Objectives Although neuropsychiatric involvement in Systemic Lupus Erythematosus (NPSLE) is one of the most complex and troubling manifestations of the disease, validated outcome instruments to be used as sensitive endpoints in controlled clinical trials are lacking. We set out a systematic literature review (SLR) to identify outcome measurement instruments and domains used to assess NPSLE. Methods The Preferred Reporting Items for systematic reviews and Meta-analysis (PRISMA) guidelines were used. Articles available in English (1967-2020), listed in PubMed, EMBASE, PsycINFO, Cochrane Library and EULAR outcome measures library were screened. All domains and outcome measurement instruments were characterized according to the OMERACT Filter 2.1, considering core areas (manifestations/abnormalities, life impact, death/lifespan, societal/resource use) and contextual factors. Results Of 3,392 abstracts evaluated, 83 studies were included in the SLR (15,974 patients, females 89.9%). Eligible studies included domains and instruments pertinent to all core areas defined by OMERACT, except for “societal/resource use”. The most common core areas were “manifestations/abnormalities”, covering 10 domains pertinent to laboratory and instrumental markers, indexes and neuropsychiatric dimension (cognitive, neurologic and psychiatric field), and “life impact”, covering 7 domains related to physical function (from both the perspective of the patient and the physician), pain and quality of life. Conclusion Our study revealed great heterogeneity in the instruments derived from populations with NPSLE and none of these had high-quality evidence. This supports the need to develop and further validate a core domain set and outcome measurement instruments to promote clinical research in this field, enhancing comparability across studies.

List of ICD-9CM codes and exemption codes (EC) for comorbidities considered in the study.

Background:Antiphospholipid (aPL) antibodies are considered in obstetric morbidity even when Sydney criteria for OAPS are not met. Classification and treatment of NC-OAPS patients and aPL carriers during pregnancy are still debated.Objectives:To increase knowledge, we evaluated and compared aPL serum profiles, exposure to antithrombotic therapies and pregnancy outcomes in OAPS, NC-OAPS and aPL carrier patients, accessing to our centre.Methods:A retrospective observational study was conducted on pregnant outpatients from January 2003 to April 2020. According to Sydney revised classification criteria, we considered lupus anticoagulant (LA), IgM and IgG anti-cardiolipin antibodies (aCL), IgM and IgG antibeta2 glycoprotein I antibodies (aβ2-GPI), to stratify aPL risk profiles [Ref]. In each pregnancy, after case stratification into high (≥ 2 aPL or LA serum positivity) versus low (single aPL positivity) risk profile, we evaluated antithrombotic treatment strategy and subsequent pregnancy outcomes as live-births, spontaneous abortions (SA) or foetal losses.Results:A total of 78 pregnancies were followed: 17 in OAPS, 9 in NC-OAPS and 52 in aPL carrier patients. Rheumatic diseases (RD) coexisted predominately in carriers (73.1%), mainly systemic lupus erythematosus (57.9%). As presented in Table 1, in OAPS and aPL plus RD carrier groups the association of acetyl-salicylic acid (ASA - mean dose 100 mg q.d.) and low-molecular weight heparin (LMWH - mean dose 4000 UI q.d.) showed a better rate of positive outcomes (97.8% of pregnancies) in high aPL risk profile, compared to monotherapy, especially with LA or triple aPL positivity. Conversely, negative outcomes occurred mostly with triple aPL positivity in the first group and double aPL in the second, despite therapy approaches. No significant data were obtained in NC-OAPS group, due to its paucity, though adverse outcomes were observed with monotherapy both in high and low risk profiles. Except aPL carriers with RD, in all other low risk subgroups, a prevalence of negative outcomes occurred using ASA alone, without statistical significance (OR 0; p= 0.45). Similarly, considering the whole population, the use of a mono or a combination therapy in high risk subgroups had not a significant correlation with pregnancy outcomes (OR 1.79; 95%CI 0.31-10.15; p= 0.50).Conclusion:In our study, negative pregnancy outcomes were sporadic, occurring mostly with ≥ 2 aPL positivity. Combination treatment showed better results overall in high aPL risk profile patients, both in OAPS and NC-OAPS or aPL carriers. Though no significant correlation between outcomes and treatments were found, we hinted how aPL-based risk stratification may be useful in adopting personalised therapies to prevent obstetric failures.Reference:[1]Miyakis S, et al (2006) International consensus statement on an update of the classification criteria for definite antiphospholipid syndrome. J Thromb Haemost 4:295–306.Table 1.Population groups, aPL risk profiles, antithrombotic therapies and pregnancy outcomes.Population groupaPL risk profileType/n° of aPLTherapy (n° of pregnancies)Pregnancy outcomesOAPSHighLAASA (1)ASA + LMWH (1)1 live-birth1 live-birth2 aPLASA + LMWH (3)3 live-births3 aPLASA + LMWH (9)7 live-births 2 foetal lossesLow1 aPLASA (2)ASA + LMWH (1)1 live-birth1 foetal loss1 live-birthNC-OAPSHighLA--2 aPLASA (1)LMWH (1)1 live-birth1 SA3 aPL--Low1 aPLASA (6)ASA + LMWH (1)5 live-births1 SA1 live-birthaPL carriers without RDHighLAASA (1)LMWH (1)1 live-birth1 live-birth2 aPLASA (1)LMWH (2)1 live-birth2 live-births3 aPLASA (1)ASA + LMWH (3)1 live-birth3 live-birthsLow1 aPLASA (5)4 live-births1 foetal lossaPL carriers with RDHighLAASA (4)ASA + LMWH (7)3 live-birth1 foetal loss6 live-births1 SA2 aPLASA (6)ASA + LMWH (4)6 live-births2 live-births1 SA1 foetal loss3 aPLLMWH (2)ASA + LMWH (5)2 live-births5 live-birthsLow1 aPLASA (8)ASA + LMWH (3)8 live-births3 live-birthsDisclosure of Interests:None declared

Targeted proteomics data from the PsA and Pso patients was subjected to univariate and multivariate analysis using a leave one out cross validation approach. The initial results revealed that the application of the PAPRICA method to the BIOCOM-Pso samples resulted in a dataset in which 88 of the 206 PAPRICA proteins could be reliably measured (CV Area < 20%; Signal to Noise ratio > 5; Library Dot Product > 0.8). This subset of the PAPRICA proteins was not able to discriminate between PsA and Pso and none of the associated peptides were significantly different between the two groups (p value < 0.05). Conclusion: Analysis of a subset of 88 of the 206 biomarker proteins in the PAPRICA method, in patients with PsA and Pso, did not reveal peptides (proteins) that were statistically different between these two groups. Multivariate analysis generated a model that was unable to discriminate between patients with PsA and Pso. The possibility that the full PAPR-ICA assay may be able to discriminate between PsA and Pso will be explored, as will supplementing the PAPRICA method with additional biomarkers including proteins that may be identified in an unbiased proteome wide screen of PsA vs Pso serum samples.