Colonization and Infection With MRSA and CRKP and Its Result in an Increased Mortality Rate Within the Intensive Care and High-Dependency Units in Barbados

Background: Methicillin-resistant Staphylococcus aureus(MRSA) and carbapenem-resistant Klebsiella pneumoniae (CRKP) are a growing public health concern in Barbados. Intensive care and critically ill patients are at a higher risk for MRSA and CRKP colonization and infection. MRSA and CRKP colonization and infection are associated with a high mortality and morbidly rate in the intensive care units (ICUs) and high-dependency units (HDUs). There is no concrete evidence in the literature regarding MRSA and CRKP colonization and infection in Barbados or the Caribbean. Objectives: We investigated the prevalence of MRSA and CRKP colonization and infection in the patients of the ICU and HDU units at the Queen Elizabeth Hospital from 2013 to 2017. Methods: We conducted a retrospective cohort analysis of patients admitted to the MICU, SICU, and HDU from January 2013 through December 2017. Data were collected as part of the surveillance program instituted by the IPC department. Admissions and weekly swabs for rectal, nasal, groin, and axilla were performed to screen for colonization with MRSA and CRKP. Follow-up was performed for positive cultures from sterile isolates, indicating infection. Positive MRSA and CRKP colonization or infection were identified, and patient notes were collected. Our exclusion criteria included patients with a of stay of <48 hours and patients with MRSA or CRKP before admission. Results: Of 3,641 of persons admitted 2,801 cases fit the study criteria. Overall, 161 (5.3%) were colonized or infected with MRSA alone, 215 (7.67%) were colonized or infected with CRKP alone, and 15 (0.53%) were colonized or infected with both MRSA and CRKP. In addition, 10 (66.6%) of patients colonized or infected with MRSA and CRKP died. Average length of stay of patients who died was 50 days. Conclusions: The results of this study demonstrate that MRSA and CRKP cocolonization and coinfection is associated with high mortality in patients within the ICU and HDU units. Patients admitted to the ICU and HDU with an average length of stay of 50 days are at a higher risk for cocolonization and coinfection with MRSA and CRKP. Stronger IPC measures must be implemented to reduce the spread and occurrence of MRSA and CRKP.Funding: NoneDisclosures: None

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Biased and unbiased estimation of the average length of stay in intensive care units in the Covid-19 pandemic

Annals of Intensive Care ◽

10.1186/s13613-020-00749-6 ◽

2020 ◽

Vol 10 (1) ◽

Cited By ~ 2

Author(s):

Nathanael Lapidus ◽

Xianlong Zhou ◽

Fabrice Carrat ◽

Bruno Riou ◽

Yan Zhao ◽

...

Keyword(s):

Intensive Care ◽

Length Of Stay ◽

Average Length ◽

Parametric Method ◽

Estimation Methods ◽

Unbiased Estimation ◽

Bed Occupancy ◽

Average Length Of Stay ◽

Discharged Patients ◽

First Admission

Abstract Background The average length of stay (LOS) in the intensive care unit (ICU_ALOS) is a helpful parameter summarizing critical bed occupancy. During the outbreak of a novel virus, estimating early a reliable ICU_ALOS estimate of infected patients is critical to accurately parameterize models examining mitigation and preparedness scenarios. Methods Two estimation methods of ICU_ALOS were compared: the average LOS of already discharged patients at the date of estimation (DPE), and a standard parametric method used for analyzing time-to-event data which fits a given distribution to observed data and includes the censored stays of patients still treated in the ICU at the date of estimation (CPE). Methods were compared on a series of all COVID-19 consecutive cases (n = 59) admitted in an ICU devoted to such patients. At the last follow-up date, 99 days after the first admission, all patients but one had been discharged. A simulation study investigated the generalizability of the methods' patterns. CPE and DPE estimates were also compared to COVID-19 estimates reported to date. Results LOS ≥ 30 days concerned 14 out of the 59 patients (24%), including 8 of the 21 deaths observed. Two months after the first admission, 38 (64%) patients had been discharged, with corresponding DPE and CPE estimates of ICU_ALOS (95% CI) at 13.0 days (10.4–15.6) and 23.1 days (18.1–29.7), respectively. Series' true ICU_ALOS was greater than 21 days, well above reported estimates to date. Conclusions Discharges of short stays are more likely observed earlier during the course of an outbreak. Cautious unbiased ICU_ALOS estimates suggest parameterizing a higher burden of ICU bed occupancy than that adopted to date in COVID-19 forecasting models. Funding Support by the National Natural Science Foundation of China (81900097 to Dr. Zhou) and the Emergency Response Project of Hubei Science and Technology Department (2020FCA023 to Pr. Zhao).

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Biased and unbiased estimation of the average length of stay in intensive care units in the COVID-19 pandemic

10.1101/2020.04.21.20073916 ◽

2020 ◽

Cited By ~ 1

Author(s):

Nathanael Lapidus ◽

Xianlong Zhou ◽

Fabrice Carrat ◽

Bruno Riou ◽

Yan Zhao ◽

...

Keyword(s):

Intensive Care ◽

Length Of Stay ◽

Average Length ◽

Parametric Method ◽

Estimation Methods ◽

Unbiased Estimation ◽

Bed Occupancy ◽

Average Length Of Stay ◽

Discharged Patients ◽

First Admission

BackgroundThe average length of stay (LOS) in the intensive care unit (ICU_ALOS) is a helpful parameter summarizing critical bed occupancy. During the outbreak of a novel virus, estimating early a reliable ICU_ALOS estimate of infected patients is critical to accurately parameterize models examining mitigation and preparedness scenarios.MethodsTwo estimation methods of ICU ALOS were compared: the average LOS of already discharged patients at the date of estimation (DPE), and a standard parametric method used for analyzing time-to-event data which fits a given distribution to observed data and includes the censored stays of patients still treated in the ICU at the date of estimation (CPE). Methods were compared on a series of all COVID-19 consecutive cases (n=59) admitted in an ICU devoted to such patients. At the last follow-up date, 99 days after the first admission, all patients but one had been discharged. A simulation study investigated the generalizability of the methods’ patterns. CPE and DPE estimates were also compared to COVID-19 estimates reported to date.FindingsLOS ≥ 30 days concerned 14 out of the 59 patients (24%), including 8 of the 21 deaths observed. Two months after the first admission, 38 (64%) patients had been discharged, with corresponding DPE and CPE estimates of ICU_ALOS (95%CI) at 13.0 days (10.4–15.6) and 23.1 days (18.1–29.7), respectively. Series’ true ICU_ALOS was greater than 21 days, well above reported estimates to date.InterpretationDischarges of short stays are more likely observed earlier during the course of an outbreak. Cautious unbiased ICU_ALOS estimates suggest parameterizing a higher burden of ICU bed occupancy than that adopted to date in COVID-19 forecasting models.FundingSupport by the National Natural Science Foundation of China (81900097 to Dr. Zhou) and the Emergency Response Project of Hubei Science and Technology Department (2020FCA023 to Pr. Zhao).

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Nutrition challenges in polytrauma patients. New trends in energy expenditure measurements

Central European Journal of Clinical Research ◽

10.2478/cejcr-2019-0008 ◽

2019 ◽

Vol 2 (1) ◽

pp. 51-57 ◽

Cited By ~ 1

Author(s):

Barbara Kołakowska

Keyword(s):

Wound Healing ◽

Intensive Care ◽

Length Of Stay ◽

Average Length ◽

Risk Of Infection ◽

Icu Patients ◽

Inflammatory Reactions ◽

Average Length Of Stay ◽

Specialized Care ◽

Polytrauma Patients

AbstractPatients hospitalized in Intensive Care Units (ICU) are in severe general condition and they need specialized care, rehabilitation and proper nutrition to improve their condition and recover as soon as possible. Therefore, it is very important that nutrition consists of all necessary elements that will cover their daily demand for nutrients. However, malnutrition among ICU patients is very common. According to statistics, up to 50% is malnourished. It enhances average length of stay, risk of infection, prolongs ventilator days, delays wound healing and translates into an increased hospital cost. It may end in multi-organ failure, what in consequence increases mortality. Polytrauma pa tients lost their energy because of intensified catabolism, due to neuroendocrine changes and inflammatory reactions, which may worsen already existing malnutrition.

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Difficulties in access and estimates of public beds in intensive care units in the state of Rio de Janeiro

Revista de Saúde Pública ◽

10.1590/s1518-8787.2016050005997 ◽

2016 ◽

Vol 50 (0) ◽

Cited By ~ 8

Author(s):

Rosane Sonia Goldwasser ◽

Maria Stella de Castro Lobo ◽

Edilson Fernandes de Arruda ◽

Simone Aldrey Angelo ◽

José Roberto Lapa e Silva ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Length Of Stay ◽

Rio De Janeiro ◽

Average Length ◽

Patient Flow ◽

The State ◽

System Stability ◽

Ministry Of Health ◽

Average Length Of Stay

ABSTRACT OBJECTIVE To estimate the required number of public beds for adults in intensive care units in the state of Rio de Janeiro to meet the existing demand and compare results with recommendations by the Brazilian Ministry of Health. METHODS The study uses a hybrid model combining time series and queuing theory to predict the demand and estimate the number of required beds. Four patient flow scenarios were considered according to bed requests, percentage of abandonments and average length of stay in intensive care unit beds. The results were plotted against Ministry of Health parameters. Data were obtained from the State Regulation Center from 2010 to 2011. RESULTS There were 33,101 medical requests for 268 regulated intensive care unit beds in Rio de Janeiro. With an average length of stay in regulated ICUs of 11.3 days, there would be a need for 595 active beds to ensure system stability and 628 beds to ensure a maximum waiting time of six hours. Deducting current abandonment rates due to clinical improvement (25.8%), these figures fall to 441 and 417. With an average length of stay of 6.5 days, the number of required beds would be 342 and 366, respectively; deducting abandonment rates, 254 and 275. The Brazilian Ministry of Health establishes a parameter of 118 to 353 beds. Although the number of regulated beds is within the recommended range, an increase in beds of 122.0% is required to guarantee system stability and of 134.0% for a maximum waiting time of six hours. CONCLUSIONS Adequate bed estimation must consider reasons for limited timely access and patient flow management in a scenario that associates prioritization of requests with the lowest average length of stay.

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Factors Affecting the Length of Stay in the Intensive Care Unit: Our Clinical Experience

BioMed Research International ◽

10.1155/2018/9438046 ◽

2018 ◽

Vol 2018 ◽

pp. 1-4 ◽

Cited By ~ 5

Author(s):

Mehmet Toptas ◽

Nilay Sengul Samanci ◽

İbrahim Akkoc ◽

Esma Yucetas ◽

Egemen Cebeci ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Length Of Stay ◽

Average Length ◽

Cerebrovascular Diseases ◽

Factors Affecting ◽

Average Length Of Stay ◽

Lengths Of Stay ◽

Life Threatening ◽

Hospital Days

Background and Aim. Long hospital days in intensive care unit (ICU) due to life-threatening diseases are increasing in the world. The primary goal in ICU is to decrease length of stay in order to improve the quality of medical care and reduce cost. The aim of our study is to identify and categorize the factors associated with prolonged stays in ICU.Materials and Method. We retrospectively analyzed 3925 patients. We obtained the patients’ demographic, clinical, diagnostic, and physiologic variables; mortality; lengths of stay by examining the intensive care unit database records.Results. The mean age of the study was 61.6 ± 18.9 years. The average length of stay in intensive care unit was 10.2 ± 25.2 days. The most common cause of hospitalization was because of multiple diseases (19.5%). The length of stay was positively correlated with urea, creatinine, and sodium. It was negatively correlated with uric acid and hematocrit levels. Length of stay was significantly higher in patients not operated on than in patients operated on (p<0.001).Conclusion. Our study showed a significantly increased length of stay in patients with cardiovascular system diseases, multiple diseases, nervous system diseases, and cerebrovascular diseases. Moreover we showed that when urea, creatinine, and sodium values increase, in parallel the length of stay increases.

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The Use of Novel Adopters for Acute Rib Fixation in Critical Chest Trauma, Undertaken by Orthopaedic Surgeons: an Observational Cohort Study

The Journal of Critical Care Medicine ◽

10.1515/jccm-2015-0016 ◽

2015 ◽

Vol 1 (3) ◽

pp. 96-101

Author(s):

Paul J. Jermin ◽

James Perry ◽

Sanjay Kalra ◽

Elizabeth Flockton ◽

Henry K. Rourke

Keyword(s):

Intensive Care ◽

Length Of Stay ◽

Injury Severity Score ◽

Severity Score ◽

Injury Severity ◽

Average Length ◽

Flail Chest ◽

Rapid Change ◽

Rib Fractures ◽

Average Length Of Stay

Abstract Background: Surgical stabilisation of acute rib fractures has recently undergone rapid change in the UK with respect to what type of injury is surgically stabilised and who undertakes the operation. This paper presents a review of the literature on surgical fixation and presents our early clinical experience using a recently introduced stabilising system. Methods: Data was prospectively collected from the first 10 patients undergoing surgical stabilisation of acute rib fractures using the Synthes Matrix RIB plating system. The data included demographics, Injury Severity Score, length of stay in Intensive Care, length of time on a ventilator, analgesic requirements, pneumonia rates and mortality. Patients were followed up until they were discharged from hospital. Results: Patients had an average Injury Severity Score of 26 (16-57), the average number of ribs fractured was 8.2 (4-14), nine patients had flail chest and one had multiple fractures, mean time from injury to fixation was 2.8 days. In the reported cohort, there were no deaths, two pneumonias (one had pneumonia on presentation). The average length of stay on a ventilator was three days and the average length of stay in Intensive Care was ten days. Conclusion: The early results of this procedure are encouraging. We feel that the modern implants will provide superior results to the highly variable implants that have previously been used. Our results support the literature, showing that with this system, there is a decrease in mortality and morbidity and a decrease in the length of time on a ventilator and stay in Intensive Care.

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

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.1051 ◽

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

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More skilled clinical management of COVID-19 patients modified mortality in an intermediate respiratory intensive care unit in Italy

Respiratory Research ◽

10.1186/s12931-021-01613-2 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Giovanna E. Carpagnano ◽

Giovanni Migliore ◽

Salvatore Grasso ◽

Vito Procacci ◽

Emanuela Resta ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Severe Acute Respiratory Syndrome ◽

Clinical Management ◽

Average Length ◽

Limited Attention ◽

Average Length Of Stay ◽

Before And After ◽

Respiratory Intensive Care Unit ◽

Transferred Patients

Abstract Background Some studies investigated epidemiological and clinical features of laboratory-confirmed patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the virus causing coronavirus disease 2019 (COVID-19), but limited attention has been paid to the follow-up of hospitalized patients on the basis of clinical setting and the expertise of clinical management. Methods In the present single-centered, retrospective, observational study, we reported findings from 87 consecutive laboratory-confirmed COVID-19 patients with moderate-to-severe acute respiratory syndrome hospitalized in an intermediate Respiratory Intensive Care Unit (RICU), subdividing the patients in two groups according to the admission date (before and after March 29, 2020). Results With improved skills in the clinical management of COVID-19, we observed a significant lower mortality in the T2 group compared with the T1 group and a significantly difference in terms of mortality among the patients transferred in Intensive Care Unit (ICU) from our intermediate RICU (100% in T1 group vs. 33.3% in T2 group). The average length of stay in intermediate RICU of ICU-transferred patients who survived in T1 and T2 was significantly longer than those who died (who died 3.3 ± 2.8 days vs. who survived 6.4 ± 3.3 days). T Conclusions The present findings suggested that an intermediate level of hospital care may have the potential to modify survival in COVID-19 patients, particularly in the present phase of a more skilled clinical management of the pandemic.

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Times of change in complex environments - Evaluating hospital co-payments in Palestine refugee camps

European Journal of Public Health ◽

10.1093/eurpub/ckaa166.1252 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

S V Valente de Almeida ◽

H Ghattas ◽

G Paolucci ◽

A Seita

Keyword(s):

Length Of Stay ◽

Policy Change ◽

Negative Binomial ◽

Negative Impact ◽

Average Length ◽

Lessons Learned ◽

Policy Impact ◽

Average Length Of Stay ◽

Ex Post ◽

The Impact

Abstract We measure the impact introducing a of 10% co-payment component on hospitalisation costs for Palestine refugees from Lebanon in public and private hospitals. This ex-post analysis provides a detailed insight on the direction and magnitude of the policy impact in terms of demand and supply for healthcare. The data was collected by the United Nations Relief and Works Agency for Palestine Refugees in the Near East and include episode level information from all public, private and Red Crescent Hospitals in Lebanon, between April 2016 and October 2017. This is a complete population episode level dataset with information from before and after the policy change. We use multinomial logit, negative binomial and linear models to estimate the policy impact on demand by type of hospital, average length of stay and treatment costs for the patient and the provider. After the new policy was implemented patients were 18% more likely to choose a (free-of-charge) PRCS hospital for secondary care, instead of a Private or Public hospital, where the co-payment was introduced. This impact was stronger for episodes with longer stays, which are also the more severe and more expensive cases. Average length of stay decreased in general for all hospitals and we could not find a statistically significant impact on costs for the provider nor the patient. We find evidence that the introduction of co-payments is hospital costs led to a shift in demand, but it is not clear to what extent the hospitals receiving this demand shift were prepared for having more patients than before, also because these are typically of less quality then the others. Regarding costs, there is no evidence that the provider managed to contain costs with the new policy, as the demand adapted to the changes. Our findings provide important information on hospitalisation expenses and the consequences of a policy change from a lessons learned perspective that should be taken into account for future policy decision making. Key messages We show that in a context of poverty, the introduction of payment for specific hospital types can be efficient for shifting demand, but has doubtable impact on costs containment for the provider. The co-payment policy can have a negative impact on patients' health since after its implementation demand increased at free-of-charge hospitals, which typically have less resources to treat patients.

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P17 An audit of Trakcare discharge times for Laparoscopic Cholecystectomy

BJS Open ◽

10.1093/bjsopen/zrab032.016 ◽

2021 ◽

Vol 5 (Supplement_1) ◽

Author(s):

Jacob Rapier ◽

Steven Hornby ◽

Jacob Rapier

Keyword(s):

Laparoscopic Cholecystectomy ◽

Length Of Stay ◽

Initial Data ◽

Best Practice ◽

Average Length ◽

Accurate Data ◽

Day Case ◽

Average Length Of Stay ◽

Number Of Patients ◽

Elective Laparoscopic Cholecystectomy

Abstract Introduction Nationally 61,220 Laparoscopic Cholecystectomies are carried out annually. Those carried out as day-cases reduce providers’ costs and increase income through the best practice tariff. The system in our trust to record discharges is ‘Trakcare’. The aim of this audit was to accurately measure the discharge times of patients undergoing elective Laparoscopic Cholecystectomies, to try and reduce the number of patients recorded as having an overnight stay by accurate data collection. Methods Initial data was collected for all elective Laparoscopic Cholecystectomy discharge times on Trakcare, over a 1 month period. This data was then re-audited prospectively both from Trakcare and discharges reported by nurses/patients. A comparison was then made of Trakcare against reported discharge times. Results Initially 54 operations were recorded, with 30 completed as day cases (55.6%). The re-audited data (on Trakcare) recorded 47 operations, with 15 completed as day cases (37.91%). Of these discharges we were able to capture 26 (55.32%) manually, and 11 were completed as day cases (42.31%). Measuring these 26 with the same operations on Trakcare we were unable to show a difference in the number of cases completed as a day case (11 vs 11), with only a 33 minute decrease in the average length of stay. Conclusion Trakcare is a reliable tool for measuring the date of discharge for patients. The recommendations in are: scheduling surgery for a time pre-13:00 shows a higher proportion of patients discharged the same day, and continue to use Trakcare to record discharge times.

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