can nonetheless be misleading because of differences in preoperative and intraoperative findings of patients. There are some common scoring systems specifically designed to cater for case mix but these have not been tried locally. This study sought to validate these scoring systems and hopefully adopt them for our teaching hospitals.

MATERIALS AND METHODS

A prospective observational cohort study was conducted at two central hospitals in Harare Two hundred and two patients undergoing a variety of major general surgical operations were recruited into the study. Results of physiological and intraoperative parameters collected from the patients' records were scored according to POSSUM, P-POSSUM and SRS scores. Predicted mortality and morbidity rates of all these subjects were then compared to the observed rates.

RESULTS

One hundred and eighty one patients participated (123 males, 58 females). Using the POSSUM morbidity score, the observed versus expected (O: E) ratio of 0.88 showed no difference (p = 0.970). Using POSSUM, P-POSSUM and SRS mortality scores, O: E ratios of 0.74, 1.06 and 1.0 respectively were obtained, the differences were not significant (p = 0.650, p = 0.987 and 0.730). All three scores were comparable on the Receiver Operating Characteristic curve. The Physiological score independently predicted mortality (p < 0.00001).

CONCLUSION

POSSUM, P-POSSUM and SRS scores are comparable and suitable for estimating outcomes after major surgery in Harare. A larger study inclusive of low risk patients is needed to generalise these findings across Zimbabwean patients.

Development of a Genetic and Clinical Data-Based (GC) Risk Score for Predicting Survival of Hepatocellular Carcinoma Patients After Tumor Resection

BACKGROUND/AIMS

Carnitine palmitoyltransferase 1A (CPT1A) is a rate-limiting enzyme in the transport of long-chain fatty acids for β-oxidation. Increasing evidence has indicated that CPT1A plays an important role in carcinogenesis. However, the expression and prognostic value of CPT1A in hepatocellular carcinoma (HCC) have not been extensively studied.

METHODS

Here, we collected 66 post-operative liver cancer tissue samples. Gene profile expression was tested by RT-PCR. Receiver operating characteristic (ROC) analysis was performed and multivariate analysis with Cox's Proportional Hazard Model was used for confirming the selected markers' predictive efficiency for HCC patients' survival. A simple risk scoring system was created based on Cox's regression modeling and bootstrap internal validation.

RESULTS

Cox multivariate regression analysis demonstrated that CPT1A, tumor size, intrahepatic metastasis, TNM stage and histological grade were independent risk factors for the prognosis of HCC patients after surgery. Our genetic and clinical data-based (GC) risk scoring system revealed that HCC patients whose total score≥3 are more likely to relapse and die than patients whose total score < 3. Finally, the good discriminatory power of our risk scoring model was validated by bootstrap internal validation.

CONCLUSIONS

The genetic and clinical data-based risk scoring model can be a promising predictive tool for liver cancer patients' prognosis after operation.

Risk scoring system for predicting axillary response after neoadjuvant chemotherapy in initially node-positive women with breast cancer

BACKGROUND

One of the current therapeutic challenges for women with breast cancer receiving neoadjuvant chemotherapy (NAC) is distinguishing women with complete axillary nodal response from those with axillary residual disease to promote a personalized therapeutic strategy including sparing axillary surgery. This study set out to develop a risk scoring system (RSS) for predicting probability of nodal pathological complete response (pCR) in women presenting with cN1 breast cancer who received NAC.

METHODS

Data of 116 women with cN1 breast cancer who received NAC between January 2009 and December 2013 were abstracted from our prospectively maintained database. A risk model based on factors impacting nodal axillary was developed.

RESULTS

The overall nodal conversion rate was 36.2% (42/116). Axillary nodal response was associated with three variables: menopausal status [Odds ratio (OR) = 0.23; 95% confidence interval (CI) 0.09-0.60], the radiological % of breast tumour shrinkage ≥50% (OR = 3.71; 95% CI 1.51-9.10), and negative hormone receptors (ER-, PR-) (OR = 2.41; 95% CI 0.99-5.87). These variables were included in the RSS and assigned scores ranging from 0 to 2. The discrimination of the RSS was 0.78 [95% confidence interval (CI) 0.69-0.86]. A total score of 3 points corresponded to the optimal threshold of the RSS. The diagnostic accuracy was 74.1%.

CONCLUSIONS

This study shows that the probability of axillary nodal pCR after NAC can be accurately predicted so that women at high probability may be spared of axillary surgery.