Transcatheter Aortic Valve Implantation Wait-Time Management: Derivation and Validation of the Canadian TAVI Triage Tool (CAN3T).

BACKGROUND: Transcatheter aortic valve implantation (TAVI) has seen indication expansion and thus exponential growth in demand over the past decade. In many jurisdictions, the growing demand has outpaced capacity, increasing wait times and preprocedural adverse events. In this study, we derived prediction models that estimate the risk of adverse events on the waitlist and developed a triage tool to identify patients who should be prioritized for TAVI. METHODS AND RESULTS: We included adult patients in Ontario, Canada referred for TAVI and followed up until one of the following events first occurred: death, TAVI procedure, removal from waitlist, or end of the observation period. We used subdistribution hazards models to find significant predictors for each of the following outcomes: (1) all-cause death while on the waitlist; (2) all-cause hospitalization while on the waitlist; (3) receipt of urgent TAVI; and (4) a composite outcome. The median predicted risk at 12 weeks was chosen as a threshold for a maximum acceptable risk while on the waitlist and incorporated in the triage tool to recommend individualized wait times. Of 13 128 patients, 586 died while on the waitlist, and 4343 had at least 1 hospitalization. A total of 6854 TAVIs were completed, of which 1135 were urgent procedures. We were able to create parsimonious models for each outcome that included clinically relevant predictors. CONCLUSIONS: The Canadian TAVI Triage Tool (CAN3T) is a triage tool to assist clinicians in the prioritization of patients who should have timely access to TAVI. We anticipate that the CAN3T will be a valuable tool as it may improve equity in access to care, reduce preventable adverse events, and improve system efficiency.

Applications of artificial intelligence and bioinformatics methodologies in the analysis of ocular biofluid markers: a scoping review.

PURPOSE: This scoping review summarizes the applications of artificial intelligence (AI) and bioinformatics methodologies in analysis of ocular biofluid markers. The secondary objective was to explore supervised and unsupervised AI techniques and their predictive accuracies. We also evaluate the integration of bioinformatics with AI tools. METHODS: This scoping review was conducted across five electronic databases including EMBASE, Medline, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Web of Science from inception to July 14, 2021. Studies pertaining to biofluid marker analysis using AI or bioinformatics were included. RESULTS: A total of 10,262 articles were retrieved from all databases and 177 studies met the inclusion criteria. The most commonly studied ocular diseases were diabetic eye diseases, with 50 papers (28%), while glaucoma was explored in 25 studies (14%), age-related macular degeneration in 20 (11%), dry eye disease in 10 (6%), and uveitis in 9 (5%). Supervised learning was used in 91 papers (51%), unsupervised AI in 83 (46%), and bioinformatics in 85 (48%). Ninety-eight papers (55%) used more than one class of AI (e.g. > 1 of supervised, unsupervised, bioinformatics, or statistical techniques), while 79 (45%) used only one. Supervised learning techniques were often used to predict disease status or prognosis, and demonstrated strong accuracy. Unsupervised AI algorithms were used to bolster the accuracy of other algorithms, identify molecularly distinct subgroups, or cluster cases into distinct subgroups that are useful for prediction of the disease course. Finally, bioinformatic tools were used to translate complex biomarker profiles or findings into interpretable data. CONCLUSION: AI analysis of biofluid markers displayed diagnostic accuracy, provided insight into mechanisms of molecular etiologies, and had the ability to provide individualized targeted therapeutic treatment for patients. Given the progression of AI towards use in both research and the clinic, ophthalmologists should be broadly aware of the commonly used algorithms and their applications. Future research may be aimed at validating algorithms and integrating them in clinical practice.

Inclusion of non-medical interventions in model-based economic evaluations for tuberculosis: A scoping review.

BACKGROUND: The economic evaluation of health interventions is important in priority setting. Several guidance documents exist to support the conduct of economic evaluations, however, there is limited guidance for the evaluation of non-medical interventions. For tuberculosis (TB), where equity-deserving groups are disproportionately impacted, assessing interventions aimed at addressing social risk factors is necessary to effectively reduce TB burden. OBJECTIVE: This scoping review seeks to assess the existing literature on model-based economic evaluations of TB interventions to gauge the extent to which non-medical interventions have been evaluated in low-TB-incidence jurisdictions. As a secondary objective, this review aims to characterize key features of existing economic evaluations of medical and non-medical interventions. METHODS: A literature search was conducted in the grey literature and MEDLINE, Embase, EconLit, and PsychINFO databases to September 6, 2022 following the Arksey and O'Malley framework. Eligible articles were those that used decision-analytic modeling for economic evaluation of TB interventions in low-TB-incidence jurisdictions. RESULTS: This review identified 127 studies that met the inclusion criteria; 11 focused on prevention, 73 on detection, and 43 on treatment of TB. Only three studies (2%) evaluated non-medical interventions, including smoking reduction strategies, improving housing conditions, and providing food vouchers. All three non-medical intervention evaluations incorporated TB transmission and robust uncertainty analysis into the evaluation. The remainder of the studies evaluated direct medical interventions, eight of which were focused on specific implementation components (e.g., video observed therapy) which shared similar methodological challenges as the non-medical interventions. The majority of remaining evaluated medical interventions were focused on comparing various screening programs (e.g., immigrant screening program) and treatment regimens. CONCLUSIONS: This scoping review identified a gap in literature in the evaluation of non-medical TB interventions. However, the identified articles provided useful examples of how economic modeling can be used to explore non-traditional interventions using existing economic evaluation methods.

Cost-Utility of Rhegmatogenous Retinal Detachment Repair With Pars Plana Vitrectomy, Scleral Buckle, and Pneumatic Retinopexy: A Microsimulation Model.

PURPOSE: To assess the cost-effectiveness of primary noncomplex rhegmatogenous retinal detachment (RRD) repair, comparing 3 different strategies, pars plana vitrectomy (PPV), scleral buckle (SB), and pneumatic retinopexy (PnR) from the health care payer perspective over a lifetime. DESIGN: Model-based cost-utility analysis. METHODS: A simulated cohort of 100,000 adult patients (≥18 years old) requiring primary noncomplex RRD repair in theoretical surgical centers in the United States. Quality-adjusted life years (QALYs), lifetime costs (2022 United States dollars), and the incremental cost-effectiveness ratio (ICER) of the 3 interventions were projected over a lifetime horizon, with a cost-effectiveness threshold of ≤$50,000 per gained QALY. RESULTS: Based on inputted parameters, the primary anatomical success was highest for PPV (95.00%) compared to SB (91.76%) and PnR (63.41%). The QALYs associated with PPV, SB, and PnR were (11.87, SD 1.62), (11.84, SD 1.63), and (11.59, SD 1.72), respectively. The incurred lifetime costs of RRD repair and associated postoperative surgeries for PPV, SB, and PnR were $4445.72 (SD 655.75), $4518.04 (662.92), and $3978.45 (728.50), respectively. Parameter-level simulations suggested that PPV was most likely to be the most cost-effective therapy compared to SB and PnR beyond a threshold of $3000/QALY. The incremental cost-effectiveness ratio for PPV compared to PnR was $1693.54. SB was dominant in all scenarios. Threshold analyses indicated that the success rate of PnR would have to be 100% and/or the cost would have to be $2000 or less over lifetime for it to be more cost-effective than PPV. CONCLUSIONS: This study found PPV to be the most cost-effective primary procedure for RRD repair at a threshold of $50,000/QALY gained over a lifetime horizon from the health care payer perspective.

Prognostic Features of Preoperative OCT in Retinal Detachments: A Systematic Review and Meta-analysis.

TOPIC: To evaluate the prognostic association between preoperative features seen on OCT imaging and postoperative visual acuity (VA) outcomes in rhegmatogenous retinal detachments (RRDs). CLINICAL RELEVANCE: Currently, there is limited literature on the prognostic value of preoperative RRD OCT features. METHODS: A literature search was conducted on Ovid MEDLINE, Ovid Embase, and Cochrane CENTRAL from inception to September 15, 2022. A meta-analysis was performed using a random-effects model. Quality of studies and evidence were assessed using the Joanna Briggs Institute tools and the Grading of Recommendations, Assessment, Development and Evaluation framework, respectively. RESULTS: A total of 1671 eyes of 1670 patients from 29 observational studies were included. Of these, 89% of eyes had a macula-off RRD at presentation. The mean average duration of detachment was 15 ± 10 days. Most eyes (62%) underwent pars plana vitrectomy. Six preoperative OCT features were analyzed: height of retinal detachment (HRD) at the fovea, central macular thickness (CMT), disruption of the ellipsoid zone (EZ) and/or external limiting membrane (ELM), intraretinal cystic cavities (ICCs), outer retinal corrugations (ORCs), and macular detachment. A greater HRD was weakly associated with postoperative VA (Pearson correlation r = 0.35; 95% confidence interval [CI], 0.20-0.48; P < 0.01), and there was no change in this association throughout the postoperative follow-up period. The CMT was not associated with postoperative VA. Eyes with disruption of the EZ and/or ELM had a postoperative VA worse by 0.35 logarithm of the minimum angle of resolution (logMAR) (95% CI, 0.15-0.54; P < 0.01) or 3 Snellen lines. Eyes with ICCs had a postoperative VA worse by 0.14 logMAR (95% CI, 0.01-0.26; P < 0.01) or 2 Snellen lines. Eyes with ORCs did not have a significantly different postoperative VA than eyes without ORCs. Eyes with macular detachment had a postoperative VA worse by 0.15 logMAR (95% CI, -0.31 to 0.00; P = 0.02) or 2 Snellen lines. Overall, the quality of studies ranged from moderate to good (73%-100%). All associations had a low quality of evidence, with CMT being of very low quality. CONCLUSION: Despite the low quality of evidence, a greater HRD, disruption of the EZ and/or ELM, presence of ICCs, and macular detachment were associated with a poor postoperative VA. We propose a standardized nomenclature for consistency and accuracy in reporting preoperative RRD OCT features for future studies. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Current uses of artificial intelligence in the analysis of biofluid markers involved in corneal and ocular surface diseases: a systematic review.

Corneal and ocular surface diseases (OSDs) carry significant psychosocial and economic burden worldwide. We set out to review the literature on the application of artificial intelligence (AI) and bioinformatics for analysis of biofluid biomarkers in corneal and OSDs and evaluate their utility in clinical decision making. MEDLINE, EMBASE, Cochrane and Web of Science were systematically queried for articles using AI or bioinformatics methodology in corneal and OSDs and examining biofluids from inception to August 2021. In total, 10,264 articles were screened, and 23 articles consisting of 1058 individuals were included. Using various AI/bioinformatics tools, changes in certain tear film cytokines that are proinflammatory such as increased expression of apolipoprotein, haptoglobin, annexin 1, S100A8, S100A9, Glutathione S-transferase, and decreased expression of supportive tear film components such as lipocalin-1, prolactin inducible protein, lysozyme C, lactotransferrin, cystatin S, and mammaglobin-b, proline rich protein, were found to be correlated with pathogenesis and/or treatment outcomes of dry eye, keratoconus, meibomian gland dysfunction, and Sjögren's. Overall, most AI/bioinformatics tools were used to classify biofluids into diseases subgroups, distinguish between OSD, identify risk factors, or make predictions about treatment response, and/or prognosis. To conclude, AI models such as artificial neural networks, hierarchical clustering, random forest, etc., in conjunction with proteomic or metabolomic profiling using bioinformatics tools such as Gene Ontology or Kyoto Encylopedia of Genes and Genomes pathway analysis, were found to inform biomarker discovery, distinguish between OSDs, help define subgroups with OSDs and make predictions about treatment response in a clinical setting.

Cost-Effectiveness of Preoperative Topical Antibiotic Prophylaxis for Endophthalmitis Following Cataract Surgery.

PURPOSE: To determine the cost-effectiveness of preoperative topical antibiotic prophylaxis for the prevention of endophthalmitis following cataract surgery. DESIGN: Cost-effectiveness analysis using a decision-analytic microsimulation model. METHODS: Preoperative topical antibiotic prophylaxis vs no-prophylaxis costs and effects were projected over a life-time horizon for a simulated cohort of 500 000 adult patients (≥18 years old) requiring cataract surgery in theoretical surgical centers in the United States. Efficacy and cost (2021 US dollars) values were obtained from the literature and discounted at 3% per year. RESULTS: Based on inputted parameters, the mean incidence of endophthalmitis following cataract surgery for preoperative topical antibiotic prophylaxis vs no-prophylaxis was 0.034% (95% CI 0%-0.2%) and 0.042% (95% CI 0%-0.3%), respectively-an absolute risk reduction of 0.008%. The mean life-time costs for cataract surgery with prophylaxis and no-prophylaxis were $2486.67 (95% CI $2193.61-$2802.44) and $2409.03 (95% CI $2129.94-$2706.69), respectively. The quality-adjusted life-years (QALYs) associated with prophylaxis and no-prophylaxis were 10.33495 (95% CI 7.81629-12.38158) and 10.33498 (95% CI 7.81284-12.38316), respectively. Assuming a cost-effectiveness criterion of ≤$50 000 per QALY gained, the threshold analyses indicated that prophylaxis would be cost-effective if the incidence of endophthalmitis after cataract surgery was greater than 5.5% or if the price of the preoperative topical antibiotic prophylaxis was less than $0.75. CONCLUSIONS: General use of preoperative topical antibiotic prophylaxis is not cost-effective compared with no-prophylaxis for the prevention of endophthalmitis following cataract surgery. Preoperative topical antibiotic prophylaxis, however, would be cost-effective at a higher incidence of endophthalmitis and/or a substantially lower price for prophylaxis.

Emerging applications of bioinformatics and artificial intelligence in the analysis of biofluid markers involved in retinal occlusive diseases: a systematic review.

PURPOSE: To review the literature on the application of bioinformatics and artificial intelligence (AI) for analysis of biofluid biomarkers in retinal vein occlusion (RVO) and their potential utility in clinical decision-making. METHODS: We systematically searched MEDLINE, Embase, Cochrane, and Web of Science databases for articles reporting on AI or bioinformatics in RVO involving biofluids from inception to August 2021. Simple AI was categorized as logistics regressions of any type. Risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Tools. RESULTS: Among 10,264 studies screened, 14 eligible articles, encompassing 578 RVO patients, met the inclusion criteria. The use and reporting of AI and bioinformatics was heterogenous. Four articles performed proteomic analyses, two of which integrated AI tools such as discriminant analysis, probabilistic clustering, and string pathway analysis. A metabolomic study used AI tools for clustering, classification, and predictive modeling such as orthogonal partial least squares discriminant analysis. However, most studies used simple AI (n = 9). Vitreous humor sample levels of interleukin-6 (IL-6), vascular endothelial growth factor (VEGF), and aqueous humor levels of intercellular adhesion molecule-1 and IL-8 were implicated in the pathogenesis of branch RVO with macular edema. IL-6 and VEGF may predict visual acuity after intravitreal injections or vitrectomy, respectively. Metabolomics and Kyoto Encyclopedia of Genes and Genomes enrichment analysis identified the metabolic signature of central RVO to be related to lower aqueous humor concentration of carbohydrates and amino acids. Risk of bias was low or moderate for included studies. CONCLUSION: Bioinformatics has applications for analysis of proteomics and metabolomics present in biofluids in RVO with AI for clinical decision-making and advancing the future of RVO precision medicine. However, multiple limitations such as simple AI use, small sample volume, inconsistent feasibility of office-based sampling, lack of longitudinal follow-up, lack of sampling before and after RVO, and lack of healthy controls must be addressed in future studies.

The Application of Artificial Intelligence in the Analysis of Biomarkers for Diagnosis and Management of Uveitis and Uveal Melanoma: A Systematic Review.

Purpose: This study aims to identify the available literature describing the utilization of artificial intelligence (AI) as a clinical tool in uveal diseases. Methods: A comprehensive literature search was conducted in 5 electronic databases, finding studies relating to AI and uveal diseases. Results: After screening 10,258 studies,18 studies met the inclusion criteria. Uveal melanoma (44%) and uveitis (56%) were the two uveal diseases examined. Ten studies (56%) used complex AI, while 13 studies (72%) used regression methods. Lactate dehydrogenase (LDH), found in 50% of studies concerning uveal melanoma, was the only biomarker that overlapped in multiple studies. However, 94% of studies highlighted that the biomarkers of interest were significant. Conclusion: This study highlights the value of using complex and simple AI tools as a clinical tool in uveal diseases. Particularly, complex AI methods can be used to weigh the merit of significant biomarkers, such as LDH, in order to create staging tools and predict treatment outcomes.

Artificial Intelligence Analysis of Biofluid Markers in Age-Related Macular Degeneration: A Systematic Review.

This systematic review explores the use of artificial intelligence (AI) in the analysis of biofluid markers in age-related macular degeneration (AMD). We detail the accuracy and validity of AI in diagnostic and prognostic models and biofluid markers that provide insight into AMD pathogenesis and progression. This review was conducted in accordance with the Preferred Reporting Items for a Systematic Review and Meta-analysis guidelines. A comprehensive search was conducted across 5 electronic databases including Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, EMBASE, Medline, and Web of Science from inception to July 14, 2021. Studies pertaining to biofluid marker analysis using AI or bioinformatics in AMD were included. Identified studies were assessed for risk of bias and critically appraised using the Joanna Briggs Institute Critical Appraisal tools. A total of 10,264 articles were retrieved from all databases and 37 studies met the inclusion criteria, including 15 cross-sectional studies, 15 prospective cohort studies, five retrospective cohort studies, one randomized controlled trial, and one case-control study. The majority of studies had a general focus on AMD (58%), while neovascular AMD (nAMD) was the focus in 11 studies (30%), and geographic atrophy (GA) was highlighted by three studies. Fifteen studies examined disease characteristics, 15 studied risk factors, and seven guided treatment decisions. Altered lipid metabolism (HDL-cholesterol, total serum triglycerides), inflammation (c-reactive protein), oxidative stress, and protein digestion were implicated in AMD development and progression. AI tools were able to both accurately differentiate controls and AMD patients with accuracies as high as 87% and predict responsiveness to anti-VEGF therapy in nAMD patients. Use of AI models such as discriminant analysis could inform prognostic and diagnostic decision-making in a clinical setting. The identified pathways provide opportunity for future studies of AMD development and could be valuable in the advancement of novel treatments.

Protocol for a systematic review and meta-analysis of the diagnostic accuracy of artificial intelligence for grading of ophthalmology imaging modalities.

BACKGROUND: With the rise of artificial intelligence (AI) in ophthalmology, the need to define its diagnostic accuracy is increasingly important. The review aims to elucidate the diagnostic accuracy of AI algorithms in screening for all ophthalmic conditions in patient care settings that involve digital imaging modalities, using the reference standard of human graders. METHODS: This is a systematic review and meta-analysis. A literature search will be conducted on Ovid MEDLINE, Ovid EMBASE, and Wiley Cochrane CENTRAL from January 1, 2000, to December 20, 2021. Studies will be selected via screening the titles and abstracts, followed by full-text screening. Articles that compare the results of AI-graded ophthalmic images with results from human graders as a reference standard will be included; articles that do not will be excluded. The systematic review software DistillerSR will be used to automate part of the screening process as an adjunct to human reviewers. After the full-text screening, data will be extracted from each study via the categories of study characteristics, patient information, AI methods, intervention, and outcomes. Risk of bias will be scored using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) by two trained independent reviewers. Disagreements at any step will be addressed by a third adjudicator. The study results will include summary receiver operating characteristic (sROC) curve plots as well as pooled sensitivity and specificity of artificial intelligence for detection of any ophthalmic conditions based on imaging modalities compared to the reference standard. Statistics will be calculated in the R statistical software. DISCUSSION: This study will provide novel insights into the diagnostic accuracy of AI in new domains of ophthalmology that have not been previously studied. The protocol also outlines the use of an AI-based software to assist in article screening, which may serve as a reference for improving the efficiency and accuracy of future large systematic reviews. TRIAL REGISTRATION: PROSPERO, CRD42021274441.

An Electronic Patient-Reported Outcomes Tool for Older Adults With Complex Chronic Conditions: Cost-Utility Analysis.

BACKGROUND: eHealth technologies for self-management can improve quality of life, but little is known about whether the benefits gained outweigh their costs. The electronic patient-reported outcome (ePRO) mobile app and portal system supports patients with multiple chronic conditions to collaborate with primary health care providers to set and monitor health-related goals. OBJECTIVE: This study aims to estimate the cost of ePRO and the cost utility of the ePRO intervention compared with usual care provided to patients with multiple chronic conditions and complex needs living in the community, from the perspective of the publicly funded health care payer in Ontario, Canada. METHODS: We developed a decision tree model to estimate the incremental cost per quality-adjusted life year (QALY) gained for the ePRO tool versus usual care over a time horizon of 15 months. Resource utilization and effectiveness of the ePRO tool were drawn from a randomized clinical trial with 6 family health teams involving 45 participants. Unit costs associated with health care utilization (adjusted to 2020 Canadian dollars) were drawn from literature and publicly available sources. A series of sensitivity analyses were conducted to assess the robustness of the findings. RESULTS: The total cost of the ePRO tool was CAD $79,467 (~US $ 63,581; CAD $1733 [~US $1386] per person). Compared with standard care, the ePRO intervention was associated with higher costs (CAD $1710 [~US $1368]) and fewer QALYs (-0.03). The findings were consistent with the clinical evidence, suggesting no statistical difference in health-related quality of life between ePRO and usual care groups. However, the tool would be considered a cost-effective option if it could improve by at least 0.03 QALYs. The probability that the ePRO is cost-effective was 17.3% at a willingness-to-pay (WTP) threshold of CAD $50,000 (~US $40,000)/QALY. CONCLUSIONS: The ePRO tool is not a cost-effective technology at the commonly used WTP value of CAD $50,000 (~US $40,000)/QALY, but long-term and the societal impacts of ePRO were not included in this analysis. Further research is needed to better understand its impact on long-term outcomes and in real-world settings. The present findings add to the growing evidence about eHealth interventions' capacity to respond to complex aging populations within finite-resourced health systems. TRIAL REGISTRATION: ClinicalTrials.gov NCT02917954; https://clinicaltrials.gov/ct2/show/NCT02917954.

Drivers and outcomes of variation in surgical versus transcatheter aortic valve replacement in Ontario, Canada: a population-based study.

OBJECTIVES: To understand the patient and hospital level drivers of the variation in surgical versus trascatheter aortic valve replacement (SAVR vs TAVR) for patients with aortic stenosis (AS) and to explore whether this variation translates into differences in clinical outcomes. BACKGROUND: Adoption of TAVR has grown exponentially worldwide. Notwithstanding, a wide variation in TAVR rates has been seen within and between countries and in some jurisdictions AS is still primarily being managed by SAVR. METHODS: We conducted a population-based retrospective cohort study in Ontario, Canada, including individuals who received TAVR or SAVR between 2016 and 2020. We developed iterative hierarchical logistic regression models for the likelihood of receiving TAVR instead of SAVR examining sequentially patient characteristics, hospital factors and year of procedure, calculating the median ORs and variance partition coefficients for each. Using Cox proportional hazards models, we examined the relationship between TAVR/SAVR ratio on all-cause mortality and readmissions. RESULTS: Annual procedures rates per million population increased from 171 to 201, mainly driven by the expansion of TAVR. TAVR/SAVR ratios differed substantially between hospitals, from 0.21 to 3.27. Neither patient nor hospital factors explained the between-hospital variation in AS treatment. The TAVR/SAVR ratio was significantly associated with clinical outcomes with high ratio hospitals having lower mortality and rehospitalisations. CONCLUSIONS: Despite the expansion of TAVR, dramatic variation exists that is not explained by patient or hospital factors. This variation was associated with differences in clinical outcomes, suggesting that further work is needed in understanding and addressing inequity of access.

Clinical manifestations and health outcomes associated with Zika virus infections in adults: A systematic review.

BACKGROUND: Zika virus (ZIKV) has generated global interest in the last five years mostly due to its resurgence in the Americas between 2015 and 2016. It was previously thought to be a self-limiting infection causing febrile illness in less than one quarter of those infected. However, a rise in birth defects amongst children born to infected pregnant women, as well as increases in neurological manifestations in adults has been demonstrated. We systemically reviewed the literature to understand clinical manifestations and health outcomes in adults globally. METHODS: This review was registered prospectively with PROPSERO (CRD 42018096558). We systematically searched for studies in six databases from inception to the end of September 2020. There were no language restrictions. Critical appraisal was completed using the Joanna Briggs Institute Critical Appraisal Tools. FINDINGS: We identified 73 studies globally that reported clinical outcomes in ZIKV-infected adults, of which 55 studies were from the Americas. For further analysis, we considered studies that met 70% of critical appraisal criteria and described subjects with confirmed ZIKV. The most common symptoms included: exanthema (5,456/6,129; 89%), arthralgia (3,809/6,093; 63%), fever (3,787/6,124; 62%), conjunctivitis (2,738/3,283; 45%), myalgia (2,498/5,192; 48%), headache (2,165/4,722; 46%), and diarrhea (337/2,622; 13%). 36/14,335 (0.3%) of infected cases developed neurologic sequelae, of which 75% were Guillain-Barré Syndrome (GBS). Several subjects reported recovery from peak of neurological complications, though some endured chronic disability. Mortality was rare (0.1%) and hospitalization (11%) was often associated with co-morbidities or GBS. CONCLUSIONS: The ZIKV literature in adults was predominantly from the Americas. The most common systemic symptoms were exanthema, fever, arthralgia, and conjunctivitis; GBS was the most prevalent neurological complication. Future ZIKV studies are warranted with standardization of testing and case definitions, consistent co-infection testing, reporting of laboratory abnormalities, separation of adult and pediatric outcomes, and assessing for causation between ZIKV and neurological sequelae.

Health-Related Quality of Life in Neurological Disorders Most Commonly Associated With Zika-Virus Infection: A Systematic Review.

OBJECTIVES: In this systematic review, we synthesize the current evidence on health-related quality of life (HRQoL) for the two of the most relevant outcomes of Zika virus infection in humans, microcephaly and Guillain-Barré Syndrome (GBS). METHODS: We searched the following databases: MEDLINE, Embase, CINAHL, LILACS, WHO's ICTRP clinical trials registries database and PROSPERO. Search terms included quality of life, microcephaly, and Guillain-Barré Syndrome. We included primary studies where HRQoL was quantitatively assessed for microcephaly and GBS using validated instruments. We used the Joanna Briggs Institute Critical Appraisal Tools to assess the risk of bias of individual studies. RESULTS: From a total of 1,657 abstracts screened and 66 full texts reviewed, 21 studies met the eligibility criteria; one study for microcephaly and 20 for GBS. Adjusted disutilities for microcephaly compared to a normative childhood utility ranged from -0.745 to -0.820. For GBS, time traded-off the expected lifetime ranged from 16 days to 3 years. HRQoL follows the clinical course of GBS, with lower scores in the first months, recovery within the first year post onset, and stabilization after one year. CONCLUSIONS: Included studies reported a wide range of HRQoL for GBS, due in part to a high level of heterogeneity in methods, inclusion criteria, follow-up and reporting of results. Opportunities exist for primary studies assessing the longitudinal HRQoL over the entire course of the diseases to inform clinical practice, economic evaluations and health policy.