Heavy metals and trace minerals in commonly available shark species from North East Arabian Sea: A human health risk perspective.

Shark is a seafood commodity that is a good source of minerals and accumulates heavy metals and trace elements through biomagnification, which can pose health risk if taken above the permissible limit. A study was conducted on commonly landed eleven shark species (Scoliodon laticaudus, Rhizopriodon oligolinx, Sphyrna lewini (CR), Carcharhinus macloti, Carcharinus limbatus, Carcharhinus amblyrhynchoides, Carcharhinus sorrah, Carcharinus falciformes(VU), Glaucostegus granulatus, Chiloscyllium arabicum, Loxodon macrorhinus) and analyzed for their heavy metal content, Hazard Index, Total Hazard Quotient, Metal Pollution Index, and also calculated the health risk associated with the consumption. Most of the heavy metals and trace minerals were found to be within the acceptable limit. The Targeted Hazard Quotient (THQ) and the Hazard Index (HI) of all the species except two were less than 1 (HI ≤ 1.0). The Metal Pollution Index (MPI) is showing either no impact or very low contamination. An overall study on hazard identification and health risk characterization in terms of heavy metals shows contamination of some heavy metals in sharks, but there is no potential human health risk associated with consumption.

Cyber Attacker Profiling for Risk Analysis Based on Machine Learning.

The notion of the attacker profile is often used in risk analysis tasks such as cyber attack forecasting, security incident investigations and security decision support. The attacker profile is a set of attributes characterising an attacker and their behaviour. This paper analyzes the research in the area of attacker modelling and presents the analysis results as a classification of attacker models, attributes and risk analysis techniques that are used to construct the attacker models. The authors introduce a formal two-level attacker model that consists of high-level attributes calculated using low-level attributes that are in turn calculated on the basis of the raw security data. To specify the low-level attributes, the authors performed a series of experiments with datasets of attacks. Firstly, the requirements of the datasets for the experiments were specified in order to select the appropriate datasets, and, afterwards, the applicability of the attributes formed on the basis of such nominal parameters as bash commands and event logs to calculate high-level attributes was evaluated. The results allow us to conclude that attack team profiles can be differentiated using nominal parameters such as bash history logs. At the same time, accurate attacker profiling requires the extension of the low-level attributes list.

External Validation of Robust Radiomic Signature to Predict 2-Year Overall Survival in Non-Small-Cell Lung Cancer.

Lung cancer is the second most fatal disease worldwide. In the last few years, radiomics is being explored to develop prediction models for various clinical endpoints in lung cancer. However, the robustness of radiomic features is under question and has been identified as one of the roadblocks in the implementation of a radiomic-based prediction model in the clinic. Many past studies have suggested identifying the robust radiomic feature to develop a prediction model. In our earlier study, we identified robust radiomic features for prediction model development. The objective of this study was to develop and validate the robust radiomic signatures for predicting 2-year overall survival in non-small cell lung cancer (NSCLC). This retrospective study included a cohort of 300 stage I-IV NSCLC patients. Institutional 200 patients' data were included for training and internal validation and 100 patients' data from The Cancer Image Archive (TCIA) open-source image repository for external validation. Radiomic features were extracted from the CT images of both cohorts. The feature selection was performed using hierarchical clustering, a Chi-squared test, and recursive feature elimination (RFE). In total, six prediction models were developed using random forest (RF-Model-O, RF-Model-B), gradient boosting (GB-Model-O, GB-Model-B), and support vector(SV-Model-O, SV-Model-B) classifiers to predict 2-year overall survival (OS) on original data as well as balanced data. Model validation was performed using 10-fold cross-validation, internal validation, and external validation. Using a multistep feature selection method, the overall top 10 features were chosen. On internal validation, the two random forest models (RF-Model-O, RF-Model-B) displayed the highest accuracy; their scores on the original and balanced datasets were 0.81 and 0.77 respectively. During external validation, both the random forest models' accuracy was 0.68. In our study, robust radiomic features showed promising predictive performance to predict 2-year overall survival in NSCLC.

Clinical Concept-Based Radiology Reports Classification Pipeline for Lung Carcinoma.

Rising incidence and mortality of cancer have led to an incremental amount of research in the field. To learn from preexisting data, it has become important to capture maximum information related to disease type, stage, treatment, and outcomes. Medical imaging reports are rich in this kind of information but are only present as free text. The extraction of information from such unstructured text reports is labor-intensive. The use of Natural Language Processing (NLP) tools to extract information from radiology reports can make it less time-consuming as well as more effective. In this study, we have developed and compared different models for the classification of lung carcinoma reports using clinical concepts. This study was approved by the institutional ethics committee as a retrospective study with a waiver of informed consent. A clinical concept-based classification pipeline for lung carcinoma radiology reports was developed using rule-based as well as machine learning models and compared. The machine learning models used were XGBoost and two more deep learning model architectures with bidirectional long short-term neural networks. A corpus consisting of 1700 radiology reports including computed tomography (CT) and positron emission tomography/computed tomography (PET/CT) reports were used for development and testing. Five hundred one radiology reports from MIMIC-III Clinical Database version 1.4 was used for external validation. The pipeline achieved an overall F1 score of 0.94 on the internal set and 0.74 on external validation with the rule-based algorithm using expert input giving the best performance. Among the machine learning models, the Bi-LSTM_dropout model performed better than the ML model using XGBoost and the Bi-LSTM_simple model on internal set, whereas on external validation, the Bi-LSTM_simple model performed relatively better than other 2. This pipeline can be used for clinical concept-based classification of radiology reports related to lung carcinoma from a huge corpus and also for automated annotation of these reports.

Spending outcomes among patients with cancer in accountable care organizations 4 years after implementation.

BACKGROUND: The long-term impact of affordable care organizations (ACOs) on cancer spending remains unknown. The authors examined whether practices that became ACOs altered their spending for patients with cancer in the first 4 years after ACO implementation. METHODS: By using national Medicare data from 2011 to 2017, a random sample of 20% of fee-for-service Medicare beneficiaries aged 65 years and older with cancer was obtained (n = 866,532), and each patient was assigned to a practice. Practices that became ACOs in the Medicare Shared Savings Program were matched to non-ACO practices. Total, cancer-specific, and service category-specific yearly spending per patient was calculated. A difference-in-differences model was used to determine spending changes associated with ACO status for patients with cancer in the 4 years after ACO implementation. RESULTS: The introduction of ACOs did not have a significant impact on overall spending for patients with cancer in the 2 years after ACO implementation (difference, -$38; 95% CI, -$268, $191; P = .74). Changes in spending also did not differ between ACO and non-ACO patients within service categories or among the 11 cancer types examined. The lack of difference in spending for patients with cancer in ACO and non-ACO practices persisted in the third and fourth years after ACO implementation (difference, -$120; 95% CI, -$284, $525; P = .56). CONCLUSIONS: ACOs did not significantly change spending for patients with cancer in the first 4 years after their implementation compared with non-ACOs. This prompts a reevaluation of the current efficacy of ACOs in reducing spending for cancer care and may encourage policymakers to reconsider the incentive structures of ACOs. LAY SUMMARY: Accountable care organizations (ACOs) were developed to curtail health care spending and improve quality, but their effects on cancer spending in their first 2 years have been minimal. The long-term impact of ACOs on cancer spending remains unknown. By using data from 866,532 Medicare beneficiaries with cancer, the authors observed that the association of a practice with an ACO did not significantly change total yearly spending per patient in the first 4 years after ACO implementation. This finding prompts a reevaluation of the current efficacy of ACOs in reducing spending for cancer care.

ACO Spending and Utilization Among Medicare Patients at the End of Life: an Observational Study.

BACKGROUND: End-of-life (EOL) costs constitute a substantial portion of healthcare spending in the USA and have been increasing. ACOs may offer an opportunity to improve quality and curtail EOL spending. OBJECTIVE: To examine whether practices that became ACOs altered spending and utilization at the EOL. DESIGN: Retrospective analysis of Medicare claims. PATIENTS: We assigned patients who died in 2012 and 2015 to an ACO or non-ACO practice. Practices that converted to ACOs in 2013 or 2014 were matched to non-ACOs in the same region. A total of 23,643 ACO patients were matched to 23,643 non-ACO patients. MAIN MEASURES: Using a difference-in-differences model, we examined changes in EOL spending and care utilization after ACO implementation. KEY RESULTS: The introduction of ACOs did not significantly impact overall spending for patients in the last 6 months of life (difference-in-difference (DID) = $192, 95%CI -$841 to $1125, P = 0.72). Changes in spending did not differ between ACO and non-ACO patients across spending categories (inpatient, outpatient, physician services, skilled nursing, home health, hospice). No differences were seen between ACO and non-ACO patients in rates of ED visits, inpatient admissions, ICU admission, mean healthy days at home, and mean hospice days at 180 and 30 days prior to death. However, non-ACO patients had a significantly greater increase in hospice utilization compared to ACO patients at 180 days (DID P-value = 0.02) and 30 days (DID P-value = 0.01) prior to death. CONCLUSIONS: With the exception of hospice care utilization, spending and utilization were not different between ACOs and non-ACO patients at the EOL. Longer follow-up may be necessary to evaluate the impact of ACOs on EOL spending and care.

Healthy days at home: A population-based quality measure for cancer patients at the end of life.

BACKGROUND: Healthy Days at Home (HDAH) is a novel population-based outcome measure. In this study, its use as a potential measure for cancer patients at the end of life (EOL) was explored. METHODS: Patient demographics and health care use among Medicare beneficiaries with cancer who died over the years 2014 to 2017 were identified. The HDAH was calculated by subtracting the following components from 180 days: number of days spent in inpatient and outpatient hospital observation, the emergency room, skilled nursing facilities (SNF), inpatient psychiatry, inpatient rehabilitation, long-term hospitals, and inpatient hospice. How HDAH and its components varied by beneficiary demographics and health care market were evaluated. A patient-level linear regression model with HDAH as the outcome, hospital referral region (HRR) random effects, and market fixed effects were specified, as well as beneficiary age, sex, and comorbidities as covariates. RESULTS: The 294,751 beneficiaries at the EOL showed a mean number of 154.0 HDAH (out of 180 days). Inpatient (10.7 days) and SNF (9.7 days) resulted in the most substantial reductions in HDAH. Males had fewer adjusted HDAH (153.1 vs 155.7, P < .001) than females; Medicaid-eligible patients had fewer HDAH compared with non-Medicaid-eligible patients (152.0 vs 154.9; P < .001). Those with hematologic malignancies had the fewest number of HDAH (148.9). Across HRRs, HDAH ranged from 10.8 fewer to 10.9 more days than the national mean. At the HRR-level, home hospice was associated with greater HDAH, whereas home health was associated with fewer HDAH. CONCLUSIONS: HDAH may be a useful measure to understand, quantify, and improve patient-centered outcomes for cancer patients at EOL.

Comparison of Patient Outcomes of Surgeons Who Are US Versus International Medical Graduates.

OBJECTIVE: The aim of this study was to compare patient outcomes between International Medical Graduate (IMG) versus US medical graduate (USMG) surgeons. SUMMARY BACKGROUND DATA: One in 7 surgeons practicing in the US graduated from a foreign medical school. However, it remains unknown whether patient outcomes differ between IMG versus USMG surgeons. METHODS: Using 20% random sample of Medicare fee-for-service beneficiaries aged 65 to 99 years who underwent 1 of 13 common nonelective surgical procedures (as a "natural experiment" as surgeons are less likely to select patients in this context) in 2011 to 2014 (638,973 patients treated by 37,221 surgeons for the mortality analysis), we compared operative mortality, complications, and length of stay (LOS) between IMG and USMG surgeons, adjusting for patient and surgeon characteristics and hospital-specific fixed effects (effectively comparing IMG and USMG surgeons within the same hospital). We also conducted stratified analyses by patients' severity of illness and procedure type. RESULTS: We found no evidence that patient outcomes differ between IMG and USMG surgeons for operative mortality [adjusted mortality, 7.3% for IMGs vs 7.3% for USMGs; adjusted odds ratio (aOR), 1.01; 95% confidence interval (CI), 0.96-1.05; P = 0.79], complication rate (adjusted complication rate, 0.6% vs 0.6%; aOR, 0.95; 95% CI, 0.85-1.06; P = 0.43), and LOS (adjusted LOS, 6.6 days vs 6.6 days; adjusted difference, +0.02 days; 95% CI, -0.05 to +0.08; P = 0.54). We also found no difference when we stratified by severity of illness and procedures. CONCLUSION: Using national data of Medicare beneficiaries who underwent common surgical procedures, we found no evidence that outcomes differ between IMG and USMG surgeons.

Persistence and Drivers of High-Cost Status Among Dual-Eligible Medicare and Medicaid Beneficiaries: An Observational Study.

Background: Little is known about the persistence of high-cost status among dual-eligible Medicare and Medicaid beneficiaries, who account for a substantial proportion of expenditures in both programs. Objective: To determine what proportion of this population has persistently high costs. Design: Observational study. Setting: Medicare-Medicaid Linked Enrollee Analytic Data Source data for 2008 to 2010. Participants: 1 928 340 dual-eligible Medicare and Medicaid beneficiaries who were alive all 3 years. Measurements: Medicare and Medicaid payments for these beneficiaries were calculated for each year. Beneficiaries were categorized as high-cost for a given year if their spending was in the top 10% for that year. Differences in spending were then examined for those who were persistently high-cost (all 3 years) versus those who were transiently high-cost (2008 but not 2009 or 2010) and those who were non-high-cost in all 3 years. Results: In the first year, 192 835 patients were high-cost. More than half (54.8%) remained high-cost across all 3 years. These patients were younger than transiently high-cost patients, with fewer medical comorbidities and greater intellectual impairment. Persistently high-cost patients spent $161 224 per year compared with $86 333 per year for transiently high-cost patients and $22 352 per year for non-high-cost patients. Most of the spending among persistently high-cost patients (68.8%) was related to long-term care, and very little (<1%) was related to potentially preventable hospitalizations for ambulatory care-sensitive conditions. Limitation: Potential misclassification of preventable spending and lack of detailed clinical data in administrative claims. Conclusion: A substantial majority of high-cost dual-eligible beneficiaries had persistently high costs over 3 years, with most of the cost related to long-term care and very little related to potentially preventable hospitalizations. Primary Funding Source: Peterson Center on Healthcare.

Lessons From the Mpox Response.

This Viewpoint discusses 3 key lessons from the mpox response that can help better manage infectious disease outbreaks in the future.

Radiation-induced brachial plexus neuropathy: A review.

Radiation-induced brachial plexus neuropathy (RIBPN) is an uncommon problem. It is a delayed nontraumatic brachial plexus neuropathy following radiation treatment for carcinomas in the region of neck, axilla, and chest wall. The incidence is more commonly reported following radiation treatment for carcinoma of breast. The neurological features are characterized by severe neurogenic pain with progressive sensory-motor deficits in the affected upper limb. The incidence has increased following improved survival rate of patients with carcinomas of neck, axilla, and chest wall. The diagnosis of RIBPN is often confused with recurrence of the tumor in the neck and axilla. The management options are limited, and external neurolysis of the involved brachial plexus with excision of the perineural scar tissue is recommended in patients with severe clinical manifestations. We review our experience in the management of RIBPN from 2004 to 2017 and highlight the features of the 11 patients with this disorder whom we encountered during this period. The relevant clinical findings, natural history, pathophysiology, radiological characteristics, and various management options are briefly discussed.

Injection-related iatrogenic peripheral nerve injuries: Surgical experience of 354 operated cases.

OBJECTIVE: A retrospective analysis of surgically treated 354 cases of injection-related iatrogenic peripheral nerve injuries was performed. The purpose of this clinical study was to present our experience in the management of various types of injection-related peripheral nerve injuries and discuss various issues that are associated with this subset of peripheral nerve injuries. METHODS: Over a 17-year period, 354 cases of injection-related iatrogenic peripheral nerve injuries were managed surgically at the Department of Neurosurgery at P.D. Hinduja Hospital and Seth G S Medical College, Mumbai. In our series, the injection-related iatrogenic nerve injuries were following intramuscular injections, brachial nerves block procedures, subclavian and jugular venous cannulation procedures for central line placements, and routine intravenous injections in the peripheral veins of the limbs. The age of the patients ranged from 5 years to 65 years. Pain, paresthesia, and sensory-motor deficits were the common presenting features in our series. The operative procedures performed in our series were external neurolysis and excision of neuroma/contused portion of the nerve and sural nerve cable grafting. The follow-up ranged from 6 months to 84 months. There were no major intraoperative complications in our series. RESULTS: In our series, functional improvement (power grade 3 or above) was noted in 190 (53.7%) patients following surgical intervention. In 164 (46.3%) patients, there was either a non-functional status or no recovery. Neurological deterioration in the form of motor weakness was noted in 9 (2.5%) patients in our series after the surgery. The best results (90.1%) were noted with radial nerve repair following surgical intervention. CONCLUSION: Injection-related iatrogenic nerve injuries are not an uncommon problem. Surgery should be the preferred treatment option when the injured nerve fails to recover following the insult. The results are rewarding in a significant percentage of patients following timely intervention. The problem of litigation attached with this type of injury is also highlighted.

National Trends in Readmission Following Inpatient Surgery in the Hospital Readmissions Reduction Program Era.

OBJECTIVE: The aim of this study was to investigate whether the Hospital Readmissions Reduction Program, a national program that introduced financial penalties for high readmission rates for certain medical conditions, had a "spillover" effect on surgical conditions. SUMMARY BACKGROUND DATA: During the past decade, there have been multiple national efforts to improve surgical care. Readmission rates are a key metric for assessing surgical quality. Whether surgical readmission rates have declined, and whether the Hospital Readmissions Reduction Program has had an influence is unclear. METHODS: Using national Medicare data, we identified patients undergoing a range of procedures during the past decade. We examined whether certain procedures that would be targeted by the HRRP had a differential change in readmissions compared to other procedures. We used an interrupted time-series model to examine readmission trends in three time periods: pre-ACA, HRRP implementation, and HRRP penalty. RESULTS: Between 2005 and 2014, 17,423,106 patients underwent the procedures of interest; risk-adjusted rates of readmission across the 8 procedures declined from 12.2% to 8.6%. Pre-ACA rates of readmission were decreasing [-0.060% per quarter (-0.072%, -0.048%), P < 0.001]. During the HRRP implementation period, the rate of decline of readmissions increased [-0.129% (-0.142%, -0.116%), P < 0.001] and continued declining at a similar rate during the penalty period [-0.118% (-0.131%, -0.105%), P < 0.001]. Largest declines in surgical readmissions were seen among the nontargeted procedures. The hospitals with the greatest reductions in medical readmissions also had the greatest drop in surgical readmissions. CONCLUSIONS: Surgical readmission rates have fallen during the past decade and rates of decline have increased during the HRRP period.

A framework for learning about improvement: embedded implementation and evaluation design to optimize learning.

Improving health care involves many actors, often working in complex adaptive systems. Interventions tend to be multi-factorial, implementation activities diverse, and contexts dynamic and complicated. This makes improvement initiatives challenging to describe and evaluate as matching evaluation and program designs can be difficult, requiring collaboration, trust and transparency. Collaboration is required to address important epidemiological principles of bias and confounding. If this does not take place, results may lack credibility because the association between interventions implemented and outcomes achieved is obscure and attribution uncertain. Moreover, lack of clarity about what was implemented, how it was implemented, and the context in which it was implemented often lead to disappointment or outright failure of spread and scale-up efforts. The input of skilled evaluators into the design and conduct of improvement initiatives can be helpful in mitigating these potential problems. While evaluation must be rigorous, if it is too rigid necessary adaptation and learning may be compromised. This article provides a framework and guidance on how improvers and evaluators can work together to design, implement and learn about improvement interventions more effectively.

Changes in Hospital-Physician Affiliations in U.S. Hospitals and Their Effect on Quality of Care.

BACKGROUND: Growing evidence shows that hospitals are increasingly employing physicians. OBJECTIVE: To examine changes in U.S. acute care hospitals that reported employment relationships with their physicians and to determine whether quality of care improved after the hospitals switched to this integration model. DESIGN: Retrospective cohort study of U.S. acute care hospitals between 2003 and 2012. SETTING: U.S. nonfederal acute care hospitals. PARTICIPANTS: 803 switching hospitals compared with 2085 nonswitching control hospitals matched for year and region. INTERVENTION: Hospitals' conversion to an employment relationship with any of their privileged physicians. MEASUREMENTS: Risk-adjusted hospital-level mortality rates, 30-day readmission rates, length of stay, and patient satisfaction scores for common medical conditions. RESULTS: In 2003, approximately 29% of hospitals employed members of their physician workforce, a number that rose to 42% by 2012. Relative to regionally matched controls, switching hospitals were more likely to be large (11.6% vs. 7.1%) or major teaching hospitals (7.5% vs. 4.5%) and less likely to be for-profit institutions (8.8% vs. 19.9%) (all P values <0.001). Up to 2 years after conversion, no association was found between switching to an employment model and improvement in any of 4 primary composite quality metrics. LIMITATIONS: The measure of integration used depends on responses to the American Hospital Association annual questionnaire, yet this measure has been used by others to examine effects of integration. The study examined performance up to 2 years after evidence of switching to an employment model; however, beneficial effects may have taken longer to appear. CONCLUSION: During the past decade, hospitals have increasingly become employers of physicians. The study's findings suggest that physician employment alone probably is not a sufficient tool for improving hospital care. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality and National Science Foundation Graduate Research Fellowship.