Comparison of quick sequential organ failure assessment and modified systemic inflammatory response syndrome criteria in a lower middle income setting

Introduction: Quick Sequential Organ Failure Assessment (qSOFA) is potentially feasible tool to identify risk of deteriorating in the context of infection for to use in resource limited settings. Purpose: To compare the discriminative ability of qSOFA and a simplified systemic inflammatory response syndrome (SIRS) score to detect deterioration in patients admitted with infection. Methods: Observational study conducted at District General Hospital Monaragala, Sri Lanka, utilising bedside available observations extracted from healthcare records. Discrimination was evaluated using area under the receiver operating curve (AUROC). 15,577 consecutive adult ( ≥ 18 years) admissions were considered. Patients classified as having infection per ICD-10 diagnostic coding were included. Results: Both scores were evaluated for their ability to discriminate patients at risk of death or a composite adverse outcome (death, cardiac arrest, intensive care unit [ICU], admission or critical care transfer). 1844 admissions (11.8%) were due to infections with 20 deaths (1.1%), 29 ICU admissions (1.6%), 30 cardiac arrests and 9 clinical transfers to a tertiary hospital (0.5%). Sixty-seven (3.6%) patients experienced at least one event. Complete datasets were available for qSOFA in 1238 (67.14%) and for simplified SIRS (mSIRS) in 1628 (88.29%) admissions. Mean (SD) qSOFA score and mSIRS score at admission were 0.58 (0.69) and 0.66 (0.79) respectively. Both demonstrated poor discrimination for predicting adverse outcome AUROC = 0.625; 95% CI, 0.56-0.69 and AUROC = 0.615; 95% CI, 0.55- 0.69 respectively) with no significant difference (p value = 0.74). Similarly, both systems had poor discrimination for predicting deaths (AUROC = 0.685; 95% CI, 0.55-0.82 and AUROC = 0.629; 95% CI, 0.50-0.76 respectively) with no statistically significant difference (p value = 0.31). Conclusions: qSOFA at admission had poor discrimination and was not superior to the bedside observations featured in SIRS. Availability of observations, especially for mentation, is poor in these settings and requires strategies to improve reporting

Comparison of quick sequential organ failure assessment and modified systemic inflammatory response syndrome criteria in a lower middle income setting

Introduction: Quick Sequential Organ Failure Assessment (qSOFA) is potentially feasible tool to identify risk of deteriorating in the context of infection for to use in resource limited settings. Purpose: To compare the discriminative ability of qSOFA and a simplified systemic inflammatory response syndrome (SIRS) score to detect deterioration in patients admitted with infection. Methods: Observational study conducted at District General Hospital Monaragala, Sri Lanka, utilising bedside available observations extracted from healthcare records. Discrimination was evaluated using area under the receiver operating curve (AUROC). 15,577 consecutive adult ( ≥ 18 years) admissions were considered. Patients classified as having infection per ICD-10 diagnostic coding were included. Results: Both scores were evaluated for their ability to discriminate patients at risk of death or a composite adverse outcome (death, cardiac arrest, intensive care unit [ICU], admission or critical care transfer). 1844 admissions (11.8%) were due to infections with 20 deaths (1.1%), 29 ICU admissions (1.6%), 30 cardiac arrests and 9 clinical transfers to a tertiary hospital (0.5%). Sixty-seven (3.6%) patients experienced at least one event. Complete datasets were available for qSOFA in 1238 (67.14%) and for simplified SIRS (mSIRS) in 1628 (88.29%) admissions. Mean (SD) qSOFA score and mSIRS score at admission were 0.58 (0.69) and 0.66 (0.79) respectively. Both demonstrated poor discrimination for predicting adverse outcome AUROC = 0.625; 95% CI, 0.56-0.69 and AUROC = 0.615; 95% CI, 0.55- 0.69 respectively) with no significant difference (p value = 0.74). Similarly, both systems had poor discrimination for predicting deaths (AUROC = 0.685; 95% CI, 0.55-0.82 and AUROC = 0.629; 95% CI, 0.50-0.76 respectively) with no statistically significant difference (p value = 0.31). Conclusions: qSOFA at admission had poor discrimination and was not superior to the bedside observations featured in SIRS. Availability of observations, especially for mentation, is poor in these settings and requires strategies to improve reporting

Evaluation of the feasibility and performance of early warning scores to identify patients at risk of adverse outcomes in a low-middle income country setting

Objective This study describes the availability of core parameters for Early Warning Scores (EWS), evaluates the ability of selected EWS to identify patients at risk of death or other adverse outcome and describes the burden of triggering that front-line staff would experience if implemented. Design Longitudinal observational cohort study. Setting District General Hospital Monaragala Participants All adult (age &gt;17 years) admitted patients. Main outcome measures Existing physiological parameters, adverse outcomes and survival status at hospital discharge were extracted daily from existing paper records for all patients over an 8-month period. Statistical Analysis Discrimination for selected aggregate weighted track and trigger systems (AWTTS) was assessed by the area under the receiver operating characteristic (AUROC) curve. Performance of EWS are further evaluated at time points during admission and across diagnostic groups. The burden of trigger to correctly identify patients who died was evaluated using positive predictive value (PPV). Results Of the 16 386 patients included, 502 (3.06%) had one or more adverse outcomes (cardiac arrests, unplanned intensive care unit admissions and transfers). Availability of physiological parameters on admission ranged from 90.97% (95% CI 90.52% to 91.40%) for heart rate to 23.94% (95% CI 23.29% to 24.60%) for oxygen saturation. Ability to discriminate death on admission was less than 0.81 (AUROC) for all selected EWS. Performance of the best performing of the EWS varied depending on admission diagnosis, and was diminished at 24 hours prior to event. PPV was low (10.44%). Conclusion There is limited observation reporting in this setting. Indiscriminate application of EWS to all patients admitted to wards in this setting may result in an unnecessary burden of monitoring and may detract from clinician care of sicker patients. Physiological parameters in combination with diagnosis may have a place when applied on admission to help identify patients for whom increased vital sign monitoring may not be beneficial. Further research is required to understand the priorities and cues that influence monitoring of ward patients.</p

Evaluation of the feasibility and performance of early warning scores to identify patients at risk of adverse outcomes in a low-middle income country setting

Objective This study describes the availability of core parameters for Early Warning Scores (EWS), evaluates the ability of selected EWS to identify patients at risk of death or other adverse outcome and describes the burden of triggering that front-line staff would experience if implemented. Design Longitudinal observational cohort study. Setting District General Hospital Monaragala Participants All adult (age >17 years) admitted patients. Main outcome measures Existing physiological parameters, adverse outcomes and survival status at hospital discharge were extracted daily from existing paper records for all patients over an 8-month period. Statistical Analysis Discrimination for selected aggregate weighted track and trigger systems (AWTTS) was assessed by the area under the receiver operating characteristic (AUROC) curve. Performance of EWS are further evaluated at time points during admission and across diagnostic groups. The burden of trigger to correctly identify patients who died was evaluated using positive predictive value (PPV). Results Of the 16 386 patients included, 502 (3.06%) had one or more adverse outcomes (cardiac arrests, unplanned intensive care unit admissions and transfers). Availability of physiological parameters on admission ranged from 90.97% (95% CI 90.52% to 91.40%) for heart rate to 23.94% (95% CI 23.29% to 24.60%) for oxygen saturation. Ability to discriminate death on admission was less than 0.81 (AUROC) for all selected EWS. Performance of the best performing of the EWS varied depending on admission diagnosis, and was diminished at 24 hours prior to event. PPV was low (10.44%). Conclusion There is limited observation reporting in this setting. Indiscriminate application of EWS to all patients admitted to wards in this setting may result in an unnecessary burden of monitoring and may detract from clinician care of sicker patients. Physiological parameters in combination with diagnosis may have a place when applied on admission to help identify patients for whom increased vital sign monitoring may not be beneficial. Further research is required to understand the priorities and cues that influence monitoring of ward patients.</p

A retrospective study of physiological observation-reporting practices and the recognition, response, and outcomes following cardiopulmonary arrest in a low-to-middle-income country

Background and Aims In Sri Lanka, as in most low‑to‑middle‑income countries (LMICs), early warning systems (EWSs) are not in use. Understanding observation‑reporting practices and response to deterioration is a necessary step in evaluating the feasibility of EWS implementation in a LMIC setting. This study describes the practices of observation reporting and the recognition and response to presumed cardiopulmonary arrest in a LMIC. Patients and Methods This retrospective study was carried out at District General Hospital Monaragala, Sri Lanka. One hundred and fifty adult patients who had cardiac arrests and were reported to a nurse responder were included in the study. Results Availability of six parameters (excluding mentation) was significantly higher at admission (P Conclusions Observations commonly used to detect deterioration are poorly reported, and reporting practices would need to be improved prior to EWS implementation. These findings reinforce the need for training in acute care and resuscitation skills for health‑care teams in LMIC settings as part of a program of improving recognition and response to acute deterioration.</p