Tag: pubmed

BMC Public Health. 2022 Jul 9;22(1):1318. doi: 10.1186/s12889-022-13713-9.

ABSTRACT

BACKGROUND: Disability retirement has been investigated in the last two decades using predictors such as measures of sickness absence, psychological, social, and organizational work factors. The impact of various health-related and sickness measures on disability retirement across various occupational group reveal a significant relation. However, current literature lacks understanding in police personnel.

METHODS: This study examines the roles of demographic and measures of sickness absence on disability retirement among police personnel in Abu Dhabi, UAE. The case-control design was used to predict disability retirement wherein controls were matched with cases according to age and gender from those who worked in the same administration as the case at baseline, to reduce the possible confounding influence of these variables. Conditional logistic regression models were used determine the odds-ratio of various measures of sickness absence in predicting disability retirement.

RESULTS: Results indicate that increased number of spells, and number of days of sickness absence can predict disability retirements among police personnel in the UAE. Results indicate that odds ratios for disability retirement for the total exposure period increased from 1.76 (95% CI = 1.42-2.20) for spells of 4-7d to 2.47 (95%CI = 1.79-3.40) for spells of > 4 weeks. When compared with their married counterparts, non-married police employees had a statistically significant increase in odds of disability retirement of almost three fold (OR = 2.93, 95% CI = 1.55-5.56). Non-field and field police officers, on the other hand, had significantly reduced odds of disability retirement compared with admin/supportive staff (OR = 0.43 and 0.28 with 95% CI = 0.19-0.96 and 0.13-0.61 respectively). Odds ratios of disability retirement at end of the exposure period for the matching variables with those obtained after additionally adjusting for all demographic variables (model b), namely, marital status, occupation, employment grade and type, and educational level. The odds ratios of disability retirement remained significantly raised for the total number of days of sickness absence and for the number of spells of sickness absence for all spell types.

CONCLUSIONS: Recommendation to reduce the number of future disability retirements among Abu Dhabi Police include structured problem-solving process addressed through stepwise meetings between the line-managers and the employee.

PMID:35810280 | DOI:10.1186/s12889-022-13713-9

Drug Saf. 2022 Jul 9. doi: 10.1007/s40264-022-01198-9. Online ahead of print.

ABSTRACT

INTRODUCTION: Hip fractures among older people are a major public health issue, which can impact quality of life and increase mortality within the year after they occur. A recent observational study found an increased risk of hip fracture in subjects who were new users of tramadol compared with codeine. These drugs have somewhat different indications. Tramadol is indicated for moderate to severe pain and can be used for an extended period; codeine is indicated for mild to moderate pain and cough suppression.

OBJECTIVE: In this observational study, we compared the risk of hip fracture in new users of tramadol or codeine, using multiple databases and analytical methods.

METHODS: Using data from the Clinical Practice Research Datalink and three US claims databases, we compared the risk of hip fracture after exposure to tramadol or codeine in subjects aged 50-89 years. To ensure comparability, large-scale propensity scores were used to adjust for confounding.

RESULTS: We observed a calibrated hazard ratio of 1.10 (95% calibrated confidence interval 0.99-1.21) in the Clinical Practice Research Datalink database, and a pooled estimate across the US databases yielded a calibrated hazard ratio of 1.06 (95% calibrated confidence interval 0.97-1.16).

CONCLUSIONS: Our results did not demonstrate a statistically significant difference between subjects treated for pain with tramadol compared with codeine for the outcome of hip fracture risk.

PMID:35810265 | DOI:10.1007/s40264-022-01198-9

Prostate Cancer Prostatic Dis. 2022 Jul 9. doi: 10.1038/s41391-022-00562-1. Online ahead of print.

ABSTRACT

BACKGROUND: Molecular biomarker tests are developed as diagnostic tools for prostate cancer (PCa) diagnosis. The SelectMDx (MDxHealth, Nijmegen, The Netherlands) test is a urinary-based biomarker test intended to be used to predict presence of high-grade PCa upon biopsy in men with elevated serum prostate-specific antigen (PSA) levels. Previous validation of the SelectMDx test revealed that 53% of the unnecessary biopsies (biopsies indicating no- or GG1 PCa) could be avoided using the SelectMDx test as a decision-tool to select men for prostate biopsy. The objective of this study is to examine the use of the commercially available SelectMDx test under routine, real-life practice.

METHODS: Men that underwent a SelectMDx test between May 2019 and December 2020 and that were originating from countries that perform the SelectMDx test on a regular basis were included in this study, resulting in 5157 cases from 10 European countries. Clinical parameters, urinary RNA scores, and test outcomes were compared between PSA groups, age groups, countries, and the validation cohort (described previously [4]) using the Mann-Whitney U test, Chi-Square test, Benjamini-Hochberg and Kruskal-Wallis tests.

RESULTS: 40.72% of the cases received a negative SelectMDx result. The test is also used in patients outside the intended-use population (PSA < 3 and >10 ng/mL). Clinical parameters (age, PSA density, DRE outcome) varied between patient population from individual countries and the validation cohort, resulting in differences in the potential number of saved biopsies using the test.

CONCLUSIONS: The potential number of reduced biopsies in clinical use was 40,72% using the SelectMDx test, assuming a negative SelectMDx test resulted in the decision not to biopsy the patient. This is higher compared to the validation cohort, which is explained by differences in patient population.

PMID:35810263 | DOI:10.1038/s41391-022-00562-1

Med Klin Intensivmed Notfmed. 2022 Jul 9. doi: 10.1007/s00063-022-00938-0. Online ahead of print.

ABSTRACT

The training of new medical colleagues in hospitals is due to various aspects such as for instance staff shortages and time pressure often very challenging for everyone involved. Using the example of the interdisciplinary intensive care unit, the positive effects of a structured training curriculum have been scientifically proven in regular employee surveys. There was a statistically significant increase in satisfaction in the quality of induction (p < 0.0001), quality of training (p < 0.0001), preparation for night shifts in the intensive care unit (p < 0.0001) and an improvement in general satisfaction in the clinic (p < 0.003) can also be shown. For these reasons, such curriculum contributes to increasing the quality of care and patient safety as well as the safety of medical staff in the medical work.

PMID:35810250 | DOI:10.1007/s00063-022-00938-0

J Perinatol. 2022 Jul 9. doi: 10.1038/s41372-022-01457-8. Online ahead of print.

ABSTRACT

OBJECTIVE: This study sought to determine if targeted drug screening of newborns was effective in identifying a positive drug test result.

STUDY DESIGN: This was a retrospective cross-sectional study. A total of 340 infants met criteria for drug screening. Sensitivity and specificity were used to evaluate each of the potential risk factors in terms of their ability to predict a positive drug test result. Two-sample t-tests were used to compare differences in Finnegan scores between babies with a positive drug test result and those with a negative one.

RESULT: The risk factor with the highest sensitivity was maternal history of drug use. The difference in the Finnegan scores between groups was statistically significant.

CONCLUSION: The risk factors associated with this study were not very sensitive. The only way to identify all infants at risk of NAS is to standardize the screening process and apply to all infants.

PMID:35810246 | DOI:10.1038/s41372-022-01457-8

Ann Surg Oncol. 2022 Jul 9. doi: 10.1245/s10434-022-12038-6. Online ahead of print.

ABSTRACT

BACKGROUND: The extent of residual disease after neoadjuvant chemotherapy (NAC) can be quantified by the Residual Cancer Burden (RCB), a prognostic tool used to estimate survival outcomes in breast cancer. This study investigated the association between RCB and locoregional recurrence (LRR).

METHODS: The study reviewed 532 women with breast cancer who underwent NAC between 2010 and 2016. Relapse in the ipsilateral breast, skin/subcutis at the surgical site, chest wall, pectoralis, or regional lymph nodes defined an LRR. The LRR cumulative incidence (LRCI) was estimated using the Fine and Gray competing-risks model, with death and distant recurrence defined as competing events. The association of LRCI with prognostic variables was evaluated.

RESULTS: Overall, 5.5% of the patients experienced an LRR after a median follow-up period of 65 months. The 5-year LRCI rates by RCB were as follows: RCB-0 (0.9%), RCB-1 (3.2%), RCB-2 (6.0%), and RCB-3 (12.9%). In the univariable analysis, LRCI varied significantly by RCB (p = 0.010). The multivariable analysis showed a significant association of LRCI with increasing RCB, and the patients with hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) phenotype were at lower risk for LRR than those with HER2+ and triple-negative cancers (p < 0.032). The patients with RCB-3 were at a higher risk for local relapse than those with RCB-0 (hazard ratio, 13.78; confidence interval, 2.25-84.45; p = 0.04). Type of operation (p = 0.04) and use of adjuvant radiation (p = 0.046) were statistically significant in the multivariable model.

CONCLUSIONS: The study results demonstrate a significant association between LRCI and increasing RCB, although distant recurrence is a substantial driver of disease outcomes. Future prospective studies should examine the role of RCB in clinical decisions regarding indications for adjuvant therapy.

PMID:35810226 | DOI:10.1245/s10434-022-12038-6

Lab Invest. 2022 Jul 9. doi: 10.1038/s41374-022-00801-y. Online ahead of print.

ABSTRACT

Great advances in deep learning have provided effective solutions for prediction tasks in the biomedical field. However, accurate prognosis prediction using cancer genomics data remains challenging due to the severe overfitting problem caused by curse of dimensionality inherent to high-throughput sequencing data. Moreover, there are unique challenges to perform survival analysis, arising from the difficulty in utilizing censored samples whose events of interest are not observed. Convolutional neural network (CNN) models provide us the opportunity to extract meaningful hierarchical features to characterize cancer subtype and prognosis outcomes. On the other hand, feature selection can mitigate overfitting and reduce subsequent model training computation burden by screening out significant genes from redundant genes. To accomplish model simplification, we developed a concise and efficient survival analysis model, named CNN-Cox model, which combines a special CNN framework with prognosis-related feature selection cascaded Wx, with the advantage of less computation demand utilizing light training parameters. Experiment results show that CNN-Cox model achieved consistent higher C-index values and better survival prediction performance across seven cancer type datasets in The Cancer Genome Atlas cohort, including bladder carcinoma, head and neck squamous cell carcinoma, kidney renal cell carcinoma, brain low-grade glioma, lung adenocarcinoma (LUAD), lung squamous cell carcinoma, and skin cutaneous melanoma, compared with the existing state-of-the-art survival analysis methods. As an illustration of model interpretation, we examined potential prognostic gene signatures of LUAD dataset using the proposed CNN-Cox model. We conducted protein-protein interaction network analysis to identify potential prognostic genes and further analyzed the biological function of 13 hub genes, including ANLN, RACGAP1, KIF4A, KIF20A, KIF14, ASPM, CDK1, SPC25, NCAPG, MKI67, HJURP, EXO1, HMMR, whose high expression is significantly associated with poor survival of LUAD patients. These findings confirmed that CNN-Cox model is effective in extracting not only prognosis factors but also biologically meaningful gene features. The codes are available at the GitHub website: https://github.com/wangwangCCChen/CNN-Cox .

PMID:35810236 | DOI:10.1038/s41374-022-00801-y

World J Surg. 2022 Jul 9. doi: 10.1007/s00268-022-06648-0. Online ahead of print.

ABSTRACT

BACKGROUND: Although laparoscopic hepatectomy (LH) is associated with improved short-term outcomes compared to open hepatectomy (OH), it is unknown whether frail patients also benefit from LH. The aim of this study was to evaluate the impact of frailty on post-operative outcomes after LH and OH.

PATIENTS AND METHODS: Consecutive patients who underwent LH and OH between January 2011 and December 2018 were identified from a prospective database. Frailty was assessed using the modified Frailty Index (mFI), with patients scoring mFI ≥ 1 deemed to be frail.

RESULTS: Of 1826 patients, 34.7% (N = 634) were frail and 18.6% (N = 340) were elderly (≥ 75 years). Frail patients had significantly higher 90-day mortality (6.6% vs. 2.9%, p < 0.001) and post-operative complications (36.3% vs. 26.1%, p < 0.001) than those who were not frail, effects that were independent of patient age on multivariate analysis. For those undergoing minor resections, the benefits of LH vs. OH were similar for frail and non-frail patients. Length of hospital stay was 53% longer in OH (vs. LH) in frail patients, compared to 58% longer in the subgroup of non-frail patients.

CONCLUSIONS: Frailty is independently associated with inferior post-operative outcomes in patients undergoing hepatectomy. However, the benefits of laparoscopic (compared to open) hepatectomy are similar for frail and non-frail patients. Frailty should not be a contraindication to laparoscopic minor hepatectomy in carefully selected patients.

PMID:35810214 | DOI:10.1007/s00268-022-06648-0

Sci Rep. 2022 Jul 9;12(1):11707. doi: 10.1038/s41598-022-15585-w.

ABSTRACT

The functional relationship between bone and cartilage is modulated by mechanical factors. Scarce data exist on the relationship between bone shape and the spatial distribution of cartilage thickness. The aim of the study was to characterise the coupled variation in knee bone morphology and cartilage thickness distributions in knees with healthy cartilage and investigate this relationship as a function of sex, height, body mass, and age. MR images of 51 knees from young adults (28.4 ± 4.1 years) were obtained from a previous study and used to train a statistical shape model of the femur, tibia, and patella and their cartilages. Five multiple linear regression models were fitted to characterise morphology as a function of sex, height, body mass, and age. A logistic regression classifier was fitted to characterise morphological differences between males and females, and tenfold cross-validation was performed to evaluate the models’ performance. Our results showed that cartilage thickness and its distribution were coupled to bone morphology. The first five shape modes captured over 90% of the variance and described coupled changes to the bone and spatial distribution of cartilage thickness. Mode 1 (size) was correlated to sex (p < 0.001) and height (p < 0.0001). Mode 2 (aspect ratio) was also correlated to sex (p = 0.006) and height (p = 0.017). Mode 4 (condylar depth) was correlated to sex only (p = 0.024). A logistic regression model trained on modes 1, 2, and 4 could classify sex with an accuracy of 92.2% (95% CI [81.1%, 97.8%]). No other modes were influenced by sex, height, body mass, or age. This study demonstrated the coupled relationship between bone and cartilage, showing that cartilage is thicker with increased bone size, diaphysis size, and decreased femoral skew. Our results show that sex and height influence bone shape and the spatial distribution of cartilage thickness in a healthy young adult population, but body mass and age do not.

PMID:35810204 | DOI:10.1038/s41598-022-15585-w

Sci Rep. 2022 Jul 9;12(1):11716. doi: 10.1038/s41598-022-16069-7.

ABSTRACT

The common cold is a leading cause of morbidity and contributes significantly to the health costs in Bhutan. The study utilized multivariate Zero-inflated Poisson regression in a Bayesian framework to identify climatic variability and spatial and temporal patterns of the common cold in Bhutan. There were 2,480,509 notifications of common cold between 2010 and 2018. Children aged < 15 years were twice (95% credible interval [CrI] 2.2, 2.5) as likely to get common cold than adults, and males were 12.4% (95 CrI 5.5%, 18.7%) less likely to get common cold than females. A 10 mm increase in rainfall lagged one month, and each 1 °C increase of maximum temperature was associated with a 5.1% (95% CrI 4.2%, 6.1%) and 2.6% (95% CrI 2.3%, 2.8%) increase in the risk of cold respectively. An increase in elevation of 100 m and 1% increase in relative humidity lagged three months were associated with a decrease in risk of common cold by 0.1% (95% CrI 0.1%, 0.2%) and 0.3% (95% CrI 0.2%, 0.3%) respectively. Seasonality and spatial heterogeneity can partly be explained by the association of common cold to climatic variables. There was statistically significant residual clustering after accounting for covariates. The finding highlights the influence of climatic variables on common cold and suggests that prioritizing control strategies for acute respiratory infection program to subdistricts and times of the year when climatic variables are associated with common cold may be an effective strategy.

PMID:35810192 | DOI:10.1038/s41598-022-16069-7