Climate Change and Cardiovascular Health: A Systematic Review.

Importance: Climate change may increase the risk of adverse cardiovascular outcomes by causing direct physiologic changes, psychological distress, and disruption of health-related infrastructure. Yet, the association between numerous climate change-related environmental stressors and the incidence of adverse cardiovascular events has not been systematically reviewed. Objective: To review the current evidence on the association between climate change-related environmental stressors and adverse cardiovascular outcomes. Evidence Review: PubMed, Embase, Web of Science, and Cochrane Library were searched to identify peer-reviewed publications from January 1, 1970, through November 15, 2023, that evaluated associations between environmental exposures and cardiovascular mortality, acute cardiovascular events, and related health care utilization. Studies that examined only nonwildfire-sourced particulate air pollution were excluded. Two investigators independently screened 20 798 articles and selected 2564 for full-text review. Study quality was assessed using the Navigation Guide framework. Findings were qualitatively synthesized as substantial differences in study design precluded quantitative meta-analysis. Findings: Of 492 observational studies that met inclusion criteria, 182 examined extreme temperature, 210 ground-level ozone, 45 wildfire smoke, and 63 extreme weather events, such as hurricanes, dust storms, and droughts. These studies presented findings from 30 high-income countries, 17 middle-income countries, and 1 low-income country. The strength of evidence was rated as sufficient for extreme temperature; ground-level ozone; tropical storms, hurricanes, and cyclones; and dust storms. Evidence was limited for wildfire smoke and inadequate for drought and mudslides. Exposure to extreme temperature was associated with increased cardiovascular mortality and morbidity, but the magnitude varied with temperature and duration of exposure. Ground-level ozone amplified the risk associated with higher temperatures and vice versa. Extreme weather events, such as hurricanes, were associated with increased cardiovascular risk that persisted for many months after the initial event. Some studies noted a small increase in cardiovascular mortality, out-of-hospital cardiac arrests, and hospitalizations for ischemic heart disease after exposure to wildfire smoke, while others found no association. Older adults, racial and ethnic minoritized populations, and lower-wealth communities were disproportionately affected. Conclusions and Relevance: Several environmental stressors that are predicted to increase in frequency and intensity with climate change are associated with increased cardiovascular risk, but data on outcomes in low-income countries are lacking. Urgent action is needed to mitigate climate change-associated cardiovascular risk, particularly in vulnerable populations.

Inherent Bias in Electronic Health Records: A Scoping Review of Sources of Bias.

Objectives: 1.1Biases inherent in electronic health records (EHRs), and therefore in medical artificial intelligence (AI) models may significantly exacerbate health inequities and challenge the adoption of ethical and responsible AI in healthcare. Biases arise from multiple sources, some of which are not as documented in the literature. Biases are encoded in how the data has been collected and labeled, by implicit and unconscious biases of clinicians, or by the tools used for data processing. These biases and their encoding in healthcare records undermine the reliability of such data and bias clinical judgments and medical outcomes. Moreover, when healthcare records are used to build data-driven solutions, the biases are further exacerbated, resulting in systems that perpetuate biases and induce healthcare disparities. This literature scoping review aims to categorize the main sources of biases inherent in EHRs. Methods: 1.2We queried PubMed and Web of Science on January 19th, 2023, for peer-reviewed sources in English, published between 2016 and 2023, using the PRISMA approach to stepwise scoping of the literature. To select the papers that empirically analyze bias in EHR, from the initial yield of 430 papers, 27 duplicates were removed, and 403 studies were screened for eligibility. 196 articles were removed after the title and abstract screening, and 96 articles were excluded after the full-text review resulting in a final selection of 116 articles. Results: 1.3Systematic categorizations of diverse sources of bias are scarce in the literature, while the effects of separate studies are often convoluted and methodologically contestable. Our categorization of published empirical evidence identified the six main sources of bias: a) bias arising from past clinical trials; b) data-related biases arising from missing, incomplete information or poor labeling of data; human-related bias induced by c) implicit clinician bias, d) referral and admission bias; e) diagnosis or risk disparities bias and finally, (f) biases in machinery and algorithms. Conclusions: 1.4Machine learning and data-driven solutions can potentially transform healthcare delivery, but not without limitations. The core inputs in the systems (data and human factors) currently contain several sources of bias that are poorly documented and analyzed for remedies. The current evidence heavily focuses on data-related biases, while other sources are less often analyzed or anecdotal. However, these different sources of biases add to one another exponentially. Therefore, to understand the issues holistically we need to explore these diverse sources of bias. While racial biases in EHR have been often documented, other sources of biases have been less frequently investigated and documented (e.g. gender-related biases, sexual orientation discrimination, socially induced biases, and implicit, often unconscious, human-related cognitive biases). Moreover, some existing studies lack causal evidence, illustrating the different prevalences of disease across groups, which does not per se prove the causality. Our review shows that data-, human- and machine biases are prevalent in healthcare and they significantly impact healthcare outcomes and judgments and exacerbate disparities and differential treatment. Understanding how diverse biases affect AI systems and recommendations is critical. We suggest that researchers and medical personnel should develop safeguards and adopt data-driven solutions with a "bias-in-mind" approach. More empirical evidence is needed to tease out the effects of different sources of bias on health outcomes.

Machine learning natural language processing for identifying venous thromboembolism: systematic review and meta-analysis.

ABSTRACT: Venous thromboembolism (VTE) is a leading cause of preventable in-hospital mortality. Monitoring VTE cases is limited by the challenges of manual medical record review and diagnosis code interpretation. Natural language processing (NLP) can automate the process. Rule-based NLP methods are effective but time consuming. Machine learning (ML)-NLP methods present a promising solution. We conducted a systematic review and meta-analysis of studies published before May 2023 that use ML-NLP to identify VTE diagnoses in the electronic health records. Four reviewers screened all manuscripts, excluding studies that only used a rule-based method. A meta-analysis evaluated the pooled performance of each study's best performing model that evaluated for pulmonary embolism and/or deep vein thrombosis. Pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with confidence interval (CI) were calculated by DerSimonian and Laird method using a random-effects model. Study quality was assessed using an adapted TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) tool. Thirteen studies were included in the systematic review and 8 had data available for meta-analysis. Pooled sensitivity was 0.931 (95% CI, 0.881-0.962), specificity 0.984 (95% CI, 0.967-0.992), PPV 0.910 (95% CI, 0.865-0.941) and NPV 0.985 (95% CI, 0.977-0.990). All studies met at least 13 of the 21 NLP-modified TRIPOD items, demonstrating fair quality. The highest performing models used vectorization rather than bag-of-words and deep-learning techniques such as convolutional neural networks. There was significant heterogeneity in the studies, and only 4 validated their model on an external data set. Further standardization of ML studies can help progress this novel technology toward real-world implementation.

Antibiotic prophylaxis following low-velocity gunshot fractures: an updated review.

PURPOSE: Low-velocity gunshot fractures (LVGFs) are a common type of gunshot-induced trauma with the potential for complications such as infection and osteomyelitis. The effectiveness of antibiotic therapy in LVGFs remains uncertain, leading to ongoing debate about the appropriate treatment. In this review, we evaluate recent updates on the current understanding of antibiotic therapy in LVGFs, how previous studies have investigated the use of antibiotics in LVGFs, and the current state of institutional policies and protocols for treating LVGFs with antibiotics. METHODS: We conducted a review of PubMed, Embase, and Web of Science databases to identify studies that investigated the use of antibiotics in LVGFs after the last review in 2013. Due to the lack of quantitative clinical trial studies, we employed a narrative synthesis approach to analyze and present the findings from the included primary studies. We categorized the outcomes based on the anatomical location of the LVGFs. RESULTS: After evaluating 67 publications with the necessary qualifications out of 578 abstracts, 17 articles were included. The sample size of the studies ranged from 22 to 252 patients. The antibiotics used in the studies varied, and the follow-up period ranged from three months to ten years. The included studies investigated the use of antibiotics in treating LVGFs at various anatomic locations, including the humerus, forearm, hand and wrist, hip, femur, tibia, and foot and ankle. CONCLUSION: Our study provides updated evidence for the use of antibiotics in LVGFs and highlights the need for further research to establish evidence-based guidelines. We also highlight the lack of institutional policies for treating LVGFs and the heterogeneity in treatments among institutions with established protocols. A single-dose antibiotic approach could be cost-effective for patients with non-operatively treated LVGFs. We suggest that a national or international registry for gunshot injuries, antibiotics, and infections could serve as a valuable resource for collecting and analyzing data related to these important healthcare issues.

Comparison of direct oral anticoagulants versus low-molecular-weight heparin in primary and metastatic brain cancers: a meta-analysis and systematic review.

BACKGROUND: The safety and efficacy of direct-acting oral anticoagulants (DOACs) for therapeutic anticoagulation in the setting of primary or metastatic brain cancer is not known. OBJECTIVES: To conduct a meta-analysis and systematic review of studies that compare the risk of intracranial hemorrhage (ICH) in patients with brain cancer treated with DOACs vs low-molecular-weight heparin (LMWH). METHODS: A literature search was conducted using PubMed, EMBASE, and Cochrane databases. Summary statistics were obtained by calculating the risk ratio (RR), and heterogeneity across studies was estimated using the I2 statistic. A total of 10 retrospective studies (n = 1638) met criteria for inclusion. The primary endpoint was the pooled RR for ICH in patients with brain tumors receiving anticoagulation with DOACs compared with those receiving LMWH. Secondary analyses included the risk of fatal ICH in each subgroup. RESULTS: The pooled RR for ICH in patients receiving DOACs vs those receiving LMWH was 0.65 (95% CI, 0.36-1.17; P = .15; I2 = 50%). In studies evaluating primary brain cancer, there was a reduction in risk of ICH with DOACs (RR, 0.35; 95% CI, 0.18-0.69; P = .003; I2 = 0%). In patients with metastatic brain cancer, there was no difference in the risk of ICH with the type of anticoagulation (RR, 1.05; 95% CI, 0.71-1.56; P = .80; I2 = 0%). The overall risk of fatal ICH was not different between anticoagulants. CONCLUSION: The risk of ICH in patients with brain cancer receiving therapeutic anticoagulation varies by anticoagulation agent and diagnosis of primary or metastatic disease.

While the Incidence of Venous Thromboembolism After Shoulder Arthroscopy Is Low, the Risk Factors Are a Body Mass Index Greater than 30 and Hypertension.

Purpose: This study aims to determine the overall incidence of venous thromboembolism (VTE) following shoulder arthroscopy and to define potential risk factors associated with its development that may help define guidelines for the use of thromboprophylaxis. Methods: A systematic review was performed using PubMed, Embase, Web of Science, CINAHL, and Cochrane databases per PRISMA guidelines. The search terms consisted of variations of "Venous Thromboembolism" and "Shoulder Arthroscopy." Information regarding arthroscopy indication, risk factors, outcomes, and patient demographics was recorded and analyzed, and pooled odds ratios were reported for each variable. Results: Six hundred eighty-five articles were identified in the initial search, and 35 articles reported DVT, PE, or VTE incidence following shoulder arthroscopy. Seventeen nonoverlapping articles with a unique patient population incidence rates. Four articles were then used for subgroup meta-analysis. The incidence rate of VTE was 0.24%, ranging from 0.01% to 5.7%. BMI >30 (OR = 1.46; 95% CI = [1.22, 1.74]; I2 = 0%) and hypertension (OR = 1.64; 95% CI = [1.03, 2.6]; I2 = 75%) were significant risk factors (P < .05) for developing VTE following shoulder arthroscopy. Diabetes (OR = 1.2; 95% CI = [0.97, 1.48]; I2 = 0%), insulin-dependent diabetes (OR = 5.58; 95% CI = [0.12, 260.19]; I2 = 85%), smoking (OR = 1.04; 95% CI = [0.79, 1.37]; I2 = 12%), male sex (OR = 0.95; 95% CI = [0.49, 1.85]; I2 = 86%) and age over 65 (OR = 4.3; 95% CI = [0.25, 72.83]; I2 = 85%) were not associated with higher VTE risk. Conclusion: The VTE incidence following shoulder arthroscopy is low at 0.24%. Patients with BMI >30 and hypertension are at a higher risk for VTE after shoulder arthroscopy. Level of Evidence: Level IV, systematic review and meta-analysis of Level I-IV studies.

Artificial intelligence in the prediction of venous thromboembolism: A systematic review and pooled analysis.

BACKGROUND: Accurate diagnostic and prognostic predictions of venous thromboembolism (VTE) are crucial for VTE management. Artificial intelligence (AI) enables autonomous identification of the most predictive patterns from large complex data. Although evidence regarding its performance in VTE prediction is emerging, a comprehensive analysis of performance is lacking. AIMS: To systematically review the performance of AI in the diagnosis and prediction of VTE and compare it to clinical risk assessment models (RAMs) or logistic regression models. METHODS: A systematic literature search was performed using PubMed, MEDLINE, EMBASE, and Web of Science from inception to April 20, 2021. Search terms included "artificial intelligence" and "venous thromboembolism." Eligible criteria were original studies evaluating AI in the prediction of VTE in adults and reporting one of the following outcomes: sensitivity, specificity, positive predictive value, negative predictive value, or area under receiver operating curve (AUC). Risks of bias were assessed using the PROBAST tool. Unpaired t-test was performed to compare the mean AUC from AI versus conventional methods (RAMs or logistic regression models). RESULTS: A total of 20 studies were included. Number of participants ranged from 31 to 111 888. The AI-based models included artificial neural network (six studies), support vector machines (four studies), Bayesian methods (one study), super learner ensemble (one study), genetic programming (one study), unspecified machine learning models (two studies), and multiple machine learning models (five studies). Twelve studies (60%) had both training and testing cohorts. Among 14 studies (70%) where AUCs were reported, the mean AUC for AI versus conventional methods were 0.79 (95% CI: 0.74-0.85) versus 0.61 (95% CI: 0.54-0.68), respectively (p < .001). However, the good to excellent discriminative performance of AI methods is unlikely to be replicated when used in clinical practice, because most studies had high risk of bias due to missing data handling and outcome determination. CONCLUSION: The use of AI appears to improve the accuracy of diagnostic and prognostic prediction of VTE over conventional risk models; however, there was a high risk of bias observed across studies. Future studies should focus on transparent reporting, external validation, and clinical application of these models.

Clinical and histological features and treatment outcomes of patients with Morbihan disease: a systematic review.

Morbihan disease (MD) is considered a rare complication of rosacea, which is difficult to diagnose and challenging to treat. Here, we performed a systematic review of available case reports and case series to summarize key clinical and pathologic features of and successful treatment regimens for MD. We conducted a search of the PubMed/MEDLINE, EMBASE, and Cochrane electronic databases from their inception to the date of search on March 6, 2023. We found that MD affects patients in the fifth decade of life on average, more commonly reported in male than female (69% vs 31%). Clinically, MD affects the eyelids, cheeks, and forehead most commonly, presenting as non-pitting, erythematous edema or an edematous plaque. On biopsy, the pathologic features, such as dermal edema, sebaceous hyperplasia, perivascular and periadnexal inflammatory infiltrate, and granulomatous reaction, are frequently reported. Out of 55 patients who were able to achieve complete response without recurrence, 35% of patients were treated with isotretinoin and 22% were treated with tetracycline antibiotics with a daily dosage range of 20-80 mg and 40-200 mg, respectively. Out of those 55 patients, 22% and 7% were treated successfully with surgical intervention and intralesional injection of steroids, respectively. Additionally, lymphatic drainage has been shown to be an effective adjunctive therapeutic tool. More studies are necessary to understand the disease mechanism to improve the diagnosis of and develop evidence-based therapies for MD.

Delivering Palliative Care to Hospitalized Oncology Patients: A Scoping Review.

CONTEXT: Early, longitudinal integration of palliative care (PC) is recommended for patients with advanced cancer, in both inpatient and outpatient settings. Despite the growth of specialty PC teams in the last decade, the majority of PC is still delivered in the inpatient setting using a traditional referral-based consult delivery model. However, traditional consultation can lead to significant variation or delay in inpatient PC utilization. New care delivery models and strategies are emerging to deliver PC to hospitalized oncology patients who would most benefit from their services and to better align with professional society recommendations. OBJECTIVES: To identify different care models to deliver PC to ho`spitalized oncology patients and summarize their impact on patient and health system-related outcomes. METHODS: We conducted a scoping review of peer-reviewed articles from 2006 to 2021 evaluating delivery of PC to oncology patients in acute inpatient care. We abstracted study characteristics, the study's intervention and comparison arms, and outcomes related to specialty PC intervention. RESULTS: We identified four delivery models that have been reported to deliver PC: 1) traditional referral-based consultation, 2) criterion-based or "triggered" consultation, 3) co-rounding with primary inpatient team, and 4) PC clinicians serving as the primary team. We summarize the known outcomes data from each model, and compare the benefits and limitations of each model. CONCLUSION: Our findings provide guidance to health systems about care delivery models to deploy and implement inpatient PC resources to best serve their unique populations.

Special Considerations for Supportive Care and Management of Complications in Elderly Patients With Multiple Myeloma.

Multiple myeloma is a progressive and incurable hematologic malignancy. It is predominantly a disease of older individuals, with a third of these patients considered to be elderly. In recent years, there has been a focus and emphasis on identifying and stratifying patients based on their functional status and frailty. There are several hallmark complications of the disease-hypercalcemia, renal insufficiency, anemia, bone pain-along with thromboembolism and compromised immunity that are common in patients with multiple myeloma. Due to the wide range of patient ages and functional status, there are, accordingly, different considerations for management of the above complications based on numerous factors, including frailty status. This review focuses on considerations and management of common complications of multiple myeloma in elderly patients. These include renal failure, skeletal complications, anemia, thromboembolism, and infectious complications.

Revision Arthroplasty Versus Open Reduction and Internal Fixation of Vancouver Type-B2 and B3 Periprosthetic Femoral Fractures.

¼: Revision arthroplasty (RA) continues to be considered the gold standard in the surgical treatment of Vancouver type-B2 and B3 periprosthetic femoral fractures. However, open reduction and internal fixation (ORIF) has been associated with satisfactory outcomes. Thus, there is an ongoing discussion regarding the optimal surgical strategy for the treatment of these fractures. ¼: In this systematic review and meta-analysis, no significant differences in clinical and radiographic outcome were observed between ORIF and RA in the treatment of Vancouver type-B2 periprosthetic femoral fractures. ¼: ORIF of Vancouver type-B3 periprosthetic femoral fractures was associated with higher revision and reoperation rates than those after RA. ¼: Compared with RA, a significantly higher rate of subsidence was found in the ORIF group in Vancouver type-B2 periprosthetic femoral fractures whereas no significant difference in terms of loosening was observed. ¼: In the comparison of RA and ORIF for the treatment of Vancouver type-B2 and B3 fractures, the percentage of patients achieving full weight-bearing did not differ significantly. ¼: Mortality rates did not differ between RA and ORIF in the treatment of Vancouver type-B2 and B3 fractures. ¼: Overall complication rates did not differ between RA and ORIF in the treatment of Vancouver type-B2 and B3 fractures. ¼: We found a high heterogeneity in applied surgical and fixation techniques in the ORIF group.

The Role of Acupuncture in Postoperative Pain Management of Patients Undergoing Knee Arthroplasty Surgery: A Systematic Review and Meta-Analysis.

¼: Acupuncture after total knee arthroplasty (TKA) may decrease the incidence of postoperative nausea and vomiting (PONV). ¼: Acupuncture did not decrease visual analog scale (VAS) scores in the 0 to 48-hour interval but did decrease VAS scores at >48 hours after TKA. ¼: The heterogeneity of the studies prevented meta-analysis of opioid use with acupuncture after TKA; a systematic review demonstrated mixed results. ¼: Additional studies are needed to investigate opioid reduction with acupuncture after TKA.