Role of plaque inflammation in symptomatic carotid stenosis.

Objective: Prior studies have shown that plaque inflammation on FDG-PET and the symptomatic carotid atheroma inflammation lumen-stenosis (SCAIL) score were associated with recurrent ischemic events, but the findings have thus far not been widely validated. Therefore, we aimed to validate the findings of prior studies. Methods: A single-center prospective cohort study that recruited patients with (1) recent TIA or ischemic stroke within the past 30 days, (2) ipsilateral carotid artery stenosis of ≥50%, and (3) were not considered for early carotid revascularization. The (1) maximum standardized uptake value (SUVmax) of the symptomatic carotid plaque, (2) the SCAIL score, and (3) stenosis severity of the symptomatic carotid artery were measured for all patients. The outcomes were (1) a 90-day ipsilateral ischemic stroke and (2) a 90-day ipsilateral symptomatic TIA or major adverse cardiovascular event (MACE). Results: Among the 131 patients included in the study, the commonest cardiovascular risk factor was hypertension (95 patients, 72.5%), followed by diabetes mellitus (77 patients, 58.8%) and being a current smoker (64 patients, 48.9%). The median (IQR) duration between the index cerebral ischemic event and recruitment to the study was 1 (0, 2.5) days. The median (IQR) duration between the index cerebral ischemic event and FDG-PET was 5 (4, 7) days. A total of 14 (10.7%) patients had a 90-day stroke, and 41 (31.3%) patients had a 90-day TIA or MACE. On comparison of the predictive performances of the SCAIL score and SUVmax, SUVmax was found to be superior to the SCAIL score for predicting both 90-day ipsilateral ischemic stroke (AUC: SCAIL = 0.79, SUVmax = 0.92; p < 0.001; 95% CI = 0.072, 0.229) and 90-day TIA or MACE (AUC: SCAIL = 0.76, SUVmax = 0.84; p = 0.009; 95% CI = 0.020, 0.143). Conclusion: Plaque inflammation as quantified on FDG-PET may serve as a reliable biomarker for risk stratification among patients with ECAD and recent TIA or ischemic stroke. Future studies should evaluate whether patients with significant plaque inflammation as quantified on FDG-PET benefit from carotid revascularization and/or anti-inflammatory therapy.

Novel Autoantibodies in Idiopathic Small Fiber Neuropathy.

OBJECTIVE: Small fiber neuropathy (SFN) is clinically and etiologically heterogeneous. Although autoimmunity has been postulated to be pathophysiologically important in SFN, few autoantibodies have been described. We aimed to identify autoantibodies associated with idiopathic SFN (iSFN) by a novel high-throughput protein microarray platform that captures autoantibodies expressed in the native conformational state. METHODS: Sera from 58 SFN patients and 20 age- and gender-matched healthy controls (HCs) were screened against >1,600 immune-related antigens. Fluorescent unit readout and postassay imaging were performed, followed by composite data normalization and protein fold change (pFC) analysis. Analysis of an independent validation cohort of 33 SFN patients against the same 20 HCs was conducted to identify reproducible proteins in both cohorts. RESULTS: Nine autoantibodies were screened with statistical significance and pFC criteria in both cohorts, with at least 50% change in serum levels. Three proteins showed consistently high fold changes in main and validation cohorts: MX1 (FC = 2.99 and 3.07, respectively, p = 0.003, q = 0.076), DBNL (FC = 2.11 and 2.16, respectively, p = 0.009, q < 0.003), and KRT8 (FC = 1.65 and 1.70, respectively, p = 0.043, q < 0.003). Further subgroup analysis into iSFN and SFN by secondary causes (secondary SFN) in the main cohort showed that MX1 is higher in iSFN compared to secondary SFN (FC = 1.61 vs 0.106, p = 0.009). INTERPRETATION: Novel autoantibodies MX1, DBNL, and KRT8 are found in iSFN. MX1 may allow diagnostic subtyping of iSFN patients. ANN NEUROL 2022;91:66-77.

Differing clinical characteristics between influenza strains among young healthy adults in the tropics.

BACKGROUND: Influenza infections may result in different clinical presentations. This study aims to determine the clinical differences between circulating influenza strains in a young healthy adult population in the tropics. METHODS: A febrile respiratory illness (FRI) (fever ≥ 37.5°C with cough and/or sore throat) surveillance program was started in 4 large military camps in Singapore on May 2009. Personnel with FRI who visited the camp clinics from 11 May 2009 to 25 June 2010 were recruited. Nasal washes and interviewer-administered questionnaires on demographic information and clinical features were obtained from consenting participants. All personnel who tested positive for influenza were included in the study. Overall symptom load was quantified by counting the symptoms or signs, and differences between strains evaluated using linear models. RESULTS: There were 434 (52.9%) pandemic H1N1-2009, 58 (7.1%) seasonal H3N2, 269 (32.8%) influenza B, and 10 (1.2%) seasonal H1N1 cases. Few seasonal influenza A (H1N1) infections were detected and were therefore excluded from analyses, together with undetermined influenza subtypes (44 (1.5%)), or more than 1 co-infecting subtype (6 (0.2%)). Pandemic H1N1-2009 cases had significantly fewer symptoms or signs (mean 7.2, 95%CI 6.9-7.4, difference 1.6, 95%CI 1.2-2.0, p < 0.001) than the other two subtypes (mean 8.7, 95%CI 8.5-9.0). There were no statistical differences between H3N2 and influenza B (p = 0.58). Those with nasal congestion, rash, eye symptoms, injected pharynx or fever were more likely to have H3N2; and those with sore throat, fever, injected pharynx or rhinorrhoea were more likely to have influenza B than H1N1-2009. CONCLUSIONS: Influenza cases have different clinical presentations in the young adult population. Pandemic H1N1 influenza cases had fewer and milder clinical symptoms than seasonal influenza. As we only included febrile cases and had no information on the proportion of afebrile infections, further research is needed to confirm whether the relatively milder presentation of pandemic versus seasonal influenza infections applies to all infections or only febrile illnesses.

Effectiveness of pandemic H1N1-2009 vaccination in reducing laboratory confirmed influenza infections among military recruits in tropical Singapore.

BACKGROUND: Limited information is available about pandemic H1N1-2009 influenza vaccine effectiveness in tropical communities. We studied the effectiveness of a pandemic H1N1 vaccination program in reducing influenza cases in Singapore. METHODS: A surveillance study was conducted among military personnel presenting with febrile respiratory illness from mid-2009 to mid-2010. Consenting individuals underwent nasal washes, which were tested with RT-PCR and subtyped. A vaccination program (inactivated monovalent Panvax H1N1-2009 vaccine) was carried out among recruits. A Bayesian hierarchical model was used to quantify relative risks in the pre- and post-vaccination periods. An autoregressive generalised linear model (GLM) was developed to minimise confounding. RESULTS: Of 2858 participants, 437 (15.3%), 60 (2.1%), and 273 (9.6%) had pandemic H1N1, H3N2, and influenza B. The ratio of relative risks for pandemic H1N1 infection before and after vaccination for the recruit camp relative to other camps was 0.14 (0.016,0.49); for H3N2, 0.44 (0.035,1.8); and for influenza B, 18 (0.77,89). Using the GLM for the recruit camp, post-vaccination weekly cases decreased by 54% (37%,67%, p<0.001) from that expected without vaccination; influenza B increased by 66 times (9-479 times, p<0.001); with no statistical difference for H3N2 (p = 0.54). CONCLUSIONS: Pandemic vaccination reduced H1N1-2009 disease burden among military recruits. Routine seasonal influenza vaccination should be considered.

A clinical diagnostic model for predicting influenza among young adult military personnel with febrile respiratory illness in Singapore.

INTRODUCTION: Influenza infections present with wide-ranging clinical features. We aim to compare the differences in presentation between influenza and non-influenza cases among those with febrile respiratory illness (FRI) to determine predictors of influenza infection. METHODS: Personnel with FRI (defined as fever ≥ 37.5 °C, with cough or sore throat) were recruited from the sentinel surveillance system in the Singapore military. Nasal washes were collected, and tested using the Resplex II and additional PCR assays for etiological determination. Interviewer-administered questionnaires collected information on patient demographics and clinical features. Univariate comparison of the various parameters was conducted, with statistically significant parameters entered into a multivariate logistic regression model. The final multivariate model for influenza versus non-influenza cases was used to build a predictive probability clinical diagnostic model. RESULTS: 821 out of 2858 subjects recruited from 11 May 2009 to 25 Jun 2010 had influenza, of which 434 (52.9%) had 2009 influenza A (H1N1), 58 (7.1%) seasonal influenza A (H3N2) and 269 (32.8%) influenza B. Influenza-positive cases were significantly more likely to present with running nose, chills and rigors, ocular symptoms and higher temperature, and less likely with sore throat, photophobia, injected pharynx, and nausea/vomiting. Our clinical diagnostic model had a sensitivity of 65% (95% CI: 58%, 72%), specificity of 69% (95% CI: 62%, 75%), and overall accuracy of 68% (95% CI: 64%, 71%), performing significantly better than conventional influenza-like illness (ILI) criteria. CONCLUSIONS: Use of a clinical diagnostic model may help predict influenza better than the conventional ILI definition among young adults with FRI.