STI epidemic re-emergence, socio-epidemiological clusters characterisation and HIV coinfection in Catalonia, Spain, during 2017-2019 : A retrospective population-based cohort study

Objectives To describe the epidemiology of sexually transmitted infections (STIs), identify and characterise socio-epidemiological clusters and determine factors associated with HIV coinfection. Design Retrospective population-based cohort. Setting Catalonia, Spain. Participants 42 283 confirmed syphilis, gonorrhoea, chlamydia and lymphogranuloma venereum cases, among 34 600 individuals, reported to the Catalan HIV/STI Registry in 2017-2019. Primary and secondary outcomes Descriptive analysis of confirmed STI cases and incidence rates. Factors associated with HIV coinfection were determined using logistic regression. We identified and characterized socio-epidemiological STI clusters by Basic Health Area (BHA) using K-means clustering. Results The incidence rate of STIs increased by 91.3% from 128.2 to 248.9 cases per 100 000 population between 2017 and 2019 (p<0.001), primarily driven by increase among women (132%) and individuals below 30 years old (125%). During 2017-2019, 50.1% of STIs were chlamydia and 31.6% gonorrhoea. Reinfections accounted for 10.8% of all cases and 6% of cases affected HIV-positive individuals. Factors associated with the greatest likelihood of HIV coinfection were male sex (adjusted OR (aOR) 23.69; 95% CI 16.67 to 35.13), age 30-39 years (versus <20 years, aOR 18.58; 95% CI 8.56 to 52.13), having 5-7 STI episodes (vs 1 episode, aOR 5.96; 95% CI 4.26 to 8.24) and living in urban areas (aOR 1.32; 95% CI 1.04 to 1.69). Living in the most deprived BHAs (aOR 0.60; 95% CI 0.50 to 0.72) was associated with the least likelihood of HIV coinfection. K-means clustering identified three distinct clusters, showing that young women in rural and more deprived areas were more affected by chlamydia, while men who have sex with men in urban and less deprived areas showed higher rates of STI incidence, multiple STI episodes and HIV coinfection. Conclusions We recommend socio-epidemiological identification and characterisation of STI clusters and factors associated with HIV coinfection to identify at-risk populations at a small health area level to design effective interventions

Detection, evaluation, and management of preoperative anaemia in the elective orthopaedic surgical patient: NATA guidelines

Previously undiagnosed anaemia is common in elective orthopaedic surgical patients and is associated with increased likelihood of blood transfusion and increased perioperative morbidity and mortality. A standardized approach for the detection, evaluation, and management of anaemia in this setting has been identified as an unmet medical need. A multidisciplinary panel of physicians was convened by the Network for Advancement of Transfusion Alternatives (NATA) with the aim of developing practice guidelines for the detection, evaluation, and management of preoperative anaemia in elective orthopaedic surgery. A systematic literature review and critical evaluation of the evidence was performed, and recommendations were formulated according to the method proposed by the Grades of Recommendation Assessment, Development and Evaluation (GRADE) Working Group. We recommend that elective orthopaedic surgical patients have a haemoglobin (Hb) level determination 28 days before the scheduled surgical procedure if possible (Grade 1C). We suggest that the patient's target Hb before elective surgery be within the normal range, according to the World Health Organization criteria (Grade 2C). We recommend further laboratory testing to evaluate anaemia for nutritional deficiencies, chronic renal insufficiency, and/or chronic inflammatory disease (Grade 1C). We recommend that nutritional deficiencies be treated (Grade 1C). We suggest that erythropoiesis-stimulating agents be used for anaemic patients in whom nutritional deficiencies have been ruled out, corrected, or both (Grade 2A). Anaemia should be viewed as a serious and treatable medical condition, rather than simply an abnormal laboratory value. Implementation of anaemia management in the elective orthopaedic surgery setting will improve patient outcomes

Coronary artery surgery: cardiotomy suction or cell salvage?

Coronary artery bypass grafting (CABG) today results in what may be regarded as acceptable levels of blood loss with many institutions avoiding allogeneic red cell transfusion in over 60% of their patients. The majority of cardiac surgeons employ cardiotomy suction to preserve autologous blood during on-pump coronary artery bypass surgery; however the use of cardiotomy suction is associated with a more pronounced systemic inflammatory response and a resulting coagulopathy as well as exacerbating the microembolic load. This leads to a tendency to increased blood loss, transfusion requirement and organ dysfunction. Conversely, the avoidance of cardiotomy suction in coronary artery bypass surgery is not associated with an increased transfusion requirement. There is therefore no indication for the routine use of cardiotomy suction in on-pump coronary artery surgery

Source Apportionment for PM samples: a chemometric approach based on the AutoCoVariance Function computation for GC-MS data treatment and organic tracers identification

This work describes the application of a signal processing method to GC–MS chromatograms of PM10 and PM2.5 samples collected in rural and urban areas. The method is focused on the computation of the two relevant parameters nmax and CPI that can be directly estimated from the AutoCoVariance Function (ACVF) computed on the acquired chromatogram. The procedure makes it possible to extract usable information hidden in the chromatogram thus reducing the labour and time required and increasing the quality and objectivity of the results

Analisi gas-cromatografica di miscele complesse di carattere ambientale: caratterizzazione di serie omologhe come marker chimici nell’identificazione della sorgente

L’identificazione e la caratterizzazione di serie omologhe di composti organici (come n-alcani, acidi carbossilici ecc.) in campioni ambientali, quali il particolato atmosferico, fornisce importanti informazioni per l’individuazione e la caratterizzazione delle sorgenti di emissione: infatti tali composti possono essere considerati marker molecolari delle sorgenti stesse. L’analisi di serie omologhe di n-alcani, è stata effettuata tramite GC-MS (Gas Cromatografia – Spettrometria di Massa) dopo una preventiva estrazione della componente organica del campione. Si è studiato un approccio matematico statistico, basato sullo studio della Funzione di Autocovarianza (ACVF), per l’estrapolazione di informazioni molecolari e strutturali a partire dal segnale gascromatografico, in particolare per l’identificazione della presenza di serie omologhe e la quantificazione dei termini della serie stessa. Il metodo è stato sviluppato per calcolare direttamente dal segnale cromatografico il valore CPI (Carbon Preference Index), che rappresenta il rapporto tra quantità di termini dispari rispetto ai pari ed è un parametro fondamentale per distinguere sorgenti di emissione naturali (preferenza termini dispari, CPI>1) ed antropiche (distribuzione omogenea termini pari/dispri, CPI~1) Il metodo è stato validato utilizzando cromatogrammi simulati ed applicato a campioni reali di particolato atmosferico di origine antropogenica e natural

Data handling of complex GC-MS signals to characterize homologous series as organic source tracers in atmospheric aerosols

A data handling approach is described for extracting information from complex GC-MS signals. The study of organic source tracers in atmospheric aerosols is discusse

Identificazione di serie omologhe di idrocarburi in particolato atmosferico

Il lavoro descrive la caratterizzazione chimica della componente organica di campioni di particolato atmosferico mediante analisi GC-MS (GasCromatografia-Spettrometria di Massa). Poiché un campione di particolato atmosferico (PM10, PM2.5) costituisce una matrice formata da un elevato numero di componenti, la sua analisi cromatografica determina un segnale molto complesso e di difficile interpretazione. Viene descritto un metodo matematico-statistico, basato sullo studio della Funzione di Autocovarianza (ACVF) calcolata a partire da un cromatogramma precedentemente linearizzato. Questo metodo risulta molto utile per l’interpretazione del segnale al fine di ricavare rilevanti informazioni sulla composizione quali-quantitativa della miscela. In particolare il metodo è molto utile per identificare la presenza di serie omologhe di composti organici da utilizzare come traccianti o marker di una specifica sorgente di contaminazione atmosferica. In particolare lo studio è stato dedicato alla caratterizzazione di idrocarburi lineari, poiché essi sono di notevole interesse per differenziare aerosol di origine antropogenica o biogenica. Lo studio dei cromatogrammi basato sul calcolo della ACVF permette di determinare il numero dei componenti delle serie omologhe e la distribuzione dei termini, per esempio la predominanza di termini pari o dispari, utile per il riconoscimento dell’origine del campione. E’ anche possibile l’identificazione e la quantificazione dell’UCM (Unresolved Complex Mixture), ossia di quella miscela di componenti che i metodi cromatografici tradizionali non sono in grado di separare o risolvere. In questo lavoro è stato sviluppato un algoritmo in linguaggio Fortran per la linearizzazione dei tempi di ritenzione del cromatogramma sperimentale, che viene effettuata utilizzando una miscela standard di una serie omologa di idrocarburi lineari (nell'intervallo del numero di atomi di carbonio del campione di interesse). Le potenzialità del metodo dell’ACVF risulta particolarmente aumentata quando esso è applicato a segnali GC-MS acquisiti in modalità SIM, monitorando frammenti di molecole specifiche. E’ in progetto l’estensione dello studio ad altre serie omologhe di composti organici, quali acidi carbossilici, alcoli, aldeidi, chetoni, per una caratterizzazione ancora più dettagliata di campioni di particolato atmosferico. Il metodo sviluppato è molto versatile e può essere applicato a segnali complessi ottenuti dall’analisi cromatografia di campioni di interesse ambientale di diversa origine

Amino acid enantiomer separation: GC-MS analysis and signal processing to detect chemical biomarkers in space analysis

This work describes a GC-MS method for enantioselective separation of amino acids: it is based on a derivatization reaction which employs a mixture of alkylchloroformate-alcohol-pyridine, as reagents to obtain the N(O,S)-alkylalkoxycarbonyl esters of amino acids. The aim is to search for a suitable candidate for amino acid separation and quantification in in-situ space GC-MS investigation of solar system body environments onboard space exploration probes. Various reaction parameters are investigated and optimized to achieve a reproducible derivatization procedure of 20 proteinogenic amino acids: the obtained derivatives were submitted to enantiomeric separation on a Chirasil-L-Val chiral capillary column. In particular, the following topics are investigated for i) the proper reagent and reaction conditions to obtain the highest derivative yield; ii) the amino acid reactivity and the MS properties of the obtained derivatives; iii) the linearity and sensitivity of the analytical method; iv) the retention behaviour of the derivatives and their enantiomeric separation. By combining the resolution power of the Chirasil-L-Val column and the high selectivity of the SIM (Single Ion Monitoring) MS detection mode, the described procedure enables the enantiomeric separation and quantification of 16 enantiomeric pairs of amino acids. To extract chemical information from the complex chromatograms obtained, a signal processing method was applied: it’s based on the study of the Experimental AutoCoVariance Function (EACVF) computed on the chromatogram acquired in digitized form. The ACVF method gives informations on the separation performance and the total number of components present in the sample. Moreover, the presence of enantiomeric pairs can be identified and their abundance estimated. The procedure is simple and fast and reproducible. It displays a wide linearity range at ppb detection limits for quantitative determinations for the 20 proteinogenic amino acids investigated