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Item Open Access Assessment of the Feasibility of Using Noninvasive Wearable Biometric Monitoring Sensors to Detect Influenza and the Common Cold Before Symptom Onset.(JAMA network open, 2021-09) Grzesiak, Emilia; Bent, Brinnae; McClain, Micah T; Woods, Christopher W; Tsalik, Ephraim L; Nicholson, Bradly P; Veldman, Timothy; Burke, Thomas W; Gardener, Zoe; Bergstrom, Emma; Turner, Ronald B; Chiu, Christopher; Doraiswamy, P Murali; Hero, Alfred; Henao, Ricardo; Ginsburg, Geoffrey S; Dunn, JessilynImportance
Currently, there are no presymptomatic screening methods to identify individuals infected with a respiratory virus to prevent disease spread and to predict their trajectory for resource allocation.Objective
To evaluate the feasibility of using noninvasive, wrist-worn wearable biometric monitoring sensors to detect presymptomatic viral infection after exposure and predict infection severity in patients exposed to H1N1 influenza or human rhinovirus.Design, setting, and participants
The cohort H1N1 viral challenge study was conducted during 2018; data were collected from September 11, 2017, to May 4, 2018. The cohort rhinovirus challenge study was conducted during 2015; data were collected from September 14 to 21, 2015. A total of 39 adult participants were recruited for the H1N1 challenge study, and 24 adult participants were recruited for the rhinovirus challenge study. Exclusion criteria for both challenges included chronic respiratory illness and high levels of serum antibodies. Participants in the H1N1 challenge study were isolated in a clinic for a minimum of 8 days after inoculation. The rhinovirus challenge took place on a college campus, and participants were not isolated.Exposures
Participants in the H1N1 challenge study were inoculated via intranasal drops of diluted influenza A/California/03/09 (H1N1) virus with a mean count of 106 using the median tissue culture infectious dose (TCID50) assay. Participants in the rhinovirus challenge study were inoculated via intranasal drops of diluted human rhinovirus strain type 16 with a count of 100 using the TCID50 assay.Main outcomes and measures
The primary outcome measures included cross-validated performance metrics of random forest models to screen for presymptomatic infection and predict infection severity, including accuracy, precision, sensitivity, specificity, F1 score, and area under the receiver operating characteristic curve (AUC).Results
A total of 31 participants with H1N1 (24 men [77.4%]; mean [SD] age, 34.7 [12.3] years) and 18 participants with rhinovirus (11 men [61.1%]; mean [SD] age, 21.7 [3.1] years) were included in the analysis after data preprocessing. Separate H1N1 and rhinovirus detection models, using only data on wearble devices as input, were able to distinguish between infection and noninfection with accuracies of up to 92% for H1N1 (90% precision, 90% sensitivity, 93% specificity, and 90% F1 score, 0.85 [95% CI, 0.70-1.00] AUC) and 88% for rhinovirus (100% precision, 78% sensitivity, 100% specificity, 88% F1 score, and 0.96 [95% CI, 0.85-1.00] AUC). The infection severity prediction model was able to distinguish between mild and moderate infection 24 hours prior to symptom onset with an accuracy of 90% for H1N1 (88% precision, 88% sensitivity, 92% specificity, 88% F1 score, and 0.88 [95% CI, 0.72-1.00] AUC) and 89% for rhinovirus (100% precision, 75% sensitivity, 100% specificity, 86% F1 score, and 0.95 [95% CI, 0.79-1.00] AUC).Conclusions and relevance
This cohort study suggests that the use of a noninvasive, wrist-worn wearable device to predict an individual's response to viral exposure prior to symptoms is feasible. Harnessing this technology would support early interventions to limit presymptomatic spread of viral respiratory infections, which is timely in the era of COVID-19.Item Open Access Automatic annotation of spatial expression patterns via sparse Bayesian factor models.(PLoS Comput Biol, 2011-07) Pruteanu-Malinici, Iulian; Mace, Daniel L; Ohler, UweAdvances in reporters for gene expression have made it possible to document and quantify expression patterns in 2D-4D. In contrast to microarrays, which provide data for many genes but averaged and/or at low resolution, images reveal the high spatial dynamics of gene expression. Developing computational methods to compare, annotate, and model gene expression based on images is imperative, considering that available data are rapidly increasing. We have developed a sparse Bayesian factor analysis model in which the observed expression diversity of among a large set of high-dimensional images is modeled by a small number of hidden common factors. We apply this approach on embryonic expression patterns from a Drosophila RNA in situ image database, and show that the automatically inferred factors provide for a meaningful decomposition and represent common co-regulation or biological functions. The low-dimensional set of factor mixing weights is further used as features by a classifier to annotate expression patterns with functional categories. On human-curated annotations, our sparse approach reaches similar or better classification of expression patterns at different developmental stages, when compared to other automatic image annotation methods using thousands of hard-to-interpret features. Our study therefore outlines a general framework for large microscopy data sets, in which both the generative model itself, as well as its application for analysis tasks such as automated annotation, can provide insight into biological questions.Item Open Access Cytokine profiles of preterm neonates with fungal and bacterial sepsis.(Pediatr Res, 2012-08) Sood, Beena G; Shankaran, Seetha; Schelonka, Robert L; Saha, Shampa; Benjamin, Danny K; Sánchez, Pablo J; Adams-Chapman, Ira; Stoll, Barbara J; Thorsen, Poul; Skogstrand, Kristin; Ehrenkranz, Richard A; Hougaard, David M; Goldberg, Ronald N; Tyson, Jon E; Das, Abhik; Higgins, Rosemary D; Carlo, Waldemar A; Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research NetworkBACKGROUND: Information on cytokine profiles in fungal sepsis (FS), an important cause of mortality in extremely low birthweight (ELBW) infants, is lacking. We hypothesized that cytokine profiles in the first 21 d of life in ELBW infants with FS differ from those with bacterial sepsis (BS) or no sepsis (NS). METHODS: In a secondary analysis of the National Institute of Child Health and Human Development Cytokine study, three groups were defined-FS (≥1 episode of FS), BS (≥1 episode of BS without FS), and NS. Association between 11 cytokines assayed in dried blood spots obtained on days 0-1, 3 ± 1, 7 ± 2, 14 ± 3, and 21 ± 3 and sepsis group was explored. RESULTS: Of 1,066 infants, 89 had FS and 368 had BS. As compared with BS, FS was more likely to be associated with lower birthweight, vaginal delivery, patent ductus arteriosus, postnatal steroids, multiple central lines, longer respiratory support and hospital stay, and higher mortality (P < 0.05). Analyses controlling for covariates showed significant group differences over time for interferon-γ (IFN-γ), interleukin (IL)-10, IL-18, transforming growth factor-β (TGF-β), and tumor necrosis factor-α (TNF-α) (P < 0.05). CONCLUSION: Significant differences in profiles for IFN-γ, IL-10, IL-18, TGF-β, and TNF-α in FS, BS, or NS in this hypothesis-generating secondary study require validation in rigorously designed prospective studies and may have implications for diagnosis and treatment.Item Open Access Design, mechanism of action, bioavailability and therapeutic effects of mn porphyrin-based redox modulators.(Medical principles and practice : international journal of the Kuwait University, Health Science Centre, 2013-01) Tovmasyan, A; Sheng, H; Weitner, T; Arulpragasam, A; Lu, M; Warner, DS; Vujaskovic, Z; Spasojevic, I; Batinic Haberle, IBased on aqueous redox chemistry and simple in vivo models of oxidative stress, Escherichia coli and Saccharomyces cerevisiae, the cationic Mn(III) N-substituted pyridylporphyrins (MnPs) have been identified as the most potent cellular redox modulators within the porphyrin class of drugs; their efficacy in animal models of diseases that have oxidative stress in common is based on their high ability to catalytically remove superoxide, peroxynitrite, carbonate anion radical, hypochlorite, nitric oxide, lipid peroxyl and alkoxyl radicals, thus suppressing the primary oxidative event. While doing so MnPs could couple with cellular reductants and redox-active proteins. Reactive species are widely accepted as regulators of cellular transcriptional activity: minute, nanomolar levels are essential for normal cell function, while submicromolar or micromolar levels impose oxidative stress, which is evidenced in increased inflammatory and immune responses. By removing reactive species, MnPs affect redox-based cellular transcriptional activity and consequently secondary oxidative stress, and in turn inflammatory processes. The equal ability to reduce and oxidize superoxide during the dismutation process and recently accumulated results suggest that pro-oxidative actions of MnPs may also contribute to their therapeutic effects. All our data identify the superoxide dismutase-like activity, estimated by log k(cat)O2-*), as a good measure for the therapeutic efficacy of MnPs. Their accumulation in mitochondria and their ability to cross the blood-brain barrier contribute to their remarkable efficacy. We summarize herein the therapeutic effects of MnPs in cancer, central nervous system injuries, diabetes, their radioprotective action and potential for imaging. Few of the most potent modulators of cellular redox-based pathways, MnTE2-PyP5+, MnTDE-2-ImP5+, MnTnHex-2-PyP5+ and MnTnBuOE-2-PyP5+, are under preclinical and clinical development.Item Open Access Development of a preoperative predictive model for major complications following adult spinal deformity surgery.(Journal of neurosurgery. Spine, 2017-06) Scheer, Justin K; Smith, Justin S; Schwab, Frank; Lafage, Virginie; Shaffrey, Christopher I; Bess, Shay; Daniels, Alan H; Hart, Robert A; Protopsaltis, Themistocles S; Mundis, Gregory M; Sciubba, Daniel M; Ailon, Tamir; Burton, Douglas C; Klineberg, Eric; Ames, Christopher P; International Spine Study GroupOBJECTIVE The operative management of patients with adult spinal deformity (ASD) has a high complication rate and it remains unknown whether baseline patient characteristics and surgical variables can predict early complications (intraoperative and perioperative [within 6 weeks]). The development of an accurate preoperative predictive model can aid in patient counseling, shared decision making, and improved surgical planning. The purpose of this study was to develop a model based on baseline demographic, radiographic, and surgical factors that can predict if patients will sustain an intraoperative or perioperative major complication. METHODS This study was a retrospective analysis of a prospective, multicenter ASD database. The inclusion criteria were age ≥ 18 years and the presence of ASD. In total, 45 variables were used in the initial training of the model including demographic data, comorbidities, modifiable surgical variables, baseline health-related quality of life, and coronal and sagittal radiographic parameters. Patients were grouped as either having at least 1 major intraoperative or perioperative complication (COMP group) or not (NOCOMP group). An ensemble of decision trees was constructed utilizing the C5.0 algorithm with 5 different bootstrapped models. Internal validation was accomplished via a 70/30 data split for training and testing each model, respectively. Overall accuracy, the area under the receiver operating characteristic (AUROC) curve, and predictor importance were calculated. RESULTS Five hundred fifty-seven patients were included: 409 (73.4%) in the NOCOMP group, and 148 (26.6%) in the COMP group. The overall model accuracy was 87.6% correct with an AUROC curve of 0.89 indicating a very good model fit. Twenty variables were determined to be the top predictors (importance ≥ 0.90 as determined by the model) and included (in decreasing importance): age, leg pain, Oswestry Disability Index, number of decompression levels, number of interbody fusion levels, Physical Component Summary of the SF-36, Scoliosis Research Society (SRS)-Schwab coronal curve type, Charlson Comorbidity Index, SRS activity, T-1 pelvic angle, American Society of Anesthesiologists grade, presence of osteoporosis, pelvic tilt, sagittal vertical axis, primary versus revision surgery, SRS pain, SRS total, use of bone morphogenetic protein, use of iliac crest graft, and pelvic incidence-lumbar lordosis mismatch. CONCLUSIONS A successful model (87% accuracy, 0.89 AUROC curve) was built predicting major intraoperative or perioperative complications following ASD surgery. This model can provide the foundation toward improved education and point-of-care decision making for patients undergoing ASD surgery.Item Open Access Development of predictive models for all individual questions of SRS-22R after adult spinal deformity surgery: a step toward individualized medicine.(European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2019-09) Ames, Christopher P; Smith, Justin S; Pellisé, Ferran; Kelly, Michael; Gum, Jeffrey L; Alanay, Ahmet; Acaroğlu, Emre; Pérez-Grueso, Francisco Javier Sánchez; Kleinstück, Frank S; Obeid, Ibrahim; Vila-Casademunt, Alba; Shaffrey, Christopher I; Burton, Douglas C; Lafage, Virginie; Schwab, Frank J; Shaffrey, Christopher I; Bess, Shay; Serra-Burriel, Miquel; European Spine Study Group; International Spine Study GroupPurpose
Health-related quality of life (HRQL) instruments are essential in value-driven health care, but patients often have more specific, personal priorities when seeking surgical care. The Scoliosis Research Society-22R (SRS-22R), an HRQL instrument for spinal deformity, provides summary scores spanning several health domains, but these may be difficult for patients to utilize in planning their specific care goals. Our objective was to create preoperative predictive models for responses to individual SRS-22R questions at 1 and 2 years after adult spinal deformity (ASD) surgery to facilitate precision surgical care.Methods
Two prospective observational cohorts were queried for ASD patients with SRS-22R data at baseline and 1 and 2 years after surgery. In total, 150 covariates were used in training machine learning models, including demographics, surgical data and perioperative complications. Validation was accomplished via an 80%/20% data split for training and testing, respectively. Goodness of fit was measured using area under receiver operating characteristic (AUROC) curves.Results
In total, 561 patients met inclusion criteria. The AUROC ranged from 56.5 to 86.9%, reflecting successful fits for most questions. SRS-22R questions regarding pain, disability and social and labor function were the most accurately predicted. Models were less sensitive to questions regarding general satisfaction, depression/anxiety and appearance.Conclusions
To the best of our knowledge, this is the first study to explicitly model the prediction of individual answers to the SRS-22R questionnaire at 1 and 2 years after deformity surgery. The ability to predict individual question responses may prove useful in preoperative counseling in the age of individualized medicine. These slides can be retrieved under Electronic Supplementary Material.Item Open Access Drug-drug interaction studies of cardiovascular drugs involving P-glycoprotein, an efflux transporter, on the pharmacokinetics of edoxaban, an oral factor Xa inhibitor.(Am J Cardiovasc Drugs, 2013-10) Mendell, Jeanne; Zahir, Hamim; Matsushima, Nobuko; Noveck, Robert; Lee, Frank; Chen, Shuquan; Zhang, George; Shi, MinggaoBACKGROUND: Edoxaban, an oral direct factor Xa inhibitor, is in development for thromboprophylaxis, including prevention of stroke and systemic embolism in patients with atrial fibrillation (AF). P-glycoprotein (P-gp), an efflux transporter, modulates absorption and excretion of xenobiotics. Edoxaban is a P-gp substrate, and several cardiovascular (CV) drugs have the potential to inhibit P-gp and increase drug exposure. OBJECTIVE: To assess the potential pharmacokinetic interactions of edoxaban and 6 cardiovascular drugs used in the management of AF and known P-gp substrates/inhibitors. METHODS: Drug-drug interaction studies with edoxaban and CV drugs with known P-gp substrate/inhibitor potential were conducted in healthy subjects. In 4 crossover, 2-period, 2-treatment studies, subjects received edoxaban 60 mg alone and coadministered with quinidine 300 mg (n = 42), verapamil 240 mg (n = 34), atorvastatin 80 mg (n = 32), or dronedarone 400 mg (n = 34). Additionally, edoxaban 60 mg alone and coadministered with amiodarone 400 mg (n = 30) or digoxin 0.25 mg (n = 48) was evaluated in a single-sequence study and 2-cohort study, respectively. RESULTS: Edoxaban exposure measured as area under the curve increased for concomitant administration of edoxaban with quinidine (76.7 %), verapamil (52.7 %), amiodarone (39.8 %), and dronedarone (84.5 %), and exposure measured as 24-h concentrations for quinidine (11.8 %), verapamil (29.1 %), and dronedarone (157.6 %) also increased. Administration of edoxaban with amiodarone decreased the 24-h concentration for edoxaban by 25.7 %. Concomitant administration with digoxin or atorvastatin had minimal effects on edoxaban exposure. CONCLUSION: Coadministration of the P-gp inhibitors quinidine, verapamil, and dronedarone increased edoxaban exposure. Modest/minimal effects were observed for amiodarone, atorvastatin, and digoxin.Item Open Access High Dimensional Variable Selection with Error Control.(Biomed Res Int, 2016) Kim, Sangjin; Halabi, SusanBackground. The iterative sure independence screening (ISIS) is a popular method in selecting important variables while maintaining most of the informative variables relevant to the outcome in high throughput data. However, it not only is computationally intensive but also may cause high false discovery rate (FDR). We propose to use the FDR as a screening method to reduce the high dimension to a lower dimension as well as controlling the FDR with three popular variable selection methods: LASSO, SCAD, and MCP. Method. The three methods with the proposed screenings were applied to prostate cancer data with presence of metastasis as the outcome. Results. Simulations showed that the three variable selection methods with the proposed screenings controlled the predefined FDR and produced high area under the receiver operating characteristic curve (AUROC) scores. In applying these methods to the prostate cancer example, LASSO and MCP selected 12 and 8 genes and produced AUROC scores of 0.746 and 0.764, respectively. Conclusions. We demonstrated that the variable selection methods with the sequential use of FDR and ISIS not only controlled the predefined FDR in the final models but also had relatively high AUROC scores.Item Open Access Measuring disease-free survival and cancer relapse using Medicare claims from CALGB breast cancer trial participants (companion to 9344).(J Natl Cancer Inst, 2006-09-20) Lamont, Elizabeth B; Herndon, James E; Weeks, Jane C; Henderson, I Craig; Earle, Craig C; Schilsky, Richard L; Christakis, Nicholas A; Cancer and Leukemia Group BTo determine the accuracy with which Medicare claims data measure disease-free survival in elderly Medicare beneficiaries with cancer, we performed a criterion validation study. We merged gold-standard clinical trial data of 45 elderly patients with node-positive breast cancer who were treated on the Cancer and Leukemia Group B (CALGB) adjuvant breast trial 9344 with Centers for Medicare and Medicaid Services (CMS) data files and compared the results of a CMS-based algorithm with the CALGB disease-free survival information to determine sensitivity and specificity. For 5-year disease-free survival, the sensitivity of the CMS-based algorithm was 100% (95% confidence interval [CI] = 81% to 100%), the specificity was 97% (95% CI = 83% to 100%), and the area under the receiver operator curve was 98[corrected]% (95% CI = 95[corrected]% to 100%). For 2-year disease-free survival, the test characteristics were less favorable: sensitivity was 83% (95% CI = 36% to 100%), specificity was 95% (95% CI = 83% to 100%), and area under the receiver operator curve was 89[corrected]% (95% CI = 72[corrected]% to 100%).Item Open Access Methods of creatine kinase-MB analysis to predict mortality in patients with myocardial infarction treated with reperfusion therapy.(Trials, 2013-05-02) Lopes, Renato D; Lokhnygina, Yuliya; Hasselblad, Victor; Newby, Kristin L; Yow, Eric; Granger, Christopher B; Armstrong, Paul W; Hochman, Judith S; Mills, James S; Ruzyllo, Witold; Mahaffey, Kenneth WBACKGROUND: Larger infarct size measured by creatine kinase (CK)-MB release is associated with higher mortality and has been used as an important surrogate endpoint in the evaluation of new treatments for ST-segment elevation myocardial infarction (STEMI). Traditional approaches to quantify infarct size include the observed CK-MB peak and calculated CK-MB area under the curve (AUC). We evaluated alternative approaches to quantifying infarct size using CK-MB values, and the relationship between infarct size and clinical outcomes. METHODS: Of 1,850 STEMI patients treated with reperfusion therapy in the COMplement inhibition in Myocardial infarction treated with Angioplasty (COMMA) (percutaneous coronary intervention (PCI)-treated) and the COMPlement inhibition in myocardial infarction treated with thromboLYtics (COMPLY) (fibrinolytic-treated) trials, 1,718 (92.9%) (COMMA, n = 868; COMPLY, n = 850) had at least five of nine protocol-required CK-MB measures. In addition to traditional methods, curve-fitting techniques were used to determine CK-MB AUC and estimated peak CK-MB. Cox proportional hazards modeling assessed the univariable associations between infarct size and mortality, and the composite of death, heart failure, shock and stroke at 90 days. RESULTS: In COMPLY, CK-MB measures by all methods were significantly associated with higher mortality (hazard ratio range per 1,000 units increase: 1.09 to 1.13; hazard ratio range per 1 standard deviation increase: 1.41 to 1.62; P <0.01 for all analyses). In COMMA, the associations were similar but did not reach statistical significance. For the composite outcome of 90-day death, heart failure, shock and stroke, the associations with all CK-MB measures were statistically significant in both the COMMA and COMPLY trials. CONCLUSIONS: Sophisticated curve modeling is an alternative to infarct-size quantification in STEMI patients, but it provides information similar to that of more traditional methods. Future studies will determine whether the same conclusion applies in circumstances other than STEMI, or to studies with different frequencies and patterns of CK-MB data collection.Item Open Access Novel Method Using Baseline Normalization and Area Under the Curve to Evaluate Differences in Outcome Between Treatment Groups and Application to Patients With Cervical Spondylotic Myelopathy Undergoing Anterior Versus Posterior Surgery.(Spine, 2015-12) Liu, Shian; Tetreault, Lindsay; Fehlings, Michael G; Challier, Vincent; Smith, Justin S; Shaffrey, Christopher I; Arnold, Paul M; Scheer, Justin K; Chapman, Jens R; Kopjar, Branko; Protopsaltis, Themistocles S; Lafage, Virginie; Schwab, Frank; Massicotte, Eric M; Yoon, Sangwook T; Ames, Christopher PRetrospective review of a prospective database.To describe a novel method that uses baseline normalization and area under the curve (AUC) to compare surgical outcomes between patients surgically treated anteriorly versus posteriorly for cervical spondylotic myelopathy (CSM).It is important to control for baseline characteristics, especially disease severity, when evaluating differences in outcomes between 2 treatment groups. However, current methods of reporting outcomes are limited perhaps diminish the health impact of the entire postoperative recovery experience.In the prospective, multicenter AO Spine North America CSM database, 147 patients had complete modified Japanese Orthopaedic Association (mJOA) data at baseline and at 6-, 12-, and 24-months postoperatively and were either treated anteriorly (n = 94) or posteriorly (n = 53). Each patient's follow-up mJOA scores were normalized by dividing them by the patient's baseline value. A graph was then plotted with the time point on the x-axis and the normalized score or "recovery index" on the y-axis. The AUC was calculated and then compared between the anterior and posterior surgical approach groups.The non-normalized recovery profile of the anterior group was better than that of the posterior group, as the patients treated anteriorly had less functional impairment at baseline. After normalization, patients in the anterior and posterior group had similar recovery indices and AUCs at 6-months following surgery. At 24-months, patients treated posteriorly had a significantly higher recovery index (1.32) and a larger AUC (16.3) than those treated anteriorly (1.11, 14.5, P = 0.004 and P = 0.006, respectively).This is the first study to apply AUC analysis to patients with CSM. In surgical patients with CSM, those treated anteriorly achieved a higher mJOA score at all time points than those treated posteriorly. The recovery indices, however, were not significantly different between approach groups at 6 months.3.Item Open Access Novel model for predicting inpatient mortality after emergency admission to hospital in Singapore: retrospective observational study.(BMJ open, 2019-09-26) Xie, Feng; Liu, Nan; Wu, Stella Xinzi; Ang, Yukai; Low, Lian Leng; Ho, Andrew Fu Wah; Lam, Sean Shao Wei; Matchar, David Bruce; Ong, Marcus Eng Hock; Chakraborty, BibhasOBJECTIVES:To identify risk factors for inpatient mortality after patients' emergency admission and to create a novel model predicting inpatient mortality risk. DESIGN:This was a retrospective observational study using data extracted from electronic health records (EHRs). The data were randomly split into a derivation set and a validation set. The stepwise model selection was employed. We compared our model with one of the current clinical scores, Cardiac Arrest Risk Triage (CART) score. SETTING:A single tertiary hospital in Singapore. PARTICIPANTS:All adult hospitalised patients, admitted via emergency department (ED) from 1 January 2008 to 31 October 2017 (n=433 187 by admission episodes). MAIN OUTCOME MEASURE:The primary outcome of interest was inpatient mortality following this admission episode. The area under the curve (AUC) of the receiver operating characteristic curve of the predictive model with sensitivity and specificity for optimised cut-offs. RESULTS:15 758 (3.64%) of the episodes were observed inpatient mortality. 19 variables were observed as significant predictors and were included in our final regression model. Our predictive model outperformed the CART score in terms of predictive power. The AUC of CART score and our final model was 0.705 (95% CI 0.697 to 0.714) and 0.817 (95% CI 0.810 to 0.824), respectively. CONCLUSION:We developed and validated a model for inpatient mortality using EHR data collected in the ED. The performance of our model was more accurate than the CART score. Implementation of our model in the hospital can potentially predict imminent adverse events and institute appropriate clinical management.Item Open Access Performance Assessment of the Universal Vital Assessment Score vs Other Illness Severity Scores for Predicting Risk of In-Hospital Death Among Adult Febrile Inpatients in Northern Tanzania, 2016-2019.(JAMA network open, 2021-12) Bonnewell, John P; Rubach, Matthew P; Madut, Deng B; Carugati, Manuela; Maze, Michael J; Kilonzo, Kajiru G; Lyamuya, Furaha; Marandu, Annette; Kalengo, Nathaniel H; Lwezaula, Bingileki F; Mmbaga, Blandina T; Maro, Venance P; Crump, John AImportance
Severity scores are used to improve triage of hospitalized patients in high-income settings, but the scores may not translate well to low- and middle-income settings such as sub-Saharan Africa.Objective
To assess the performance of the Universal Vital Assessment (UVA) score, derived in 2017, compared with other illness severity scores for predicting in-hospital mortality among adults with febrile illness in northern Tanzania.Design, setting, and participants
This prognostic study used clinical data collected for the duration of hospitalization among patients with febrile illness admitted to Kilimanjaro Christian Medical Centre or Mawenzi Regional Referral Hospital in Moshi, Tanzania, from September 2016 through May 2019. All adult and pediatric patients with a history of fever within 72 hours or a tympanic temperature of 38.0 °C or higher at screening were eligible for enrollment. Of 3761 eligible participants, 1132 (30.1%) were enrolled in the parent study; of those, 597 adults 18 years or older were included in this analysis. Data were analyzed from December 2019 to September 2021.Exposures
Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), quick Sequential Organ Failure Assessment (qSOFA), Systemic Inflammatory Response Syndrome (SIRS) assessment, and UVA.Main outcomes and measures
The main outcome was in-hospital mortality during the same hospitalization as the participant's enrollment. Crude risk ratios and 95% CIs for in-hospital death were calculated using log-binomial risk regression for proposed score cutoffs for each of the illness severity scores. The area under the receiver operating characteristic curve (AUROC) for estimating the risk of in-hospital death was calculated for each score.Results
Among 597 participants, the median age was 43 years (IQR, 31-56 years); 300 participants (50.3%) were female, 198 (33.2%) were HIV-infected, and in-hospital death occurred in 55 (9.2%). By higher risk score strata for each score, compared with lower risk strata, risk ratios for in-hospital death were 3.7 (95% CI, 2.2-6.2) for a MEWS of 5 or higher; 2.7 (95% CI, 0.9-7.8) for a NEWS of 5 or 6; 9.6 (95% CI, 4.2-22.2) for a NEWS of 7 or higher; 4.8 (95% CI, 1.2-20.2) for a qSOFA score of 1; 15.4 (95% CI, 3.8-63.1) for a qSOFA score of 2 or higher; 2.5 (95% CI, 1.2-5.2) for a SIRS score of 2 or higher; 9.1 (95% CI, 2.7-30.3) for a UVA score of 2 to 4; and 30.6 (95% CI, 9.6-97.8) for a UVA score of 5 or higher. The AUROCs, using all ordinal values, were 0.85 (95% CI, 0.80-0.90) for the UVA score, 0.81 (95% CI, 0.75-0.87) for the NEWS, 0.75 (95% CI, 0.69-0.82) for the MEWS, 0.73 (95% CI, 0.67-0.79) for the qSOFA score, and 0.63 (95% CI, 0.56-0.71) for the SIRS score. The AUROC for the UVA score was significantly greater than that for all other scores (P < .05 for all comparisons) except for NEWS (P = .08).Conclusions and relevance
This prognostic study found that the NEWS and the UVA score performed favorably compared with other illness severity scores in predicting in-hospital mortality among a hospitalized cohort of adults with febrile illness in northern Tanzania. Given its reliance on readily available clinical data, the UVA score may have utility in the triage and prognostication of patients admitted to the hospital with febrile illness in low- to middle-income settings such as sub-Saharan Africa.Item Open Access Predictors of Superior Recovery Kinetics in Adult Cervical Deformity Correction: An Analysis Using a Novel Area Under the Curve Methodology.(Spine, 2021-05) Pierce, Katherine E; Passias, Peter G; Brown, Avery E; Bortz, Cole A; Alas, Haddy; Lafage, Renaud; Lafage, Virginie; Ames, Christopher; Burton, Douglas C; Hart, Robert; Hamilton, Kojo; Gum, Jeffrey; Scheer, Justin; Daniels, Alan; Bess, Shay; Soroceanu, Alex; Klineberg, Eric; Shaffrey, Christopher; Line, Breton; Schwab, Frank A; Smith, Justin S; on behalf of the International Spine Study Group (ISSG)Study design
Retrospective review of a prospective database.Objective
The aim of this study was to identify demographic, surgical, and radiographic factors that predict superior recovery kinetics following cervical deformity (CD) corrective surgery.Summary of background data
Analyses of CD corrective surgery use area under the curve (AUC) to assess health-related quality of life (HRQL) metrics throughout recovery.Methods
Outcome measures were baseline (BL) to 1-year (1Y) health-related quality of life (HRQL) (Neck Disability Index [NDI]). CD criteria were C2-7 Cobb angle >10°, coronal Cobb angle >10°, C2-C7 sagittal vertical axis (cSVA) >4 cm, TS-CL >10°, or chin-brow vertical angle >25°. AUC normalization divided BL and postoperative outcomes by BL. Normalized scores (y axis) were plotted against follow-up (x axis). AUC was calculated and divided by cumulative follow-up length to determine overall, time-adjusted recovery (Integrated Health State [IHS]). IHS NDI was stratified by quartile, uppermost 25% being "Superior" Recovery Kinetics (SRK) versus "Normal" Recovery Kinetics (NRK). BL demographic, clinical, and surgical information predicted SRK using generalized linear modeling.Results
Ninety-eight patients included (62 ± 10 years, 28 ± 6 kg/m2, 65% females, Charlson Comorbidity Index: 0.95), 6% smokers, 31% smoking history. Surgical approach was: combined (33%), posterior (49%), anterior (18%). Posterior levels fused: 8.7, anterior: 3.6, estimated blood loss: 915.9ccs, operative time: 495 minutes. Ames BL classification: cSVA (53.2% minor deformity, 46.8% moderate), TS-CL (9.8% minor, 4.3% moderate, 85.9% marked), horizontal gaze (27.4% minor, 46.6% moderate, 26% marked). Relative to BL NDI (Mean: 47), normalized NDI decreased at 3 months (0.9 ± 0.5, P = 0.260) and 1Y (0.78 ± 0.41, P < 0.001). NDI IHS correlated with age (P = 0.011), sex (P = 0.042), anterior approach (P = 0.042), posterior approach (P = 0.042). Greater BL pelvic tilt (PT) (SRK: 25.6°, NRK: 17°, P = 0.002), pelvic incidence-lumbar lordosis (PI-LL) (SRK: 8.4°, NRK: -2.8°, P = 0.009), and anterior approach (SRK: 34.8%, NRK: 13.3%; P = 0.020) correlated with SRK. 69.4% met MCID for NDI (<Δ-15) and 63.3% met substantial clinical benefit for NDI (<Δ-10); 100% of SRK met both MCID and substantial clinical benefit. The predictive model for SRK included (AUC = 88.1%): BL visual analog scale (VAS) EuroQol five-dimensional descriptive system (EQ5D) (odds rario [OR] 0.96, 95% confidence interval [CI]: 0.92-0.99), BL swallow sleep score (OR: 1.04, 95% CI: 1.01-1.06), BL PT (OR: 1.12, 95% CI: 1.03-1.22), BL modified Japanese Orthopedic Association scale (mJOA) (OR: 1.5, 95% CI: 1.07-2.16), BL T4-T12, BL T10-L2, BL T12-S1, and BL L1-S1.Conclusion
Superior recovery kinetics following CD surgery was predicted with high accuracy using BL patient-reported (VAS EQ5D, swallow sleep, mJOA) and radiographic factors (PT, TK, T10-L2, T12-S1, L1-S1). Awareness of these factors can improve decision-making and reduce postoperative neck disability.Level of Evidence: 3.Item Open Access Validation of ICDPIC software injury severity scores using a large regional trauma registry.(Inj Prev, 2015-10) Greene, Nathaniel H; Kernic, Mary A; Vavilala, Monica S; Rivara, Frederick PBACKGROUND: Administrative or quality improvement registries may or may not contain the elements needed for investigations by trauma researchers. International Classification of Diseases Program for Injury Categorisation (ICDPIC), a statistical program available through Stata, is a powerful tool that can extract injury severity scores from ICD-9-CM codes. We conducted a validation study for use of the ICDPIC in trauma research. METHODS: We conducted a retrospective cohort validation study of 40,418 patients with injury using a large regional trauma registry. ICDPIC-generated AIS scores for each body region were compared with trauma registry AIS scores (gold standard) in adult and paediatric populations. A separate analysis was conducted among patients with traumatic brain injury (TBI) comparing the ICDPIC tool with ICD-9-CM embedded severity codes. Performance in characterising overall injury severity, by the ISS, was also assessed. RESULTS: The ICDPIC tool generated substantial correlations in thoracic and abdominal trauma (weighted κ 0.87-0.92), and in head and neck trauma (weighted κ 0.76-0.83). The ICDPIC tool captured TBI severity better than ICD-9-CM code embedded severity and offered the advantage of generating a severity value for every patient (rather than having missing data). Its ability to produce an accurate severity score was consistent within each body region as well as overall. CONCLUSIONS: The ICDPIC tool performs well in classifying injury severity and is superior to ICD-9-CM embedded severity for TBI. Use of ICDPIC demonstrates substantial efficiency and may be a preferred tool in determining injury severity for large trauma datasets, provided researchers understand its limitations and take caution when examining smaller trauma datasets.Item Open Access Voriconazole pharmacokinetics following HSCT: results from the BMT CTN 0101 trial.(The Journal of antimicrobial chemotherapy, 2016-08) Hope, William W; Walsh, Thomas J; Goodwin, Joanne; Peloquin, Charles A; Howard, Alan; Kurtzberg, Joanne; Mendizabal, Alan; Confer, Dennis L; Bulitta, Jürgen; Baden, Lindsey R; Neely, Michael N; Wingard, John R; Blood and Marrow Transplant Clinical Trials NetworkBackground
Voriconazole is a first-line agent for the prevention and treatment of a number of invasive fungal diseases. Relatively little is known about the relationship between drug exposure and the prevention of invasive fungal infections.Patients and methods
A pharmacokinetic-pharmacodynamic substudy was performed as part of the BMT CTN 0101 trial, which was a randomized clinical trial comparing voriconazole with fluconazole for the prevention of invasive fungal infections in HSCT recipients. A previously described population pharmacokinetic model was used to calculate the maximum a posteriori Bayesian estimates for 187 patients. Drug exposure in each patient was quantified in terms of the average AUC and average trough concentrations. The relationship between drug exposure and the probability of breakthrough infection was investigated using logistic regression. AUC and trough concentrations in patients with and without breakthrough infection were compared.Results
Pharmacokinetic data from each patient were readily described using the maximum a posteriori Bayesian estimates. There were only five patients that had a breakthrough infection while receiving voriconazole in the first 100 days post-HSCT. For these patients, there was no statistically significant relationship between the average AUC or average trough concentration and the probability of breakthrough infection [OR (95% CI) 1.026 (0.956-1.102) and 1.108 (0.475-2.581), respectively]. P value for these estimates was 0.474 and 0.813, respectively.Conclusions
Given the very small number of proven/probable infections, it was difficult to identify any differences in drug exposure in HSCT recipients with and without breakthrough fungal infections.