EP.FRI.650 Are we calculating and documenting the NELA Score pre-operatively?

2021 ◽  
Vol 108 (Supplement_7) ◽  
Author(s):  
Sakshi Rajain ◽  
Sita Kotecha ◽  
Harjeet Singh Narula
Keyword(s):  
Patient Care ◽  
Risk Score ◽  
Clinical Decision Making ◽  
Further Education ◽  
Emergency Laparotomy ◽  
Care Hospital ◽  
Common Procedure ◽  
Risk Calculation ◽  
Risk Of Death ◽  
Primary Care Hospital

Abstract Aim Emergency laparotomy is a common procedure associated with high risk of mortality and morbidity. NELA risk score calculation for patients undergoing emergency laparotomy improves the quality of patient care and compares the organisation of patient care provided to the outcomes following surgery. The aim of this study was to determine if NELA score was calculated and documented pre-laparotomy. Methods A retrospective analysis was conducted for patients who had emergency laparotomy at a primary care hospital in England. This study included reviewing the case notes and consent forms to assess if NELA risk score was calculated. Following further education of the surgical team, the audit loop was closed.The primary outcome was to identify not only calculation but also that the score was documented. Results Measures taken to enhance NELA risk calculation included theatre co-ordinator asking for NELA risk score while booking for laparotomy and documentation on the booking form and posters on surgical ward. Consequently, 40% notes included Scoring which improved to 70% after making the above changes.  Conclusion The NELA risk score should be calculated for all patients undergoing emergency laparotomy as it estimates an individual’s risk of death within 30 days of surgery. It also standardises the risk calculation among all laparotomy patients and aids in clinical decision making, therefore is vital to be calculated in pre-operative phase. To ensure it is correctly calculated at all times, regular teaching and updates of NELA score is recommended.

Debates in Dysphagia Management: How Do You Use Evidence-Based Practice in Your Dysphagia Patient Care?

2011 ◽  
Vol 20 (4) ◽  
pp. 121-123
Author(s):  
Jeri A. Logemann
Keyword(s):  
Decision Making ◽  
Patient Care ◽  
Clinical Outcomes ◽  
Clinical Judgment ◽  
Clinical Decision Making ◽  
Evidence Based Practice ◽  
Clinical Decision ◽  
Evidence Based ◽  
Clinical Method ◽  
Do So

Evidence-based practice requires astute clinicians to blend our best clinical judgment with the best available external evidence and the patient's own values and expectations. Sometimes, we value one more than another during clinical decision-making, though it is never wise to do so, and sometimes other factors that we are unaware of produce unanticipated clinical outcomes. Sometimes, we feel very strongly about one clinical method or another, and hopefully that belief is founded in evidence. Some beliefs, however, are not founded in evidence. The sound use of evidence is the best way to navigate the debates within our field of practice.

scholarly journals Contamination of Healthcare Worker Personal Protective Equipment with MRSA Outside the Intensive Care Unit Setting

2020 ◽  
Vol 41 (S1) ◽  
pp. s27-s28
Author(s):  
Gita Nadimpalli ◽  
Lisa Pineles ◽  
Karly Lebherz ◽  
J. Kristie Johnson ◽  
David Calfee ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Patient Care ◽  
Direct Patient Care ◽  
Care Group ◽  
Surveillance Culture ◽  
Care Hospital ◽  
Contact Precautions ◽  
Patient Interactions ◽  
The Right

Background: Estimates of contamination of healthcare personnel (HCP) gloves and gowns with methicillin-resistant Staphylococcus aureus (MRSA) following interactions with colonized or infected patients range from 17% to 20%. Most studies were conducted in the intensive care unit (ICU) setting where patients had a recent positive clinical culture. The aim of this study was to determine the rate of MRSA transmission to HCP gloves and gown in non-ICU acute-care hospital units and to identify associated risk factors. Methods: Patients on contact precautions with history of MRSA colonization or infection admitted to non-ICU settings were randomly selected from electronic health records. We observed patient care activities and cultured the gloves and gowns of 10 HCP interactions per patient prior to doffing. Cultures from patients’ anterior nares, chest, antecubital fossa and perianal area were collected to quantify bacterial bioburden. Bacterial counts were log transformed. Results: We observed 55 patients (Fig. 1), and 517 HCP–patient interactions. Of the HCP–patient interactions, 16 (3.1%) led to MRSA contamination of HCP gloves, 18 (3.5%) led to contamination of HCP gown, and 28 (5.4%) led to contamination of either gloves or gown. In addition, 5 (12.8%) patients had a positive clinical or surveillance culture for MRSA in the prior 7 days. Nurses, physicians and technicians were grouped in “direct patient care”, and rest of the HCPs were included in “no direct care group.” Of 404 interactions, 26 (6.4%) of providers in the “direct patient care” group showed transmission of MRSA to gloves or gown in comparison to 2 of 113 (1.8%) interactions involving providers in the “no direct patient care” group (P = .05) (Fig. 2). The median MRSA bioburden was 0 log 10CFU/mL in the nares (range, 0–3.6), perianal region (range, 0–3.5), the arm skin (range, 0-0.3), and the chest skin (range, 0–6.2). Detectable bioburden on patients was negatively correlated with the time since placed on contact precautions (rs= −0.06; P < .001). Of 97 observations with detectable bacterial bioburden at any site, 9 (9.3%) resulted in transmission of MRSA to HCP in comparison to 11 (3.6%) of 310 observations with no detectable bioburden at all sites (P = .03). Conclusions: Transmission of MRSA to gloves or gowns of HCP caring for patients on contact precautions for MRSA in non-ICU settings was lower than in the ICU setting. More evidence is needed to help guide the optimal use of contact precautions for the right patient, in the right setting, for the right type of encounter.Funding: NoneDisclosures: None

scholarly journals Temporal Changes in Central-Line–Associated Bloodstream Infection Time Between Events, 2017–2018 Versus 2015–2016

2020 ◽  
Vol 41 (S1) ◽  
pp. s403-s404
Author(s):  
Jonathan Edwards ◽  
Katherine Allen-Bridson ◽  
Daniel Pollock
Keyword(s):  
Length Of Stay ◽  
Patient Care ◽  
Average Length ◽  
Bloodstream Infections ◽  
Central Line ◽  
Significant Shift ◽  
Care Hospital ◽  
Average Length Of Stay ◽  
Period 2 ◽  
Hospital Bed

Background: The CDC NHSN surveillance coverage includes central-line–associated bloodstream infections (CLABSIs) in acute-care hospital intensive care units (ICUs) and select patient-care wards across all 50 states. This surveillance enables the use of CLABSI data to measure time between events (TBE) as a potential metric to complement traditional incidence measures such as the standardized infection ratio and prevention progress. Methods: The TBEs were calculated using 37,705 CLABSI events reported to the NHSN during 2015–2018 from medical, medical-surgical, and surgical ICUs as well as patient-care wards. The CLABSI TBE data were combined into 2 separate pairs of consecutive years of data for comparison, namely, 2015–2016 (period 1) and 2017–2018 (period 2). To reduce the length bias, CLABSI TBEs were truncated for period 2 at the maximum for period 1; thereby, 1,292 CLABSI events were excluded. The medians of the CLABSI TBE distributions were compared over the 2 periods for each patient care location. Quantile regression models stratified by location were used to account for factors independently associated with CLABSI TBE, such as hospital bed size and average length of stay, and were used to measure the adjusted shift in median CLABSI TBE. Results: The unadjusted median CLABSI TBE shifted significantly from period 1 to period 2 for the patient care locations studied. The shift ranged from 20 to 75.5 days, all with 95% CIs ranging from 10.2 to 32.8, respectively, and P < .0001 (Fig. 1). Accounting for independent associations of CLABSI TBE with hospital bed size and average length of stay, the adjusted shift in median CLABSI TBE remained significant for each patient care location that was reduced by ∼15% (Table 1). Conclusions: Differences in the unadjusted median CLABSI TBE between period 1 and period 2 for all patient care locations demonstrate the feasibility of using TBE for setting benchmarks and tracking prevention progress. Furthermore, after adjusting for hospital bed size and average length of stay, a significant shift in the median CLABSI TBE persisted among all patient care locations, indicating that differences in patient populations alone likely do not account for differences in TBE. These findings regarding CLABSI TBEs warrant further exploration of potential shifts at additional quantiles, which would provide additional evidence that TBE is a metric that can be used for setting benchmarks and can serve as a signal of CLABSI prevention progress.Funding: NoneDisclosures: None

scholarly journals The REASON score: an epigenetic and clinicopathologic score to predict risk of poor survival in patients with early stage oral squamous cell carcinoma

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Chi T. Viet ◽  
Gary Yu ◽  
Kesava Asam ◽  
Carissa M. Thomas ◽  
Angela J. Yoon ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Early Stage ◽  
Genome Wide Association Studies ◽  
Gene Methylation ◽  
Poor Survival ◽  
Risk Of Death

Abstract Background Oral squamous cell carcinoma (OSCC) is a capricious cancer with poor survival rates, even for early-stage patients. There is a pressing need to develop more precise risk assessment methods to appropriately tailor clinical treatment. Genome-wide association studies have not produced a viable biomarker. However, these studies are limited by using heterogeneous cohorts, not focusing on methylation although OSCC is a heavily epigenetically-regulated cancer, and not combining molecular data with clinicopathologic data for risk prediction. In this study we focused on early-stage (I/II) OSCC and created a risk score called the REASON score, which combines clinicopathologic characteristics with a 12-gene methylation signature, to predict the risk of 5-year mortality. Methods We combined data from an internal cohort (n = 515) and The Cancer Genome Atlas (TCGA) cohort (n = 58). We collected clinicopathologic data from both cohorts to derive the non-molecular portion of the REASON score. We then analyzed the TCGA cohort DNA methylation data to derive the molecular portion of the risk score. Results 5-year disease specific survival was 63% for the internal cohort and 86% for the TCGA cohort. The clinicopathologic features with the highest predictive ability among the two the cohorts were age, race, sex, tobacco use, alcohol use, histologic grade, stage, perineural invasion (PNI), lymphovascular invasion (LVI), and margin status. This panel of 10 non-molecular features predicted 5-year mortality risk with a concordance (c)-index = 0.67. Our molecular panel consisted of a 12-gene methylation signature (i.e., HORMAD2, MYLK, GPR133, SOX8, TRPA1, ABCA2, HGFAC, MCPH1, WDR86, CACNA1H, RNF216, CCNJL), which had the most significant differential methylation between patients who survived vs. died by 5 years. All 12 genes have already been linked to survival in other cancers. Of the genes, only SOX8 was previously associated with OSCC; our study was the first to link the remaining 11 genes to OSCC survival. The combined molecular and non-molecular panel formed the REASON score, which predicted risk of death with a c-index = 0.915. Conclusions The REASON score is a promising biomarker to predict risk of mortality in early-stage OSCC patients. Validation of the REASON score in a larger independent cohort is warranted.

scholarly journals Broad-based SARS-CoV-2 Testing Program for Healthcare Workers in a Primary Care Hospital In France

2021 ◽  
Author(s):  
Julie Chas ◽  
Marine Nadal ◽  
Martin Siguier ◽  
Anne Fajac ◽  
Michel Denis ◽  
...  
Keyword(s):  
Primary Care ◽  
Healthcare Workers ◽  
Care Hospital ◽  
Testing Program ◽  
Primary Care Hospital

scholarly journals Infection Prevention Time Required for Construction and Design at a Large Tertiary-Care Hospital, 2019

2020 ◽  
Vol 41 (S1) ◽  
pp. s69-s70
Author(s):  
Angie Dains ◽  
Michael Edmond ◽  
Daniel Diekema ◽  
Stephanie Holley ◽  
Oluchi Abosi ◽  
...  
Keyword(s):  
Infection Control ◽  
Patient Care ◽  
Construction Projects ◽  
Small Scale ◽  
Care Hospital ◽  
Class Iii ◽  
Construction Sites ◽  
Wide Range ◽  
Time Required ◽  
Class Iv

Background: Including infection preventionists (IPs) in hospital design, construction, and renovation projects is important. According to the Joint Commission, “Infection control oversights during building design or renovations commonly result in regulatory problems, millions lost and even patient deaths.” We evaluated the number of active major construction projects at our 800-bed hospital with 6.0 IP FTEs and the IP time required for oversight. Methods: We reviewed construction records from October 2018 through October 2019. We classified projects as active if any construction occurred during the study period. We describe the types of projects: inpatient, outpatient, non–patient care, and the potential impact to patient health through infection control risk assessments (ICRA). ICRAs were classified as class I (non–patient-care area and minimal construction activity), class II (patients are not likely to be in the area and work is small scale), class III (patient care area and work requires demolition that generates dust), and class IV (any area requiring environmental precautions). We calculated the time spent visiting construction sites and in design meetings. Results: During October 2018–October 2019, there were 51 active construction projects with an average of 15 active sites per week. These sites included a wide range of projects from a new bone marrow transplant unit, labor and delivery expansion and renovation, space conversion to an inpatient unit to a project for multiple air handler replacements. All 51 projects were classified as class III or class IV. We visited, on average, 4 construction sites each week for 30 minutes per site, leaving 11 sites unobserved due to time constraints. We spent an average of 120 minutes weekly, but 450 minutes would have been required to observe all 15 sites. Yearly, the required hours to observe these active construction sites once weekly would be 390 hours. In addition to the observational hours, 124 hours were spent in design meetings alone, not considering the preparation time and follow-up required for these meetings. Conclusions: In a large academic medical center, IPs had time available to visit only a quarter of active projects on an ongoing basis. Increasing dedicated IP time in construction projects is essential to mitigating infection control risks in large hospitals.Funding: NoneDisclosures: None

Risk Stratification of Patients Undergoing Primary Pci for Stemi Using Dynamic Timi Risk Score at A Tertiary Care Cardiac Center

2021 ◽  
Vol 15 (11) ◽  
pp. 3252-3256
Author(s):  
Jehangir Hasan ◽  
Muhammad Hashim Kalwar ◽  
Javed Khurshed Shaikh ◽  
Syed Mohammad Haleem ◽  
Muhammad Hassan Butt ◽  
...  
Keyword(s):  
Risk Score ◽  
Clinical Decision Making ◽  
Tertiary Care ◽  
Case Series ◽  
Primary Pci ◽  
St Segment Elevation ◽  
Case Series Study ◽  
Femoral Route ◽  
Timi Risk Score ◽  
Cardiac Center

Objective: To determine the frequency of severity based on dynamic TIMI scoring among STEMI patients undergoing primary PCI at a tertiary care Cardiac center. Subject and Methods: This case series study was carried out on 171 patients admitted with acute STEMI undergoing PPCI at the department of cardiology NICVD, Karachi for six months from February 1st to July 30th, 2018. After the selection of patients, they were shifted to the Cath lab, the arterial sheath was passed through the femoral route only although the radial route is also present but to reduce the bias we choose the same femoral route only. Angiography was done and the area of occlusion identified was ballooned/stented by the interventional cardiologist having experience of at least 03 years. The study parameters of dynamic TIMI risk score points were recorded on a predesigned proforma. Results: The mean age of the patients of the study subjects was 59.89±12.67, Distribution of gender was stated, 133(77.78%) patients were male and (22.22%) were female. Outcome dynamic TIMI risk score severity was stated, 86(50.29%) patients had a low risk, 62(36.26%) patients had a moderate risk, 23(13.45%) patients had a high risk. Conclusion: When used in STEMI patients, this new approach shows the ever-changing risks and could be helpful in clinical decision-making as well as risk assessment. Keywords: ST-segment elevation myocardial infarction; Primary percutaneous coronary intervention, TIMI

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