Predictors of medication use during pregnancy: a cohort study

Background Sociodemographic characteristics and health behaviours are associated with medication use in pregnancy, but it is unclear if they are independent predictors because women´s health status has hardly been accounted for. We aimed to identify predictors of use of medications and of iron/folic acid. Methods This cohort included pregnant women recruited in a prenatal clinic in Trieste, Italy, from 2007 to 2009. Dispensations were obtained from the regional outpatient dispensation database through record linkage. We calculated the Odds Ratio (OR), with 95% confidence interval (95%CI), of ≥ 1 dispensation of (a) any medication and (b) iron/folic acid, using unconditional logistic regression. The final model adjusted for age, partner education, housing size, comorbidities.   Findings Of 767 women, 70.5% had ≥ 1 dispensation of any medication and 46.1% of iron/folic acid. Use of any medication was predicted by immigrant status of the woman (OR 1.21; 95%CI 0.57–2.53) or of her partner (1.51; 0.67–3.40), ≤ high school degree of the woman (1.11; 0.61–2.03) or of her partner (1.21; 0.75–1.95), unemployment (1.47; 0.72–2.98), smoking (1.25; 0.65–2.40), alcohol consumption (≥5 drinks/week: 2.78; 1.78–4.34), and obesity (1.33; 0.59–2.99). Use of iron and/or folic acid was predicted by ≤ high school degree (0.65; 0.40–1.08), smoking (0.80: 0.47–1.37), and obesity (0.62; 0.31–1.25). Discussion In this cohort, characteristics including education, immigrant and employment status, smoking, alcohol consumption, and obesity independently predicted medication use. Interventions to promote safe use of medications should carefully consider women´s characteristics

Hospitalizations due to respiratory failure in patients with Amyotrophic Lateral Sclerosis and their impact on survival: A population-based cohort study

Background: Respiratory failure, infections and aspiration pneumonia, are the main causes of morbidity and mortality in Amyotrophic Lateral Sclerosis (ALS). In a population-based cohort, we assessed (a) hospital utilization and (b) impact of hospitalization for respiratory failure on survival. Methods: All patients with incident ALS in Friuli Venezia Giulia region, Italy, from 2002 to 2009, were identified through multiple sources. Diagnosis was validated through clinical documentation review. For each patient, we extracted the records of all hospitalizations after ALS diagnosis from the regional hospitalization database. Cox proportional hazards model survival Hazard Ratio (HR), with 95 % Confidence Interval (95 % CI), was calculated. Results: Out of 262 patients, 98.1 % had at least 1 and 58.0 % 653 hospitalizations. Emergency admissions occurred in 77.5 % of patients and a diagnosis of respiratory failure in 55.0 %. Patients underwent a total of 885 hospitalizations. The leading diagnosis was respiratory failure (31.6 % of hospitalizations). This diagnosis occurred most frequently in emergency (45.6 %) than in elective admissions (26.4 %). The second leading diagnosis was pneumonia (14.2 %), 24.9 and 6.3 % respectively. The leading procedure was mechanical ventilation (18.4 %), performed in 29.9 % of emergency and in 12.4 % of elective admissions. After adjustment for site of onset, age and diagnostic delay, a first hospitalization for respiratory failure had a strong adverse effect on survival (HR 4.00; 95 % CI 3.00; 5.34). Conclusions: Respiratory failure, pneumonia and aspiration pneumonia were major determinants of hospitalizations and emergency admissions and often dealt with in emergency admissions. A first hospitalization for respiratory failure had a strong adverse effect on survival. Strategies to improve home management of respiratory conditions in patients with ALS and to optimize hospital care utilization are neede

Medication use during pregnancy, gestational age and date of delivery: Agreement between maternal self-reports and health database information in a cohort

Supplemental tables. Table S1. Agreement between questionnaire and prescription redemption database for selected therapeutic classes by time of questionnaire completion. Table S2. Number of women with information on hypertension during pregnancy and agreement between questionnaire and birth certificate database. Table S3. Number of women with information on hypertension during pregnancy in questionnaire and in birth certificate database and use of antihypertensive medications according to questionnaire and prescription database. Positive Predictive Value and Negative Predictive Value of prescriptions for antihypertensive medications recorded in questionnaire and in birth certificate database. (DOCX 23 kb

Prognostic features of gastro-entero-pancreatic neuroendocrine neoplasms in primary and metastatic sites: Grade, mesenteric tumour deposits and emerging novelties

Updates in classification of gastro-entero-pancreatic neuroendocrine neoplasms better reflect the biological characteristics of these tumours. In the present study, we analysed the characteristics of neuroendocrine tumours that could aid in a more precise stratification of risk groups. In addition, we have highlighted the importance of grade (re)assessment based on investigation of secondary tumour lesions. Two hundred and sixty-four cases of neuroendocrine tumours of gastro-entero-pancreatic origin from three centres were included in the study. Tumour morphology, mitotic count and Ki67 labelling index were evaluated in specimens of primary tumours, lymph node metastases and distant metastases. These variables were correlated with overall survival (OS) and relapse-free survival (RFS). Tumour stage, number of affected lymph nodes, presence of tumour deposits and synchronous/metachronous metastases were tested as possible prognostic features. Mitotic count, Ki-67 labelling index, primary tumour site, tumour stage, presence of tumour deposits and two or more affected lymph nodes were significant predictors of OS and RFS. At the same time, mitotic count and Ki-67 labelling index can be addressed as continuous variables determining prognosis. We observed a very high correlation between the measures of proliferative activity in primary and secondary tumour foci. The presence of isolated tumour deposits was identified as an important determinant of both RFS and OS for pancreatic (hazard ratio [HR] = 7.61, 95% confidence interval [CI] = 3.96-14.6, P < 0.0001 for RFS; HR = 3.28, 95% CI = 1.56-6.87, P = 0.0017 for OS) and ileal/jejunal neuroendocrine tumours (HR = 1.98, 95% CI = 1.25-3.13, P = 0.0036 for RFS and HR 2.59, 95% CI = 1.27-5.26, P = 0.009 for OS). The present study identifies the presence of mesenterial tumour deposits as an important prognostic factor for gastro-entero-pancreatic neuroendocrine tumours, provides evidence that proliferative parameters need to be treated as continuous variables and further supports the importance of grade determination in all available tumour foci

High mitochondrial DNA content is a key determinant of stemness, proliferation, cell migration, and cancer metastasis in vivo

Here, we examined the potential role of mitochondrial DNA (mtDNA) levels in conveying aggressive phenotypes in cancer cells, using two widely-used breast cell lines as model systems (MCF7[ER+] and MDA-MB-231[ER-]). These human breast cancer cell lines were fractionated into mtDNA-high and mtDNA-low cell sub-populations by flow cytometry, using SYBR Gold as a vital probe to stain mitochondrial nucleoids in living cells. Enrichment of mtDNA-high and mtDNA-low cell sub-populations was independently validated, using a specific DNA-binding mAb probe (AC-30-10), and mitochondrial-based functional assays. As predicted, mtDNA-high MCF7 cells showed significant increases in mitochondrial mass, membrane potential, and superoxide production, as well as increased mitochondrial respiration and ATP production. Moreover, mtDNA-high MCF7 cells demonstrated increases in stemness features, such as anchorage-independent growth and CD44 levels, as well as drug-resistance to Gemcitabine and Tamoxifen. Proliferation rates were also significantly increased, with a dramatic shift towards the S- and G2/M-phases of the cell cycle; this was indeed confirmed by RNA-Seq analysis. Complementary results were obtained with MDA-MB-231 cells. More specifically, mtDNA-high MDA-MB-231 cells showed increases in stemness features and ATP production, as well as rapid cell cycle progression. Moreover, mtDNA-high MDA-MB-231 cells also exhibited increases in both cell migration and invasion, suggesting a role for mtDNA in distant metastasis. To test this hypothesis more directly, a preclinical in vivo model was utilized. For this purpose, MDA-MB-231 tumour cell grafts were treated with an established mtDNA synthesis inhibitor, namely Alovudine (3’-deoxy-3’-fluorothymidine). As expected, drug-induced depletion of mtDNA led to a shift from mitochondrial to glycolytic metabolism. Interestingly, Alovudine very effectively reduced the formation of spontaneous metastases by nearly 70%, but minimally inhibited tumour growth by approximately 20%. Taken together, these data suggest that high mtDNA content is a key driver of stemness, proliferation, and migration, as well as cancer cell metastasis

A computational index derived from whole-genome copy number analysis is a novel tool for prognosis in early stage lung squamous cell carcinoma.

AbstractSquamous cell carcinoma of the lung is remarkable for the extent to which the same chromosomal abnormalities are detected in individual tumours. We have used next generation sequencing at low coverage to produce high resolution copy number karyograms of a series of 89 non-small cell lung tumours specifically of the squamous cell subtype. Because this methodology is able to create karyograms from formalin-fixed paraffin-embedded material, we were able to use archival stored samples for which survival data were available and correlate frequently occurring copy number changes with disease outcome. No single region of genomic change showed significant correlation with survival. However, adopting a whole-genome approach, we devised an algorithm that relates to total genomic damage, specifically the relative ratios of copy number states across the genome. This algorithm generated a novel index, which is an independent prognostic indicator in early stage squamous cell carcinoma of the lung

Profiling of Flavonol Derivatives for the Development of Antitrypanosomatidic Drugs

Flavonoids represent a potential source of new antitrypanosomatidic leads. Starting from a library of natural products, we combined target-based screening on pteridine reductase 1 with phenotypic screening on Trypanosoma brucei for hit identification. Flavonols were identified as hits, and a library of 16 derivatives was synthesized. Twelve compounds showed EC50 values against T. brucei below 10 \u3bcM. Four X-ray crystal structures and docking studies explained the observed structure-activity relationships. Compound 2 (3,6-dihydroxy-2-(3-hydroxyphenyl)-4H-chromen-4-one) was selected for pharmacokinetic studies. Encapsulation of compound 2 in PLGA nanoparticles or cyclodextrins resulted in lower in vitro toxicity when compared to the free compound. Combination studies with methotrexate revealed that compound 13 (3-hydroxy-6-methoxy-2-(4-methoxyphenyl)-4H-chromen-4-one) has the highest synergistic effect at concentration of 1.3 \u3bcM, 11.7-fold dose reduction index and no toxicity toward host cells. Our results provide the basis for further chemical modifications aimed at identifying novel antitrypanosomatidic agents showing higher potency toward PTR1 and increased metabolic stability

Automated Analysis of Proliferating Cells Spatial Organisation Predicts Prognosis in Lung Neuroendocrine Neoplasms

SIMPLE SUMMARY: Lung neuroendocrine neoplasms (lung NENs) are categorised by morphology, defining a classification sometimes unable to reflect ultimate clinical outcome, particularly for the intermediate domains of adenocarcinomas and large-cell neuroendocrine carcinomas. Moreover, subjectivity and poor reproducibility characterise diagnosis and prognosis assessment of all NENs. The aim of this study was to design and evaluate an objective and reproducible approach to the grading of lung NENs, potentially extendable to other NENs, by exploring a completely new perspective of interpreting the well-recognised proliferation marker Ki-67. We designed an automated pipeline to harvest quantitative information from the spatial distribution of Ki-67-positive cells, analysing its heterogeneity in the entire extent of tumour tissue—which currently represents the main weakness of Ki-67—and employed machine learning techniques to predict prognosis based on this information. Demonstrating the efficacy of the proposed framework would hint at a possible path for the future of grading and classification of NENs. ABSTRACT: Lung neuroendocrine neoplasms (lung NENs) are categorised by morphology, defining a classification sometimes unable to reflect ultimate clinical outcome. Subjectivity and poor reproducibility characterise diagnosis and prognosis assessment of all NENs. Here, we propose a machine learning framework for tumour prognosis assessment based on a quantitative, automated and repeatable evaluation of the spatial distribution of cells immunohistochemically positive for the proliferation marker Ki-67, performed on the entire extent of high-resolution whole slide images. Combining features from the fields of graph theory, fractality analysis, stochastic geometry and information theory, we describe the topology of replicating cells and predict prognosis in a histology-independent way. We demonstrate how our approach outperforms the well-recognised prognostic role of Ki-67 Labelling Index on a multi-centre dataset comprising the most controversial lung NENs. Moreover, we show that our system identifies arrangement patterns in the cells positive for Ki-67 that appear independently of tumour subtyping. Strikingly, the subset of these features whose presence is also independent of the value of the Labelling Index and the density of Ki-67-positive cells prove to be especially relevant in discerning prognostic classes. These findings disclose a possible path for the future of grading and classification of NENs

Validation of discharge diagnosis coding for amyotrophic lateral sclerosis in an Italian regional healthcare database

Objectives: (a) to estimate the accuracy of International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code for amyotrophic lateral sclerosis (ALS) in the Hospital Discharge Database (HDD) of the Italian region Friuli-Venezia Giulia; (b) to identify the predictors of a true positive ALS code; (c) to compare incident and prevalent cases obtained from HDD with those identified in a retrospective population-based study. Methods: Records of all patients discharged 2010-2014 with an ICD-9-CM code for ALS and other motor neuron diseases were extracted from the HDD. For each record, all the available clinical documentation was evaluated to confirm or reject the diagnosis of ALS. ALS incident and prevalent cases were identified. Validity measures were calculated both overall and stratified by patient and hospitalization characteristics. Adjusted odds ratio (aOR), with 95% confidence interval (95%CI), of a true positive code was estimated using unconditional logistic regression. Results: ALS code had sensitivity 92.9%, specificity 75.3%, positive predictive value (PPV) 92.3%, and negative predictive value (NPV) 76.8%. A true positive ALS code was predicted by concurrent codes for respiratory interventions (aOR: 3.82; 95%CI: 2.09-6.99), primary position code (2.78; 1.68-4.62), non-programed hospitalization (2.06; 1.18-3.61), male patient (1.56; 1.06-2.29), and hospitalization length <14 days (1.42; 1.07-2.84). Two hundred and thirty-six prevalent and 187 incident cases were identified, 84% of those detected in the population-based study. Conclusion: ALS code shows very good accuracy and identifies a high percentage of true positive, incident and prevalent cases, but additional sources and an algorithm based on selected variables may further improve case identification