Rural and Urban patients' Requirements and Experiences of Out-of-hours medical care after cancer (RUREO): a questionnaire study.

OBJECTIVE: To investigate how individuals diagnosed with cancer use out-of-hours (OOH) medical services, describe the behavioural determinants of OOH service use and explore whether there are differences between urban and rural dwellers. DESIGN AND SETTING: A cross-sectional questionnaire study conducted in Northeast Scotland. PARTICIPANTS: The questionnaire was sent to 2549 individuals diagnosed with cancer in the preceding 12 months identified through the National Health Service Grampian Cancer Care Pathway database. 490 individuals returned the questionnaire (19.2% response rate), 61.8% were urban and 34.9% were rural. OUTCOMES: Outcomes were differences in frequency of medical service use and attitudes towards OOH services between urban and rural participants. Patient experience (qualitative data) was compared. RESULTS: Daytime services were used much more frequently than OOH services-83.3% of participants had never contacted an OOH primary care service in the preceding 12 months but 44.2% had used their daytime general practitioner at least four times. There were no significant differences between urban and rural dwellers in the patterns of OOH or daytime service use, the behavioural determinants of service use or the experiences of OOH services. Rural dwellers were significantly less likely to agree that OOH services were close by and more likely to agree that where they lived made it difficult to access these services. Rural dwellers were no more likely to agree or disagree that distance would affect their decision to contact OOH services. Qualitative results highlighted barriers to accessing OOH services exist for all patients but that long travel distances can be offset by service configuration, travel infrastructure and access to a car. CONCLUSIONS: Urban and rural dwellers have similar beliefs, attitudes towards and patterns of OOH service use. In Northeast Scotland, place of residence is unlikely to be the most important factor in influencing decisions about whether to access OOH medical care.

Mechanisms and clinical relevance of the bidirectional relationship of viral infections with metabolic diseases.

Viruses have been present during all evolutionary steps on earth and have had a major effect on human history. Viral infections are still among the leading causes of death. Another public health concern is the increase of non-communicable metabolic diseases in the last four decades. In this Review, we revisit the scientific evidence supporting the presence of a strong bidirectional feedback loop between several viral infections and metabolic diseases. We discuss how viruses might lead to the development or progression of metabolic diseases and conversely, how metabolic diseases might increase the severity of a viral infection. Furthermore, we discuss the clinical relevance of the current evidence on the relationship between viral infections and metabolic disease and the present and future challenges that should be addressed by the scientific community and health authorities.

Autoimmune manifestations of CTLA-4 haploinsufficiency in two patients of Southeast Asian ethnicity.

We report 2 patients who first developed cutaneous manifestations, followed by autoimmune phenomena, infections, and hypogammaglobulinemia. They were initially diagnosed with common variable immunodeficiency; however, the diagnosis was revised to cytotoxic T-lymphocyte antigen 4 haploinsufficiency after genetic and functional testing.

Anaphylatoxin Complement 5a in Pfizer BNT162b2-Induced Immediate-Type Vaccine Hypersensitivity Reactions.

The underlying immunological mechanisms of immediate-type hypersensitivity reactions (HSR) to COVID-19 vaccines are poorly understood. We investigate the mechanisms of immediate-type hypersensitivity reactions to the Pfizer BNT162b2 vaccine and the response of antibodies to the polyethylene glycol (PEG)ylated lipid nanoparticle after two doses of vaccination. Sixty-seven participants, median age 35 and 77.3% females who tolerated two doses of the BNT162b2 vaccine (non-reactors), were subjected to various blood-sampling time points. A separate group of vaccine reactors (10 anaphylaxis and 37 anonymised tryptase samples) were recruited for blood sampling. Immunoglobulin (Ig)G, IgM and IgE antibodies to the BNT162b2 vaccine, biomarkers associated with allergic reaction, including tryptase for anaphylaxis, complement 5a(C5a), intercellular adhesion molecule 1 (ICAM-1) for endothelial activation and Interleukin (IL)-4, IL-10, IL-33, tumour necrosis factor (TNF) and monocyte chemoattractant protein (MCP-1), were measured. Basophil activation test (BAT) was performed in BNT162b2-induced anaphylaxis patients by flow cytometry. The majority of patients with immediate-type BNT162b2 vaccine HSR demonstrated raised C5a and Th2-related cytokines but normal tryptase levels during the acute reaction, together with significantly higher levels of IgM antibodies to the BNT162b2 vaccine (IgM 67.2 (median) vs. 23.9 AU/mL, p < 0.001) and ICAM-1 when compared to non-reactor controls. No detectable IgE antibodies to the BNT162b2 vaccine were found in these patients. The basophil activation tests by flow cytometry to the Pfizer vaccine, 1,2-dimyristoyl-rac-glycero-3-methoxypolyethylene glycol (DMG-PEG) and PEG-2000 were negative in four anaphylaxis patients. Acute hypersensitivity reactions post BNT162b2 vaccination suggest pseudo-allergic reactions via the activation of anaphylatoxins C5a and are independent of IgE-mechanisms. Vaccine reactors have significantly higher levels of anti-BNT162b2 IgM although its precise role remains unclear.

Measuring Caspase Activity Using a Fluorometric Assay or Flow Cytometry.

The activation of cysteine proteases, known as caspases, remains an important process in multiple forms of cell death. Caspases are critical initiators and executioners of apoptosis, the most studied form of programmed cell death. Apoptosis occurs during developmental processes and is a necessary event in tissue homeostasis. Pyroptosis is another form of cell death that utilizes caspases and is a critical process in activating the immune system through the activation of the inflammasome, which results in the release of members of the interleukin-1 (IL-1) family. To assess caspase activity, target substrates can be assessed. However, sensitivity can be an issue when examining single cells or low-level activity. We demonstrate how a fluorogenic substrate can be used with a population-based assay or single-cell assay by flow cytometry. With proper controls, different amino acid sequences can be used to identify which caspases are active. Using these assays, the simultaneous loss of the inhibitors of apoptosis proteins upon tumor necrosis factor (TNF) stimulation has been identified, which primarily induces apoptosis in macrophages rather than other forms of cell death.

Robust SNP-based prediction of rheumatoid arthritis through machine-learning-optimized polygenic risk score.

BACKGROUND: The popular statistics-based Genome-wide association studies (GWAS) have provided deep insights into the field of complex disorder genetics. However, its clinical applicability to predict disease/trait outcomes remains unclear as statistical models are not designed to make predictions. This study employs statistics-free machine-learning (ML)-optimized polygenic risk score (PRS) to complement existing GWAS and bring the prediction of disease/trait outcomes closer to clinical application. Rheumatoid Arthritis (RA) was selected as a model disease to demonstrate the robustness of ML in disease prediction as RA is a prevalent chronic inflammatory joint disease with high mortality rates, affecting adults at the economic prime. Early identification of at-risk individuals may facilitate measures to mitigate the effects of the disease. METHODS: This study employs a robust ML feature selection algorithm to identify single nucleotide polymorphisms (SNPs) that can predict RA from a set of training data comprising RA patients and population control samples. Thereafter, selected SNPs were evaluated for their predictive performances across 3 independent, unseen test datasets. The selected SNPs were subsequently used to generate PRS which was also evaluated for its predictive capacity as a sole feature. RESULTS: Through robust ML feature selection, 9 SNPs were found to be the minimum number of features for excellent predictive performance (AUC > 0.9) in 3 independent, unseen test datasets. PRS based on these 9 SNPs was significantly associated with (P < 1 × 10-16) and predictive (AUC > 0.9) of RA in the 3 unseen datasets. A RA ML-PRS calculator of these 9 SNPs was developed ( https://xistance.shinyapps.io/prs-ra/ ) to facilitate individualized clinical applicability. The majority of the predictive SNPs are protective, reside in non-coding regions, and are either predicted to be potentially functional SNPs (pfSNPs) or in high linkage disequilibrium (r2 > 0.8) with un-interrogated pfSNPs. CONCLUSIONS: These findings highlight the promise of this ML strategy to identify useful genetic features that can robustly predict disease and amenable to translation for clinical application.

Montreal cognitive assessment as a screening instrument for cognitive impairment in systemic lupus erythematosus patients without overt neuropsychiatric manifestations.

OBJECTIVES: The Montreal Cognitive Assessment (MoCA) is an increasingly used screening tool for cognitive impairment. The aim of this study was to examine how MoCA performed in identifying cognitive impairment (CI) domains in SLE patients compared with formal standardized neuropsychological testing (NPT). Factors related to SLE disease, immunologic and psychological state associated with CI were also explored. METHODS: This cross-sectional study recruited 50 SLE patients without overt neuropsychiatric manifestations from April 2017 to May 2018. The patients were evaluated with MoCA, formal NPT and the Depression, Anxiety, and Stress Scales (DASS) 42-item self-report questionnaire. Values of sensitivity and specificity were computed for different cut-offs of MoCA within each cognitive domain of NPT and descriptive analysis was used to identify the factors affecting cognitive function. RESULTS: The median score for MoCA was 27.5 (range 22-30). Using a MoCA cutoff of <26, 18 (36%) were identified to have CI using NPT compared to 8 (16%) using MoCA. The most frequently affected cognitive domain was executive functioning with 15 affected patients. Sensitivities and specificities of the MoCA range from 50% to 100% and 5.7% to 16.7%, respectively, across cognitive domains. A lower MoCA cutoff of <25 improve sensitivity of identifying impairment in executive functioning from 60% to 80%. In univariate analysis, DASS scores, disease activity, presence of antiphospholipid antibodies, presence of concurrent autoimmune disease, current, and cumulative corticosteroid therapy did not predict cognitive performance. CONCLUSION: MoCA may be a useful screening tool to identify the most frequently affected cognitive domain which is executive functioning using a lower cutoff of <25 in SLE patients without overt neuropsychiatric manifestations.

Epstein Barr virus-mediated transformation of B cells from XIAP-deficient patients leads to increased expression of the tumor suppressor CADM1.

X-linked lymphoproliferative disease (XLP) is either caused by loss of the SLAM-associated protein (SAP; XLP-1) or the X-linked inhibitor of apoptosis (XIAP; XLP-2). In both instances, infection with the oncogenic human Epstein Barr virus (EBV) leads to pathology, but EBV-associated lymphomas only emerge in XLP-1 patients. Therefore, we investigated the role of XIAP during B cell transformation by EBV. Using humanized mice, IAP inhibition in EBV-infected mice led to a loss of B cells and a tendency to lower viral titers and lymphomagenesis. Loss of memory B cells was also observed in four newly described patients with XIAP deficiency. EBV was able to transform their B cells into lymphoblastoid cell lines (LCLs) with similar growth characteristics to patient mothers' LCLs in vitro and in vivo. Gene expression analysis revealed modest elevated lytic EBV gene transcription as well as the expression of the tumor suppressor cell adhesion molecule 1 (CADM1). CADM1 expression on EBV-infected B cells might therefore inhibit EBV-associated lymphomagenesis in patients and result in the absence of EBV-associated malignancies in XLP-2 patients.

Evaluation of Patients with Vaccine Allergies Prior to mRNA-Based COVID-19 Vaccination.

During the initial rollout of coronavirus disease 2019 (COVID-19) vaccination in Singapore, the Ministry of Health (MOH) issued a recommendation that patients with a history of any previous vaccine allergy be referred to an allergist for further review of their suitability to proceed with mRNA-based COVID-19 vaccines. Patients fulfilling the above criterion were divided into three groups: immediate reaction (Group A), delayed reaction (Group B) and no/irrelevant reaction (Group C). They were subjected to either a skin prick test (SPT) and intradermal test (IDT) with polyethylene glycol (PEG) or polysorbate-containing products; direct injection with the Pfizer BNT162b2 vaccine in the allergy clinic; or injection at community vaccination centres, respectively. Groups A and B were also invited to complete a questionnaire survey on post-vaccination reactions, and blood sampling pre-vaccination and 1 h after the first dose of the BNT162b2 vaccine to measure immunoglobulin (Ig) G, IgM and IgE antibodies to the Pfizer BNT162b2 vaccine via ELISA assays immobilised with the BNT162b2 vaccine, as well as levels of allergic cytokines interleukin (IL)-4 and IL-33, complement C5a and the endothelial activation marker intercellular adhesion molecule-1 (ICAM-1). Groups A and B comprised 62 (20.5%) patients each. In Group A, two subjects (3.2%) with equivocal IDT results tolerated both doses of the BNT162b2 vaccine without major allergic reactions. The remaining 60 (96.8%) in Group A and 62 (100%) in Group B completed both doses of BNT162b2 vaccination without major adverse reactions. Among the 99 who completed the questionnaire survey, 13 (13%) patients reported mild allergic reactions after the first dose of the vaccine. Immunoglobulin (Ig) G and M antibodies, but not IgE antibodies to the Pfizer BNT162b2 vaccine were detected in 67 subjects prior to vaccination. The presence of anti-Pfizer BNT162b2 IgG and IgM prior to vaccination did not result in major allergic reactions nor increases in Th2-related cytokines (IL-4, IL-33), complement activation products (C5a) or endothelial activation (ICAM-1). The majority of those with suspected reactions to non-COVID-19 polysorbate-containing vaccines tolerated the BNT162b2 vaccine. Excipient skin tests for PEG and polysorbate prior to vaccination are unnecessary.

Functional coding haplotypes and machine-learning feature elimination identifies predictors of Methotrexate Response in Rheumatoid Arthritis patients.

BACKGROUND: Major challenges in large scale genetic association studies include not only the identification of causative single nucleotide polymorphisms (SNPs), but also accounting for SNP-SNP interactions. This study thus proposes a novel feature engineering approach integrating potentially functional coding haplotypes (pfcHap) with machine-learning (ML) feature selection to identify biologically meaningful, possibly causative genetic factors, that take into consideration potential SNP-SNP interactions within the pfcHap, to best predict for methotrexate (MTX) response in rheumatoid arthritis (RA) patients. METHODS: Exome sequencing from 349 RA patients were analysed, of which they were split into training and unseen test set. Inferred pfcHaps were combined with 30 non-genetic features to undergo ML recursive feature elimination with cross-validation using the training set. Predictive capacity and robustness of the selected features were assessed using six popular machine learning models through a train set cross-validation and evaluated in an unseen test set. FINDINGS: Significantly, 100 features (95 pfcHaps, 5 non-genetic factors) were identified to have good predictive performance (AUC: 0.776-0.828; Sensitivity: 0.656-0.813; Specificity: 0.684-0.868) across all six ML models in an unseen test dataset for the prediction of MTX response in RA patients. INTERPRETATION: Majority of the predictive pfcHap SNPs were predicted to be potentially functional and some of the genes in which the pfcHap resides in were identified to be associated with previously reported MTX/RA pathways. FUNDING: Singapore Ministry of Health's National Medical Research Council (NMRC) [NMRC/CBRG/0095/2015; CG12Aug17; CGAug16M012; NMRC/CG/017/2013]; National Cancer Center Research Fund and block funding Duke-NUS Medical School.; Singapore Ministry of Education Academic Research Fund Tier 2 grant MOE2019-T2-1-138.

Machine learning using genetic and clinical data identifies a signature that robustly predicts methotrexate response in rheumatoid arthritis.

OBJECTIVE: To develop a hypothesis-free model that best predicts response to MTX drug in RA patients utilizing biologically meaningful genetic feature selection of potentially functional single nucleotide polymorphisms (pfSNPs) through robust machine learning (ML) feature selection methods. METHODS: MTX-treated RA patients with known response were divided in a 4:1 ratio into training and test sets. From the patients' exomes, potential features for classifier prediction were identified from pfSNPs and non-genetic factors through ML using recursive feature elimination with cross-validation incorporating the random forest classifier. Feature selection was repeated on random subsets of the training cohort, and consensus features were assembled into the final feature set. This feature set was evaluated for predictive potential using six ML classifiers, first by cross-validation within the training set, and finally by analysing its performance with the unseen test set. RESULTS: The final feature set contains 56 pfSNPs and five non-genetic factors. The majority of these pfSNPs are located in pathways related to RA pathogenesis or MTX action and are predicted to modulate gene expression. When used for training in six ML classifiers, performance was good in both the training set (area under the curve: 0.855-0.916; sensitivity: 0.715-0.892; and specificity: 0.733-0.862) and the unseen test set (area under the curve: 0.751-0.826; sensitivity: 0.581-0.839; and specificity: 0.641-0.923). CONCLUSION: Sensitive and specific predictors of MTX response in RA patients were identified in this study through a novel strategy combining biologically meaningful and machine learning feature selection and training. These predictors may facilitate better treatment decision-making in RA management.

Validation of Tokyo Guidelines 2007 and Tokyo Guidelines 2013/2018 Criteria for Acute Cholangitis and Predictors of In-Hospital Mortality.

BACKGROUND: Acute cholangitis (AC) is a common emergency with a significant mortality risk. The Tokyo Guidelines (TG) provide recommendations for diagnosis, severity stratification, and management of AC. However, validation of the TG remains poor. This study aims to validate TG07, TG13, and TG18 criteria and identify predictors of in-hospital mortality in patients with AC. METHODS: This is a retrospective audit of patients with a discharge diagnosis of AC in the year 2016. Demographic, clinical, investigation, management and mortality data were documented. We performed a multinomial logistic regression analysis with stepwise variable selection to identify severity predictors for in-hospital mortality. RESULTS: Two hundred sixty-two patients with a median age of 75.9 years (IQR 64.8-82.8) years were included for analysis. TG13/TG18 diagnostic criteria were more sensitive than TG07 diagnostic criteria (85.1 vs. 75.2%; p < 0.006). The majority of the patients (n = 178; 67.9%) presented with abdominal pain, pyrexia (n = 156; 59.5%), and vomiting (n = 123; 46.9%). Blood cultures were positive in 95 (36.3%) patients, and 79 (83.2%) patients had monomicrobial growth. The 30-day, 90-day, and in-hospital mortality numbers were 3 (1.1%), 11 (4.2%), and 15 (5.7%), respectively. In multivariate analysis, type 2 diabetes mellitus (OR = 12.531; 95% CI 0.354-116.015; p = 0.026), systolic blood pressure <100 mm Hg (OR = 10.108; 95% CI 1.094-93.395; p = 0.041), Glasgow coma score <15 (OR = 38.16; 95% CI 1.804-807.191; p = 0.019), and malignancy (OR = 14.135; 95% CI 1.017-196.394; p = 0.049) predicted in-hospital mortality. CONCLUSION: TG13/18 diagnostic criteria are more sensitive than TG07 diagnostic criteria. Type 2 diabetes mellitus, systolic blood pressure <100 mm Hg, Glasgow coma score <15, and malignant etiology predict in-hospital mortality in patients with AC. These predictors could be considered in acute stratification and treatment of patients with AC.

Pseudo-Anaphylactic Reactions to Pfizer BNT162b2 Vaccine: Report of 3 Cases of Anaphylaxis Post Pfizer BNT162b2 Vaccination.

Anaphylactic reactions were observed after Singapore's national coronavirus disease 2019 (COVID-19) vaccination programme started in December 2020. We report the clinical and laboratory features of three patients in our institution who developed anaphylactic reactions after receiving the Pifzer BNT162b2 vaccine. IgM and IgG antibodies, but not IgE antibodies to the Pfizer BNT162b2 vaccine, were detected in all subjects. Similarly, mild to high elevated levels of anti-polyethylene glycol (PEG) IgG (1035-19709 U/mL, vs. vaccine-naive < 265 U/mL, vaccine-tolerant < 785 U/mL) and IgM (1682-5310 U/mL, vs. vaccine-naive < 1011 U/mL, vaccine-tolerant < 1007 U/mL) were detected in two out of three patients via commercial ELISA. High levels of serum anaphylatoxin C3a (79.0 ± 6.3 µg/mL, mean ± SD, vs. normal < 10 µg/mL) were observed in all three patients during the acute phase of the reaction, while tryptase levels, a marker of mast cell activation, were not elevated. Finally, one patient with the highest levels of anti-PEG IgG, IgM, and anti-Pfizer BNT162b2 IgG and IgM exhibited an enhanced Th2 cytokine serum profile during an acute reaction, with high levels of IL-4 (45.7 pg/mL, vs. vaccine-naive/tolerant < 2.30 pg/mL), IL-33 (86.4 pg/mL, vs. vaccine-naive/tolerant < 5.51 pg/mL) and IL-10 (22.9 pg/mL, vs. vaccine-naive/tolerant < 12.49 pg/mL) diminishing over time following corticosteroid treatment. Taken together, we propose these cases of anaphylaxis described are driven by a complement activation-related pseudoallergy (CAPRA), rather than classical IgE-mediated mechanisms.

BRD9 is a druggable component of interferon-stimulated gene expression and antiviral activity.

Interferon (IFN) induction of IFN-stimulated genes (ISGs) creates a formidable protective antiviral state. However, loss of appropriate control mechanisms can result in constitutive pathogenic ISG upregulation. Here, we used genome-scale loss-of-function screening to establish genes critical for IFN-induced transcription, identifying all expected members of the JAK-STAT signaling pathway and a previously unappreciated epigenetic reader, bromodomain-containing protein 9 (BRD9), the defining subunit of non-canonical BAF (ncBAF) chromatin-remodeling complexes. Genetic knockout or small-molecule-mediated degradation of BRD9 limits IFN-induced expression of a subset of ISGs in multiple cell types and prevents IFN from exerting full antiviral activity against several RNA and DNA viruses, including influenza virus, human immunodeficiency virus (HIV1), and herpes simplex virus (HSV1). Mechanistically, BRD9 acts at the level of transcription, and its IFN-triggered proximal association with the ISG transcriptional activator, STAT2, suggests a functional localization at selected ISG promoters. Furthermore, BRD9 relies on its intact acetyl-binding bromodomain and unique ncBAF scaffolding interaction with GLTSCR1/1L to promote IFN action. Given its druggability, BRD9 is an attractive target for dampening ISG expression under certain autoinflammatory conditions.

Loss of cIAP1 in Endothelial Cells Limits Metastatic Extravasation through Tumor-Derived Lymphotoxin Alpha.

In this study, we determined whether Smac mimetics play a role in metastasis, specifically in circulation, tumor extravasation and growth in a metastatic site. Reports suggest inducing the degradation of IAPs through use of Smac mimetics, alters the ability of the tumor cell to metastasize. However, a role for the immune or stromal compartment in affecting the ability of tumor cells to metastasize upon loss of IAPs has not been defined. To address this open question, we utilized syngeneic tumor models in a late-stage model of metastasis. Loss of cIAP1 in the endothelial compartment, rather than depletion of cIAP2 or absence of cIAP1 in the hematopoietic compartment, caused reduction of tumor load in the lung. Our results underline the involvement of the endothelium in hindering tumor cell extravasation upon loss of cIAP1, in contrast to the immune compartment. Endothelial specific depletion of cIAP1 did not lead to cell death but resulted in an unresponsive endothelium barrier to permeability factors causing a decrease in tumor cell extravasation. Surprisingly, lymphotoxin alpha (LTA), and not TNF, secreted by the tumor cells, was critical for the extravasation. Using TCGA, we found high LTA mRNA expression correlated with decreased survival in kidney carcinoma and associated with advanced disease stage. Our data suggest that Smac mimetics, targeting cIAP1/2, reduce metastasis to the lung by inhibiting tumor cell extravasation.

Trial monitoring via a futility criterion for interim results on a count data endpoint and a continuous endpoint.

Assumptions made at design stage regarding the true treatment effect, background event rate and other factors may not always hold. Thus, long-term and large-scale studies may be designed with an interim analysis in order that the trials may be stopped early due to futility to save resource. There are many considerations of trial conducts for this type of trials. In this paper, we use a mock study to illustrate systematically the thinking and procedures for trial monitoring with a futility criterion for the interim results on a count data endpoint and a continuous endpoint. We focus on the discussions of blinded trial monitoring, the probability of meeting the futility criterion, conditional power/probability of success, Bayesian inference, potential delayed treatment effect and subgroup analysis. The experience should be applicable to future studies with similar features.

Validation of TG07 and TG13/TG18 criteria for acute cholangitis and predictors of in-hospital mortality in patients over 80 years old.

Aim of the study: This study aims to validate Tokyo guidelines (TG) TG07/TG13/TG18 criteria and identify predictors of in-hospital mortality in acute cholangitis (AC) patients over 80 years old. Material and methods: This is a retrospective audit of AC patients from January 2009 to December 2016. Demographic, clinical, investigation, management, and mortality data were studied. Multinomial logistic regression analysis with stepwise variable selection identified predictors for in-hospital mortality. Results: Three hundred and eighty-eight patients were treated for AC. One hundred and sixty-two (41.8%) patients were male. 230 (59.3%) patients had a history of biliary disease, 161 (41.5%) patients had type 2 diabetes mellitus (T2DM), and 98 (25.3%) patients had ischaemic heart disease (IHD). Abdominal pain (n = 226, 58.2%), pyrexia (n = 247, 63.7%), and vomiting (n = 159, 41.0%) were the common presenting symptoms. 191 (49.2%) patients had abdominal tenderness. Positive blood cultures were recorded in patients 158 (40.7%) patients. Escherichia coli was the most commonly identified organism (n = 117, 30.2%). 77 (19.8%), 188 (48.5%) and 123 (31.7%) patients were graded with mild, moderate, and severe AC, respectively. 30-day, 90-day, and in-hospital mortality were 9 (2.3%), 19 (4.9%) and 38 (9.8%), respectively. On multivariate analysis, systolic blood pressure ≤ 100 mmHg (OR = 3.817, 95% CI: 1.365-10.761, p = 0.011), hypoalbuminaemia < 28 gm/l (OR = 6.052, 95% CI: 2.635-13.904, p < 0.001), serum creatinine ≥ 176.8 (OR = 2.787, 95% CI: 1.146-6.778, p = 0.024) and international normalized ratio (INR) > 1.5 (OR = 3.247, 95% CI: 1.234-8.544, p = 0.017) were independent predictors of in-hospital mortality. Conclusions: Hypotension, hypoalbuminaemia, elevated creatinine, and elevated INR predict in-hospital mortality in AC patients over 80 years old.

Conversion among the 28-joint count activity indices for rheumatoid arthritis.

OBJECTIVE: Disease activity indices for rheumatoid arthritis (RA) are important in clinical practice and research. Although they are closely correlated, they are not in good agreement. We derived formulae to convert values from one of the four 28-joint count indices (disease activity score using erythrocyte sedimentation rate [DAS28-ESR], disease activity score using C-reactive protein [DAS28-CRP], clinical disease activity index [CDAI], and simple disease activity index [SDAI]) to any of the others. METHODS: We obtained data from 175 patients from our RA registry with concurrent CRP and ESR and established the nature of relationships between the indices using these data. Subsequently, we developed empiric conversion formulae. Furthermore, we developed new cutoff values for classifying disease activity to minimize the disparity among indices, using an iterative method. RESULTS: The relationships between DAS28-ESR and DAS28-CRP and between SDAI and CDAI were approximately linear; the others were quadratic. Quadratic equations approximated the relationship between DAS, SDAI, and CDAI, whereas natural logarithms function approximated the relationship between DAS28-ESR and DAS28-CRP. Patients are frequently categorized into inconsistent disease activity states with any two indices, with the disparity ranging from 9.7% to 40.6%. The new cutoff values were developed to minimize the discrepant activity state categorization, reducing the disparity range to 6.3%-32.6%. CONCLUSION: We derived empiric formulae that connect DAS28-ESR, DAS28-CRP, SDAI, and CDAI. Moreover, we developed new cutoff values to minimize the discrepant activity state categorization with different indices.

Impact of geography on Scottish cancer diagnoses in primary care: Results from a national cancer diagnosis audit.

BACKGROUND: A recent meta-analysis of global research found cancer patients living in rural locations are 5% less likely to survive than their urban counterparts, a survival disadvantage that has never been satisfactorily explained. AIMS: [1] To describe and compare primary-care involvement in the diagnosis of cancer between rural and urban patients in Scotland. [2] To compare the length of key diagnostic pathway intervals between rural and urban cancer patients in Scotland. METHODS: Participating GPs in the Scottish National Cancer Audit of cancer diagnosis (2017) collected data from primary-care medical records on the diagnostic pathway of patients diagnosed in 2014. Residential postcodes designated the patients as rural or urban dwellers. Key cancer diagnostic pathway intervals (primary, diagnostic, secondary, and treatment) were compared using binary logistic regression. Descriptive analysis included comparison of patient characteristics, and routes to diagnosis. RESULTS: 73 Scottish general practices provided data on 1,905 cancer diagnoses. Rural patients did not have higher odds of prolonged diagnostic intervals compared to urban patients but were significantly more likely to have had a cancer alarm feature at presentation and three or more primary-care consultations prior to referral. Rural GPs were significantly more likely to perceive an avoidable delay in their patient's diagnostic pathway. CONCLUSION: There was no evidence that rural patients were more likely to be subject to prolonged cancer diagnostic delays than urban patients. Rural patients may experience primary care differently in the lead-up to a cancer diagnosis. The effect on outcome is probably negligible, but further research is required to confirm this.