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The potential of the combined use of ESI-QqTOF-MS and ESI-QqTOF-MS/MS with mass-spectral library search for the identification of therapeutic and illicit drugs has been evaluated. Reserpine was used for standardizing experimental conditions and for characterization of the performance of the applied mass spectrometric system. Experiments revealed that because of the mass accuracy, the stability of calibration, and the reproducibility of fragmentation, the QqTOF mass spectrometer is an appropriate platform for establishment of a tandem-mass-spectral library. Three-hundred and nineteen substances were used as reference samples to build the spectral library. For each reference compound, product-ion spectra were acquired at ten different collision-energy values between 5 eV and 50 eV. For identification of unknown compounds, a library search algorithm was developed. The closeness of matching between a measured product-ion spectrum and a spectrum stored in the library was characterized by a value called “match probability”, which took into account the number of matched fragment ions, the number of fragment ions observed in the two spectra, and the sum of the intensity differences calculated for matching fragments. A large value for the match probability indicated a close match between the measured and the reference spectrum. A unique feature of the library search algorithm--an implemented spectral purification option--enables characterization of multi-contributor fragment-ion spectra. With the aid of this software feature, substances comprising only 1.0% of the total amount of binary mixtures were unequivocally assigned, in addition to the isobaric main contributors. The spectral library was successfully applied to the characterization of 39 forensic casework samples.

The retrospective investigation of the exposure to toxic substances by general unknown screening of hair is still a difficult task because of the large number of possible poisons, the low sample amount and the difficult sample matrix. In this study the use of liquid chromatography–hybrid quadrupole time-of-flight mass spectrometry (LC–QTOF-MS) was tested as a promising technique for this purpose. In the optimized procedure, 20mg hair were decontaminated with water and acetone and two times extracted by 18h incubation with 0.5ml of a mixture of methanol/acetonitrile/H2O/ammonium formate at 37°C. A mixture of deuterated standards from different drug groups was added for quantification and method control. The united extracts were evaporated to a residue of 0.5ml and 5μl were injected without clean-up for LC–QTOF-MS measurement (instrument Agilent 6530) with positive electrospray ionization and in data dependent acquisition mode. For peak identification the accurate mass data base and spectral library of the authors was used which contains accurate mass CID spectra of more than 2500 and theoretically calculated accurate mass data of more than 7500 toxicologically relevant substances. Validation at the example of 24 illegal drugs, their metabolites and benzodiazepines resulted in limits of detection of 0.003–0.015ng/mg, and limits of quantification of 0.006–0.021ng/mg with good accuracy and intra- and interday reproducibility. The matrix effect by ion suppression/enhancement was 72–107% for basic drugs and 42–75% for benzodiazepines. Yields of the hair extraction above 90% were determined for 59 drugs or metabolites. The method was applied to hair samples from 30 drug fatalities and from 60 death cases with known therapeutic drug intake at life time. Altogether 212 substances were identified with a frequency per drug of 1–40 (mean 4.2) and per case of 2–33 (mean 10.2), between them 35 illegal drug related substances and 154 therapeutic drugs. Comparison with the data known from case histories and from the analysis of blood, urine and gastric content showed only a low agreement, with many unexpected drugs detected and many reported drugs not detected in hair. Basic drugs and metabolites such as opioides, cocaine, amphetamines, several groups of antidepressants, neuroleptics, beta-blockers or the metamizole metabolite noramidopyrine were found with high frequency whereas acidic and several neutral drugs such as cannabinoids, salicylic acid, furosemide, barbiturates, phenprocoumone or cardiac glycosides could not be detected with sufficient sensitivity, mainly because of the low ion yield of positive ESI for these compounds. The advantage of a comprehensive acquisition of all substances is paid by a lower sensitivity in comparison to targeted screening LC–MS/MS procedures. In conclusion, the procedure of sample preparation and LC–QTOF-MS analysis proved to be a robust and sensitive routine method in which the qualitative screening for a wide variety of toxic substances in hair is combined with the quantitative determination of selected illegal drugs.

•We report a case of severe poisoning with α-pyrrolidinovalerophenone (α-PVP).•α-PVP and its 2″-oxo-metabolite were identified in urine by GC–MS.•The concentration of α-PVP was determined in serum.•The presented data were linked to the clinical condition excited delirium syndrome. α-Pyrrolidinovalerophenone (α-PVP) is a synthetic cathinone belonging to the group of “second generation” pyrrolidinophenones that becomes more and more popular as a designer psychostimulant. Here we provide toxicological analytical support for a severe poisoning with α-PVP. Serum and urine samples that were sent to our laboratory were subjected to a general unknown screening procedure. The procedure includes immunoassay-based screening of drugs of abuse in serum and systematic toxicological analysis of urine and serum after neutral and basic liquid–liquid extraction followed by gas chromatography–mass spectrometry (GC–MS). Whereas the immunoassay delivered negative results, analyzing the urine sample by GC–MS in full scan mode disclosed the presence of α-PVP and its metabolites α-(2″-oxo-pyrrolidino)valerophenone (2″-oxo-α-PVP) and 1-phenyl-2-(pyrrolidin-1-yl)pentan-1-ol (OH-α-PVP). In the acetylated urine sample we found additionally N,N-bis-dealkyl-PVP. In serum, α-PVP could be detected after solid phase extraction and a concentration of 29ng/mL was determined. Other forensic relevant substances were not detected. The presented data can explain the psychotic symptoms and behavioural pattern of the subject after abuse of α-PVP, leading to a clinical condition similar to excited delirium syndrome.

Designer benzodiazepines (DBZDs) have become of particular importance in the past few years. The metabolite monitoring of DBZD in biological fluids could be of great interest in clinical and forensic toxicology. However, DBZD metabolites are not known or not commercially available. The identification of some DBZD metabolites has been mostly explored by self-administration studies or by in vitro studies followed by high-resolution mass spectrometry. The question arose whether a unit resolution instrument could be efficient enough to allow the identification of DBZD metabolites. In this study, we used an in vitro experiment where eight DBZDs (diclazepam, flubromazepam, etizolam, deschloroetizolam, flubromazolam, nifoxipam, meclonazepam and clonazolam) were incubated with human liver microsomes (HLMs) and metabolite identification was carried out by using a UHPLC coupled to a QTRAP triple quadrupole linear iontrap tandem mass spectrometer system. Post-mortem samples obtained from a real poisoning case, involving deschloroetizolam and diclazepam, were also analysed and discussed. Our study using HLM allowed the identification of 26 metabolites of the 8 DBZDs. These were denitro-, mono- or di-hydroxylated and desmethyl metabolites. In the forensic case, diclazepam was not detected whereas its metabolites (lormetazepam and lorazepam) were present at high concentrations in urine. We also identified hydroxy-deschloroetizolam in urine, while the parent compound was not detected in this matrix. This supports the approach that LC coupled to a simple QTRAP could be used by laboratories to identify other not-known/not-commercialized new psychoactive substance (NPS) metabolites.

In clinical or forensic toxicology, general unknown screening procedures are used to identify as many xenobiotics as possible, belonging to numerous chemical classes. We present here a general unknown screening procedure based on liquid chromatography coupled with use of a single linear ion trap mass spectrometer, and focus on the identification of pesticides and/or metabolites in whole blood. After solid-phase extraction (SPE), the compounds of interest were separated using a reversed-phase column and identified by the mass spectrometer operated first in the full-scan mass spectrometry (MS) mode, in the positive and negative polarities, followed by MS² and MS³ scanning of ions selected in data-dependent acquisition. The total scan time was 2.45 s. Two mass spectral libraries (MS² and MS³), each of 450 spectra, were created for the 320 pesticides and metabolites detected after injection of pure solutions. Robustness of the spectra and matrix effects were studied and were satisfactory for the present application. Detection limits for the 320 compounds were studied by extracting 1 mL spiked blood at concentrations between 10 µg/L and 10 mg/L. If necessary, it was possible to decrease the detection limits of some compounds by 10-100-fold by scanning MS² in only one polarity, owing to a shorter total scan time. However, at the same time, the detection specificity decreased as no confirmation could be recorded in the following MS³ scan and no information could be registered in the other polarity. So, in these rare cases, confirmation by another method was required.

A convenient mass spectrometric approach for the identification of toxicologically relevant compounds in tablets and tablet residues is presented. For comprehensive forensic-toxicological analysis electrospray ionization mass spectrometry was accomplished in positive as well as in negative ion mode on a quadrupole–quadrupole–time-of-flight instrument. Dissolved samples were introduced into the mass spectrometer by flow-injection. Mass spectra as well as tandem mass spectra were acquired. A data-dependent acquisition strategy was used to switch between the mass spectrometric modes. Identification was accomplished via search within a tandem mass spectral library. The applied database contained 8252 spectra collected from 836 compounds in positive ion mode as well as 1023 spectra collected from 103 compounds in negative ion mode. A total of 22 casework samples collected during autopsies from mouth, oesophagus or gastric contents, seized by the police, or found with patients at hospital were screened. Twelve samples contained compounds only detectable in positive ion mode (sildenafil, dihydrocodeine, diphenhydramine, oxprenolol, N-methyl-3,4-methylenedioxyamphetamine, morphine, amphetamine, caffeine, pemoline, orphenadrine, m-chlorphenylpiperazine and tramadol), six samples contained species exclusively detectable in negative ion mode (salicylic acid, acetylsalicylic acid, ibuprofen, ketorolac, valproic acid and phenobarbital), and three samples contained diclofenac detectable in both ionization polarities. One sample did not contain any compound amenable to mass spectrometric analysis. For verification all samples were additionally analyzed by GC/MS. Both methods revealed identical results for all but one sample. The beta-adrenergic blocker oxprenolol was exclusively detected by the flow-injection method.

The systematic analysis of postmortem samples is one of the most challenging tasks in forensic toxicology. For determining cause of death, analysis of different tissues can be indispensable. Automation of these analyses would increase reproducibility and therefore lead to more reliable and comparable results. Recent developments in analytical toxicology and the availability of automation devices for various analytical stages, such as sampling, preliminary testing, sample extraction, chromatographic separation, identification, and data processing are examined and discussed. At present only parts of the analytical procedure have been automated—however, the goal should be the integration of these parts into a single, continuous process. Currently, only one “fully-automated” procedure for the comprehensive screening of blood and urine (excluding sample pretreatment, which remains separate) has been published. But it can be expected that automation of analytical procedures in forensic toxicology will indeed progress, even with regard to the very complex screening of postmortem samples.

This trial showed that the addition of abdominopelvic CT to routine measures in patients with unprovoked venous thrombosis did not detect additional occult cancers. The incidence of cancer in first unprovoked venous thrombosis was 4%, not 10% as had been previously reported. Venous thromboembolism, which comprises deep-vein thrombosis and pulmonary embolism, is the third most common cardiovascular disorder. 1 – 3 It is classified as provoked when it is associated with a transient risk factor (e.g., trauma, surgery, prolonged immobility, or pregnancy or the puerperium) and as unprovoked when it is associated with neither a strong transient risk factor nor overt cancer. Unprovoked venous thromboembolism may be the earliest sign of cancer 4 , 5 ; up to 10% of patients with unprovoked venous thromboembolism receive a diagnosis of cancer in the year after their diagnosis of venous thromboembolism. 6 More than 60% of occult cancers are . . .

Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC. Bill & Melinda Gates Foundation.

Background People with malignancy of undefined primary origin (MUO) have a poor prognosis and may undergo a protracted diagnostic workup causing patient distress and high cancer related costs. Not having a primary diagnosis limits timely site-specific treatment and access to precision medicine. There is a need to improve the diagnostic process, and healthcare delivery and support for these patients. This trial aims to implement and evaluate an optimal model of care for people presenting with MUO to reduce time to diagnosis, improve patient experiences and reduce healthcare costs. Methods/design This is a pragmatic stepped-wedge cluster randomised trial comparing a control phase of standard practice with an intervention phase. Patient inclusion criteria are: 1) age 18 years or older, 2) presenting with suspected metastatic malignancy without an obvious primary site on imaging, 3) clinically appropriate to undergo diagnostic work-up and 4) able to provide written or verbal consent. The intervention is a new model of care comprising four key components: standardised diagnostic workup, dedicated cancer care coordinators, virtual multidisciplinary meetings and a website resource for patients, carers and clinicians. The primary endpoint is the time to completion of minimum diagnostic workup. Secondary outcomes are whether the type of tumour is diagnosed, clinical trial participation, referral to palliative care, patient-reported physical, social and mental health, patient-reported understanding and uncertainty. Implementation outcomes include acceptability, feasibility, fidelity and adoption and health care use and costs. Intervention implementation will be supported using clinical leadership, education and reinforcement. Patients who consent to having their data collected will receive the model of care active at the site at the time of recruitment. Patients will complete a patient-reported outcomes questionnaire four months after study enrolment. A health economic analysis will be included. Across 15 hospitals, a total sample size of 240 is planned. Discussion There is a lack of intervention research for people presenting with MUO. The stepped-wedge design seeks to mitigate the potential challenge of enrolling people with a poor prognosis and high symptom burden in trials. This research will generate important evidence with scalability for future research at trial completion. Trial registration ACTRN12622001504707