Hearing loss is highly prevalent in occupational populations, but it could be effectively prevented through early monitoring. There is still a lack of studies on the risk assessment of hearing loss.
To construct three risk assessment models for hearing loss in oil workers, and evaluate their performance to obtain the optimal one.
A cross-sectional study was conducted. Participants were 1 423 workers of an oil company who received the occupational health examination from 2018 to 2019 in the Jingxia Hospital of North China Petroleum Administration. Their general demographic data, audiometric test and laboratory test results were collected. Unconditional multivariable Logistic regression was used to explore the factors influencing hearing loss. Python was used to build the random forest, XG Boost, and BP neural network models with factors potentially associated with hearing loss determined based on a literature review and expert opinions incorporated. The discriminative ability of the models were evaluated using the receiver operating characteristic curve (ROC) , and the calibration ability of the model was tested using the calibration curve.
The prevalence of hearing loss changed significantly according to age, gender, monthly household income, history of diabetes, labor intensity, physical exercise, ototoxic chemical exposure, sleep disturbance, shift, and high temperature exposure (P<0.05) . The prevalence of hearing loss rose with the increase in years of work and cumulative noise exposure (P<0.05) . The results of unconditional multivariate Logistic regression analysis showed that 50- years old, diabetes, ototoxic, chemical exposure, insomnia, shift, 30-years of work and cumulative noise exposure≥90 dB (A) ·year were risk factors for hearing loss in oil workers (P<0.05) , monthly household income≥11 000 and moderate labor intensity were protective factors for hearing loss in oil workers (P<0.05) . The AUC of the random forest in assessing hearing loss risk in oil workers was 0.95, with 95.99% accuracy, 91.43% sensitivity, 97.69% specificity, a Youden index of 0.89 and a F1 score of 0.74, the AUC of the XG Boost model in assessing hearing loss risk in oil workers was 0.93, with 95.22% accuracy, 89.09% sensitivity, 97.50% specificity, a Youden index of 0.87 and a F1 score of 0.73, and that of the BP neural network model in assessing hearing loss risk in oil workers was 0.83, with 88.62% accuracy, 70.13% sensitivity, 95.47% specificity, a Youden index of 0.66 and a F1 score of 0.73. The Brier score of the random forest was 0.04, with an observation-to-expectation (O/E) ratio of 1.02 and a calibration-in-the-large of 0.029. The Brier score, O/E ratio and calibration-in-the-large of the XG Boost model were 0.04, 1.04 and 0.032, respectively. The Brier score of the BP neural network model was 0.11, with an O/E ratio of 1.21 and a calibration-in-the-large of 0.097. The calibration efficiency of the random forest model was the best.
The random forest model outperformed the XG Boost model and the BP neural network model, which could be adopted to assess the risk of hearing loss in oil workers more accurately.
China owns a huge number of asthma patients and an increasing incidence of asthma, but low rate of overall control and high rate of acute asthma exacerbation. Moreover, there is a lack of methods for systematically screening the risks of acute exacerbation of asthma.
To develop a risk prediction questionnaire for acute exacerbation of asthma after screening the associated risk factors using the modified Delphi technique, providing a reference for building a multidimensional risk prediction model of asthma acute exacerbation.
Based on literature reports and our clinical pre-investigation results, an expert consultation questionnaire on risk predictors of acute exacerbation of asthma was developed, and was distributed through E-mail to 30 experts for review through two rounds of online consultation survey using the modified Delphi technique conducted from April to October 2021. SPSS 25.0 was used to assign weight and analyze the risk predictors. Then according to the screening criteria developed by the experts, the risk predictors were finally determined.
Both two rounds of consultation achieved a 100% response rate. The familiarity, judgment, and authority coefficients as well as Kendall's W were 0.894, 0.963, 0.929, and 0.331, respectively, for the first round of expert consultation (P<0.001) , and were 0.920, 0.976, 0.948, and 0.437, respectively, for the second round of expert consultation (P<0.001) . The determined risk predictors of acute exacerbation of asthma include six domains (clinical symptoms and signs, conditions, quality of life, biological information, traditional Chinese medicine syndromes and basic demographics) , and 29 indices including severity of asthma, Asthma Control Test, wheezing, chest tightness, allergy history, hormone therapy, work and living environment, eosinophils, number of exacerbations in the past year, treatment compliance, climate and seasonal changes, and so on.
The based on the modified Delphi method, the risk predictors of acute exacerbation of asthma determined using expert consultation with the modified Delphi technique include the aforementioned six domains and 29 indices, which is relatively concise, and can provide a reference for follow-up studies.
Low back pain (LBP) is the leading cause of hypokinesia globally. Currently, the reporting of outcomes in clinical trials for LBP lacks consistency, utility, and standardization, and the results of studies in the same field cannot be combined for comparison. Thus, the homogeneity and utility of outcomes need to be enhanced.
To assess the quality of randomized controlled trials (RCTs) for LBP and their outcome reports, then to analyze the variations of reported outcomes and measurements among different interventions for LBP, and to explore homogeneous and practical outcome indices for LBP.
Four clinical trials registry platforms (Complementary Medicine Field Trials Register, Back and Neck Review Group Trials Register, ClinicalTrials.gov, WHO ICTRP) and seven databases (Cochrane Library, PubMed, Web of Science, CNKI, Wanfang Data, SinoMed, VIP) were searched for RCTs about LBP treated by traditional Chinese medicine (TCM) , western medicine (WM) and integrated traditional Chinese and western medicine (TCM-WM) published during 2017 to 2021. Information was extracted and analyzed descriptively.
In total, 1 014 RCTs of LBP with WM treatment, 624 RCTs of LBP with TCM treatment, and 392 RCTs of LBP with integrated TCM-WM treatment were included. Overall, the quality of RCTs was low and the reporting of outcome in different interventions was deficient. Through our assessment, the total Jadad score was 2 (2, 4) for RCTs of LBP with WM treatment, 2 (2, 3) for RCTs of LBP with TCM treatment, and 2 (2, 2) for those of LBP with integrated TCM-WM treatment, with more than 50% of the RCTs having a total Jadad score of 2, and more than 10% having a Jadad score of 3. More than 80% of the RCTs had an outcome score of 1. The number of indices reported in RCTs about WM for LBP ranged from 1 to 8 (with a median value of 2) , and the top five outcome domains reported with frequency were pain level (28.2%) , physical function (28.0%) , hospital-related outcomes (8.0%) , economic indices (8.0%) , and adverse events/effects (8.0%) , and the top three scales used to evaluate outcomes were the Visual Analogue Scale (VAS) /Verbal Rating Scale (VRS) , the Oswestry Disability Index (ODI) , and Japanese Orthopaedic Association Score (JOA) . The number of indices reported in RCTs about TCM for LBP ranged from 1 to 6 (with a median value of 2) , and the top five outcome domains reported with frequency were pain level (45%) , physical function (27%) , others (14%) , overall quality of life (5%) , and musculoskeletal and connective tissue outcomes (2%) , and the main scales used included VAS/VRS, ODI, short-form McGill Pain Questionnaire (SF-MPQ) , the Numerical Rating Scale/ Numeric Pain Rating Scale (NRS/NPRS) , Roland-Morris Disability Questionnaire (RMDQ/RMD) , and 12-Item Short Form Health Survey/ 36-Item Short Form Health Survey (SF-12/SF-36) . The number of indices reported in RCTs for LBP with integrated TCM-WM treatment was 1-12 (with a median value of 2) , and the top five outcome domains reported with high frequency were physical function (39%) , pain level (34%) , others (9%) , overall quality of life (5%) , and musculoskeletal and connective tissue outcomes (4%) , and the scales used with high frequency were VAS/VRS, ODI, JOA, SF-12/SF-36, RMDQ, and NRS/NPRS. The evaluation dimensions of outcomes for three interventions were all mainly based on pain level and physical function, and the measurements were focused on the VAS/VRS scale (WM: 22.16%, TCM: 32.97%, integrated TCM-WM: 30.94%) and the ODI/CODI scale (WM: 15.88%, TCM: 18.74%, integrated TCM-WM: 20.07%) , and the common outcome indices with corresponding measurements were pain level (VAS/VRS) , physical function (ODI/RMD) , overall quality of life (SF-12/SF-36) and imaging results (X-ray/CT/MRI) .
By means of quality evaluation and data analysis, the result showed that all RCTs for LBP and their outcome reports had low-quality. The main outcome assessments among three interventions were pain level and physical function, and the main measurements were the VAS/VRS scale and the ODI/CODI scale. Pain level, physical function, quality of life, and imaging results were commonly reported through varied interventions. In brief, the results provide a basis for the future construction of Core Outcome Sets (COS) and Intervention-related Specific Outcome Sets (In-SOS) for LBP.
