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Saeed, M.

Publications and source records attributed to Saeed, M..

36 records · Page 2Linked to original sources

In-silico Screening of Origanum vulgare Phytocompounds as Potential Drug Agents Against Vp35 Protein of the Ebola Virus

The leading cause of the Ebola virus outbreak during 2013-16 in Western Africa was a lack of targeted anti- viral drug choices, a fast rate of mutations and the unavailability of many of the structural proteins and annotations within its genome. The surroundings of the Ebola River in DR-Congo fail to get rid of this endemic, the reason behind this was believed to be its origin from non-human primates, which made its risk assessment and tracing difficult. The Vp35 is a multifunctional protein with innate immune antagonistic properties and is considered one of the most suitable drug targets within this virus. The main motive of this study is to discover a potential anti-viral drug against the Ebola virus by targeting the aforementioned protein with different phytocompounds of oregano that have the lowest binding energies and qualifies over different simulation parameters, so firstly, molecular docking was performed on its 28 compounds using PyRx to get the best complexes with minimum binding energies e.g., -8.9Kcal/mol. Ligands with the best docking scores were gone through Lipinskis rule of five for drug likeliness potential. For the drug affirmation, molecular dynamic simulation was also performed with the best two docked complexes using NAMD/VMD to find out their conformational stability through RMSD, RMSF, Rg, SASA and H-bond analyses. Current computer-generated prediction suggested that Ursolic acid and Oleanolic acid possess potential inhibitory effects against virus replication. Furthermore, paradigm shifts of usage of natural and herbal products for treating infectious diseases are being encouraged here, However, further wet-lab experiments and clinical trials are still needed to determine the robustness of these virtually tested phytocompounds against the Vp35 protein of the Ebola virus.

bioinformatics↗

Role of spike in the pathogenic and antigenic behavior of SARS-CoV-2 BA.1Omicron

The recently identified, globally predominant SARS-CoV-2 Omicron variant (BA.1) is highly transmissible, even in fully vaccinated individuals, and causes attenuated disease compared with other major viral variants recognized to date1-7. The Omicron spike (S) protein, with an unusually large number of mutations, is considered the major driver of these phenotypes3,8. We generated chimeric recombinant SARS-CoV-2 encoding the S gene of Omicron in the backbone of an ancestral SARS-CoV-2 isolate and compared this virus with the naturally circulating Omicron variant. The Omicron S-bearing virus robustly escapes vaccine-induced humoral immunity, mainly due to mutations in the receptor-binding motif (RBM), yet unlike naturally occurring Omicron, efficiently replicates in cell lines and primary-like distal lung cells. In K18-hACE2 mice, while Omicron causes mild, non-fatal infection, the Omicron S-carrying virus inflicts severe disease with a mortality rate of 80%. This indicates that while the vaccine escape of Omicron is defined by mutations in S, major determinants of viral pathogenicity reside outside of S.

microbiology↗

High resolution photocatalytic mapping of SARS-CoV-2 Spike protein-host cell membrane interactions

Identifying protein environments at the virus-host cell interface can improve our understanding of viral entry and pathogenesis. SARS-CoV-2, the virus behind the ongoing COVID-19 pandemic, uses the cell surface ACE2 protein as a major receptor, but the contribution of other cellular proteins in the entry process is unknown. To probe the microenvironment of SARS-CoV-2 Spike-ACE2 protein interactomes on human cells, we developed a photocatalyst-based viral-host protein microenvironment mapping platform (ViraMap) employing iridium photocatalysts conjugated to Spike for visible-light driven proximity labelling on host cells. Application of ViraMap on ACE2-expressing cells captured ACE2, the established co-receptor NRP1, as well as other proteins implicated in host cell entry and immunomodulation. We further investigated these enriched proteins via loss-of-function and over-expression in pseudotype and authentic infection models and observed that the Ig receptor PTGFRN and tyrosine kinase ligand EFNB1 can serve as SARS-CoV-2 entry factors. Our results highlight additional host targets that participate infection and showcase ViraMap for interrogating virus-host cell surface interactomes.

biochemistry↗

Immunomodulatory effects of Simvastatin in Toll-like receptor-2 stimulated Rheumatoid arthritis synoviocytes

Fibroblast-like synoviocytes (FLS) are major effector cells in Rheumatoid arthritis (RA). Toll-like receptor-2 (TLR2) activation of FLS plays a key role in RA pathogenesis. Recently, statins have been shown to modulate RA. We investigated the immunomodulatory effects of simvastatin (SMV) in vitro, in FLS cell lines from control and RA subjects, in the presence of TLR2 activation. Normal and RA FLS cultures (1x105 cells/well) were treated with SMV then activated with TLR2 ligand (Pam3CSK4 100g/ml) for 24-hours. SMV caused dose-dependent cytotoxicity in both cell lines as assessed by Alamar-blue assay and increased ROS production measured by flow cytometry. Gene expression of anti-oxidants including GSR, TXNRD1, PRDX1, SOD2 and MT3 was upregulated. BNIP3 expression was increased 2200-fold in RA-FLS after SMV/TLR2 treatment pointing to apoptosis as a cause of observed cytotoxicity. Apoptosis increased in both cell lines with SMV to 25%. Akt decreased dose-dependently in RA FLS assessed by western blots. IP-1, IP-2 and IP3 decreased with SMV/TLR2 treatment indicating cell survival while IL-6 increased dose-dependently. Thus, SMV induces apoptosis in FLS by upregulating BNIP3 and inhibiting Akt. FLS react to survive by increasing IL-6, decreasing IP-1 and IP-2 and upregulating anti-oxidant genes. SMV has immunomodulatory properties and may be used in RA as adjunctive therapy in combination with other more potent disease-modifying medications.

immunology↗

Macrophages govern antiviral responses in human lung tissues protected from SARS-CoV-2 infection

The majority of SARS-CoV-2 infections among healthy individuals result in asymptomatic to mild disease. However, the immunological mechanisms defining effective lung tissue protection from SARS-CoV-2 infection remain elusive. Unlike mice solely engrafted with human fetal lung xenograft (fLX), mice co-engrafted with fLX and a myeloid-enhanced human immune system (HNFL mice) are protected against SARS-CoV-2 infection, severe inflammation, and histopathology. Effective control of viral infection in HNFL mice associated with significant macrophage infiltration, and the induction of a potent macrophage-mediated interferon response. The pronounced upregulation of the USP18-ISG15 axis (a negative regulator of IFN responses), by macrophages was unique to HNFL mice and represented a prominent correlate of reduced inflammation and histopathology. Altogether, our work shed light on unique cellular and molecular correlates of lung tissue protection during SARS-CoV-2 infection, and underscores macrophage IFN responses as prime targets for developing immunotherapies against coronavirus respiratory diseases. HIGHLIGHTSO_LIMice engrafted with human fetal lung xenografts (fLX-mice) are highly susceptible to SARS-CoV-2. C_LIO_LICo-engraftment with a human myeloid-enriched immune system protected fLX-mice against infection. C_LIO_LITissue protection was defined by a potent and well-balanced antiviral response mediated by infiltrating macrophages. C_LIO_LIProtective IFN response was dominated by the upregulation of the USP18-ISG15 axis. C_LI

microbiology↗

Susceptibilities of human ACE2 genetic variants in coronavirus infection

The COVID-19 pandemic, caused by SARS-CoV-2, has resulted in more than 1603 million cases worldwide and 3.4 million deaths (as of May 2021), with varying incidences and death rates among regions/ethnicities. Human genetic variation can affect disease progression and outcome, but little is known about genetic risk factors for SARS-CoV-2 infection. The coronaviruses SARS-CoV, SARS-CoV-2 and HCoV-NL63 all utilize the human protein angiotensin-converting enzyme 2 (ACE2) as the receptor to enter cells. We hypothesized that the genetic variability in ACE2 may contribute to the variable clinical outcomes of COVID-19. To test this hypothesis, we first conducted an in silico investigation of single-nucleotide polymorphisms (SNPs) in the coding region of ACE2 gene. We then applied an integrated approach of genetics, biochemistry and virology to explore the capacity of select ACE2 variants to bind coronavirus spike protein and mediate viral entry. We identified the ACE2 D355N variant that restricts the spike protein-ACE2 interaction and consequently limits infection both in vitro and in vivo. In conclusion, ACE2 polymorphisms could modulate susceptibility to SARS-CoV-2, which may lead to variable disease severity.

microbiology↗

Fatal neuroinvasion of SARS-CoV-2 in K18-hACE2 mice is partially dependent on hACE2 expression

Animal models recapitulating distinctive features of severe COVID-19 are critical to enhance our understanding of SARS-CoV-2 pathogenesis. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. The precise mechanisms of lethality in this mouse model remain unclear. Here, we evaluated the spatiotemporal dynamics of SARS-CoV-2 infection for up to 14 days post-infection. Despite infection and moderate pneumonia, rapid clinical decline or death of mice was invariably associated with viral neuroinvasion and direct neuronal injury (including brain and spinal neurons). Neuroinvasion was observed as early as 4 dpi, with virus initially restricted to the olfactory bulb supporting axonal transport via the olfactory neuroepithelium as the earliest portal of entry. No evidence of viremia was detected suggesting neuroinvasion occurs independently of entry across the blood brain barrier. SARS-CoV-2 tropism was not restricted to ACE2-expressing cells (e.g., AT1 pneumocytes), and some ACE2-positive lineages were not associated with the presence of viral antigen (e.g., bronchiolar epithelium and brain capillaries). Detectable ACE2 expression was not observed in neurons, supporting overexpression of ACE2 in the nasal passages and neuroepithelium as more likely determinants of neuroinvasion in the K18-hACE2 model. Although our work incites caution in the utility of the K18-hACE2 model to study global aspects of SARS-CoV-2 pathogenesis, it underscores this model as a unique platform for exploring the mechanisms of SARS-CoV-2 neuropathogenesis that may have clinical relevance acknowledging the growing body of evidence that suggests COVID-19 may result in long-standing neurologic consequences. IMPORTANCECOVID-19 is predominantly a respiratory disease caused by SARS-CoV-2 that has infected more than 191 million people with over 4 million fatalities (2021-07-20). The development of animal models recapitulating distinctive features of severe COVID-19 is critical to enhancing our understanding of SARS-CoV-2 pathogenesis and in the evaluation of vaccine and therapeutic efficacy. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. Here, we show lethality of this model is invariably associated with viral neuroinvasion linked with viral replication and assembly. Importantly, pneumonia albeit invariably present was generally moderate with the absence of culturable infectious virus at peak neuroinvasion. The dynamics of viral neuroinvasion and pneumonia were only partially dependent on hACE2. Overall, this study provides an in-depth sequential characterization of the K18-hACE2 model following SARS-CoV-2 infection, highlighting its significance to further study the mechanisms of SARS-CoV-2 neuropathogenesis.

pathology↗

SARS-CoV-2 Requires Cholesterol for Viral Entry and Pathological Syncytia Formation

Many enveloped viruses induce multinucleated cells (syncytia), reflective of membrane fusion events caused by the same machinery that underlies viral entry. These syncytia are thought to facilitate replication and evasion of the host immune response. Here, we report that co-culture of human cells expressing the receptor ACE2 with cells expressing SARS-CoV-2 spike, results in synapse-like intercellular contacts that initiate cell-cell fusion, producing syncytia resembling those we identify in lungs of COVID-19 patients. To assess the mechanism of spike/ACE2-driven membrane fusion, we developed a microscopy-based, cell-cell fusion assay to screen [~]6000 drugs and >30 spike variants. Together with cell biological and biophysical approaches, the screen reveals an essential role for membrane cholesterol in spike-mediated fusion, which extends to replication-competent SARS-CoV-2 isolates. Our findings provide a molecular basis for positive outcomes reported in COVID-19 patients taking statins, and suggest new strategies for therapeutics targeting the membrane of SARS-CoV-2 and other fusogenic viruses. HighlightsO_LICell-cell fusion at ACE2-spike clusters cause pathological syncytia in COVID-19 C_LIO_LIDrug screen reveals critical role for membrane lipid composition in fusion C_LIO_LISpikes unusual membrane-proximal cysteines and aromatics are essential for fusion C_LIO_LICholesterol tunes relative infectivity of SARS-CoV-2 viral particles C_LI

cell biology↗

SARS-CoV-2 desensitizes host cells to interferon through inhibition of the JAK-STAT pathway

SARS-CoV-2 can infect multiple organs, including lung, intestine, kidney, heart, liver, and brain. The molecular details of how the virus navigates through diverse cellular environments and establishes replication are poorly defined. Here, we performed global proteomic analysis of the virus-host interface in a newly established panel of phenotypically diverse, SARS-CoV-2-infectable human cell lines representing different body organs. This revealed universal inhibition of interferon signaling across cell types following SARS-CoV-2 infection. We performed systematic analyses of the JAK-STAT pathway in a broad range of cellular systems, including immortalized cell lines and primary-like cardiomyocytes, and found that several pathway components were targeted by SARS-CoV-2 leading to cellular desensitization to interferon. These findings indicate that the suppression of interferon signaling is a mechanism widely used by SARS-CoV-2 in diverse tissues to evade antiviral innate immunity, and that targeting the viral mediators of immune evasion may help block virus replication in patients with COVID-19.

microbiology↗

SARS-CoV-2 infected cells present HLA-I peptides from canonical and out-of-frame ORFs

T cell-mediated immunity may play a critical role in controlling and establishing protective immunity against SARS-CoV-2 infection; yet the repertoire of viral epitopes responsible for T cell response activation remains mostly unknown. Identification of viral peptides presented on class I human leukocyte antigen (HLA-I) can reveal epitopes for recognition by cytotoxic T cells and potential incorporation into vaccines. Here, we report the first HLA-I immunopeptidome of SARS-CoV-2 in two human cell lines at different times post-infection using mass spectrometry. We found HLA-I peptides derived not only from canonical ORFs, but also from internal out-of-frame ORFs in Spike and Nucleoprotein not captured by current vaccines. Proteomics analyses of infected cells revealed that SARS-CoV-2 may interfere with antigen processing and immune signaling pathways. Based on the endogenously processed and presented viral peptides that we identified, we estimate that a pool of 24 peptides would provide one or more peptides for presentation by at least one HLA allele in 99% of the human population. These biological insights and the list of naturally presented SARS-CoV-2 peptides will facilitate data-driven selection of peptides for immune monitoring and vaccine development.

immunology↗

The Effect Of Famotidine On SARS-CoV-2 Proteases And Virus Replication

The lack of coronavirus-specific antiviral drugs has instigated multiple drug repurposing studies to redirect previously approved medicines for the treatment of SARS-CoV-2, the coronavirus behind the ongoing COVID-19 pandemic. A recent, large-scale, retrospective clinical study showed that famotidine, when administered at a high dose to hospitalized COVID-19 patients, reduced the rates of intubation and mortality. A separate, patient-reported study associated famotidine use with improvements in mild to moderate symptoms such as cough and shortness of breath. While a prospective, multi-center clinical study is ongoing, two parallel in silico studies have proposed one of the two SARS-CoV-2 proteases, 3CLpro or PLpro, as potential molecular targets of famotidine activity; however, this remains to be experimentally validated. In this report, we systematically analyzed the effect of famotidine on viral proteases and virus replication. Leveraging a series of biophysical and enzymatic assays, we show that famotidine neither binds with nor inhibits the functions of 3CLpro and PLpro. Similarly, no direct antiviral activity of famotidine was observed at concentrations of up to 200 M, when tested against SARS-CoV-2 in two different cell lines, including a human cell line originating from lungs, a primary target of COVID-19. These results rule out famotidine as a direct-acting inhibitor of SARS-CoV-2 replication and warrant further investigation of its molecular mechanism of action in the context of COVID-19.

pharmacology and toxicology↗

SARS-CoV-2 Infection of Pluripotent Stem Cell-derived Human Lung Alveolar Type 2 Cells Elicits a Rapid Epithelial-Intrinsic Inflammatory Response

The most severe and fatal infections with SARS-CoV-2 result in the acute respiratory distress syndrome, a clinical phenotype of coronavirus disease 2019 (COVID-19) that is associated with virions targeting the epithelium of the distal lung, particularly the facultative progenitors of this tissue, alveolar epithelial type 2 cells (AT2s). Little is known about the initial responses of human lung alveoli to SARS-CoV-2 infection due in part to inability to access these cells from patients, particularly at early stages of disease. Here we present an in vitro human model that simulates the initial apical infection of the distal lung epithelium with SARS-CoV-2, using AT2s that have been adapted to air-liquid interface culture after their derivation from induced pluripotent stem cells (iAT2s). We find that SARS-CoV-2 induces a rapid global transcriptomic change in infected iAT2s characterized by a shift to an inflammatory phenotype predominated by the secretion of cytokines encoded by NF-kB target genes, delayed epithelial interferon responses, and rapid loss of the mature lung alveolar epithelial program. Over time, infected iAT2s exhibit cellular toxicity that can result in the death of these key alveolar facultative progenitors, as is observed in vivo in COVID-19 lung autopsies. Importantly, drug testing using iAT2s confirmed an antiviral dose-response to remdesivir and demonstrated the efficacy of TMPRSS2 protease inhibition, validating a putative mechanism used for viral entry in human alveolar cells. Our model system reveals the cell-intrinsic responses of a key lung target cell to infection, providing a physiologically relevant platform for further drug development and facilitating a deeper understanding of COVID-19 pathogenesis.

molecular biology↗

Fractal Genomics of SOD1 Evolution

To understand the fundamental processes of gene evolution such as the impact of point mutations and segmental duplications on statistical topography, Superoxide Dismutase-1 (SOD1) orthologous sequences (n=50) were studied. These demonstrated scale invariant self-similarity patterns and long-range correlations (LRC) indicating fractal organization. Phylogenetic hierarchies changed when SOD1 orthologs were grouped according to fractal measures, indicating statistical topographies can be used to study gene evolution. Sliding window k-mer analysis showed that majority of k-mers across all SOD1 orthologs were unique, with very few duplications. Orthologs from simpler species contributed minimally (<1% of k-mers) to more complex species. Both simple and complex random processes failed to produce significant matching k-mer sequences for SOD1 orthologs. Point mutations causing amyotrophic lateral sclerosis did not impact the fractal organization of human SOD1. Hence, SOD1 did not evolve by a patchwork of repetitive sequences modified by point mutations. Instead, this study proposes that SOD1 gene sequences evolved by regulated interweaving of unique oligomer sequences that led to LRC, signifying convergent evolution. Summary StatementSOD1 has long-range correlations which resulted not from point mutations, segmental duplications or patching together sequences from simpler organisms. Instead, SOD1 underwent convergent evolution by repeated unique sequence assemblies.

genomics↗

IgA MAb blocks SARS-CoV-2 Spike-ACE2 interaction providing mucosal immunity

COVID-19 caused by SARS-CoV-2 has become a global pandemic requiring the development of interventions for the prevention or treatment to curtail mortality and morbidity. No vaccine to boost mucosal immunity or as a therapeutic has yet been developed to SARS-CoV-2. In this study we discover and characterize a cross-reactive human IgA monoclonal antibody, MAb362. MAb362 binds to both SARS-CoV and SARS-CoV-2 spike proteins and competitively blocks hACE2 receptor binding, by completely overlapping the hACE2 structural binding epitope. Furthermore, MAb362 IgA neutralizes both pseudotyped SARS-CoV and SARS-CoV-2 in human epithelial cells expressing hACE2. SARS-CoV-2 specific IgA antibodies, such as MAb362, may provide effective immunity against SARS-CoV-2 by inducing mucosal immunity within the respiratory system, a potentially critical feature of an effective vaccine.

microbiology↗

Genomic convergence of locus-based GWAS meta-analysis identifies DDX11 as a novel Systemic Lupus Erythematosus gene

Genome-wide association studies (GWAS) of systemic lupus erythematosus (SLE) explain only [~]15% of genetic risk, indicating genes of modest effect remain to be discovered. Association clustering methods such as OASIS are more apt at identifying modest genetic effects. 410 genes were mapped to previously identified OASIS GWAS SLE loci and investigated for expression in SLE GEO datasets. GSE50395 dataset from Cordoba was used for validation. Blood eQTL for significant SNPs in SLE loci and STRING for functional pathways of differentially expressed genes was used. Confirmatory qPCR on monocytes of 12 SLE patients and controls was performed. We identified 55 genes that were differentially expressed in at least 2 SLE GEO datasets with all probes directionally aligned. DDX11 was downregulated in both GEO (P=3.60E-02) and Cordoba (P=8.02E-03) datasets and confirmed by qPCR (P=0.001). The most significant SNP, rs3741869 (P=3.2E-05) in OASIS locus 12p11.21, containing DDX11, was a cis-eQTL regulating DDX11 expression (P=8.62E-05). DDX11 interacted with multiple genes including STAT1/STAT4. Genomic convergence with OASIS and multiple expression datasets identifies novel genes. DDX11, RNA helicase involved in genome stability, is repressed in SLE. Summary StatementMore than 100 genes for SLE have been identified but they explain only [~]15% of heritability. GWAS are challenged by risk genes of modest effect. Using locus-based GWAS mapping and multiple gene expression replications, DDX11 was identified as a novel SLE gene. DDX11, repressed in SLE, may be used as a clinical diagnostic tool.

genomics↗

LY6E impairs coronavirus fusion and confers immune control of viral disease

Zoonotic coronaviruses (CoVs) are significant threats to global health, as exemplified by the recent emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)1. Host immune responses to CoV are complex and regulated in part through antiviral interferons. However, the interferon-stimulated gene products that inhibit CoV are not well characterized2. Here, we show that interferon-inducible lymphocyte antigen 6 complex, locus E (LY6E) potently restricts cellular infection by multiple CoVs, including SARS-CoV, SARS-CoV-2, and Middle East respiratory syndrome coronavirus (MERS-CoV). Mechanistic studies revealed that LY6E inhibits CoV entry into cells by interfering with spike protein-mediated membrane fusion. Importantly, mice lacking Ly6e in hematopoietic cells were highly susceptible to murine CoV infection. Exacerbated viral pathogenesis in Ly6e knockout mice was accompanied by loss of hepatic and splenic immune cells and reduction in global antiviral gene pathways. Accordingly, we found that Ly6e directly protects primary B cells and dendritic cells from murine CoV infection. Our results demonstrate that LY6E is a critical antiviral immune effector that controls CoV infection and pathogenesis. These findings advance our understanding of immune-mediated control of CoV in vitro and in vivo, knowledge that could help inform strategies to combat infection by emerging CoV.

microbiology↗

Control and simulation impact on nonlinear Hepatitis-B model by using Pade-approximation based Differential Evolution

Hepatitis B is the main public health problem of the whole world. In epidemiology, mathematical models perform a key role in understanding the dynamics of infectious diseases. This paper proposes Pade approximation (Pa) with Differential Evolution (DE) for obtaining solution of Hepatitis-B model which is nonlinear numerically. The proposed strategy transforms the nonlinear model into optimization problem by using Pade approximation. Initial conditions are converted into problem constraints and constraint problem become unconstraint by using penalty function. DE is obtained numerical solution of Hepatitis-B model by solving the established problem of optimization. There is no need to choose step lengths in proposed Pade-approximation based Differential Evolution (PaDE) technique and also PaDE converges to true steady state points. Finally, a convergence and error analysis evidence that the convergence speed of PaDE is greater than Non-Standard Finite Difference (NSFD) method for different time steps.

developmental biology↗

A Methodology for Evaluating the Performance of Alerting and Detection Algorithms Running on Continuous Patient Data

ObjectivesClinicians in the intensive care unit (ICU) are presented with a large number of physiological data consisting of periodic and frequently sampled measurements, such as heart rate and blood pressure, as well as aperiodic measurements, such as noninvasive blood pressure and laboratory studies. Because this data can be overwhelming, there is considerable interest in designing algorithms that help integrate and interpret this data and assist ICU clinicians in detecting or predicting in advance patients who may be deteriorating. In order to decide whether to deploy such algorithms in a clinical trial, it is important to evaluate these algorithms using retrospective data. However, the fact that these algorithms will be running continuously, i.e., repeatedly sampling incoming patient data, presents some novel challenges for algorithm evaluation. Commonly used measures of performance such as sensitivity and positive predictive value (PPV) are easily applied to static \"snapshots\" of patient data, but can be very misleading when applied to indicators or alerting algorithms that are running on continuous data. Our objective is to create a method for evaluating algorithm performance on retrospective data with the algorithm running continuously throughout the patients stay as it would in a real ICU.\n\nMethodsWe introduce our evaluation methodology in the context of evaluating an algorithm, a Hemodynamic Instability Indicator (HII), for assisting bedside ICU clinicians with the early detection of hemodynamic instability before the onset of acute hypotension. Each patients ICU stay is divided into segments that are labelled as hemodynamically stable or unstable based on clinician interventions typically aimed at treating hemodynamic instability. These segments can be of varying length with varying degrees of exposure to potential alerts, whether true positive or false positive. Furthermore, to simulate how clinicians might interact with the alerting algorithm, we use a dynamic alert supervision mechanism which suppresses subsequent alerts unless the indicator has significantly deteriorated since the prior alert. Under these conditions determining what counts as a positive or negative instance, and calculations of sensitivity, specificity, and positive predictive value can be problematic. We introduce a methodology for consistently counting positive and negative instances. The methodology distinguishes between counts based on alerting events and counts based on sub-segments, and show how they can be applied in calculating measures of performance such as sensitivity, specificity, positive predictive value.\n\nResultsThe introduced methodology is applied to retrospective evaluation of two algorithms, HII and an alerting algorithm based on systolic blood pressure. We use a database, consisting of data from 41,707 patients from 25 US hospitals, to evaluate the algorithms. Both algorithms are evaluated running continuously throughout each patients stay as they would in a real ICU setting. We show how the introduced performance measures differ for different algorithms and for different assumptions.\n\nDiscussionThe standard measures of diagnostic tests in terms of true positives, false positives, etc. are based on certain assumptions which may not apply when used in the context of measuring the performance on an algorithm running continuously, and thus repeatedly sampling from the same patient. When such measures are being reported it is important that the underlying assumptions be made explicit; otherwise, the results can be very misleading.\n\nConclusionWe introduce a methodology for evaluating how an alerting algorithm or indicator will perform running continuously throughout every patients ICU stay, not just for a subset of patients for selected episodes.

bioinformatics↗