Dynamic Scoring System Research Articles

Dynamic predictive scores for cardiac surgery-associated agitated delirium: a single-center retrospective observational study

BackgroundPrevention, screening, and early treatment are the aims of postoperative delirium management. The scoring system is an objective and effective tool to stratify potential delirium risk for patients undergoing cardiac surgery.MethodsPatients who underwent cardiac surgery between January 1, 2012, and January 1, 2019, were enrolled in our retrospective study. The patients were divided into a derivation cohort (n = 45,744) and a validation cohort (n = 11,436). The AD predictive systems were formulated using multivariate logistic regression analysis at three time points: preoperation, ICU admittance, and 24 h after ICU admittance.ResultsThe prevalence of AD after cardiac surgery in the whole cohort was 3.6% (2,085/57,180). The dynamic scoring system included preoperative LVEF ≤ 45%, serum creatinine > 100 µmol/L, emergency surgery, coronary artery disease, hemorrhage volume > 600 mL, intraoperative platelet or plasma use, and postoperative LVEF ≤ 45%. The area under the receiver operating characteristic curve (AUC) values for AD prediction were 0.68 (preoperative), 0.74 (on the day of ICU admission), and 0.75 (postoperative). The Hosmer‒Lemeshow test indicated that the calibration of the preoperative prediction model was poor (P = 0.01), whereas that of the pre- and intraoperative prediction model (P = 0.49) and the pre, intra- and postoperative prediction model (P = 0.35) was good.ConclusionsUsing perioperative data, we developed a dynamic scoring system for predicting the risk of AD following cardiac surgery. The dynamic scoring system may improve the early recognition of and the interventions for AD.

Managing surgical waiting lists through dynamic priority scoring

Prioritising elective surgery patients under the Australian three-category system is inherently subjective due to variability in clinician decision making and the potential for extraneous factors to influence category assignment. As a result, waiting time inequities can exist which may lead to adverse health outcomes and increased morbidity, especially for patients deemed to be low priority. This study investigated the use of a dynamic priority scoring (DPS) system to rank elective surgery patients more equitably, based on a combination of waiting time and clinical factors. Such a system enables patients to progress on the waiting list in a more objective and transparent manner, at a rate relative to their clinical need. Simulation results comparing the two systems indicate that the DPS system has potential to assist in managing waiting lists by standardising waiting times relative to urgency category, in addition to improving waiting time consistency for patients of similar clinical need. In clinical practice, this system is likely to reduce subjectivity, increase transparency, and improve overall efficiency of waiting list management by providing an objective metric to prioritise patients. Such a system is also likely to increase public trust and confidence in the systems used to manage waiting lists.

Improving the decision to switch from first- to second-line therapy in multiple sclerosis: A dynamic scoring system

Background: In relapsing-remitting multiple sclerosis (RRMS), early identification of suboptimal responders can prevent disability progression. Objective: We aimed to develop and validate a dynamic score to guide the early decision to switch from first- to second-line therapy. Methods: Using time-dependent propensity scores (PS) from a French cohort of 12,823 patients with RRMS, we constructed one training and two validation PS-matched cohorts to compare the switched patients to second-line treatment and the maintained patients. We used a frailty Cox model for predicting individual hazard ratios (iHRs). Results: From the validation PS-matched cohort of 348 independent patients with iHR ⩽ 0.69, we reported the 5-year relapse-free survival at 0.14 (95% confidence interval (CI) 0.09–0.22) for the waiting group and 0.40 (95% CI 0.32–0.51) for the switched group. From the validation PS-matched cohort of 518 independent patients with iHR > 0.69, these values were 0.37 (95% CI 0.30–0.46) and 0.44 (95% CI 0.37–0.52), respectively. Conclusions: By using the proposed dynamic score, we estimated that at least one-third of patients could benefit from an earlier switch to prevent relapse.

Reply to Supady et al. On the Use of Hemadsorption with CytoSorb in Patients with Septic Shock. Comment on "Kogelmann et al. First Evaluation of a New Dynamic Scoring System Intended to Support Prescription of Adjuvant CytoSorb Hemoadsorption Therapy in Patients with Septic Shock. J. Clin. Med. 2021, 10, 2939".

Thank you very much for your interest in our research [...].

Time-adjusted average Mayo endoscopic score predicts the risk of disease extent progression in distal ulcerative colitis patients.

BackgroundUlcerative colitis (UC) is a chronic lifelong disease. The disease extent of UC can progress over time. This study aimed to assess whether cumulative inflammatory burden (CIB) is associated with disease extension in distal UC (proctitis [E1] and left-sided colitis [E2]) patients, and to develop a quantified indicator of CIB.MethodsIn this retrospective study based on a prospective registry, distal UC patients receiving colonoscopies in Xijing Hospital (Xi’an, China) from January 2000 to May 2019 were studied. We developed a new score, namely the time-adjusted average Mayo endoscopic score (TA-MES), calculated as dividing the sum of the cumulative average MES over a period of surveillance time by the length of the endoscopic examination interval, to quantify the CIB. Cox regression was used to identify other potential risk factors.ResultsA total of 295 UC patients were followed for 1,487.02 patient-years. Among them, 140 patients (47.5%) experienced disease extension. Multivariate analysis showed that the TA-MES was significantly associated with disease extension in E1 (hazard ratio [HR], 2.90; 95% confidence interval [CI], 1.58–5.33, P = 0.001) and E2 (HR, 1.89; 95% CI, 1.16–3.09, P = 0.011) patients. Other risk factors included hemoglobin of <90 g/L and appendiceal skip inflammation; the protective factors included age, E2 at diagnosis, former smoking, and 5-aminosalicylic acid dose. Otherwise, MES at diagnosis, maximal MES, and mean MES failed to estimate the risk of disease extension.ConclusionTA-MES is a good quantified indicator of CIB and is independently associated with increased disease extension in distal UC patients. Whether the dynamic multiple scoring system could be used as a risk factor in other chronic relapsing–remitting diseases is a direction for future research.

On the Use of Hemadsorption with CytoSorb in Patients with Septic Shock. Comment on Kogelmann et al. First Evaluation of a New Dynamic Scoring System Intended to Support Prescription of Adjuvant CytoSorb Hemoadsorption Therapy in Patients with Septic Shock. J. Clin. Med. 2021, 10, 2939.

With great interest we read the article by Klaus Kogelmann and co-authors on the "First Evaluation of a New Dynamic Scoring System Intended to Support Prescription of Adjuvant CytoSorb Hemoadsorption Therapy in Patients with Septic Shock" [...].

114. Optimization of Inpatient Antibiotic Use via an Electronic Antimicrobial Stewardship Module and an Infectious Diseases Pharmacy Resident

BackgroundAntibiotic resistance is a public health crisis and antimicrobial stewardship (AMS) pharmacists serve a crucial role in preventing inappropriate use. At Montefiore Medical Center (1,500-bed hospital), a new electronic medical record AMS module was implemented with assistance from an infectious diseases (ID) pharmacy resident in October 2020. The module utilizes a dynamic scoring system to assist in prioritizing interventions, including bug-drug mismatches, insufficient coverage, or de-escalation. The AMS module is operationalized by ID pharmacists during the week and an ID pharmacy resident every other weekend. The objective of this study was to assess the impact of an ID pharmacy resident performing AMS module interventions on broad spectrum antibiotic use.MethodsAn observational study of AMS module interventions on antibiotic use (AU) in days of therapy per 1,000 days present and standardized antimicrobial administration ratio (SAAR) was performed. AU data for piperacillin-tazobactam (P/T) and SAAR prior to (October 2019– December 2019) and after (October 2020 – December 2020) the integration of an ID pharmacy resident and the AMS module was compared. Additional data collected included total number and type of interventions.ResultsA total of 539 interventions were made by AMS pharmacists and 36.5% of these were completed by the ID pharmacy resident. Across 6 different units, there was a statistically significant decrease in the SAAR for broad spectrum antibacterial agents (Figure 1), and a decrease of at least 10% in P/T use during the two different time periods (Table 1). An estimated P/T cost reduction of 26% of (&48,708 to &36,235.80) was observed. AMS pharmacists made 63 interventions in respective units. The top three intervention types were dose/frequency/duration recommendations, pharmacokinetic vancomycin dosing/monitoring, and de-escalation. The acceptance rate of interventions was 99% (534 accepted interventions/539 total interventions).Figure 1. SAAR Comparison of Broad-Spectrum Agents Table 1. AU Rate of Piperacillin-tazobactam ConclusionOverall, there was a statistically significant impact on SAARs and a >10% change in P/T AU rate with an estimated cost reduction >25% on select units after implementation of the AMS module with an ID pharmacy resident.Disclosures Kelsie Cowman, MPH, Merck (Research Grant or Support) Priya Nori, MD, Merck (Grant/Research Support) Priya Nori, MD, Nothing to disclose Yi Guo, PharmD, BCIDP, Merck (Research Grant or Support)

A Novel Machine Learning-Derived Dynamic Scoring System Predicts Risk of Thrombosis in Polycythemia Vera (PV) Patients

A Novel Machine Learning-Derived Dynamic Scoring System Predicts Risk of Thrombosis in Polycythemia Vera (PV) Patients

Diagnostic and prognostic scoring systems for autoimmune hepatitis: a review.

Auto-immune hepatitis (AIH) is a rare condition which primarily affects young women. Several diagnostic scoring systems exist based on clinical, biochemical, immunologic and histologic characteristics of AIH. Additionally, prognostic parameters can be identified. The purpose of this literature review is to compare the clinical value, strengths and limitations of these diagnostic and prognostic scoring systems. A literature search was performed in two databases and selected based on diagnostic and prognostic criteria. Only studies concerning AIH in adults were included. The backbone of scoring systems remains the revised AIH criteria published in 1999 and the simplified from 2008. The revised system shows a higher sensitivity, lower specificity and lower diagnostic accuracy compared to the simplified. Limitations to these scoring systems include limited diagnostic accuracy in acute or fulminant liver failure, insufficient inclusion of atypical auto-antibodies and lacking diagnostic power in presence of overlap syndromes. Concerning these overlap syndromes, the Paris criteria show a higher diagnostic accuracy compared to the scoring systems for AIH. Presently, no clinical prognostic scoring systems are available. However, a first system based on response to treatment accurately predicts long-term survival in AIH. Diagnostic scoring systems are useful in diagnosing AIH and have complementary value. However, they are no substitute for the gold standard of appropriate clinical assessment and are mostly useful in defining cohorts for research purposes. An evolution towards a more dynamic scoring system, using prognostic parameters and the progression of typical features, seems more valuable than the current diagnostic systems.

First Evaluation of a New Dynamic Scoring System Intended to Support Prescription of Adjuvant CytoSorb Hemoadsorption Therapy in Patients with Septic Shock.

Introduction: Despite advances in critical care medicine, adjunctive approaches in sepsis therapy have failed to prove their efficacy. Notwithstanding promising results using hemoadsorption (CytoSorb), questions remain concerning timing and dosing. We created a dynamic scoring system (DSS) to assess patients with early septic shock and performed a first evaluation of the system in this patient population. Methods: Data from 502 patients with septic shock according to Sepsis-3 criteria were retrospectively analyzed. Score parameters were documented at the time of diagnosis (T0) and 6 h later (T6) to calculate a dynamic score. Survival on day 7 and 56 as well as ICU and hospital mortality were analyzed in regard to the score as well as the delay of hemoadsorption therapy. Results: Of the 502 patients analyzed, 198 received adjunctive CytoSorb treatment and 304 received standard therapy. Septic shock was typically represented by 5 points, while >6 points indicated a situation refractory to standard therapy with the worst outcome in patients shown by >8 points. The differences in mortality between the score groups (<6, 6–8, >8 points) were significant. Analysis further showed a significant 56-day, ICU and hospital survival advantage in CytoSorb patients when therapy was started early. Conclusion: We created a scoring system allowing for the assessment of the clinical development of patients in the early phase of septic shock. Applying this approach, we were able to detect populations with a distinct mortality pattern. The data also showed that an early start of CytoSorb therapy was associated with significantly improved survival. As a next step, this easy-to-apply scoring system would require validation in a prospective manner to learn whether patients to be treated with hemoadsorption therapy in the course of septic shock could thereby be identified.

AÂ New Dynamic PET-Based Scoring System Improves Outcome Prediction in Patients with Diffuse Large B-Cell Lymphoma

Introduction:The PETAL trial is a multicenter randomized controlled study for patients with aggressive lymphomas of diverse histologies (EudraCT 2006-001641-33, NCT00554164). In patients with diffuse large B-cell lymphoma (DLBCL) interim PET (iPET) reliably predicted progression-free survival (PFS) and overall survival (OS). Interim PET-based treatment changes had no impact on outcome (ASH 2014, abstract 391; ASH 2016, abstract 1857). To further improve outcome prediction we developed a new dynamic scoring system combining baseline total metabolic tumor volume (TMTV) with age and early iPET response.Methods:TMTV was measured in 510 patients with newly diagnosed DLBCL participating in the PETAL trial. Patients aged 18 to 80 years with a positive baseline PET received 2 cycles of rituximab (R), cyclophosphamide, doxorubicin, vincristine and prednisone (CHOP) followed by iPET and randomisation. In total, patients received 6 or 8 cycles of standard R-CHOP or 2 cycles of R-CHOP followed by 6 cycles of an intensive protocol originally designed for the treatment of Burkitt's lymphoma. A favorable iPET was defined as a reduction of the maximum SUV by > 66% compared to baseline. By using the 41% maximum standardized uptake value (SUV41max) thresholding method, baseline TMTV was calculated. Cut-off values were determined by receiver operating characteristic (ROC) analysis. The Youden index was used to compute the optimal cut-off point. Kaplan-Meier survival analysis was performed to estimate PFS and OS. By using uni- and multivariate cox-regression prognostic factors were analyzed.Results:Median follow-up was 4.4 years. The optimal cut-off for baseline TMTV was identified to be 313 cm3 with 310 patients (60.8%) belonging to the low TMTV group (range, 0.91-306.24 cm3) and 200 patients (39.2 %) belonging to the high TMTV group (319.71-8895.88cm3). A low baseline TMTV (< 313 cm3) was associated with a significantly better 5-year PFS (77.1% vs. 50.2%, p < 0.0001) and 5-year OS (84.1% vs. 64.3%, p < 0.0001). By creating a new prognostic score based on age (> 60 years =1 point), baseline TMTV (≥ 313 cm3 =1 point) and early iPET response (unfavorable =1 point) we identified four different risk groups: low (0 points) with a 5-year PFS of 84.6% (95% confidence interval [CI] 74.5% - 90.9%) and a 5-year OS of 91.9% (CI 82.3% - 96.4%), intermediate (1 point) with a 5-year PFS of 68.5% (CI 61.3% - 74.6%, p = 0.0003, hazard ratio [HR] 2.78) and a 5-year OS of 79.8% (CI 73.5%-84.8%, p = 0.0054, HR 2.78), high (2 points) with a 5-year PFS of 46.8% (CI 36.5%-56.5%, p < 0.0001, HR 6.31) and a 5-year OS of 56.7% (CI 45.9%-66.2%, p < 0.0001, HR 8.15) and very high (3 points) with a 5-year PFS of 18.3% (CI 3.7%-41.8%, p < 0.0001, HR 14.91) and a 5-year OS of 23.3% (CI 6.2%-46.7%, p < 0.0001, HR 18.75).Conclusion:Baseline TMTV is highly predictive for outcome in patients with DLBCL. By combining baseline TMTV with age and early iPET response we developed a new and easy to apply PET-based scoring system that detects patients at high and very high risk of disease progression and early death. Compared to the International Prognostic Index [IPI] and the enhanced NCCN-IPI the new score provided much better separation of curves. [Display omitted] DisclosuresHüttmann:Bristol-Myers Squibb, Takeda, Celgene, Roche: Honoraria; Gilead, Amgen: Other: Travel cost.

Development of a Dynamic Diagnosis Grading System for Infertility Using Machine Learning

Many indicators need to be considered when judging the condition of patients with infertility, which makes diagnosis and treatment complicated. To construct a dynamic scoring system for infertility to assist clinicians in efficiently and accurately assessing the condition of patients with infertility. This prognostic study reviewed 95 868 medical records of couples with infertility in which women had undergone in vitro fertilization and embryo transfer at the Reproductive Center of Tongji Medical College, Huazhong University of Science and Technology, in Wuhan, Hubei, China, from January 2006 to May 2019. A dynamic diagnosis and grading system for infertility was constructed. The analysis was conducted between May 20, 2019, and April 15, 2020. Patients were divided into pregnant and nonpregnant groups according to eventual pregnancy results. The evaluation index system was constructed based on the test results of the significant difference between the 2 groups of indicators and the clinician's experience. Random forest machine learning was used to determine the weight of the index, and the entropy-based feature discretization algorithm classified the abnormality of the index and the patient's condition. A 10-fold cross-validation method was used to test the validity of the system. A total of 60 648 couples with infertility were enrolled, in which 15 021 women became pregnant, with a mean (SD) age of 30.30 (4.02) years. A total of 45 627 couples were in the nonpregnant group, with a mean (SD) age among women of 32.17 (5.58) years. Seven indicators were selected to build the dynamic grading system for patients with infertility: age, body mass index, follicle-stimulating hormone level, antral follicle count, anti-Mullerian hormone level, number of oocytes, and endometrial thickness. The importance weight of each indicator obtained by the random forest algorithm was 0.1748 for age, 0.0785 for body mass index, 0.0581 for follicle-stimulating hormone level, 0.1214 for antral follicle count, 0.1616 for anti-Mullerian hormone level, 0.2307 for number of oocytes, and 0.1749 for endometrial thickness. The grading system divided the condition of the patient with infertility into 5 grades from A to E. The worst E grade represented a 0.90% pregnancy rate, and the pregnancy rate in the A grade was 53.82%. The cross-validation results showed that the stability of the system was 95.94% (95% CI, 95.14%-96.74%). This machine learning-derived algorithm may assist clinicians in making an efficient and accurate initial judgment on the condition of patients with infertility.

Specialty Pharmacy and Physician Partnership Optimizes Clinical Pathway Adherence in Myelofibrosis (MF): Initial Analysis of a Quality Improvement Initiative

Specialty Pharmacy and Physician Partnership Optimizes Clinical Pathway Adherence in Myelofibrosis (MF): Initial Analysis of a Quality Improvement Initiative

Developing and validating a decision support tool for media selection to mitigate drainage waters

The nitrate nitrogen (NO3-N) and ammonium (NH4-N) and/or dissolved reactive phosphorus (DRP) load in drainage water from farms can be managed by reactive or biological media filters. The nutrient content of the drainage water can be obtained directly from water analysis, which immediately focuses attention on filter media selection. There are many factors that may be important before choosing a medium or media e.g. nutrient removal capacity, lifetime, hydraulic conductivity, the potential for “pollution swapping”, attenuation of non-target contaminants (e.g. pesticides, organic carbon, etc.), and local availability and transportation cost of media to site. In this study, a novel decision support tool (DST) was developed, which brought all these factors together in one place for five nutrient scenarios. A systematic literature review was conducted to create a database containing 75 media with an associated static scoring system across seven criteria (% of nutrient concentration reduction, removal of other pollutants, lifetime, hydraulic conductivity, negative externalities) and a dynamic scoring system across two criteria (delivery cost and availability). The DST was tested using case studies from Ireland, Belgium and USA with different agricultural practices and nutrient scenarios. It was then validated by SWOT (strength, weakness, opportunities and threats) analysis. The DST provided a rapid, easily modifiable screening of many media-based treatments for specific dual or single nutrient-based water drainage problems. This provides stakeholders (farmers/regulators/advisors) with a versatile, flexible and robust yet easy-to-understand framework to make informed choices on appropriate media-based mitigation measures according to users’ relevant technical, economic and logistical factors.

Development and application of dynamic scoring information system for critically ill patients

Objective To develop and preliminarily apply a dynamic scoring information system for critically ill patients to optimize the management system for critically ill patients. Methods Totally 55 risk factors of three groups were selected based on Acute Physiology and Chronic Health Evaluation Scoring System, Tiss-28 Scoring System 2, critical value and expert consensus and included in the information platform, which was connected to the hospital's information and data system. A dynamic scoring system was designed and developed independently. The system consisted of two modules: alarm and clinical decision-making. An operation protocol was made by the Department of Nursing and included into the nursing management system to ensure that the system could run effectively. Data of inpatients in Tenth People's Hospital of Tongji University from October 2015 to October 2017 was selected. The disease recognition of the dynamic scoring system and the existing MEWS alarm and scoring system and the success rate of treatment in critically ill patients before and after the dynamic scoring system was introduced were compared. Results The area under receiver operating characteristic curves (AUC-ROC) of the dynamic scoring system was 0.947 (95%CI 0.930-0.964) , which showed higher recognition of critical illness compared with the MEWS alarm and scoring system (P<0.05) . After the dynamic information system was introduced, the success rate of treatment in critically ill patients was 68.61%, which was higher than that before it was applied (χ2=10.046; P=0.002) . Conclusions The dynamic scoring system can accurately evaluate patients' disease and provide digital data and a list of clinical decisions for nurses, thus improving the success rate of treatment in critically ill patients and enhancing nurses' clinical decision-making ability. Key words: Critical illness; Scoring system; Informatization; Clinical decision-making; Alarm

Covering the Cover

Covering the Cover

Development and validation of the International Hidradenitis Suppurativa Severity Score System (IHS4), a novel dynamic scoring system to assess HS severity.

A validated tool for the dynamic severity assessment of hidradenitis suppurativa/acne inversa (HS) is lacking. To develop and validate a novel dynamic scoring system to assess the severity of HS. A Delphi voting procedure was conducted among the members of the European Hidradenitis Suppurativa Foundation (EHSF) to achieve consensus towards an initial HS Severity Score System (HS4). Strengths and weaknesses of HS4 were examined by a multicentre prospective study. Multivariate logistic regression, discriminant analysis and receiver operating characteristic curves, as well as examination for correlation (Spearman's rho) and agreement (Cohen's kappa) with existing scores, were engaged to recognize the variables for a new International HS4 (IHS4) that was established by a second Delphi round. Consensus HS4 was based on number of skin lesions, number of skin areas involved and Dermatology Life Quality Index (DLQI), and was evaluated by a sample of 236 patients from 11 centres. Subsequently, a multivariate regression model calculated adjusted odds ratios for several clinical signs. Nodules, abscesses and draining tunnels resulted as the scoring variables. Three candidate scores were presented to the second Delphi round. The resulting IHS4 score is arrived at by the number of nodules (multiplied by 1) plus the number of abscesses (multiplied by 2) plus the number of draining tunnels (multiplied by 4). A total score of 3 or less signifies mild, 4-10 signifies moderate and 11 or higher signifies severe disease. Cohen's kappa was fair (κ = 0·32) compared with Hurley classification, and moderate (κ = 0·49) compared with Expert Opinion. Correlation was good (ρ > 0·6) with Hurley classification, Expert Opinion, Physician's Global Assessment and Modified Sartorius score, and moderate for DLQI (ρ = 0·36). The novel IHS4 is a validated tool to dynamically assess HS severity and can be used both in real-life and the clinical trials setting.

Development and Validation of a Chronic Pancreatitis Prognosis Score in 2 Independent Cohorts

The clinical course of chronic pancreatitis is unpredictable. There is no model to assess disease severity or progression or predict patient outcomes. We performed a prospective study of 91 patients with chronic pancreatitis; data were collected from patients seen at academic centers in Europe from January 2011 through April 2014. We analyzed correlations between clinical, laboratory, and imaging data with number of hospital readmissions and in-hospital days over the next 12 months; the parameters with the highest degree of correlation were used to develop a 3-stage chronic pancreatitis prognosis score (COPPS). The predictive strength was validated in 129 independent subjects identified from 2 prospective databases. The mean number of hospital admissions was 1.9 (95% confidence interval [CI], 1.39-2.44) and 15.2 for hospital days (95% CI, 10.76-19.71) for the development cohort and 10.9 for the validation cohort (95% CI, 7.54-14.30) (P= .08). Based on bivariate correlations, pain (numeric rating scale), level of glycated hemoglobin A1c, level of C-reactive protein, body mass index, and platelet count were used to develop the COPPS system. The patients' median COPPS was 8.9 points (range, 5-14). The system accurately discriminated stages of disease severity (low to high): A (5-6 points), B(7-9), and C (10-15). In Pearson correlation analysis of thedevelopment cohort, the COPPS correlated with hospital admissions (0.39; P < .01) and number of hospital days (0.33; P< .01). The correlation was validated in the validation set (Pearson correlation values of 0.36 and 0.44; P < .01). COPPS did not correlate with results from the Cambridge classification system. We developed and validated an easy to use dynamic multivariate scoring system, similar to the Child-Pugh-Score for liver cirrhosis. The COPPS allows objective monitoring of patients with chronic pancreatitis, determining risk for readmission to hospital and potential length of hospital stay.

Balancing the Efficacy and Safety of Implementing a Piperacillin/tazobactam (PTZ) Antibiotic Time-out

BackgroundWith the rise of antimicrobial resistance, the Centers for Disease Control and Joint Commission have promulgated a national initiative for antimicrobial stewardship programs (ASP). ASP use a multimodal approach such as antibiotic time outs to limit the duration of empiric therapy. Yale New Haven Hospital implemented the use of a 72-hour stop in the electronic medical system (EMR) for empiric PTZ orders. To mitigate the risk of orders inadvertently falling off, a dynamic scoring system was created in the EMR to alert pharmacists of expiring orders in real time. The primary objective of this study was to evaluate the duration of empiric PTZ prior to and after the implementation of the antibiotic time-out. Secondary outcomes included de-escalation, appropriateness of dosing, and safety.MethodsA retrospective cohort study using the EMR was conducted. Cases were defined as adult inpatients who had empiric orders for PTZ without positive cultures. The control group consisted of patients from September to October of 2014, prior to the 72-hour stop. The intervention group included patients from September to October of 2016. Due to the nationwide shortage of PTZ in 2015, this year was excluded in addition to patients with culture documented infections, stem cell/solid organ transplants or febrile neutropenia. Data collected included baseline demographics, renal function, PTZ dose, frequency and duration, indication and final antibiotic selection.ResultsOf the 537 random patients reviewed, 300 met inclusion criteria; 150 patients in the control group and 150 patients in the intervention group. The average duration of PTZ decreased from 4 days in the control group to 3 days in the intervention group (P = 0.0013). Overall antibiotic use decreased from 6 days in the control group to 5 days in the intervention group (P = <0.0001). There was an increase in the correct dose and frequency from 35% to 60% of orders in the intervention group compared with the control group (P = 0.004). With the aid of the scoring system, there were no orders that fell off inappropriately in the intervention group.ConclusionFollowing the successful implementation of a 72-hour antibiotic timeout we saw a significant decrease in the duration of empiric use, inappropriate dosing and an increase in the rate of antibiotic de-escalation.Disclosures All authors: No reported disclosures.

Comprehensive Genetic Analyses Of 213 PMF Patients Revealed 13% Of SRSF2 Mutations Being Strongly Correlated To ASXL1 Mutations

IntroductionPrimary myelofibrosis (PMF) is a myeloproliferative neoplasm, characterized amongst others by stem-cell derived clonal myeloproliferation, bone marrow fibrosis, anemia, splenomegaly, constitutional symptoms and leukemic progression. Diagnosis is based in most cases on cytomorphology/histology demonstrating fibrosis as well as on mutations in JAK2 or MPL. The Dynamic Prognostic Scoring System (DIPSS)-plus is the current base for prognostication using different clinical parameters including karyotype. Furthermore, molecular genetic alterations are currently addressed to provide additional prognostic information. Recently, besides JAK2 and MPL further gene mutations have been described in a limited number of patients, including ASXL1 and SRSF2. AimTo analyze in a large cohort the frequency of SRSF2 and ASXL1 mutations in PMF patients, and to identify their prognostic impact in the context of other previously described gene mutations. Patients and MethodsDiagnosis was done according to WHO classification. The cohort comprised 82 female and 131 male patients. In all cases a BCR-ABL rearrangement was excluded by RT-PCR or fluorescence in situ hybridization. JAK2V617F mutation was analyzed in all cases by melting curve analysis, MPLW515 mutation was subsequently analyzed in JAK2V617 wild type (wt) patients. In addition, we analyzed all patients for SRSF2 mutations by Sanger sequencing of the mutational hot spot region coding for amino acid Pro95. Cytogenetics was available in 139 patients. Patients were grouped in favorable (n=121) and unfavorable (n=18) karyotypes based on the DIPSS-plus-scoring system. Based on the previously described correlation of SRSF2mut with ASXL1mut and SETBP1mut in other myeloid entities, SRSF2 mutated cases were also analyzed for mutations in ASXL1 and SETBP1by Sanger sequencing. Follow-up data was available for 136 patients. Results56% (120/213) of the patients showed JAK2V617F mutations and 18.0% (16/89) of JAK2wt patients carried a mutation in MPLW515 summing up to 65.1% of patients with an already established molecular marker. Of note, SRSF2 was mutated in 12.7% (27/213) of all PMF patients. Patients with SRSF2 mutation had higher white blood cell counts in comparison to SRSF2wt patients (20.00x109/L vs. 7.35x109/L; p=0.005), but there was no correlation to gender, age, hemoglobin level, platelet count or % of myeloblasts in the peripheral blood. In 17 SRSF2mut cases the karyotype was available, 12 were normal karyotype, while two cases showed an unfavorable karyotype according to DIPSS-plus with +8 and i(17)(q10), respectively. The remaining three aberrations belong to the favorable aberration group (del(20q), del(13q), and der(14)). There was no correlation of SRSF2 mutations to the cytogenetic subgroups normal karyotype (n=91) or DIPSS categories favorable and unfavorable aberrations. SRSF2 mutations were also equally distributed between both JAK2V617 or MPLW515 mutated and wild type cases. 18/27 SRSF2mut cases carried also either a JAK2 or MPL mutation, while 9 cases showed no additional JAK2 or MPL mutation. Therefore 30.6% patients remain that carry no mutation in at least one of the three genes investigated first. Interestingly, ASXL1 was frequently mutated in SRSF2 mutated patients (16/23 analyzed SRSF2mut patients) while none of the 24 analyzed SRSF2 mutated cases showed a mutation in SETBP1. To evaluate a potential influence of gene mutations on clinical outcome the overall survival (OS) was calculated. We could confirm that JAK2V617F had no prognostic impact. The same was true for MPLW515 mutations. In contrast to other studies we could not find any impact of SRSF2mutations on OS. Only cytogenetics, i.e. the normal karyotype showed a trend to a prognostic relevance: the median 3 year OS was 70.8% in patients with normal karyotype (n=56) but 58.8% in patients with cytogenetic aberrations (n=29; p=0.153). Conclusion1) SRSF2 is mutated in 13% of PMF patients. 2) SRSF2 mutated patients show frequently an additional ASXL1 mutation but no coincidence with SETBP1. 3) The prognostic relevance of cytogenetic aberrations was confirmed, while the molecular marker SRSF2 shows no impact on prognosis. Disclosures:Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Eder:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.