Do methods of hospital pre-alerts influence the on-scene times for acute pre-hospital stroke patients? A retrospective observational study

2021 ◽  
Vol 6 (2) ◽  
pp. 19-25
Author(s):  
Jacob Gunn
Keyword(s):  
Standard Deviation ◽  
Observational Study ◽  
Acute Stroke ◽  
Ambulance Service ◽  
Time Saving ◽  
North East ◽  
Admission Policies ◽  
The Mean ◽  
Time Critical ◽  
Mean Time

Introduction: Stroke is one of the leading causes of death and disability worldwide. The ambulance service is often the first medical service to reach an acute stroke patient, and due to the time-critical nature of stroke, a time-critical assessment and rapid transport to a hyper acute stroke unit are essential. As stroke services have been centralised, different hospitals have implemented different pre-alert admission policies that may affect the on-scene time of the attending ambulance crew. The aim of this study is to investigate if the different pre-alert admission policies affect time on scene.Method: The current study is a retrospective quantitative observational study using data routinely collected by North East Ambulance Service NHS Foundation Trust. The time on scene was divided into two variables; group one was a telephone pre-alert in which a telephone discussion with the receiving hospital is required before they accept admission of the patient. Group two was a radio-style pre-alert in which the attending clinician makes an autonomous decision on the receiving hospital and alerts them via a short radio message of the incoming patient. These times were then compared to identify if there was any difference between them.Results: Data on 927 patients over a three-month period, from October to December 2019, who had received the full stroke bundle of care, were within the thrombolysis window and recorded as a stroke by the attending clinician, were split into the variable groups and reported on. The mean time on scene for a telephone call pre-alert was 33 minutes and 19 seconds, with a standard deviation of 13 minutes and 8 seconds. The mean on-scene time for a radio pre-alert was 28 minutes and 24 seconds, with a standard deviation of 11 minutes and 51 seconds.Conclusion: A pre-alert given via radio instead of via telephone is shown to have a mean time saving of 4 minutes and 55 seconds, representing an important decrease in time which could be beneficial to patients.

scholarly journals STROKE OUTCOMES IN NON-DIABETIC, DENOVO DIABETIC AND DIABETIC INDIAN PATIENTS MEASURED BY MODIFIED RANKIN SCALE: AN OBSERVATIONAL STUDY

2017 ◽  
Vol 9 (8) ◽  
pp. 94
Author(s):  
Syed Junaid Ahmed ◽  
Abdur Rahman Mohd Masood ◽  
Safiya Sumana ◽  
Khadeer Ahmed Ghori ◽  
Javed Akhtar Ansari ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Observational Study ◽  
Hospital Admission ◽  
Acute Stroke ◽  
Mean Difference ◽  
Modified Rankin Scale ◽  
Stroke Patients ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
The Mean

Objective: Hyperglycemia is a known risk factor which adversely impacts the outcomes in stroke patients compared to patients with normal blood glucose levels. Patients suffering from an acute stroke who are previously nonhyperglycemic may show elevated blood glucose levels. The present study was designed to measure the outcomes in denovo diabetic and diabetic stroke patients compared to nondiabetics.Methods: A prospective observational study over a period of 6 mo, in which 103 patients were divided into three cohorts based on their blood glucose levels (nondiabetic, denovo diabetic and diabetics). The modified Rankin scale (mRS) score was calculated at in-hospital admission and discharge in these three cohorts. The initial and final scores were correlated and mean differences with respect to outcomes between all the three cohorts was calculated.Results: The mean mRS at the time of hospital admission in diabetics and nondiabetics was 3.6±0.81 and 3.3±0.78 which decreased to 2.8±0.95 and 2.9±0.83 respectively at the time of discharge. The mean mRS score in denovo diabetic stroke patients during in-hospital admission was 4±0.81 which was calculated as 3.7±0.85 at the time of discharge. The mean difference in mRS score in diabetics vs non-diabetics was found to be 0.73±0.8 (p =<0.001). The mean difference in mRS score of denovo diabetics vs non-diabetics and denovo diabetics vs diabetics was 0.30±0.63 and 0.38±0.61 respectively (p = 0.1).Conclusion: Results of these observational study in Indian patients, highlights the need for controlling hyperglycemia in stroke patients to improve outcomes and to prevent mortality arising out of acute stroke attacks.

scholarly journals CORRELATIONS OF THE MEAN TIME AND MEAN MAGNITUDE OF ACCELERATING PRESHOCKS WITH THE ORIGIN TIME AND MAGNITUDE OF MAINSHOCK

2017 ◽  
Vol 43 (4) ◽  
pp. 2154
Author(s):  
E. M. Scordilis
Keyword(s):  
Standard Deviation ◽  
South America ◽  
Strain Rate ◽  
Central Asia ◽  
Earthquake Prediction ◽  
Critical Region ◽  
Origin Time ◽  
The Mean ◽  
Benioff Strain ◽  
Mean Time

Forty-five preshock sequences preceding corresponding strong (M≥6.4) mainshocks which occurred recently (since 1980) in a variety of seismotectonic regimes (W. Mediterranean, Aegean, Anatolia, California, Japan, Central Asia, South America) have been examined to identify new predictive properties. It has been observed that the mean origin time, , and the mean magnitude, of the accelerating preshocks of each sequence are correlated with the origin time, tc, and the magnitude, M, of the mainshock, respectively. The following relations have been derived: where sa (in Joule ½ /yr.104 Km2 ) is the Benioff strain rate in each preshock (critical) region and σ is the corresponding standard deviation. The possibility for using these relations as constraints in attempts for intermediate term earthquake prediction is discussed.

Abstract 29: A Neighborhood Local Volunteer Response Network Improves Response Time for Cardiac Arrest

Circulation ◽  
2018 ◽  
Vol 138 (Suppl_2) ◽  
Author(s):  
Karl B Kern ◽  
Carter Newton ◽  
Charles " Wunder ◽  
Thomas P Colberg ◽  
Marvin J Slepian
Keyword(s):  
Cardiac Arrest ◽  
Response Times ◽  
Retirement Community ◽  
Time Of Arrival ◽  
Time Saving ◽  
Response Network ◽  
Community Boundaries ◽  
The Mean ◽  
Mean Time ◽  
Hospital Cardiac Arrest

Background: Minutes are crucial in the treatment of out-of-hospital cardiac arrest (CA). Immediate chest compressions and early defibrillation are keys to good outcomes. Local neighborhood volunteer (vol) response programs may decrease delays to early CPR and AED use. We hypothesized that a coordinated effort of alerting trained neighborhood vols simultaneously with 911 activation of professional EMS providers would provide earlier CPR and defibrillation in such communities. Methods: We developed a program of simultaneously alerting CPR and AED trained neighborhood vols and the local EMS system for cardiac arrest events in a retirement community in Southern Arizona, encompassing approximately 17,300 homes and 21,500 residents. EMS services are provided by 5 stations within the community boundaries. Within a single housing development neighborhood, 9 vols and the closest EMS station were involved in 3 days of mock CA notifications (total of 12 different alerts at various times during daytime hours were sent). This provided a total of 120 response opportunities, 12 for EMS and 108 for vols. The distance to the mock event and the time from alert to arrival were recorded and compared. Results: In the selected 55+ neighborhood, the two groups differed significantly in both distance to the mock cardiac arrest event and in response times. The volunteers average 0.33±0.19 miles from the mock CA incidences while the closest EMS station was 3.3 miles from the tested neighborhood (p<0.0001). Response times (time from call to arrival) were also different. The earliest Vol arrived at 1min 30sec±48sec*, 2 Vols & AED at 1min 38 sec±53sec*, all arriving Vols at 3min 23 sec*, and EMS at 7min 20 sec±1min 13sec (*p<0.0001 vs EMS). Conclusion: When the neighborhood volunteers in this testing period were geographically closer to the mock CA event, they arrived significantly sooner to the scene than did the EMS service. The mean time of arrival for at least 2 vols with an AED was 5 min 42 sec faster than the professional rescuers. The implications for such a time saving could be as much as a 240% increase (25% to 85%) in survival for those with shockable rhythms.

scholarly journals Tracheostomy in the coronavirus disease 2019 patient: evaluating feasibility, challenges and early outcomes of the 14-day guidance

2020 ◽  
Vol 134 (8) ◽  
pp. 688-695 ◽  
Author(s):  
N Glibbery ◽  
K Karamali ◽  
C Walker ◽  
I Fitzgerald O'Connor ◽  
B Fish ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Standard Deviation ◽  
Intensive Care Unit Discharge ◽  
Organ Support ◽  
Unit Discharge ◽  
Surgical Tracheostomy ◽  
Ventilatory Assistance ◽  
The Mean ◽  
Mean Time

AbstractObjectivesTo report feasibility, early outcomes and challenges of implementing a 14-day threshold for undertaking surgical tracheostomy in the critically ill coronavirus disease 2019 patient.MethodsTwenty-eight coronavirus disease 2019 patients underwent tracheostomy. Demographics, risk factors, ventilatory assistance, organ support and logistics were assessed.ResultsThe mean time from intubation to tracheostomy formation was 17.0 days (standard deviation = 4.4, range 8–26 days). Mean time to decannulation was 15.8 days (standard deviation = 9.4) and mean time to intensive care unit stepdown to a ward was 19.2 days (standard deviation = 6.8). The time from intubation to tracheostomy was strongly positively correlated with: duration of mechanical ventilation (r(23) = 0.66; p < 0.001), time from intubation to decannulation (r(23) = 0.66; p < 0.001) and time from intubation to intensive care unit discharge (r(23) = 0.71; p < 0.001).ConclusionPerforming a tracheostomy in coronavirus disease 2019 positive patients at 8–14 days following intubation is compatible with favourable outcomes. Multidisciplinary team input is crucial to patient selection.

But What About Swimming and Cycling? How to “Count” Non-Ambulatory Activity When Using Pedometers to Assess Physical Activity

2006 ◽  
Vol 3 (3) ◽  
pp. 257-266 ◽  
Author(s):  
Ruth Miller ◽  
Wendy Brown ◽  
Catrine Tudor-Locke
Keyword(s):  
Physical Activity ◽  
Standard Deviation ◽  
Step Count ◽  
Ambulatory Activity ◽  
The Mean ◽  
Ambulatory Activities ◽  
Mean Time

Background:The aims of this study were to describe the amount of non-ambulatory physical activity (PA) undertaken by a sample of Australian workers, and to evaluate different methods of accounting for non-ambulatory activities when using pedometers to measure physical activity.Methods:Adults age 18 to 64 y (N = 204) wore a pedometer and recorded steps and non-step activity in a logbook for 7 d. Non-ambulatory activity was recorded by 28% of the participants (N = 52) with cycling and swimming the most frequently reported.Results:The mean time reported for non-ambulatory activities was 82.8 (standard deviation 80.0) min/wk. On average, participants recorded 8873 (standard deviation 2757) steps/d. Time in non-ambulatory activities was converted to steps equivalents using three different conversion methods. Use of the three methods added 333 to 721 steps/d in the whole sample, but 1153 to 2566 steps/d for those who reported non-ambulatory activity.Conclusions:Suggestions are provided for accounting for non-ambulatory activities in interventions which rely on step count measures.

Ambulance service call handler and clinician identification of stroke in North East Ambulance Service

2021 ◽  
Vol 6 (2) ◽  
pp. 59-65
Author(s):  
Graham McClelland ◽  
Emma Burrow
Keyword(s):  
Acute Stroke ◽  
Early Recognition ◽  
Stroke Care ◽  
Service Evaluation ◽  
Ambulance Service ◽  
Stroke Patients ◽  
Face To Face ◽  
North East ◽  
Audit Data ◽  
Suspected Stroke

Introduction: Emergency medical services (EMS) are the first point of contact for most acute stroke patients. The EMS response is triggered by ambulance call handlers who triage calls and then an appropriate response is allocated. Early recognition of stroke is vital to minimise the call to hospital time as the availability and effectiveness of reperfusion therapies are time dependent. Minimising the pre-hospital phase by accurate call handler stroke identification, short EMS on-scene times and rapid access to specialist stroke care is vital. The aims of this study were to evaluate stroke identification by call handlers and clinicians in North East Ambulance Service (NEAS) and report on-scene times for suspected stroke patients.Methods: A retrospective service evaluation was conducted linking routinely collected data between 1 and 30 November 2019 from three sources: NEAS Emergency Operations Centre; NEAS clinicians; and hospital stroke diagnoses.Results: The datasets were linked resulting in 2214 individual cases. Call handler identification of acute stroke was 51.5% (95% CI 45.3‐57.8) sensitive with a positive predictive value (PPV) of 12.8% (95% CI 11.4‐14.4). Face-to-face clinician identification of stroke was 76.1% (95% CI 70.4‐81.1) sensitive with a PPV of 27.4% (95% CI 25.3‐29.7). The median on-scene time was 33 (IQR 25‐43) minutes, with call handler and clinician identification of stroke resulting in shorter times.Conclusion: This service evaluation using ambulance data linked with national audit data showed that the sensitivity of NEAS call handler and clinician identification of stroke are similar to figures published on other systems but the PPV of call handler and clinician identification stroke could be improved. However, sensitivity is paramount while timely identification of suspected stroke patients and rapid transport to definitive care are the primary functions of EMS. Call handler identification of stroke appears to affect the time that clinicians spend at scene with suspected stroke patients.

scholarly journals An Observational Study of Patient Characteristics Associated with the Mode of Admission to Acute Stroke Services in North East, England

PLoS ONE ◽  
2013 ◽  
Vol 8 (10) ◽  
pp. e76997 ◽  
Author(s):  
Christopher I. Price ◽  
Victoria Rae ◽  
Jay Duckett ◽  
Ruth Wood ◽  
Joanne Gray ◽  
...  
Keyword(s):  
Observational Study ◽  
Acute Stroke ◽  
Patient Characteristics ◽  
North East ◽  
Stroke Services

scholarly journals Comparison of Perimetric Outcomes from Melbourne Rapid Fields Tablet Perimeter Software and Humphrey Field Analyzer in Glaucoma Patients

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Harsh Kumar ◽  
Mithun Thulasidas
Keyword(s):  
Standard Deviation ◽  
Visual Field ◽  
Rural Areas ◽  
Visual Fields ◽  
Test Time ◽  
Mean Deviation ◽  
Time Saving ◽  
Humphrey Field Analyzer ◽  
Probability Plot ◽  
The Mean

Purpose. To compare visual field results obtained using Melbourne Rapid Fields (MRF) iPad-based perimeter software and Humphrey Field Analyzer (HFA) 24-2 Swedish Interactive Threshold Algorithm (SITA) standard program in glaucoma patients. Design. A cross-sectional observational study. Methods. In this single-centre study involving patients diagnosed with glaucoma, the perimetric outcomes of MRF were compared against those returned from the HFA 24-2 SITA standard. Outcomes included mean deviation (MD), pattern standard deviation (PSD), visual field index (VFI)/visual capacity (VC), foveal threshold, test time, number of points depressed at P<5% on PSD probability plot, and glaucoma hemifield test/color coded indicator. Results. The study included 28 eyes of 28 glaucoma patients. Mean (standard deviation) test times were 342.07 (56.70) seconds for MRF and 375.11 (88.95) for HFA 24-2 SITA standard P=0.046. Mean MD was significantly lower for MRF (Δ = 3.09, P<0.001), and mean PSD was significantly higher for MRF (Δ = 1.40, P=0.005) compared with HFA. The mean foveal threshold for the MRF was significantly lower than the mean HFA foveal threshold ((Δ = 9.25, P<0.001). The number of points depressed at P<5% on the PSD probability plot was significantly less for MRF P<0.001. Other perimetric outcomes showed no significant differences between both. Bland–Altman plots showed that considerable variability existed between the programs. Conclusion. MRF is a good cost-effective, time-saving, user-friendly tool for monitoring visual fields in settings where access to traditional perimetry is limited. The lack of Internet strength in rural areas and questionable detection of early cases may be two points in MRF fields requiring an upgrade.

scholarly journals Focused Assessment with Sonography for Trauma (FAST) training for first-year resident physicians at a university hospital in Japan: A longitudinal, observational study

2021 ◽  
Vol 9 ◽  
pp. 205031212110443
Author(s):  
Koshi Ota ◽  
Koji Oba ◽  
Yuri Ito ◽  
Jacky Cheng ◽  
Kanna Ota ◽  
...  
Keyword(s):  
Emergency Medicine ◽  
Standard Deviation ◽  
Observational Study ◽  
Test Score ◽  
Primary Outcome ◽  
First Year ◽  
Longitudinal Observational Study ◽  
Hands On ◽  
The Mean ◽  
Prospective Longitudinal

Background: Ultrasound training is an essential part of residency programs during emergency medicine rotations for first-year trainees (postgraduate year 1). The Focused Assessment with Sonography for Trauma examination used to assess for internal bleeding in trauma patients is one of the essential skills postgraduate year 1 residents must acquire during the emergency medicine rotation. Method: A prospective, longitudinal, observational study of postgraduate year 1 residents during a 2-month long emergency medicine rotation conducted from 1 April 2019 to 31 May 2021. The primary outcome was the mean difference between the hands-on Focused Assessment with Sonography for Trauma examination scores of the first week of the emergency medicine rotation and the same hands-on Focused Assessment with Sonography for Trauma examination scores of the last week of the emergency medicine rotation. All postgraduate year 1 residents had open access to the ultrasound machine to practice examining on other postgraduate year 1 residents or could use it on real patients under supervision of emergency medicine physicians. Result: A total of 91 postgraduate year 1 residents (65 male and 26 female) were recruited and submitted to the hands-on Focused Assessment with Sonography for Trauma test in both the first and last weeks of the rotation. The mean test score for the postgraduate year 1 residents in the first week was 7.81 (standard deviation = 2.11). The mean test score in the last week was 16.17 (standard deviation = 2.60). The primary outcome of this study was the score difference between the first and last weeks (mean = 8.35, 95% confidence interval = 7.73 to 8.94, p < 0.001, paired t-test). Conclusion: Hands-on practical Focused Assessment with Sonography for Trauma training for postgraduate year 1 residents during emergency medicine rotations significantly improved their Focused Assessment with Sonography for Trauma test scores.

scholarly journals Processing and Interpretation Times of CT Angiogram and CT Perfusion in Stroke

2005 ◽  
Vol 32 (4) ◽  
pp. 483-486 ◽  
Author(s):  
Ashok Srinivasan ◽  
Mayank Goyal ◽  
Cheemun Lum ◽  
Thanh Nguyen ◽  
William Miller
Keyword(s):  
Acute Stroke ◽  
Ct Perfusion ◽  
Group Iii ◽  
Ct Angiogram ◽  
Group I ◽  
Or Groups ◽  
Significant Difference ◽  
The Mean ◽  
Time Required ◽  
Mean Time

ABSTRACT:Objective:To determine the mean time for acquiring computed tomogram perfusion (CTP) and CT angiogram (CTA) images in acute stroke. To determine and compare processing and interpretation times amongst three groups of radiologists with varying degree of expertise: two radiology residents (Group I), two neuroradiology fellows (Group II) and four consultant neuroradiologists (Group III).Methods:The mean time of acquisition of CTA and CTP studies was calculated among ten patients presenting with acute stroke. All readers had to process the CTA and CTP images, interpret them (for presence or absence of thrombus and penumbra) and save them on the GE Advantage Windows workstation. The mean time for processing and interpreting these studies was calculated.Results:The mean time for acquisition of CTA and CTP studies in the ten patients was 14.6 ± 5.9 minutes. The time taken for CTA processing and interpretation in Groups I, II and III was 2.3 ± 1.3 min, 1.6 ± 0.4 min and 1.5 ± 0.7 min respectively. The time required for CTP processing and interpretation by the same groups was 5.2 ± 1.7 min, 4.5 ± 1.5 min and 4.1 ± 1.1 min respectively. There was a statistically significant difference of means between Groups I and III in the CTA and CTP processing and interpretation times (p=0.02, p=0.01 respectively) but no statistical difference between Groups I and II (p=0.15, p=0.22 respectively) or Groups II and III (p=0.31, p=0.30 respectively).Conclusion:The CTA and CTP studies can be performed, processed and interpreted quickly in acute stroke.

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