A comparison of different scores for diagnosis and mortality prediction of adults with sepsis in Low-and-Middle-Income Countries: a systematic review and meta-analysis

Adégbitè, Bayodé Roméo; Edoa, Jean Ronald; Ndoumba, Wilfrid F Ndzebe; Mbadinga, Lia Betty Dimessa; Mombo-Ngoma, Ghyslain; Jacob, Shevin T.; Rylance, Jamie; Hänscheid, Thomas; Adegnika, Ayôla Akim; Grobusch, Martin P.

doi:10.1016/j.eclinm.2021.101184

Cited by 30 publications

(41 citation statements)

References 39 publications

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“…Sequential Organ Failure Assessment (SOFA) score is being used as a prognostic factor in sepsis, but it requires multiple laboratory indices that would not be rapidly available in the setting of an emergency department ( 11 ). This was the reason that many later studies tried to develop easier to use prognostic factors like the quick SOFA as we discussed.…”

Section: Discussionmentioning

confidence: 99%

Comparison of the Relationship Between SI and RASI Scores With the Outcome of Sepsis Patients

et al. 2022

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The aim of this study was to compare the relationship between shock index (SI) and respiratory adjusted shock index (RASI) scores with the final outcome of sepsis patients referred to the emergency department. This was prospective research that examined individuals who had been diagnosed with sepsis, determined by the presence of at least two of the three quick sepsis-related organ failure assessment (qSOFA) criteria and the presence of an infectious disease based on a diagnosis made by a hospital physician of Imam Reza and Ghaemshahr of Mashhad in 2019. Demographic information of patients, SI score, RASI score, and information related to the patient's clinical symptoms were recorded in the checklist. The final outcome of this study was considered mortality. Data analysis was performed using descriptive and inferential tests. In the present study, a total of 178 patients, 46 patients (25.8%) were transferred to the intensive care unit, and 98 patients (55.1%) were admitted to the normal wards. Eighty-five patients (47.75%) died and the mean length of hospital stay of all patients was 11.07 ± 9.23 days. Forty-four patients (24.7%) had referred with a decreased level of consciousness and 44 patients (24.7%) presented with confusion. The rest of the patients reported normal levels of consciousness. Kaplan Mir analysis with log-rank was performed to determine the difference in survival distribution in different SI groups: Survival distribution was not statistically different for the four defined groups (based on statistical quartiles (P = 0.320). Receiver operator curves were considered as the date of death in the case of the deceased and the date of discharge from the hospital in the case of the living as censored. The AUC of the RASI scoring system for predicting mortality was 0.614 (P = 0.009) while this value was not significant for SI (P = 0.152). In logistic regression analysis, it was found that by adjusting for the variables of age, sex, sepsis etiology, blood pressure and heart rate, level of consciousness, and gender, patients with the lower respiratory rate (OR 1.6, z = −0.159 p = 0.007), younger age (OR 1.6, z = −0.029 p = 0.006) and higher RASI score are more in risk of mortality (OR 1.29, z = 1.209, p = 0.031). The results of our study showed that RASI scoring can be a good criterion for predicting the chance of mortality in patients with sepsis and could be used complementary to previous criteria such as SI. Patients with high RASI scores should be given more attention to reducing the chance of death.

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Section: Discussionmentioning

confidence: 99%

Comparison of the Relationship Between SI and RASI Scores With the Outcome of Sepsis Patients

et al. 2022

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“…Physiologic parameters and clinical laboratory parameters were modelled as dichotomous or ordinal parameters at clinically relevant cut offs. Screening tools were dichotomized according to current usage, including qSOFA score ≥2 (range, 0 [best] to 3 [worst] points), SIRS score ≥ 2 (range, 0 [best] to 4 [worst] points), MEWS ≥5 (range, 0 [best] to 13 [worst] points), NEWS ≥5 (range, 0 [best] to 20 [worst] points), and UVA ≥2 (range, 0 [best] to 13 [worst]) 10 and were evaluated in Cox regression models unadjusted and adjusted for age and sex for risk of death 9 . Glasgow Coma Scale Score (GCS; range, 3 [worst] to 15 [best] points) of less than 15 was used for estimation of the qSOFA score, and a GCS of ≤3 for unresponsiveness for NEWS, and GCS score 3-15 for the “alert, verbal, pain, unresponsive” scale (AVPU; alert: GCS 13-15, voice: GCS 9-12; pain: GCS 4-8; unresponsiveness: GCS ≤3) score approximation for MEWS 15 16 .…”

Section: Methodsmentioning

confidence: 99%

“…Patients were not involved in recruitment, design, conduct, or dissemination plans of our research. Results [worst]) 10 and were evaluated in Cox regression models unadjusted and adjusted for age and sex for risk of death 9 . Glasgow Coma Scale Score (GCS; range, 3 [worst] to 15 [best] points) of less than 15 was used for estimation of the qSOFA score, and a GCS of ≤3 for unresponsiveness for NEWS, and GCS score 3-15 for the "alert, verbal, pain, unresponsive" scale (AVPU; alert: GCS 13-15, voice: GCS 9-12; pain: GCS 4-8; unresponsiveness: GCS ≤3) score approximation for MEWS 15 16 .…”

Section: Patient and Public Involvementmentioning

confidence: 99%

The performance of screening tools for predicting mortality across multi-site international sepsis cohorts

Blair

Mehta

Oppong

et al. 2022

Preprint

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BackgroundDirect comparisons of sepsis screening tools for prognostication have largely been limited to single-centre or high-income countries despite a disproportionately high burden of sepsis in low- and middle-income countries (LMICs). We evaluated the performance of commonly used sepsis screening tools across prospective sepsis cohorts in the United States, Cambodia, and Ghana.MethodsFrom 2014 to 2021, participants with 2 or more SIRS (Systemic Inflammatory Response Syndrome) criteria and suspected infection were enrolled in emergency departments and medical wards at hospitals in the Cambodia and Ghana and hospitalized participants with suspected infection were enrolled in the United States. Cox proportional hazards regression was performed, and Harrell’s C-statistic calculated to determine 28-day mortality prediction performance of the qSOFA score ≥2, SIRS score ≥3, NEWS ≥5, MEWS ≥5, or UVA score ≥2, Screening tools were compared to baseline risk (age and sex) with the Wald test.ResultsThe cohorts included 567 participants (42.9% female) including 187 participants from Kumasi, Ghana, 200 participants from Takeo, Cambodia, and 180 participants from Durham, North Carolina in the United States. The pooled mortality was 16.4% at 28-days. The mortality prediction accuracy increased from baseline risk with the MEWS (C-statistic: 0.63, 95% CI: 0.58, 0.68; p=0.002), NEWS (C-statistic: 0.68; 95% confidence interval [CI]: 0.64, 0.73; p<0.001), qSOFA (C-statistic: 0.70, 95% CI: 0.64, 0.75; p<0.001), UVA score (C-statistic: 0.73, 95% CI: 0.69, 0.78; p<0.001), but not with SIRS (0.60; 95% CI: 0.54, 0.65; p=0.13). Within individual cohorts, only the UVA score in Ghana performed better than baseline risk (C-statistic: 0.77; 95% CI: 0.71, 0.83; p<0.001).ConclusionsAmong the cohorts, MEWS, NEWS, qSOFA, and UVA scores performed better than baseline risk, largely driven by accuracy improvements in Ghana, while SIRS scores did not improve prognostication accuracy. Prognostication scores should be validated within the target population prior to clinical use.Key questionsWhat is already known on this topic – While single-centre cohorts and retrospective analyses have been performed, the optimal sepsis screening tool for prognostication in low- and middle-income countries is unknown.What this study adds – The MEWS, NEWS, qSOFA scores, but not SIRS, were additive over baseline risk for prognostication in prospective hospitalized infection cohorts, but with variable additive performance within each cohort.How this study might affect research, practice or policy - Prognostication scores should be validated within the target population prior to clinical use.

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“…[20] Data from developing countries suggest that a positive qSOFA score is associated with a higher risk of mortality in patients with infections. [21,22] The discriminatory power of qSOFA is, however, variable and sometimes inferior to other available scores. [22] The overall accuracy or discriminatory power of a predictive tool is extremely important.…”

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confidence: 99%

“…[21,22] The discriminatory power of qSOFA is, however, variable and sometimes inferior to other available scores. [22] The overall accuracy or discriminatory power of a predictive tool is extremely important. In the context of making meaningful management decisions with the use of a qSOFA score, the ED physician would prefer a highly sensitive tool to avoid missing an infection, while an intensivist would favour a tool with higher specificity to be able to exclude an infection with certainty.…”

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confidence: 99%

Positioning the role of qSOFA for screening and prognostication in critically ill medical and surgical patients with suspected sepsis

Paruk

2021

AJTCCM

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A comparison of different scores for diagnosis and mortality prediction of adults with sepsis in Low-and-Middle-Income Countries: a systematic review and meta-analysis

Cited by 30 publications

References 39 publications

Comparison of the Relationship Between SI and RASI Scores With the Outcome of Sepsis Patients

Comparison of the Relationship Between SI and RASI Scores With the Outcome of Sepsis Patients

The performance of screening tools for predicting mortality across multi-site international sepsis cohorts

Positioning the role of qSOFA for screening and prognostication in critically ill medical and surgical patients with suspected sepsis

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