Enteric fever is a febrile illness, occurring mostly in Asia and Africa, which can present as a severe and possibly fatal disease. Currently, a case fatality rate (CFR) of 1% is assumed when evaluating the global burden of enteric fever. Until now, no meta-analysis has been conducted to summarize mortality from enteric fever. Therefore, we conducted a systematic review and meta-analysis to aggregate all available evidence. We estimated an overall CFR of 2.49% (95% confidence interval, 1.65%–3.75%; n = 44), and a CFR in hospitalized patients of 4.45% (2.85%–6.88%; n = 21 of 44). There was considerably heterogeneity in estimates of the CFR from individual studies. Neither age nor antimicrobial resistance were significant prognostic factors, but limited data were available for these analyses. The combined estimate of the CFR for enteric fever is higher than previously estimated, and the evaluation of prognostic factors, including antimicrobial resistance, urgently requires more data.

Although effective in reducing relapse rate and delaying progression, current therapies for multiple sclerosis (MS) do not completely halt disease progression. T cell autoimmunity to myelin antigens is considered one of the main mechanisms driving MS. It is characterized by autoreactivity to disease-initiating myelin antigen epitope(s), followed by a cascade of epitope spreading, which are both strongly patient-dependent. Targeting a variety of MS-associated antigens by myelin antigen-presenting tolerogenic dendritic cells (tolDC) is a promising treatment strategy to re-establish tolerance in MS. Electroporation with mRNA encoding myelin proteins is an innovative technique to load tolDC with the full spectrum of naturally processed myelin-derived epitopes. In this study, we generated murine tolDC presenting myelin oligodendrocyte glycoprotein (MOG) using mRNA electroporation and we assessed the efficacy of MOG mRNA-electroporated tolDC to dampen pathogenic T cell responses in experimental autoimmune encephalomyelitis (EAE). For this, MOG35–55-immunized C57BL/6 mice were injected intravenously at days 13, 17, and 21 post-disease induction with 1α,25-dihydroxyvitamin D3-treated tolDC electroporated with MOG-encoding mRNA. Mice were scored daily for signs of paralysis. At day 25, myelin reactivity was evaluated following restimulation of splenocytes with myelin-derived epitopes. Ex vivo magnetic resonance imaging (MRI) was performed to assess spinal cord inflammatory lesion load. Treatment of MOG35–55-immunized C57BL/6 mice with MOG mRNA-electroporated or MOG35–55-pulsed tolDC led to a stabilization of the EAE clinical score from the first administration onwards, whereas it worsened in mice treated with non-antigen-loaded tolDC or with vehicle only. In addition, MOG35–55-specific pro-inflammatory pathogenic T cell responses and myelin antigen epitope spreading were inhibited in the peripheral immune system of tolDC-treated mice. Finally, magnetic resonance imaging analysis of hyperintense spots along the spinal cord was in line with the clinical score. Electroporation with mRNA is an efficient and versatile tool to generate myelin-presenting tolDC that are capable to stabilize the clinical score in EAE. These results pave the way for further research into mRNA-electroporated tolDC treatment as a patient-tailored therapy for MS.

Background: Consumer-oriented wearable devices (CWDs) such as smartphones and smartwatches have gained prominence for their ability to detect atrial fibrillation (AF) through proprietary algorithms using electrocardiography or photoplethysmography (PPG)–based digital recordings. Despite numerous individual validation studies, a direct comparison of interdevice performance is lacking. Objective: This study aimed to evaluate and compare the ability of CWDs to distinguish between sinus rhythm and AF. Methods: Patients exhibiting sinus rhythm or AF were enrolled through a cardiology outpatient clinic. The participants were instructed to perform heart rhythm measurements using a handheld 6-lead electrocardiogram (ECG) device (KardiaMobile 6L), a smartwatch-derived single-lead ECG (Apple Watch), and two PPG-based smartphone apps (FibriCheck and Preventicus) in a random sequence, with simultaneous 12-lead reference ECG as the gold standard. Results: A total of 122 participants were included in the study: median age 69 (IQR 61-77) years, 63.9% (n=78) men, 25% (n=30) with AF, 9.8% (n=12) without prior smartphone experience, and 73% (n=89) without experience in using a smartwatch. The sensitivity to detect AF was 100% for all devices. The specificity to detect sinus rhythm was 96.4% (95% CI 89.5%-98.8%) for KardiaMobile 6L, 97.8% (95% CI 91.6%‐99.5%) for Apple Watch, 98.9% (95% CI 92.5%‐99.8%) for FibriCheck, and 97.8% (95% CI 91.5%‐99.4%) for Preventicus (P=.50). Insufficient quality measurements were observed in 10.7% (95% CI 6.3%-17.5%) of cases for both KardiaMobile 6L and Apple Watch, 7.4% (95% CI 3.9%‐13.6%) for FibriCheck, and 14.8% (95% CI 9.5%‐22.2%) for Preventicus (P=.21). Participants preferred Apple Watch over the other devices to monitor their heart rhythm. Conclusions: In this study population, the discrimination between sinus rhythm and AF using CWDs based on ECG or PPG was highly accurate, with no significant variations in performance across the examined devices.

Background. Threshold analysis is used to determine the threshold value of an input parameter at which a health care strategy becomes cost-effective. Typically, it is performed in a deterministic manner, in which inputs are varied one at a time while the remaining inputs are each fixed at their mean value. This approach will result in incorrect threshold values if the cost-effectiveness model is nonlinear or if inputs are correlated. Objective. To propose a probabilistic method for performing threshold analysis, which accounts for the joint uncertainty in all input parameters and makes no assumption about the linearity of the cost-effectiveness model. Methods. Three methods are compared: 1) deterministic threshold analysis (DTA); 2) a 2-level Monte Carlo approach, which is considered the gold standard; and 3) a regression-based method using a generalized additive model (GAM), which identifies threshold values directly from a probabilistic sensitivity analysis sample. Results. We applied the 3 methods to estimate the minimum probability of hospitalization for typhoid fever at which 3 different vaccination strategies become cost-effective in Uganda. The threshold probability of hospitalization at which routine vaccination at 9 months with catchup campaign to 5 years becomes cost-effective is estimated to be 0.060 and 0.061 (95% confidence interval [CI], 0.058–0.064), respectively, for 2-level and GAM. According to DTA, routine vaccination at 9 months with catchup campaign to 5 years would never become cost-effective. The threshold probability at which routine vaccination at 9 months with catchup campaign to 15 years becomes cost-effective is estimated to be 0.092 (DTA), 0.074 (2-level), and 0.072 (95% CI, 0.069–0.075) (GAM). GAM is 430 times faster than the 2-level approach. Conclusions. When the cost-effectiveness model is nonlinear, GAM provides similar threshold values to the 2-level Monte Carlo approach and is computationally more efficient. DTA provides incorrect results and should not be used.

Repeated single-point measurements of thoracic bioimpedance at a single (low) frequency are strongly related to fluid changes during hemodialysis. Extension to semi-continuous measurements may provide longitudinal details in the time pattern of the bioimpedance signal, and multi-frequency measurements may add in-depth information on the distribution between intra- and extracellular fluid. This study aimed to investigate the feasibility of semi-continuous multi-frequency thoracic bioimpedance measurements by a wearable device in hemodialysis patients. Therefore, thoracic bioimpedance was recorded semi-continuously (i.e., every ten minutes) at nine frequencies (8–160 kHz) in 68 patients during two consecutive hemodialysis sessions, complemented by a single-point measurement at home in-between both sessions. On average, the resistance signals increased during both hemodialysis sessions and decreased during the interdialytic interval. The increase during dialysis was larger at 8 kHz (∆ 32.6 Ω during session 1 and ∆ 10 Ω during session 2), compared to 160 kHz (∆ 29.5 Ω during session 1 and ∆ 5.1 Ω during session 2). Whereas the resistance at 8 kHz showed a linear time pattern, the evolution of the resistance at 160 kHz was significantly different (p < 0.0001). Measuring bioimpedance semi-continuously and with a multi-frequency current is a major step forward in the understanding of fluid dynamics in hemodialysis patients. This study paves the road towards remote fluid monitoring.

Repeated single-point measurements of thoracic bioimpedance at single (low)-frequency are strongly related to fluid changes during hemodialysis. Extension to semi-continuous measurements may provide longitudinal details in the time pattern of the bioimpedance signal, and multifrequency measurements may add in-depth information on the distribution between intra- and extracellular fluid. This study aims to investigate the feasibility of semi-continuous multifrequency thoracic bioimpedance measurements by a wearable device in hemodialysis patients. Therefore, thoracic bioimpedance was recorded semi-continuously (i.e. every ten minutes) at nine frequencies (8 – 160 kHz) in 68 patients during two consecutive hemodialysis sessions, complemented by a single-point measurement at home in-between both sessions. On average, the resistance signals increased during both hemodialysis sessions and decreased during the interdialytic interval. The increase during dialysis was larger at 8 kHz (∆ 32.6 Ω during session 1 and ∆ 10 Ω during session 2) compared to 160 kHz (∆ 29.5 Ω during session 1 and ∆ 5.1 Ω during session 2). Whereas the resistance at 8 kHz showed a linear time pattern, the evolution of the resistance at 160 kHz was significantly different [p < 0.0001]. Measuring bioimpedance semi-continuously and with a multifrequency current is a major step forward in the understanding of fluid dynamics in hemodialysis patients. This study paves the road towards remote fluid monitoring.