Commentary: Morphoproteomics and Data Mining of the Medical Literature Define the Pathobiology of COVID-19 Pneumonitis in Humans and Provide Adjuvant Therapeutic Options.

Due to the resurgence of COVID-19, understanding the biology of SARS-CoV-2 is an opportunity to develop adjuvant therapies that could target its pathobiology and lessen the severity of the COVID-19 infection so that our patients could survive. This commentary serves to accomplish this by using published morphoproteomic findings with data mining of the medical literature to define the pathobiology of COVID-19 pneumonitis and provide combinatorial and relatively non-toxic adjuvant therapies that have been successful against this viral infection.

Inherited Proteoglycan Biosynthesis Defects-Current Laboratory Tools and Bikunin as a Promising Blood Biomarker.

Proteoglycans consist of proteins linked to sulfated glycosaminoglycan chains. They constitute a family of macromolecules mainly involved in the architecture of organs and tissues as major components of extracellular matrices. Some proteoglycans also act as signaling molecules involved in inflammatory response as well as cell proliferation, adhesion, and differentiation. Inborn errors of proteoglycan metabolism are a group of orphan diseases with severe and irreversible skeletal abnormalities associated with multiorgan impairments. Identifying the gene variants that cause these pathologies proves to be difficult because of unspecific clinical symptoms, hardly accessible functional laboratory tests, and a lack of convenient blood biomarkers. In this review, we summarize the molecular pathways of proteoglycan biosynthesis, the associated inherited syndromes, and the related biochemical screening techniques, and we focus especially on a circulating proteoglycan called bikunin and on its potential as a new biomarker of these diseases.

Autoantibody Discovery, Assay Development and Adoption: Death Valley, the Sea of Survival and Beyond.

Dating to the discovery of the Lupus Erythematosus (LE) cell in 1948, there has been a dramatic growth in the discovery of unique autoantibodies and their cognate targets, all of which has led to the availability and use of autoantibody testing for a broad spectrum of autoimmune diseases. Most studies of the sensitivity, specificity, commutability, and harmonization of autoantibody testing have focused on widely available, commercially developed and agency-certified autoantibody kits. However, this is only a small part of the spectrum of autoantibody tests that are provided through laboratories world-wide. This manuscript will review the wider spectrum of testing by exploring the innovation pathway that begins with autoantibody discovery followed by assessment of clinical relevance, accuracy, validation, and then consideration of regulatory requirements as an approved diagnostic test. Some tests are offered as "Research Use Only (RUO)", some as "Laboratory Developed Tests (LDT)", some enter Health Technology Assessment (HTA) pathways, while others are relegated to a "death valley" of autoantibody discovery and become "orphan" autoantibodies. Those that achieve regulatory approval are further threatened by the business world's "Darwinian Sea of Survival". As one example of the trappings of autoantibody progression or failure, it is reported that more than 200 different autoantibodies have been described in systemic lupus erythematosus (SLE), a small handful (~10%) of these have achieved regulatory approval and are widely available as commercial diagnostic kits, while a few others may be available as RUO or LDT assays. However, the vast majority (90%) are orphaned and languish in an autoantibody 'death valley'. This review proposes that it is important to keep an inventory of these "orphan autoantibodies" in 'death valley' because, with the increasing availability of multi-analyte arrays and artificial intelligence (MAAI), some can be rescued to achieve a useful role in clinical diagnostic especially in light of patient stratification and precision medicine.

Temporal trends and yield of clinical diagnostic genetic testing in adult neurology.

While genetics evaluation is increasingly utilized in adult neurology patients, its usage and efficacy are not well characterized. Here, we report our experience with 1461 consecutive patients evaluated in an adult neurogenetics clinic at a large academic medical center between January 2015 and March 2020. Of the 1461 patients evaluated, 1215 patients were referred for the purposes of identifying a genetic diagnosis for an undiagnosed condition, 90.5% of whom underwent genetic testing. The modalities of genetic testing utilized varied across referral diagnostic categories, including a range of utilization of whole exome sequencing (WES) as an initial test in 13.9% of neuromuscular patients to 52.9% in white matter disorder patients. The usage of WES increased over time, from 7.7% of initial testing in 2015 to a peak of 27.3% in 2019. Overall, genetic testing yielded a causal genetic diagnosis in 30.7% of patients. This yield was higher in certain referring diagnosis categories, such as neuromuscular (39.0%) and epilepsy (29.8%). Our study demonstrates that evaluation at an adult neurogenetics referral center can yield diagnoses in a substantial fraction of patients. Additional research will be needed to determine optimal genetic testing strategies and cost effectiveness of adult neurogenetics evaluation.

Anti-C1q Autoantibodies: Standard Quantification and Innovative ELISA.

Autoantibodies against complement C1q (anti-C1q) are an excellent marker for active nephritis in SLE patients. Here, we describe a typical protocol for the quantification of anti-C1q using immobilized C1q (important for the presentation of relevant cryptic epitopes) and a high salt buffer for the incubation steps (to prevent immune-complex binding to intact C1q). More recently, a linear epitope on the C1q A chain, that is targeted by anti-C1q, has been described (A08). The assay using this peptide seems to be more specific and more sensitive for the detection of active nephritis in SLE patients than the conventional anti-C1q assay, but further studies are required to establish the role of anti-A08 of C1q in the clinical routine.

Changes in Test Volumes During Coronavirus Disease 2019 (COVID-19): A Laboratory Stewardship Opportunity.

CONTEXT.­: Coronavirus disease 2019 (COVID-19) changed the dynamics of health care delivery, shifting patient priorities and deferring care perceived as less urgent. Delayed or eliminated care may place patients at risk for adverse outcomes. OBJECTIVE.­: To identify opportunities for laboratory test stewardship to close potential gaps in care created by the COVID-19 pandemic. DESIGN.­: The study was a retrospective time series design examining laboratory services received before and during the COVID-19 pandemic at a large metropolitan health system serving women and children. RESULTS.­: Laboratory test volumes displayed 3 distinct patterns: (1) a decrease during state lockdown, followed by near-complete or complete recovery; (2) no change; and (3) a persistent decrease. Tests that diagnose or monitor chronic illness recovered only partially. For example, hemoglobin A1c initially declined 80% (from 2232 for April 2019 to 452 for April 2020), and there was a sustained 16% drop (28-day daily average 117 at August 30, 2019, to 98 at August 30, 2020) 4 months later. Blood lead dropped 39% (from 2158 for April 2019 to 1314 for April 2020) and remained 23% lower after 4 months. CONCLUSIONS.­: The pandemic has taken a toll on patients, practitioners, and health systems. Laboratory professionals have access to data that can provide insight into clinical practice and identify pandemic-related gaps in care. During the pandemic, the biggest patient threat is underuse, particularly among tests to manage chronic diseases and for traditionally underserved communities and people of color. A laboratory stewardship program, focused on peri-pandemic care, positions pathologists and other laboratory professionals as health care leaders with a commitment to appropriate, equitable, and efficient care.

Time series analysis of the demand for COVID-19 related chest imaging during the first wave of the SARS-CoV-2 pandemic: An explorative study.

OBJECTIVES: The aim of this study was to investigate possible patterns of demand for chest imaging during the first wave of the SARS-CoV-2 pandemic and derive a decision aid for the allocation of resources in future pandemic challenges. MATERIALS AND METHODS: Time data of requests for patients with suspected or confirmed coronavirus disease 2019 (COVID-19) lung disease were analyzed between February 27th and May 27th 2020. A multinomial logistic regression model was used to evaluate differences in the number of requests between 3 time intervals (I1: 6am - 2pm, I2: 2pm - 10pm, I3: 10pm - 6am). A cosinor model was applied to investigate the demand per hour. Requests per day were compared to the number of regional COVID-19 cases. RESULTS: 551 COVID-19 related chest imagings (32.8% outpatients, 67.2% in-patients) of 243 patients were conducted (33.3% female, 66.7% male, mean age 60 ± 17 years). Most exams for outpatients were required during I2 (I1 vs. I2: odds ratio (OR) = 0.73, 95% confidence interval (CI) 0.62-0.86, p = 0.01; I2 vs. I3: OR = 1.24, 95% CI 1.04-1.48, p = 0.03) with an acrophase at 7:29 pm. Requests for in-patients decreased from I1 to I3 (I1 vs. I2: OR = 1.24, 95% CI 1.09-1.41, p = 0.01; I2 vs. I3: OR = 1.16, 95% CI 1.05-1.28, p = 0.01) with an acrophase at 12:51 pm. The number of requests per day for outpatients developed similarly to regional cases while demand for in-patients increased later and persisted longer. CONCLUSIONS: The demand for COVID-19 related chest imaging displayed distinct distribution patterns depending on the sector of patient care and point of time during the SARS-CoV-2 pandemic. These patterns should be considered in the allocation of resources in future pandemic challenges with similar disease characteristics.

Trends in Low-Value Health Service Use and Spending in the US Medicare Fee-for-Service Program, 2014-2018.

Importance: Low-value care, defined as care offering no net benefit in specific clinical scenarios, is associated with harmful outcomes in patients and wasteful spending. Despite a national education campaign and increasing attention on reducing health care waste, recent trends in low-value care delivery remain unknown. Objective: To assess national trends in low-value care use and spending. Design, Setting, and Participants: In this cross-sectional study, analyses of low-value care use and spending from 2014 to 2018 were conducted using 100% Medicare fee-for-service enrollment and claims data. Included individuals were aged 65 years or older and continuously enrolled in Medicare parts A, B, and D during each measurement year and the previous year. Data were analyzed from September 2019 through December 2020. Exposure: Being enrolled in fee-for-service Medicare for a period of time, in years. Main Outcomes and Measures: The Milliman MedInsight Health Waste Calculator was used to assess 32 claims-based measures of low-value care associated with Choosing Wisely recommendations and other professional guidelines. The calculator designates services as wasteful, likely wasteful, or not wasteful based on an absence of indication of appropriate use in the claims history; calculator-designated wasteful services were defined as low-value care. Spending was calculated as claim-line level (ie, spending on the low-value service) and claim level (ie, spending on the low-value service plus associated services), adjusting for inflation. Results: Among 21 045 759 individuals with fee-for-service Medicare (mean [SD] age, 77.4 [7.9] years; 12 515 915 [59.5%] women), the percentage receiving any of 32 low-value services decreased from 36.3% (95% CI, 36.3%-36.4%) to 33.6% (95% CI, 33.6%-33.6%) from 2014 to 2018. Uses of low-value services per 1000 individuals decreased from 677.8 (95% CI, 676.2-679.5) to 632.7 (95% CI, 632.6-632.8) from 2014 to 2018. Three services comprised approximately two-thirds of uses among 32 low-value services per 1000 individuals: preoperative laboratory testing decreased from 213.8 (95% CI, 213.4-214.2) to 166.2 (95% CI, 166.2-166.2), while opioids for back pain increased from 154.4 (95% CI, 153.6-155.2) to 182.1 (95% CI, 182.1-182.1) and antibiotics for upper respiratory infections increased from 75.0 (95% CI, 75.0-75.1) to 82 (95% CI, 82.0-82.0). Spending per 1000 individuals on low-value care also decreased, from $52 765.5 (95% CI, $51 952.3-$53 578.6) to $46 921.7 (95% CI, $46 593.7-$47 249.7) at the claim-line level and from $160 070.4 (95% CI, $158 999.8-$161 141.0) to $144 741.1 (95% CI, $144 287.5-$145 194.7) at the claim level. Conclusions and Relevance: This cross-sectional study found that among individuals with fee-for-service Medicare receiving any of 32 measured services, low-value care use and spending decreased marginally from 2014 to 2018, despite a national education campaign in collaboration with clinician specialty societies and increased attention on low-value care. While most use of low-value care came from 3 services, 1 of these was opioid prescriptions, which increased over time despite the harms associated with their use. These findings may represent several opportunities to prevent patient harm and lower spending.

Association of Preadmission Metformin Use and Prognosis in Patients With Sepsis and Diabetes Mellitus: A Systematic Review and Meta-Analysis.

Background and Aim: A growing body of evidence suggests that preadmission metformin use could decrease the mortality of septic patients with diabetes mellitus (DM); however, the findings remain controversial. Therefore, this meta-analysis was conducted on available studies to confirm the relationship between preadmission metformin use and mortality in patients with sepsis and DM. Methods: A comprehensive search of the PubMed, Embase, and Cochrane Library databases was performed for studies published before August 8, 2021. Observational studies assessing the correlation between metformin use and mortality in patients with sepsis and DM were considered eligible studies. We used the Newcastle-Ottawa Scale (NOS) to assess the outcome quality of each included article. Furthermore, the odds ratios (ORs) and 95% confidence intervals (CIs) were analyzed using the inverse variance method with random effects modeling. Results: Eleven articles including 8195 patients were analyzed in this meta-analysis. All the included articles were scored as low risk of bias. Our results showed that preadmission metformin use had a lower mortality rate (OR, 0.74; 95% CIs, 0.62-0.88, P < 0.01) in patients with sepsis and DM. Surprisingly, there was no statistically significant difference in the levels of serum creatinine (weighted mean difference (WMD), 0.36; 95% CIs, -0.03-0.75; P = 0.84) and lactic acid (WMD, -0.16; 95% CIs, -0.49-0.18; P = 0.07) between preadmission metformin use and non-metformin use. Conclusions: This study is the most comprehensive meta-analysis at present, which shows that preadmission metformin use may reduce mortality and not increase the levels of serum creatinine and lactic acid in adult patients with sepsis and DM. Therefore, these data suggest that the potential efficacy of metformin could be assessed in future clinical studies. Systematic Review Registration: https://inplasy.com/?s=INPLASY2021100113, identifier INPLASY2021100113.

Quantifying Plasmodium falciparum infections clustering within households to inform household-based intervention strategies for malaria control programs: An observational study and meta-analysis from 41 malaria-endemic countries.

BACKGROUND: Reactive malaria strategies are predicated on the assumption that individuals infected with malaria are clustered within households or neighbourhoods. Despite the widespread programmatic implementation of reactive strategies, little empirical evidence exists as to whether such strategies are appropriate and, if so, how they should be most effectively implemented. METHODS AND FINDINGS: We collated 2 different datasets to assess clustering of malaria infections within households: (i) demographic health survey (DHS) data, integrating household information and patent malaria infection, recent fever, and recent treatment status in children; and (ii) data from cross-sectional and reactive detection studies containing information on the household and malaria infection status (patent and subpatent) of all-aged individuals. Both datasets were used to assess the odds of infections clustering within index households, where index households were defined based on whether they contained infections detectable through one of 3 programmatic strategies: (a) Reactive Case Detection (RACD) classifed by confirmed clinical cases, (b) Mass Screen and Treat (MSAT) classifed by febrile, symptomatic infections, and (c) Mass Test and Treat (MTAT) classifed by infections detectable using routine diagnostics. Data included 59,050 infections in 208,140 children under 7 years old (median age = 2 years, minimum = 2, maximum = 7) by microscopy/rapid diagnostic test (RDT) from 57 DHSs conducted between November 2006 and December 2018 from 23 African countries. Data representing 11,349 infections across all ages (median age = 22 years, minimum = 0.5, maximum = 100) detected by molecular tools in 132,590 individuals in 43 studies published between April 2006 and May 2019 in 20 African, American, Asian, and Middle Eastern countries were obtained from the published literature. Extensive clustering was observed-overall, there was a 20.40 greater (95% credible interval [CrI] 0.35-20.45; P < 0.001) odds of patent infections (according to the DHS data) and 5.13 greater odds (95% CI 3.85-6.84; P < 0.001) of molecularly detected infections (from the published literature) detected within households in which a programmatically detectable infection resides. The strongest degree of clustering identified by polymerase chain reaction (PCR)/ loop mediated isothermal amplification (LAMP) was observed using the MTAT strategy (odds ratio [OR] = 6.79, 95% CI 4.42-10.43) but was not significantly different when compared to MSAT (OR = 5.2, 95% CI 3.22-8.37; P-difference = 0.883) and RACD (OR = 4.08, 95% CI 2.55-6.53; P-difference = 0.29). Across both datasets, clustering became more prominent when transmission was low. However, limitations to our analysis include not accounting for any malaria control interventions in place, malaria seasonality, or the likely heterogeneity of transmission within study sites. Clustering may thus have been underestimated. CONCLUSIONS: In areas where malaria transmission is peri-domestic, there are programmatic options for identifying households where residual infections are likely to be found. Combining these detection strategies with presumptively treating residents of index households over a sustained time period could contribute to malaria elimination efforts.

[Digital morphology analyzers in hematology: a French survey]. / État des lieux des pratiques d'utilisation du microscope automatisé en hématologie en France.

Digital morphology hematology analyzers are becoming more prevalent in laboratories Aims: investigate practices and assess the benefits and limits of digital automated microscopy in hematology. METHODS: questionnaire sent by e-mail in 2018 to French public and private laboratories. RESULTS: out of 118 responses (56 private, 62 public), 117 participants had a CellaVision® microscope, 1 had a West Medica®. Practices were sometimes different, especially in the choice of smears to be digitized or for quality controls (16.1% had internal quality controls, 48.3% external quality controls); 62.1% never used the red blood cell (RBC) characterization tool; the number of cells counted varied from 100 to 400. The study reported a high rate of agreement for these benefits: traceability (95.7%), staff training (94.1%), eye strain (91.4%), risk of error (87.2%), time saving (83.6%). Among the disadvantages, apart from the inadequate search for platelets clumps (93.2%), the agreement rates were often lower: adaptation to digital images (61.2%), difficult assessment of atypical morphologies (49.6%) or RBC morphology (49.6%). CONCLUSION: despite well-established benefits, standardization of practices and technical improvement are still needed.

Diagnostic utility of genetic testing in patients undergoing renal biopsy.

High-throughput DNA testing is becoming established as a standard diagnostic test in the renal clinic. Previously published studies on cohorts of patients with unexplained chronic kidney disease of a suspected genetic aetiology have suggested a diagnostic yield for genomic sequencing of up to 18%. Here we determine the yield of targeted gene panel in a clinically unscreened cohort of patients referred for percutaneous native renal biopsy. Patients who underwent renal biopsy for investigation of chronic kidney disease were sequenced using a genomic sequencing panel covering 227 genes in which variation is known to be associated with monogenic chronic kidney disease (CKD). Candidate disease-causing variants were assessed for pathogenicity using guidelines from the American College for Medical Genetics and Genomics. Fifty CKD patients were recruited and sequenced. A molecular diagnosis was obtained for two patients (4%). A molecular diagnosis is possible using genomic testing in ∼4% of clinically unscreened patients undergoing renal biopsy. Genetic screening may be useful for diagnosis in a subset of CKD patients but is most valuable when applied to patients with suspected heritable forms of kidney disease.

The COVID-19 Diagnostic Dilemma: a Clinician's Perspective.

In this commentary, we provide a broad overview of how the rapidly evolving coronavirus disease 2019 (COVID-19) diagnostic landscape has impacted clinical care during the COVID-19 pandemic. We review aspects of both molecular and serologic testing and discuss the logistical challenges faced with each. We also highlight the progress that has been made in the development and implementation of these assays as well as the need for ongoing improvement in diagnostic testing capabilities.

Trends and Innovations in Biosensors for COVID-19 Mass Testing.

Fast and widespread diagnosis is crucial to fighting against the outbreak of COVID-19. This work surveys the landscape of available and emerging biosensor technologies for COVID-19 testing. Molecular diagnostic assays based on quantitative reverse transcription polymerase chain reaction are used in most clinical laboratories. However, the COVID-19 pandemic has overwhelmed testing capacity and motivated the development of fast point-of-care tests and the adoption of isothermal DNA amplification. Antigenic and serological rapid tests based on lateral-flow immunoassays suffer from low sensitivity. Advanced digital systems enhance performance at the expense of speed and the need for large equipment. Emerging technologies, including CRISPR gene-editing tools, benefit from high sensitivity and specificity of molecular diagnostics and the easy use of lateral-flow assays. DNA sequencing and sample pooling strategies are highlighted to bring out the full capacity of the available biosensor technologies and accelerate mass testing.

Proteomic applications in pathology and laboratory medicine: Present state and future prospects.

Clinical mass spectrometry applications have traditionally focused on small molecules, particularly in the areas of therapeutic drug monitoring, toxicology, and measurement of endogenous and exogenous steroids. More recently, the use of matrix assisted laser desorption/ionization time of flight mass spectrometry for the identification of microbial pathogens has been widely implemented. Following this evolution, there has been an expanding role for the measurement of peptides and proteins in pathology and laboratory medicine. This review explores the current state of protein measurement by clinical mass spectrometry and the analytical strategies employed, as well as emerging applications in clinical chemistry, clinical microbiology and anatomical pathology.