Cardiovascular Disease Risk Factor Control in People With and Without HIV.

BACKGROUND: Management of hypertension, dyslipidemia, diabetes and other modifiable factors may mitigate the cardiovascular disease (CVD) risk in people with human immunodeficiency virus (HIV, PWH) compared with people without HIV (PWoH). METHODS: This was a retrospective cohort study of 8285 PWH and 170 517 PWoH from an integrated health system. Risk factor control was measured using a novel disease management index (DMI) accounting for amount/duration above treatment goals (0% to 100% [perfect control]), including 2 DMIs for hypertension (diastolic and systolic blood pressure), 3 for dyslipidemia (low-density lipoprotein, total cholesterol, triglycerides), and 1 for diabetes (HbA1c). CVD risk by HIV status was evaluated overall and in subgroups defined by DMIs, smoking, alcohol use, and overweight/obesity in adjusted Cox proportional hazards models. RESULTS: PWH and PWoH had similar DMIs (80%-100%) except for triglycerides (worse for PWH) and HbA1c (better for PWH). In adjusted models, PWH had an elevated risk of CVD compared with PWoH (hazard ratio [HR], 1.18; 95% confidence interval [CI], 1.07-1.31). This association was attenuated in subgroups with controlled dyslipidemia and diabetes but remained elevated for PWH with controlled hypertension or higher total cholesterol. The strongest HIV status association with CVD was seen in the subgroup with frequent unhealthy alcohol use (HR, 2.13; 95% CI, 1.04-4.34). CONCLUSIONS: Control of dyslipidemia and diabetes, but not hypertension, attenuated the HIV status association with CVD. The strong association of HIV and CVD with frequent unhealthy alcohol use suggests enhanced screening and treatment of alcohol problems in PWH is warranted.

Social Determinants of Health and Limitation of Life-Sustaining Therapy in Neurocritical Care: A CHoRUS Pilot Project.

BACKGROUND: Social determinants of health (SDOH) have been linked to neurocritical care outcomes. We sought to examine the extent to which SDOH explain differences in decisions regarding life-sustaining therapy, a key outcome determinant. We specifically investigated the association of a patient's home geography, individual-level SDOH, and neighborhood-level SDOH with subsequent early limitation of life-sustaining therapy (eLLST) and early withdrawal of life-sustaining therapy (eWLST), adjusting for admission severity. METHODS: We developed unique methods within the Bridge to Artificial Intelligence for Clinical Care (Bridge2AI for Clinical Care) Collaborative Hospital Repository Uniting Standards for Equitable Artificial Intelligence (CHoRUS) program to extract individual-level SDOH from electronic health records and neighborhood-level SDOH from privacy-preserving geomapping. We piloted these methods to a 7 years retrospective cohort of consecutive neuroscience intensive care unit admissions (2016-2022) at two large academic medical centers within an eastern Massachusetts health care system, examining associations between home census tract and subsequent occurrence of eLLST and eWLST. We matched contextual neighborhood-level SDOH information to each census tract using public data sets, quantifying Social Vulnerability Index overall scores and subscores. We examined the association of individual-level SDOH and neighborhood-level SDOH with subsequent eLLST and eWLST through geographic, logistic, and machine learning models, adjusting for admission severity using admission Glasgow Coma Scale scores and disorders of consciousness grades. RESULTS: Among 20,660 neuroscience intensive care unit admissions (18,780 unique patients), eLLST and eWLST varied geographically and were independently associated with individual-level SDOH and neighborhood-level SDOH across diagnoses. Individual-level SDOH factors (age, marital status, and race) were strongly associated with eLLST, predicting eLLST more strongly than admission severity. Individual-level SDOH were more strongly predictive of eLLST than neighborhood-level SDOH. CONCLUSIONS: Across diagnoses, eLLST varied by home geography and was predicted by individual-level SDOH and neighborhood-level SDOH more so than by admission severity. Structured shared decision-making tools may therefore represent tools for health equity. Additionally, these findings provide a major warning: prognostic and artificial intelligence models seeking to predict outcomes such as mortality or emergence from disorders of consciousness may be encoded with self-fulfilling biases of geography and demographics.

Representing and utilizing clinical textual data for real world studies: An OHDSI approach.

Clinical documentation in electronic health records contains crucial narratives and details about patients and their care. Natural language processing (NLP) can unlock the information conveyed in clinical notes and reports, and thus plays a critical role in real-world studies. The NLP Working Group at the Observational Health Data Sciences and Informatics (OHDSI) consortium was established to develop methods and tools to promote the use of textual data and NLP in real-world observational studies. In this paper, we describe a framework for representing and utilizing textual data in real-world evidence generation, including representations of information from clinical text in the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), the workflow and tools that were developed to extract, transform and load (ETL) data from clinical notes into tables in OMOP CDM, as well as current applications and specific use cases of the proposed OHDSI NLP solution at large consortia and individual institutions with English textual data. Challenges faced and lessons learned during the process are also discussed to provide valuable insights for researchers who are planning to implement NLP solutions in real-world studies.

NSAID use and clinical outcomes in COVID-19 patients: a 38-center retrospective cohort study.

BACKGROUND: Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community-acquired pneumonia. Observations shortly after the start of the COVID-19 pandemic in 2020 suggested that ibuprofen was associated with an increased risk of adverse events in COVID-19 patients, but subsequent observational studies failed to demonstrate increased risk and in one case showed reduced risk associated with NSAID use. METHODS: A 38-center retrospective cohort study was performed that leveraged the harmonized, high-granularity electronic health record data of the National COVID Cohort Collaborative. A propensity-matched cohort of 19,746 COVID-19 inpatients was constructed by matching cases (treated with NSAIDs at the time of admission) and 19,746 controls (not treated) from 857,061 patients with COVID-19 available for analysis. The primary outcome of interest was COVID-19 severity in hospitalized patients, which was classified as: moderate, severe, or mortality/hospice. Secondary outcomes were acute kidney injury (AKI), extracorporeal membrane oxygenation (ECMO), invasive ventilation, and all-cause mortality at any time following COVID-19 diagnosis. RESULTS: Logistic regression showed that NSAID use was not associated with increased COVID-19 severity (OR: 0.57 95% CI: 0.53-0.61). Analysis of secondary outcomes using logistic regression showed that NSAID use was not associated with increased risk of all-cause mortality (OR 0.51 95% CI: 0.47-0.56), invasive ventilation (OR: 0.59 95% CI: 0.55-0.64), AKI (OR: 0.67 95% CI: 0.63-0.72), or ECMO (OR: 0.51 95% CI: 0.36-0.7). In contrast, the odds ratios indicate reduced risk of these outcomes, but our quantitative bias analysis showed E-values of between 1.9 and 3.3 for these associations, indicating that comparatively weak or moderate confounder associations could explain away the observed associations. CONCLUSIONS: Study interpretation is limited by the observational design. Recording of NSAID use may have been incomplete. Our study demonstrates that NSAID use is not associated with increased COVID-19 severity, all-cause mortality, invasive ventilation, AKI, or ECMO in COVID-19 inpatients. A conservative interpretation in light of the quantitative bias analysis is that there is no evidence that NSAID use is associated with risk of increased severity or the other measured outcomes. Our results confirm and extend analogous findings in previous observational studies using a large cohort of patients drawn from 38 centers in a nationally representative multicenter database.

Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network.

BACKGROUND: We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient's risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients. METHODS: We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date. RESULTS: Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69-0.81, COVER-I: 0.73-0.91, and COVER-F: 0.72-0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations. CONCLUSIONS: This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use.

Health System-Based Unhealthy Alcohol Use Screening and Treatment Comparing Demographically Matched Participants With and Without HIV.

BACKGROUND: Unhealthy alcohol use among persons living with HIV (PLWH) is linked to significant morbidity, and use of alcohol services may differ by HIV status. Our objective was to compare unhealthy alcohol use screening and treatment by HIV status in primary care. METHODS: Cohort study of adult (≥18 years) PLWH and HIV-uninfected participants frequency matched 20:1 to PLWH by age, sex, and race/ethnicity who were enrolled in a large integrated healthcare system in the United States, with information ascertained from an electronic health record. Outcomes included unhealthy alcohol screening, prevalence, provider-delivered brief interventions, and addiction specialty care visits. Other predictors included age, sex, race/ethnicity, neighborhood deprivation index, depression, smoking, substance use disorders, Charlson comorbidity index, prior outpatient visits, insurance type, and medical facility. Cox proportional hazards models were used to compute hazard ratios (HR) for the outcomes of time to unhealthy alcohol use screening and time to first addiction specialty visit. Poisson regression with robust standard errors was used to compute prevalence ratios (PR) for other outcomes. RESULTS: 11,235 PLWH and 227,320 HIV-uninfected participants were included. By 4.5 years after baseline, most participants were screened for unhealthy alcohol use (85% of PLWH and 93% of HIV-uninfected), but with a lower rate among PLWH (adjusted HR 0.84, 95% CI 0.82 to 0.85). PLWH were less likely, compared with HIV-uninfected participants, to report unhealthy drinking among those screened (adjusted PR 0.74, 95% CI 0.69 to 0.79), and among those who screened positive, less likely to receive brief interventions (adjusted PR 0.82, 95% CI 0.75 to 0.90), but more likely (adjusted HR 1.7, 95% CI 1.2 to 2.4) to have an addiction specialty visit within 1 year. CONCLUSIONS: Unhealthy alcohol use was lower in PLWH, but the treatment approach by HIV status differed. PLWH reporting unhealthy alcohol use received less brief interventions and more addiction specialty care than HIV-uninfected participants.

HemOnc: A new standard vocabulary for chemotherapy regimen representation in the OMOP common data model.

Systematic application of observational data to the understanding of impacts of cancer treatments requires detailed information models allowing meaningful comparisons between treatment regimens. Unfortunately, details of systemic therapies are scarce in registries and data warehouses, primarily due to the complex nature of the protocols and a lack of standardization. Since 2011, we have been creating a curated and semi-structured website of chemotherapy regimens, HemOnc.org. In coordination with the Observational Health Data Sciences and Informatics (OHDSI) Oncology Subgroup, we have transformed a substantial subset of this content into the OMOP common data model, with bindings to multiple external vocabularies, e.g., RxNorm and the National Cancer Institute Thesaurus. Currently, there are >73,000 concepts and >177,000 relationships in the full vocabulary. Content related to the definition and composition of chemotherapy regimens has been released within the ATHENA tool (athena.ohdsi.org) for widespread utilization by the OHDSI membership. Here, we describe the rationale, data model, and initial contents of the HemOnc vocabulary along with several use cases for which it may be valuable.

Harms of cervical cancer screening in the United States and the Netherlands.

We studied harms related to cervical cancer screening and management of screen-positive women in the United States (US) and the Netherlands. We utilized data from four US integrated health care systems (SEARCH), the US National Health Interview Survey, New Mexico state, the Netherlands national histopathology registry, and included studies on adverse health effects of cervical screening. We compared the number of Papanicolaou (Pap) smear tests, abnormal test results, punch biopsies, treatments, health problems (anxiety, pain, bleeding and discharge) and preterm births associated with excisional treatments. Results were age-standardized to the 2007 US population. Based on SEARCH, an estimated 36 million Pap tests were performed in 2007 for 91 million US women aged 21-65 years, leading to 2.3 million abnormal Pap tests, 1.5 million punch biopsies, 0.3 million treatments for precancerous lesions, 5 thousand preterm births and over 8 million health problems. Under the Netherlands screening practice, fewer Pap tests (58%), abnormal test results (64%), punch biopsies (75%), treatment procedures (40%), preterm births (60%) and health problems (63%) would have occurred. The SEARCH data did not differ much from other US data for 2007 or from more recent data up to 2013. Thus compared to the less intensive screening practice in the Netherlands, US practice of cervical cancer screening may have resulted in two- to threefold higher harms, while the effects on cervical cancer incidence and mortality are similar. The results are also of high relevance in making recommendations for HPV screening. Systematic collection of harms data is needed for monitoring and for better incorporation of harms in making screening recommendations.

Evidence for chemokine synergy during neutrophil migration in ARDS.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a life-threatening condition characterised by pulmonary oedema, respiratory failure and severe inflammation. ARDS is further characterised by the recruitment of neutrophils into the lung interstitium and alveolar space. OBJECTIVES: The factors that regulate neutrophil infiltration into the inflamed lung and our understanding of the pathomechanisms in ARDS remain incomplete. This study aimed at determining the role of the chemokine (C-C motif) ligand (CCL)2 and CCL7 in ARDS. METHODS: CCL2 and CCL7 protein levels were measured in bronchoalveolar lavage (BAL) fluid obtained from lipopolysaccharide(LPS)-challenged human volunteers and two separate cohorts of patients with ARDS. Neutrophil chemotaxis to ARDS BAL fluid was evaluated and the contribution of each was assessed and compared with chemokine (C-X-C motif) ligand 8 (CXCL8). Chemokine receptor expression on neutrophils from blood or BAL fluid of patients with ARDS was analysed by flow cytometry. RESULTS: CCL2 and CCL7 were significantly elevated in BAL fluid recovered from LPS-challenged volunteers and patients with ARDS. BAL fluid from patients with ARDS was highly chemotactic for human neutrophils and neutralising either CCL2 or CCL7 attenuated the neutrophil chemotactic response. Moreover, CCL2 and CCL7 synergised with CXCL8 to promote neutrophil migration. Furthermore, neutrophils isolated from the blood or BAL fluid differentially regulated the cell surface expression of chemokine (C-X-C motif) receptor 1 and C-C chemokine receptor type 2 during ARDS. CONCLUSION: This study highlights important inflammatory chemokines involved in regulating neutrophil migration, which may have potential value as therapeutic targets for the treatment of ARDS.

Regulation of neutrophilic inflammation by proteinase-activated receptor 1 during bacterial pulmonary infection.

Neutrophils are key effector cells of the innate immune response to pathogenic bacteria, but excessive neutrophilic inflammation can be associated with bystander tissue damage. The mechanisms responsible for neutrophil recruitment to the lungs during bacterial pneumonia are poorly defined. In this study, we focus on the potential role of the major high-affinity thrombin receptor, proteinase-activated receptor 1 (PAR-1), during the development of pneumonia to the common lung pathogen Streptococcus pneumoniae. Our studies demonstrate that neutrophils were indispensable for controlling S. pneumoniae outgrowth but contributed to alveolar barrier disruption. We further report that intra-alveolar coagulation (bronchoalveolar lavage fluid thrombin-antithrombin complex levels) and PAR-1 immunostaining were increased in this model of bacterial lung infection. Functional studies using the most clinically advanced PAR-1 antagonist, SCH530348, revealed a key contribution for PAR-1 signaling in influencing neutrophil recruitment to lung airspaces in response to both an invasive and noninvasive strain of S. pneumoniae (D39 and EF3030) but that PAR-1 antagonism did not impair the ability of the host to control bacterial outgrowth. PAR-1 antagonist treatment significantly decreased pulmonary levels of IL-1ß, CXCL1, CCL2, and CCL7 and attenuated alveolar leak. Ab neutralization studies further demonstrated a nonredundant role for IL-1ß, CXCL1, and CCL7 in mediating neutrophil recruitment in response to S. pneumoniae infection. Taken together, these data demonstrate a key role for PAR-1 during S. pneumoniae lung infection that is mediated, at least in part, by influencing multiple downstream inflammatory mediators.

Cardio-oncology: The Role of Big Data.

Despite its challenges, a "big data" approach offers a unique opportunity within the field of cardio-oncology. A pharmacovigilant approach using large data sets can help characterize cardiovascular toxicities of the rapidly expanding armamentarium of targeted therapies. Creating a broad coalition of data sharing can provide insights into the incidence of cardiotoxicity and stimulate research into the underlying mechanisms. Population health necessitates the use of big data and can help inform public health interventions to prevent both cancer and cardiovascular disease. As a relatively new discipline, cardio-oncology is poised to take advantage of big data.

Health literacy-listening skill and patient questions following cancer prevention and screening discussions.

OBJECTIVE: Patient question-asking is essential to shared decision making. We sought to describe patients' questions when faced with cancer prevention and screening decisions, and to explore differences in question-asking as a function of health literacy with respect to spoken information (health literacy-listening). METHODS: Four-hundred and thirty-three (433) adults listened to simulated physician-patient interactions discussing (i) prophylactic tamoxifen for breast cancer prevention, (ii) PSA testing for prostate cancer and (iii) colorectal cancer screening, and identified questions they would have. Health literacy-listening was assessed using the Cancer Message Literacy Test-Listening (CMLT-Listening). Two authors developed a coding scheme, which was applied to all questions. Analyses examined whether participants scoring above or below the median on the CMLT-Listening asked a similar variety of questions. RESULTS: Questions were coded into six major function categories: risks/benefits, procedure details, personalizing information, additional information, decision making and credibility. Participants who scored higher on the CMLT-Listening asked a greater variety of risks/benefits questions; those who scored lower asked a greater variety of questions seeking to personalize information. This difference persisted after adjusting for education. CONCLUSION: Patients' health literacy-listening is associated with distinctive patterns of question utilization following cancer screening and prevention counselling. Providers should not only be responsive to the question functions the patient favours, but also seek to ensure that the patient is exposed to the full range of information needed for shared decision making.

Enhanced inflammation in aged mice following infection with Streptococcus pneumoniae is associated with decreased IL-10 and augmented chemokine production.

Streptococcus pneumoniae is the most common cause of severe pneumonia in the elderly. However, the impact of aging on the innate inflammatory response to pneumococci is poorly defined. We compared the innate immune response in old vs. young adult mice following infection with S. pneumoniae. The accumulation of neutrophils recovered from bronchoalveolar lavage fluid and lung homogenates was increased in aged compared with young adult mice, although bacterial outgrowth was similar in both age groups, as were markers of microvascular leak. Aged mice had similar levels of IL-1ß, TNF, IFN-γ, IL-17, and granulocyte colony-stimulating factor following S. pneumoniae infection, compared with young mice, but increased levels of the chemokines CXCL9, CXCL12, CCL3, CCL4, CCL5, CCL11, and CCL17. Moreover, levels of IL-10 were significantly lower in aged animals. Neutralization of IL-10 in infected young mice was associated with increased neutrophil recruitment but no decrease in bacterial outgrowth. Furthermore, IL-10 neutralization resulted in increased levels of CCL3, CCL5, and CXCL10. We conclude that aging is associated with enhanced inflammatory responses following S. pneumoniae infection as a result of a compromised immunomodulatory cytokine response.

Cervical cancer screening and follow-up in 4 geographically diverse US health care systems, 1998 through 2007.

BACKGROUND: Cervical cancer screening and follow-up guidelines have changed considerably in recent years, but to the authors' knowledge few published reports exist to estimate the impact of these changes in community-based settings. The authors examined the patterns and results of cervical cancer testing and follow-up over a decade in 4 geographically diverse US health care systems to inform the future evaluation of changes resulting from increased uptake of the human papillomavirus (HPV) vaccination. METHODS: The authors studied women aged 21 to 65 years who were members of one of these health systems at any time between 1998 and 2007. Data were collected and standardized across sites, based on receipt of Papanicolaou (Pap) and HPV tests, HPV vaccination, cervical biopsies, and treatment of cervical dysplasia. Annual rates (per 1000 person-years) of Pap testing, HPV testing, and cervical biopsy and treatment procedures were calculated. Screening intervals and trends in the results of screening Pap tests and cervical biopsies also were examined. RESULTS: Pap testing rates decreased (from 483 per 1000 person-years in 2000 to 412 per 1000 person-years in 2007) and HPV testing rates increased over the study period. Screening frequency varied across health care systems, and many women continued to receive annual testing. All 4 sites moved to less frequent screening over the study period without marked changes in the overall use of cervical biopsy or treatment. CONCLUSIONS: Despite differences over time and across health plans in rates of cervical cancer testing and follow-up cervical procedures, the authors found no notable differences in Pap test results, diagnostic or treatment procedure rates, or pathological outcomes. This finding suggests that the longer screening intervals did not lead to more procedures or more cancer diagnoses.

Proteinase-activated receptor-1, CCL2, and CCL7 regulate acute neutrophilic lung inflammation.

PAR1 plays a central role in mediating the interplay between coagulation and inflammation, but its role in regulating acute neutrophilic inflammation is unknown. We report that antagonism of PAR1 was highly effective at reducing acute neutrophil accumulation in a mouse model of LPS-induced lung inflammation. PAR1 antagonism also reduced alveolar-capillary barrier disruption in these mice. This protection was associated with a reduction in the expression of the chemokines, CCL2 and CCL7, but not the proinflammatory cytokines, TNF and IL-6, or the classic neutrophil chemoattractants, CXCL1 and CXCL2. Antibody neutralization of CCL2 and CCL7 significantly reduced LPS-induced total leukocyte and neutrophil accumulation, recovered from the bronchoalveolar lavage fluid of challenged mice. Immunohistochemical analysis revealed that CCL2 predominantly localized to alveolar macrophages and pulmonary epithelial cells, whereas CCL7 was restricted to the pulmonary epithelium. In keeping with these observations, the intranasal administration of recombinant CCL2 (rCCL2) and rCCL7 led to the accumulation of neutrophils within the lung airspaces of naive mice in the absence of any underlying inflammation. Flow cytometry analysis further demonstrated an increase in Ly6G(hi) neutrophils expressing the chemokine receptors, CCR1 and CCR2, isolated from mouse lungs compared with circulating neutrophils. Conversely, the expression of CXCR2 decreased on neutrophils isolated from the lung compared with circulating neutrophils. Furthermore, this switch in chemokine receptor expression was accentuated after acute LPS-induced lung inflammation. Collectively, these findings reveal a novel role for PAR1 and the chemokines, CCL2 and CCL7, during the early events of acute neutrophilic inflammation.

The mercurial nature of neutrophils: still an enigma in ARDS?

The acute respiratory distress syndrome (ARDS) is a life-threatening lung condition resulting from direct and indirect insults to the lung. It is characterized by disruption of the endothelial-epithelial barrier, alveolar damage, pulmonary edema, and respiratory failure. A key feature of ARDS is the accumulation of neutrophils in the lung microvasculature, interstitium, and alveolar space. Despite a clear association between neutrophil influx into the lung and disease severity, there is some debate as to whether neutrophils directly contribute to disease pathogenesis. The primary function of neutrophils is to provide immediate host defense against pathogenic microorganisms. Neutrophils release numerous antimicrobial factors such as reactive oxygen species, proteinases, and neutrophil extracellular traps. However, these factors are also toxic to host cells and can result in bystander tissue damage. The excessive accumulation of neutrophils in ARDS may therefore contribute to disease progression. Central to neutrophil recruitment is the release of chemokines, including the archetypal neutrophil chemoattractant IL-8, from resident pulmonary cells. However, the chemokine network in the inflamed lung is complex and may involve several other chemokines, including CXCL10, CCL2, and CCL7. This review will therefore focus on the experimental and clinical evidence supporting neutrophils as key players in ARDS and the chemokines involved in recruiting them into the lung.

Proteinase-activated receptors in fibroproliferative lung disease.

The coagulation cascade plays a central role in the pathogenesis of fibroproliferative lung diseases such as the acute respiratory distress syndrome (ARDS) and idiopathic pulmonary fibrosis (IPF) through multifaceted effects on haemostasis, inflammation and tissue repair. However, targeting the coagulation cascade using traditional anticoagulant approaches has not resulted in improved outcomes for these patients. The cellular effects of the coagulation cascade are mediated via a family of four proteinase-activated receptors (PAR(1-4)). PARs are G protein-coupled receptors that have a unique method of activation involving proteolytic cleavage. They play key roles in mediating the interplay between coagulation and inflammation and tissue repair and fibrosis. Current evidence suggests a central role for PAR(1) and PAR(2) in influencing these responses, although data from animal models suggest that their contribution is highly dependent on both the nature of the insult and disease status. Nonetheless, these receptors may represent important targets in conditions associated with uncontrolled coagulation signalling responses including IPF, ARDS, asthma and chronic obstructive pulmonary disease.

Approaches for classifying the indications for colonoscopy using detailed clinical data.

BACKGROUND: Accurate indication classification is critical for obtaining unbiased estimates of colonoscopy effectiveness and quality improvement efforts, but there is a dearth of published systematic classification approaches. The objective of this study was to evaluate the effects of data-source and adjudication on indication classification and on estimates of the effectiveness of screening colonoscopy on late-stage colorectal cancer diagnosis risk. METHODS: This was an observational study in members of four U.S. health plans. Eligible persons (n = 1039) were age 55-85 and had been enrolled for 5 years or longer in their health plans during 2006-2008. Patients were selected based on late-stage colorectal cancer diagnosis in a case-control design; each case patient was matched to 1-2 controls by study site, age, sex, and health plan enrollment duration. Reasons for colonoscopies received in the 10-year period before the reference date were collected from three medical records sources (progress notes; referral notes; procedure reports) and categorized using an algorithm, with committee adjudication of some tests. We evaluated indication classification concordance before and after adjudication and used logistic regressions with the Wald Chi-square test to compare estimates of the effects of screening colonoscopy on late-stage colorectal cancer diagnosis risk for each of our data sources to the adjudicated indication. RESULTS: Classification agreement between each data-source and adjudication was 78.8-94.0% (weighted kappa = 0.53-0.72); the highest agreement (weighted kappa = 0.86-0.88) was when information from all data sources was considered together. The choice of data-source influenced the association between screening colonoscopy and late-stage colorectal cancer diagnosis; estimates based on progress notes were closest to those based on the adjudicated indication (% difference in regression coefficients = 2.4%, p-value = 0.98), as compared to estimates from only referral notes (% difference in coefficients = 34.9%, p-value = 0.12) or procedure reports (% difference in coefficients = 27.4%, p-value = 0.23). CONCLUSION: There was no single gold-standard source of information in medical records. The estimates of colonoscopy effectiveness from progress notes alone were the closest to estimates using adjudicated indications. Thus, the details in the medical records are necessary for accurate indication classification.

Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management: A PIONEER Analysis Based on Big Data.

BACKGROUND: Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics. OBJECTIVE: To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data. DESIGN, SETTING, AND PARTICIPANTS: From an initial cohort of >100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data. RESULTS AND LIMITATIONS: The most common comorbidities were hypertension (35-73%), obesity (9.2-54%), and type 2 diabetes (11-28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12-25%) and emergency department visits (10-14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent. CONCLUSIONS: Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and outcomes of PCa patients managed conservatively using real-world data. PATIENT SUMMARY: Up to 25% of men with prostate cancer (PCa) managed conservatively experienced hospitalization and emergency department visits within the 1st year after diagnosis; 6% experienced PCa-related symptoms. The probability of receiving therapies for PCa decreased according to time elapsed after the diagnosis.