scholarly journals Creation and Assessment of a Clinical Predictive Calculator and Mortality Associated With Candida krusei Bloodstream Infections

2018 ◽  
Vol 5 (2) ◽  
Author(s):  
Ryan Kronen ◽  
Kevin Hsueh ◽  
Charlotte Lin ◽  
William G Powderly ◽  
Andrej Spec
Keyword(s):  
Clinical Decision Making ◽  
Cox Regression ◽  
Hematologic Malignancy ◽  
Vital Signs ◽  
Bloodstream Infections ◽  
Patient Characteristics ◽  
Clinical Decision ◽  
Mortality Rates ◽  
Candida Krusei ◽  
Crude Mortality

Abstract Background Candida krusei bloodstream infection (CK BSI) is associated with high mortality, but whether this is due to underlying comorbidities in affected patients or the organism itself is unknown. Identifying patient characteristics that are associated with CK BSI is crucial for clinical decision-making and prognosis. Methods We conducted a retrospective analysis of hospitalized patients with Candida BSI at our institution between 2002 and 2015. Data were collected on demographics, comorbidities, medications, procedures, central lines, vital signs, and laboratory values. Multivariable logistic and Cox regression were used to identify risk factors associated with CK and mortality, respectively. Results We identified 1873 individual patients who developed Candida BSI within the study period, 59 of whom had CK BSI. CK BSI was predicted by hematologic malignancy, gastric malignancy, neutropenia, and the use of prophylactic azole antifungals, monoclonal antibodies, and β-lactam/β-lactamase inhibitor combinations. The C-statistic was 0.86 (95% confidence interval, 0.81–0.91). The crude mortality rates were 64.4% for CK BSI and 41.4% for non-CK BSI. Although CK was associated with higher mortality in univariable Cox regression, this relationship was no longer significant with the addition of the following confounders: lymphoma, neutropenia, glucocorticoid use, chronic liver disease, and elevated creatinine. Conclusions Six patient comorbidities predicted the development of CK BSI with high accuracy. Although patients with CK BSI have higher crude mortality rates than patients with non-CK BSI, this difference is not significant when accounting for other patient characteristics.

scholarly journals Task Shifting: The Use of Laypersons for Acquisition of Vital Signs Data for Clinical Decision Making in the Emergency Room Following Traumatic Injury

2017 ◽  
Vol 41 (12) ◽  
pp. 3066-3073 ◽  
Author(s):  
Bryce E. Haac ◽  
Jared R. Gallaher ◽  
Charles Mabedi ◽  
Andrew J. Geyer ◽  
Anthony G. Charles
Keyword(s):  
Decision Making ◽  
Emergency Room ◽  
Clinical Decision Making ◽  
Traumatic Injury ◽  
Vital Signs ◽  
Clinical Decision ◽  
Task Shifting

scholarly journals Necrotizing fasciitis: presentation, microbiology and outcomes in a community hospital

2020 ◽  
Vol 7 (8) ◽  
pp. 2471
Author(s):  
Mercy N. Jimenez ◽  
Emily S. Seltzer ◽  
Bhavana Devanabanda ◽  
Martine Louis ◽  
Nageswara Mandava
Keyword(s):  
New York ◽  
Necrotizing Fasciitis ◽  
Clinical Decision Making ◽  
Community Hospital ◽  
Average Length ◽  
Retrospective Chart Review ◽  
Patient Characteristics ◽  
Clinical Decision ◽  
Blood Cultures ◽  
Average Length Of Stay

Background: Necrotizing fasciitis (NF) is an aggressive and often fatal, soft tissue infection. Delayed surgical therapy leads to worsened outcomes. This study evaluates the mortality, outcomes, and characteristics of patients with NF in a diverse New York City Community Hospital Network.Methods: Retrospective chart review from 2012 to 2019 using ICD-9 and ICD-10 codes of gas gangrene, Fournier’s gangrene, and necrotizing fasciitis was done. Of the 297 patients reviewed 28 met inclusion criteria of imaging findings, operative reports, and clinical diagnosis of NF by an attending surgeon.Results: On average patients in ER were seen by the surgical team within less than 12 hours. Most patients were debrided within 10 hours of surgical consultation and on average received 2.2 procedures. Of the wound cultures obtained 65.38% were polymicrobial in nature. The average length of stay was 17.4 days and 32% of patients required ICU admission. The surgical mortality rate was 7.61%.Conclusions: Necrotizing fasciitis is a rare entity and increasing provider knowledge on patient characteristics as well as the complexity of these patients and the types and number of procedures they require may help guide clinical decision making. We identified that while most of our patients had negative blood cultures on admission, those that had positive blood cultures had multiple organisms growing. Knowing that these patients are complex and likely require multiple procedures, prompt operative intervention is key.

scholarly journals Vital signs assessed in initial clinical encounters predict COVID-19 mortality in an NYC hospital system

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Elza Rechtman ◽  
Paul Curtin ◽  
Esmeralda Navarro ◽  
Sharon Nirenberg ◽  
Megan K. Horton
Keyword(s):  
Machine Learning ◽  
New York ◽  
Clinical Decision Making ◽  
Care Delivery ◽  
Vital Signs ◽  
Clinical Decision ◽  
Rapid Identification ◽  
Gradient Boosting ◽  
Hospital System ◽  
Response Strategies

AbstractTimely and effective clinical decision-making for COVID-19 requires rapid identification of risk factors for disease outcomes. Our objective was to identify characteristics available immediately upon first clinical evaluation related COVID-19 mortality. We conducted a retrospective study of 8770 laboratory-confirmed cases of SARS-CoV-2 from a network of 53 facilities in New-York City. We analysed 3 classes of variables; demographic, clinical, and comorbid factors, in a two-tiered analysis that included traditional regression strategies and machine learning. COVID-19 mortality was 12.7%. Logistic regression identified older age (OR, 1.69 [95% CI 1.66–1.92]), male sex (OR, 1.57 [95% CI 1.30–1.90]), higher BMI (OR, 1.03 [95% CI 1.102–1.05]), higher heart rate (OR, 1.01 [95% CI 1.00–1.01]), higher respiratory rate (OR, 1.05 [95% CI 1.03–1.07]), lower oxygen saturation (OR, 0.94 [95% CI 0.93–0.96]), and chronic kidney disease (OR, 1.53 [95% CI 1.20–1.95]) were associated with COVID-19 mortality. Using gradient-boosting machine learning, these factors predicted COVID-19 related mortality (AUC = 0.86) following cross-validation in a training set. Immediate, objective and culturally generalizable measures accessible upon clinical presentation are effective predictors of COVID-19 outcome. These findings may inform rapid response strategies to optimize health care delivery in parts of the world who have not yet confronted this epidemic, as well as in those forecasting a possible second outbreak.

scholarly journals A prospective evaluation of the Flacker-Kiely One Year Mortality Score and the added value of NT-proBNP

2020 ◽  
Vol 11 (2) ◽  
pp. 13
Author(s):  
Kjell Krüger ◽  
Bård R. Kittang ◽  
Sabine P. Solheim ◽  
Kristian Jansen
Keyword(s):  
Heart Failure ◽  
Failure Criterion ◽  
Clinical Decision Making ◽  
Cox Regression ◽  
Clinical Decision ◽  
Blood Chemistry ◽  
Discriminatory Power ◽  
Added Value ◽  
Youden Index ◽  
Mortality Data

Objective: Several mortality indices have been constructed to aid clinical decision making in older adults. We aimed to prospectively validate the Flacker-Kiely (FK) mortality index in a Norwegian nursing home cohort, which has not been done before, and explore whether NT-ProBNP could improve its discriminatory power.Methods: We performed a cohort/mortality study. From November 2017 to July 2018, physicians in all public long-term nursing homes in Bergen, Norway, scored residents according to the original Flacker Kiely index. Mortality data were derived from the Norwegian Cause of Death Registry and NT-ProBNP values were obtained from routinely collected blood chemistry. An alternative FK index using the NT-ProBNP-value as a marker for the presence of heart failure was constructed (FK NT-ProBNP index). The ProBNP cut-off value was selected based on a Cox regression model (“dead/alive 1 year”/” NT-ProBNP (Ng/l)”, where the value with the highest Youden index was identified. We judged index performance by using c-statistics.Results: Both the original FK index and the constructed FK NT-ProBNP index discriminated between risk strata. The FK NT-ProBNP index yielded a C-index of 0.66 compared to 0.62 for the original FK index. Optimal discriminatory power was shown with a NT-ProBNP cut-off value of 1,595 Ng/l as heart failure criterion, and FK NT-ProBNP score 6.6.Conclusions: The prospective mortality estimation ability of the FK-index was comparable to previous retrospective studies. The inclusion of NT-ProBNP as a heart failure criterion strengthen the discriminatory power and utility of the index, both in clinic and administration.

scholarly journals Case-based surveillance of antimicrobial resistance with full susceptibility profiles

2019 ◽  
Vol 1 (3) ◽  
Author(s):  
Sukhyun Ryu ◽  
Benjamin J Cowling ◽  
Peng Wu ◽  
Scott Olesen ◽  
Christophe Fraser ◽  
...  
Keyword(s):  
Public Health ◽  
Antimicrobial Resistance ◽  
Clinical Decision Making ◽  
Clinical Importance ◽  
Patient Characteristics ◽  
Clinical Decision ◽  
Control Measures ◽  
Resistant Bacteria ◽  
Susceptibility Profiles ◽  
Case Based

Abstract Surveillance of antimicrobial resistance (AMR) is essential for clinical decision-making and for public health authorities to monitor patterns in resistance and evaluate the effectiveness of interventions and control measures. Existing AMR surveillance is typically based on reports from hospital laboratories and public health laboratories, comprising reports of pathogen frequencies and resistance frequencies among each species detected. Here we propose an improved framework for AMR surveillance, in which the unit of surveillance is patients with specific conditions, rather than biological samples of a particular type. In this ‘case-based’ surveillance, denominators as well as numerators will be clearly defined with clinical relevance and more comparable at the local, national and international level. In locations with sufficient resources, individual-based data on patient characteristics and full antibiotic susceptibility profiles would provide high-quality evidence for monitoring resistant pathogens of clinical importance, clinical treatment of infections and public health responses to outbreaks of infections with resistant bacteria.

scholarly journals Dantrolene in the treatment of MDMA-related hyperpyrexia: a systematic review

CJEM ◽  
2010 ◽  
Vol 12 (05) ◽  
pp. 435-442 ◽  
Author(s):  
Brian E. Grunau ◽  
Matthew O. Wiens ◽  
Jeffrey R. Brubacher
Keyword(s):  
Systematic Review ◽  
Clinical Decision Making ◽  
Case Reports ◽  
Data Extraction ◽  
Patient Characteristics ◽  
Clinical Decision ◽  
Poison Control ◽  
Published Data ◽  
Published Evidence

ABSTRACTObjective:The use of dantrolene in the treatment of hyperpyrexia related to MDMA (3,4-methylenedioxymethamphetamine) is controversial, with little data available to guide clinical decision-making. Although the treatment is recommended by several poison control centres, published data are primarily in the form of case reports and animal and in vitro experiments. We conducted a systematic review to investigate the published evidence regarding the safety and benefits of dantrolene for MDMA-related hyperpyrexia in humans.Data sources:A systematic search of Embase and MEDLINE was conducted from the earliest possible date to November 2008.Study selection:All human trials and case reports of MDMA-related hyperpyrexia were considered.Data extraction:Data were abstracted systematically and characteristics including use of dantrolene, adverse reactions attributed to dantrolene, peak temperature, complications from MDMA-related hyperpyrexia and survival were recorded.Data synthesis:Our search yielded 668 articles of which 53, reporting 71 cases of MDMA-induced hyperpyrexia, met our inclusion criteria. No clinical trials, randomized controlled trials, observational studies or meta-analyses were identified. Dantrolene was used in 26 cases. Patient characteristics were similar in the dantrolene and no dantrolene groups. The proportion of survivors was higher in the dantrolene group (21/26) than in the no dantrolene group (25/45). This difference was especially pronounced in those with extreme (≥ 42°C) and severe (≥ 40°C) fever, with a survival rate of 8 of 13 and 10 of 10, respectively, in the dantrolene group compared with 0 of 4 and 15 of 27 in the no dantrolene group. There were no reports of adverse events attributable to dantrolene with the exception of a possible association with an episode of transient hypoglycemia.Conclusion:Our systematic review suggests that dantrolene is safe for patients with MDMA-related hyperpyrexia. Dantrolene may also be associated with improved survival and reduced complications, especially in patients with extreme (≥ 42°C) or severe (≥ 40°C) hyperpyrexia, although this conclusion must be interpreted with caution given the risk of reporting or publication bias.

Trends in COVID-19 Risk-Adjusted Mortality Rates

2020 ◽  
Author(s):  
Leora I Horwitz ◽  
Simon A Jones ◽  
Robert J Cerfolio ◽  
Fritz Francois ◽  
Joseph Greco ◽  
...  
Keyword(s):  
New York ◽  
Hospital Mortality ◽  
Health System ◽  
Vital Signs ◽  
Patient Characteristics ◽  
Mortality Rates ◽  
Standardized Mortality Ratio ◽  
Marginal Effect ◽  
Average Probability ◽  
Mortality Ratio

Early reports showed high mortality from coronavirus disease 2019 (COVID-19). Mortality rates have recently been lower, raising hope that treatments have improved. However, patients are also now younger, with fewer comorbidities. We explored whether hospital mortality was associated with changing demographics at a 3-hospital academic health system in New York. We examined in-hospital mortality or discharge to hospice from March through August 2020, adjusted for demographic and clinical factors, including comorbidities, admission vital signs, and laboratory results. Among 5,121 hospitalizations, adjusted mortality dropped from 25.6% (95% CI, 23.2-28.1) in March to 7.6% (95% CI, 2.5-17.8) in August. The standardized mortality ratio dropped from 1.26 (95% CI, 1.15-1.39) in March to 0.38 (95% CI, 0.12-0.88) in August, at which time the average probability of death (average marginal effect) was 18.2 percentage points lower than in March. Data from one health system suggest that mortality from COVID-19 is decreasing even after accounting for patient characteristics.

scholarly journals NLP Methods for Extraction of Symptoms from Unstructured Data for Use in Prognostic COVID-19 Analytic Models

2021 ◽  
Vol 72 ◽  
pp. 429-474
Author(s):  
Greg M. Silverman ◽  
Himanshu S. Sahoo ◽  
Nicholas E. Ingraham ◽  
Monica Lupei ◽  
Michael A. Puskarich ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Clinical Decision Making ◽  
Quality Care ◽  
Vital Signs ◽  
Clinical Decision ◽  
Prognostic Models ◽  
P Value ◽  
Rule Based ◽  
Presenting Symptoms ◽  
Increased Risk

Statistical modeling of outcomes based on a patient's presenting symptoms (symptomatology) can help deliver high quality care and allocate essential resources, which is especially important during the COVID-19 pandemic. Patient symptoms are typically found in unstructured notes, and thus not readily available for clinical decision making. In an attempt to fill this gap, this study compared two methods for symptom extraction from Emergency Department (ED) admission notes. Both methods utilized a lexicon derived by expanding The Center for Disease Control and Prevention's (CDC) Symptoms of Coronavirus list. The first method utilized a word2vec model to expand the lexicon using a dictionary mapping to the Uni ed Medical Language System (UMLS). The second method utilized the expanded lexicon as a rule-based gazetteer and the UMLS. These methods were evaluated against a manually annotated reference (f1-score of 0.87 for UMLS-based ensemble; and 0.85 for rule-based gazetteer with UMLS). Through analyses of associations of extracted symptoms used as features against various outcomes, salient risks among the population of COVID-19 patients, including increased risk of in-hospital mortality (OR 1.85, p-value < 0.001), were identified for patients presenting with dyspnea. Disparities between English and non-English speaking patients were also identified, the most salient being a concerning finding of opposing risk signals between fatigue and in-hospital mortality (non-English: OR 1.95, p-value = 0.02; English: OR 0.63, p-value = 0.01). While use of symptomatology for modeling of outcomes is not unique, unlike previous studies this study showed that models built using symptoms with the outcome of in-hospital mortality were not significantly different from models using data collected during an in-patient encounter (AUC of 0.9 with 95% CI of [0.88, 0.91] using only vital signs; AUC of 0.87 with 95% CI of [0.85, 0.88] using only symptoms). These findings indicate that prognostic models based on symptomatology could aid in extending COVID-19 patient care through telemedicine, replacing the need for in-person options. The methods presented in this study have potential for use in development of symptomatology-based models for other diseases, including for the study of Post-Acute Sequelae of COVID-19 (PASC).

scholarly journals Prognostic Factors and a Nomogram Predicting Overall Survival in Patients with Limb Chondrosarcomas: A Population-Based Study

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Xinjie Wu ◽  
Yanlei Wang ◽  
Wei Sun ◽  
Mingsheng Tan
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Clinical Decision Making ◽  
Proportional Hazards ◽  
Cox Regression ◽  
Training Group ◽  
Clinical Decision ◽  
The United States ◽  
Cox Proportional Hazards ◽  
Predictive Values

Introduction. We aimed to develop and validate a nomogram for predicting the overall survival of patients with limb chondrosarcomas. Methods. The Surveillance, Epidemiology, and End Results (SEER) program database was used to identify patients diagnosed with chondrosarcomas, from which data was extracted from 18 registries in the United States between 1973 and 2016. A total of 813 patients were selected from the database. Univariate and multivariate analyses were performed using Cox proportional hazards regression models on the training group to identify independent prognostic factors and construct a nomogram to predict the 3- and 5-year survival probability of patients with limb chondrosarcomas. The predictive values were compared using concordance indexes ( C -indexes) and calibration plots. Results. All 813 patients were randomly divided into a training group ( n = 572 ) and a validation group ( n = 241 ). After univariate and multivariate Cox regression, a nomogram was constructed based on a new model containing the predictive variables of age, site, grade, tumor size, histology, stage, and use of surgery, radiotherapy, or chemotherapy. The prediction model provided excellent C -indexes (0.86 and 0.77 in the training and validation groups, respectively). The good discrimination and calibration of the nomograms were demonstrated for both the training and validation groups. Conclusions. The nomograms precisely and individually predict the overall survival of patients with limb chondrosarcomas and could assist personalized prognostic evaluation and individualized clinical decision-making.

scholarly journals Trends in Pediatric Candidemia: Epidemiology, Anti-Fungal Susceptibility and Patient Characteristics in a Children’s Hospital

2020 ◽  
Author(s):  
Anabel Piqueras ◽  
Lakshmi Ganapathi ◽  
Jane F. Carpenter ◽  
Thomas Rubio ◽  
Thomas J. Sandora ◽  
...  
Keyword(s):  
Incidence Rate ◽  
Antifungal Agent ◽  
Neonatal Intensive Care ◽  
Clinical Decision Making ◽  
Species Distributions ◽  
Bloodstream Infections ◽  
Clinical Decision ◽  
The United States ◽  
Morbidity And Mortality ◽  
Susceptibility Patterns

Background. Candida bloodstream infections (CBSIs) have decreased among pediatric populations in the United States, but remain an important cause of morbidity and mortality. Species distributions and susceptibility patterns of CBSI isolates diverge widely between children and adults. Awareness of these patterns can inform clinical decision-making for empiric or pre-emptive therapy of children at risk for candidemia. Methods. CBSIs occurring from 2006-2016 among patients in a large children&rsquo;s hospital were analyzed for age specific trends in incidence rate, risk factors for breakthrough-CBSI and death, as well as underlying conditions. Candida species distributions and susceptibility patterns were evaluated in addition to antifungal agent use. Results. The overall incidence rate of CBSI among this complex patient population was 1.97/1,000 patient-days. About half of CBSI episodes occurred in immunocompetent children and 14% in Neonatal Intensive Care Unit (NICU) patients. Antifungal resistance was minimal: 96.7% of isolates were fluconazole-, 99% were micafungin-, and all were amphotericin susceptible. Liposomal amphotericin was the most commonly prescribed antifungal agent including for NICU patients. Overall CBSI-associated mortality was 13.7%; there were no deaths associated with CBSI among NICU patients after 2011. Conclusions. Pediatric CBSI characteristics differ substantially from those in adults. Improved management of underlying diseases and antimicrobial stewardship may further decrease morbidity and mortality from CBSI while continuing to maintain low resistance rates among Candida isolates.

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