Characteristics, management, and in-hospital mortality among patients with severe sepsis in intensive care units in Japan: the FORECAST study.

This article by Abe and colleagues appeared in the November 2018 issue of Critical Care.
Background:  Sepsis is a leading cause of death and long-term disability in developed countries. A comprehensive report on the incidence, clinical characteristics, and evolving management of sepsis is important. Thus, this study aimed to evaluate the characteristics, management,and outcomes of patients with severe sepsis in Japan.
Methods:  This is a cohort study of the Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome,Sepsis, and Trauma (FORECAST) study, which was a multicentre, prospective cohort study conducted at 59 intensive care units (ICUs) from January 2016 to March 2017. We included adult patients with severe sepsis based on the sepsis-2 criteria.
Results:  In total, 1184 patients (median age 73 years,inter quartile range (IQR) 64-81) with severe sepsis were admitted to the ICU during the study period. The most common comorbidity was diabetes mellitus(23%). Moreover, approximately 63% of patients had septic shock. The median Sepsis-related Organ Failure Assessment (SOFA) score was 9 (IQR 6-11). The most common site of infection was the lung (31%). Approximately 54% of the participants had positive blood cultures. The compliance rates for the entire 3-h bundle, measurement of central venous pressure, and assessment of central venous oxygen saturation were 64%, 26%, and 7%, respectively. A multi level logistic regression model showed that closed ICUs and non-university hospitals were more compliant with the entire 3-h bundle. The in-hospital mortality rate of patients with severe sepsis was 23% (21-26%). Older age, multiple co-morbidities, suspected site of infection, and increasing SOFA scores correlated with in-hospital mortality, based on the generalized estimating equation model. The length of hospital stay was 24 (12-46) days. Approximately 37% of the patients were discharged home after recovery.
Conclusion:  Our prospective study showed that sepsis management in Japan was characterized by a high compliance rate for the 3-h bundle and low compliance rate for central venous catheter measurements. The in-hospital mortality rate in Japan was comparable to that of other developed countries. Only one third of the patients were discharged home, considering the aging population with multiple co-morbidities in the ICUs in Japan.
The full text of the article is freely available via this link.

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TroponinI at admission in the intensive care unit predicts the need of dialysis in septic patients

This article by de Almeida Thiengo and colleagues was published in BMC Nephrology in November 2018.
Background:  In a previous study we showed that troponin I (TnI) > 0.42 ng/mL predicted the need of dialysis in a group of 29 septic patients admitted to the intensive care unit (ICU). We aimed to confirm such finding in a larger independent sample.
Methods:  All septic patients admitted to an ICU from March 2016 to February 2017 were included if age between 18 and 90 years, onset of sepsis  0.42 ng/mL. These patients had serum creatinine slightly higher (1.66 ± 0.34 vs. 1.32 ± 0.39 mg/dL; P <  0.0001)than those with lower TnI and similar urine output (1490 ± 682 vs. 1406 ± 631 mL;P = 0.44). At the end of the follow-up period, 70.0% of the patients with lower TnI were alive in comparison with 38.6% of those with higher TnI (p = 0.0014).After 30 days, 69.3 and 2.9% of the patients with lower and higher TnI levels remained free of dialysis, respectively (p  0.42 ng/mL persisted as a strong predictor of dialysis need (hazard ratio 3.48 [95%CI 1.69-7.18]).
Conclusions:  TnI levels at ICU admission are a strong independent predictor of dialysis need in sepsis.
The full text of the article is freely available via this link.

Automated monitoring compared to standard care for the early detection of sepsis in critically ill patients

This Cochrane Systematic Review by Warttig and colleagues was published in June 2018.  The full text of the systematic review is available via this link.
Background:  Sepsis is a life‐threatening condition that is usually diagnosed when a patient has a suspected or documented infection, and meets two or more criteria for systemic inflammatory response syndrcochrane-57-1ome (SIRS). The incidence of sepsis is higher among people admitted to critical care settings such as the intensive care unit (ICU) than among people in other settings. If left untreated sepsis can quickly worsen; severe sepsis has a mortality rate of 40% or higher, depending on definition. Recognition of sepsis can be challenging as it usually requires patient data to be combined from multiple unconnected sources, and interpreted correctly, which can be complex and time consuming to do. Electronic systems that are designed to connect information sources together, and automatically collate, analyse, and continuously monitor the information, as well as alerting healthcare staff when pre‐determined diagnostic thresholds are met, may offer benefits by facilitating earlier recognition of sepsis and faster initiation of treatment, such as antimicrobial therapy, fluid resuscitation, inotropes, and vasopressors if appropriate. However, there is the possibility that electronic, automated systems do not offer benefits, or even cause harm. This might happen if the systems are unable to correctly detect sepsis (meaning that treatment is not started when it should be, or it is started when it shouldn’t be), or healthcare staff may not respond to alerts quickly enough, or get ‘alarm fatigue’ especially if the alarms go off frequently or give too many false alarms.

Objectives:  To evaluate whether automated systems for the early detection of sepsis can reduce the time to appropriate treatment (such as initiation of antibiotics, fluids, inotropes, and vasopressors) and improve clinical outcomes in critically ill patients in the ICU.

Search methods:  We searched CENTRAL; MEDLINE; Embase; CINAHL; ISI Web of science; and LILACS, clinicaltrials.gov, and the World Health Organization trials portal. We searched all databases from their date of inception to 18 September 2017, with no restriction on country or language of publication.
Selection criteria:  We included randomized controlled trials (RCTs) that compared automated sepsis‐monitoring systems to standard care (such as paper‐based systems) in participants of any age admitted to intensive or critical care units for critical illness. We defined an automated system as any process capable of screening patient records or data (one or more systems) automatically at intervals for markers or characteristics that are indicative of sepsis. We defined critical illness as including, but not limited to postsurgery, trauma, stroke, myocardial infarction, arrhythmia, burns, and hypovolaemic or haemorrhagic shock. We excluded non‐randomized studies, quasi‐randomized studies, and cross‐over studies . We also excluded studies including people already diagnosed with sepsis.
Data collection and analysis:  We used the standard methodological procedures expected by Cochrane. Our primary outcomes were: time to initiation of antimicrobial therapy; time to initiation of fluid resuscitation; and 30‐day mortality. Secondary outcomes included: length of stay in ICU; failed detection of sepsis; and quality of life. We used GRADE to assess the quality of evidence for each outcome.

Main results:  We included three RCTs in this review. It was unclear if the RCTs were three separate studies involving 1199 participants in total, or if they were reports from the same study involving fewer participants. We decided to treat the studies separately, as we were unable to make contact with the study authors to clarify.
All three RCTs are of very low study quality because of issues with unclear randomization methods, allocation concealment and uncertainty of effect size. Some of the studies were reported as abstracts only and contained limited data, which prevented meaningful analysis and assessment of potential biases.
The studies included participants who all received automated electronic monitoring during their hospital stay. Participants were randomized to an intervention group (automated alerts sent from the system) or to usual care (no automated alerts sent from the system).
Evidence from all three studies reported ‘Time to initiation of antimicrobial therapy’. We were unable to pool the data, but the largest study involving 680 participants reported median time to initiation of antimicrobial therapy in the intervention group of 5.6 hours (interquartile range (IQR) 2.3 to 19.7) in the intervention group (n = not stated) and 7.8 hours (IQR 2.5 to 33.1) in the control group (n = not stated).
No studies reported ‘Time to initiation of fluid resuscitation’ or the adverse event ‘Mortality at 30 days’. However very low‐quality evidence was available where mortality was reported at other time points. One study involving 77 participants reported 14‐day mortality of 20% in the intervention group and 21% in the control group (numerator and denominator not stated). One study involving 442 participants reported mortality at 28 days, or discharge was 14% in the intervention group and 10% in the control group (numerator and denominator not reported). Sample sizes were not reported adequately for these outcomes and so we could not estimate confidence intervals.

Very low‐quality evidence from one study involving 442 participants reported ‘Length of stay in ICU’. Median length of stay was 3.0 days in the intervention group (IQR = 2.0 to 5.0), and 3.0 days (IQR 2.0 to 4.0 in the control).
Very low‐quality evidence from one study involving at least 442 participants reported the adverse effect ‘Failed detection of sepsis’. Data were only reported for failed detection of sepsis in two participants and it wasn’t clear which group(s) this outcome occurred in.
No studies reported ‘Quality of life’.
Authors’ conclusions:  It is unclear what effect automated systems for monitoring sepsis have on any of the outcomes included in this review. Very low‐quality evidence is only available on automated alerts, which is only one component of automated monitoring systems. It is uncertain whether such systems can replace regular, careful review of the patient’s condition by experienced healthcare staff.

Timing of Renal-Replacement Therapy in Patients with Acute Kidney Injury and Sepsis

This article by the IDEAL-ICU Trial Investigators and the CRICS TRIGGERSEP Network was published in the New England journal of medicine in October 2018.
Background:  Acute kidney injury is the most frequent complication in patients with septic shock and is an independent risk factor for death. Although renal-replacement therapy is the standard of care for severe acute kidney injury, the ideal time for initiation remains controversial.
Methods:  In a multicentre, randomized, controlled trial, we assigned patients with early-stage septic shock who had severe acute kidney injury at the failure stage of the risk, injury, failure, loss, and end-stage kidney disease (RIFLE) classification system but without life-threatening complications related to acute kidney injury to receive renal-replacement therapy either within 12 hours after documentation of failure-stage acute kidney injury (early strategy) or after a delay of 48 hours if renal recovery had not occurred (delayed strategy). The failure stage of the RIFLE classification system is characterized by a serum creatinine level 3 times the baseline level (or ≥4 mg per deciliter with a rapid increase of ≥0.5 mg per deciliter), urine output less than 0.3 ml per kilogram of body weight per hour for 24 hours or longer, or anuria for at least 12 hours. The primary outcome was death at 90 days.
Results:  The trial was stopped early for futility after the second planned interim analysis. A total of 488 patients underwent randomization; there were no significant between-group differences in the characteristics at baseline. Among the 477 patients for whom follow-up data at 90 days were available, 58% of the patients in the early-strategy group (138 of 239 patients) and 54% in the delayed-strategy group (128 of 238 patients) had died (P=0.38). In the delayed-strategy group, 38% (93 patients) did not receive renal-replacement therapy. Criteria for emergency renal-replacement therapy were met in 17% of the patients in the delayed-strategy group (41 patients).
Conclusions:  Among patients with septic shock who had severe acute kidney injury, there was no significant difference in overall mortality at 90 days between patients who were assigned to an early strategy for the initiation of renal-replacement therapy and those who were assigned to a delayed strategy.
The printed copy of the New England Journal of Medicine is available in the Health Care Library on D Level of Rotherham Hospital.

Sepsis incidence and mortality are underestimated in Australian intensive care unit administrative data

This research by Heldens and colleagues was published in the Medical Journal of Australia in September 2018.
Objectives:  To compare estimates of the incidence and mortality of sepsis and septic shock among patients in Australian intensive care units (ICUs) according to clinical diagnoses or binational intensive care database (ANZICS CORE) methodology.
Design, Setting, Participants:  Prospective inception cohort study (3-month inception period, 1 October – 31 December 2016, with 60-day follow-up); daily screening of all patients in a tertiary hospital 60-bed multidisciplinary ICU.
Main Outcomes:  Diagnoses of sepsis and septic shock according to clinical criteria and database criteria; in-hospital mortality (censored at 60 days).
Results:  Of 864 patients admitted to the ICU, 146 (16.9%) were diagnosed with sepsis by clinical criteria and 98 (11%) according to the database definition (P < 0.001); the sensitivity of the database criteria for sepsis was 52%, the specificity 97%. Forty-nine patients (5.7%) were diagnosed with septic shock by clinical criteria and 83 patients (9.6%) with the database definition (P < 0.001); the sensitivity of the database criteria for septic shock was 65%, the specificity 94%. In-hospital mortality of patients diagnosed with sepsis was greater in the clinical diagnosis group (39/146, 27%) than in the database group (17/98, 17%; P = 0.12); for septic shock, mortality was significantly higher in the clinical diagnosis group (13/83, 16%) than in the database group (18/49, 37%; P = 0.006).
Conclusions:  When compared with the reference standard – prospective clinical diagnosis – ANZICS CORE database criteria significantly underestimate the incidence of sepsis and overestimate the incidence of septic shock, and also result in lower estimated hospital mortality rates for each condition.
The full text of this article is freely available via this link.

Red blood cell distribution width predicts long-term outcomes in sepsis patients admitted to the intensive care unit

This research by Han and colleagues was published in Clinica chimica acta; international journal of clinical chemistry September 2018 issue.
Background:  Although some underpowered studies have proven that increased red blood cell distribution width (RDW) may be associated with short-term prognosis of sepsis, the long-term prognostic value of RDW remains largely unknown.
Methods:  This retrospective observational study was based on the Medical Information Mart for Intensive Care III (MIMIC III), a large critical care database. Baseline RDW and conventional disease severity scores were extracted along with data on 4-year mortality, of adult patients with severe sepsis upon first admission to the intensive care unit (ICU). The prognostic value of RDW was analysed with Kapan-Meier cure, Cox model, receiver operating characteristic (ROC) curve analysis, net reclassification index (NRI) and integrated discriminatory index (IDI).
Results:  A total of 4264 subjects were included. The area under ROC curve of RDW for predicting 4-year mortality was 0.64 (95% CI: 0.63-0.66). In multivariable Cox model, increased RDW was independently associated with all-cause mortality, irrespective of anemia. With conventional severity scores as reference, RDW had continuous NRI comprised between 0.18 and 0.20, and IDI comprised between 0.30 and 0.40.
Conclusions:  RDW values significantly predicts long-term all-cause mortality in critically ill patients with severe sepsis beyond conventional severity scores.
To access the full text of these articles via the journal’s homepage you require a personal subscription to the journal. Library members can order individual articles via the Rotherham NHS Foundation Trust Library and Knowledge Service using the article requests online via this link.

Automated monitoring for the early detection of sepsis in patients receiving care in intensive care units

Review question:  Can automated systems for the early detection of sepsis reduce the time to treatment and improve outcomes in patients in the intensive care unit (ICU), in comparison to standard care?
cochrane-57-1Background:  Sepsis happens when a person develops an infection and their immune system overreacts to it. If sepsis is not managed it can quickly develop into septic shock, which causes organs such as the liver and heart to stop working properly. People can be affected by sepsis at any time but people in intensive care settings are more likely to be affected by it. Septic shock is fatal for 20% to 70% of people admitted to intensive care in Europe. There is no single diagnostic test that can tell if someone has sepsis or not. Instead, the results of several tests (such as blood tests) have to be reviewed along with other information about the patient (such as their medical history), and clinical observations (such as heart rate, temperature, and blood pressure). This process can be time consuming and complicated to do. People already admitted to intensive care are likely to be very unwell and it can be difficult to tell if abnormal results are because of the problem that caused them to be admitted to intensive care, or because of sepsis.
Automated monitoring systems are electronic systems that can collect and analyse information from different sources, and can be used to alert staff when the signs and symptoms of sepsis have been identified. This may mean that sepsis is diagnosed at the earliest possible time, enabling treatment to begin before organ damage happens. However, there is the possibility that automated monitoring systems don’t help, or even cause harm. This might happen if the systems are unable to correctly detect sepsis (meaning that treatment is not started when it should be, or it is started when it shouldn’t be), or health care staff may not respond to alerts quickly enough, especially if the systems give too many false alarms.
Study characteristics:  We conducted a search to identify evidence published before September 2017. Studies were eligible for inclusion if they compared automated sepsis monitoring to standard care (such as paper‐based systems) in people admitted to intensive or critical care units for critical illness. We did not include non‐randomized studies (studies where participants were not allocated to treatment groups by chance), quasi‐randomized studies (studies where participants were allocated to treatment groups by a method that is not truly down to chance, such as date of birth or medical number), and cross‐over studies (where participants first receive one treatment and then cross over to receive the other treatment). Studies including people already diagnosed with sepsis were also excluded.
Key results:  We included three randomized controlled trials (studies where participants were allocated to treatment groups by chance), involving 1199 participants in this review. Overall there were no significant differences in time to start of antimicrobial therapy (such as antimicrobial and antifungal treatments, very low‐quality evidence), length of stay in the intensive care setting (very low‐quality evidence), or in mortality at 14 days, 28 days or discharge (very low‐quality evidence) when automated monitoring systems were compared to standard care. Very low‐quality evidence was available on failed detection of sepsis but data reporting was too unclear to enable us to analyse this in a meaningful way. Other outcomes that we wished to assess like time to initiation of fluid resuscitation (the process of increasing the amount of fluids in the body), mortality at 30 days, and quality of life were not reported in any of the studies.
Quality of the evidence:  Results of this review show limited, very low‐quality evidence, which has prevented us from drawing meaningful conclusions. It is unclear what effect automated systems for monitoring sepsis have on any outcomes included in this review, and therefore we are uncertain if automated sepsis monitoring is beneficial or not. Additional, high‐quality evidence is needed to help address our review question.
The full text of this Cochrane Review is freely available via this link.