METHODS: Full and partial economic evaluations, published in English, associated with the management of neonatal systemic infections in South Asia will be included. Any intervention related to management of neonatal systemic infections will be eligible for inclusion. Comparison can include a placebo or alternative standard of care. Interventions without any comparators will also be eligible for inclusion. Outcomes of this review will include measures related to resource use, costs and cost-effectiveness. Electronic searches will be conducted on PubMed, CINAHL, MEDLINE (Ovid), EMBASE, Web of Science, EconLit, the Centre for Reviews and Dissemination Library (CRD) Database, Popline, IndMed, MedKnow, IMSEAR, the Cost Effectiveness Analysis (CEA) Registry and Pediatric Economic Database Evaluation (PEDE). Conference proceedings and grey literature will be searched in addition to performing back referencing of bibliographies of included studies. Two authors will independently screen studies (in title, abstract and full-text stages), extract data and assess risk of bias. A narrative summary and tables will be used to summarize the characteristics and results of included studies.
DISCUSSION: Neonatal systemic infections can have significant economic repercussions on the families, health care providers and, cumulatively, the nation. Pediatric economic evaluations have focused on the under-five age group, and published consolidated economic evidence for neonates is missing in the developing world context. To the best of our knowledge, this is the first review of economic evidence on neonatal systemic infections in the South Asian context. Further, this protocol provides an underst anding of the methods used to design and evaluate economic evidence for methodological quality, transparency and focus on health equity. This review will also highlight existing gaps in research and identify scope for further research.
SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017047275.
METHODS: Different electronic databases were searched in a non-systematic way to find out the literature of interest.
RESULTS: The level of ferritin rises in many inflammatory conditions including autoimmune disorders. However, in four inflammatory diseases (i.e., adult-onset Still's diseases, macrophage activation syndrome, catastrophic antiphospholipid syndrome, and sepsis), high levels of ferritin are observed suggesting it as a remarkable biomarker and pathological involvement in these diseases. Acting as an acute phase reactant, ferritin is also involved in the cytokine-associated modulator of the immune response as well as a regulator of cytokine synthesis and release which are responsible for the inflammatory storm.
CONCLUSION: This review article presents updated information on the role of ferritin in inflammatory and autoimmune diseases with an emphasis on hyperferritinaemic syndrome.
MATERIALS: We recruited consecutively adult patients with SIRS admitted to an intensive care unit. They were divided into sepsis and noninfectious SIRS based on clinical assessment with or without positive cultures. Concentrations of PCT and IL-6 were measured daily over the first 3 days.
RESULTS: A total of 239 patients were recruited, 164 (68.6%) had sepsis, and 68 (28.5%) died in hospital. The PCT levels were higher in sepsis compared with noninfectious SIRS throughout the 3-day period (P < .0001). On admission, PCT concentration was diagnostic of sepsis (area under the curve of 0.63 [0.55-0.71]), and IL-6 was predictive of mortality, (area under the curve of 0.70 [0.62-0.78]). Peak IL-6 concentration improved the risk assessment of Sequential Organ Failure Assessment (SOFA) score for prediction of mortality among those who went on to die by an average of 5% and who did not die by 2%
CONCLUSIONS: Procalcitonin measured on intensive care unit admission was diagnostic of sepsis, and IL-6 was predictive of mortality. Addition of IL-6 concentration to SOFA score improved risk assessment for prediction of mortality. Future studies should include clinical indices, for example, SOFA score, for prognostic evaluation of biomarkers.
METHODS: This study included 159 septic patients admitted to an intensive care unit. Leukocytes count, procalcitonin (PCT), interleukin-6 (IL-6), and paraoxonase (PON) and arylesterase (ARE) activities of PON-1 were assayed from blood obtained on ICU presentation. Logistic regression was used to derive sepsis mortality score (SMS), a prediction equation describing the relationship between biomarkers and 30-day mortality.
RESULTS: The 30-day mortality rate was 28.9%. The SMS was [еlogit(p)/(1+еlogit(p))]×100; logit(p)=0.74+(0.004×PCT)+(0.001×IL-6)-(0.025×ARE)-(0.059×leukocytes count). The SMC had higher area under the receiver operating characteristic curve (95% Cl) than SOFA score [0.814 (0.736-0.892) vs. 0.767 (0.677-0.857)], but is not statistically significant. When the SMS was added to the SOFA score, prediction of 30-day mortality improved compared to SOFA score used alone [0.845 (0.777-0.899), p=0.022].
CONCLUSIONS: A sepsis mortality score using baseline leukocytes count, PCT, IL-6 and ARE was derived, which predicted 30-day mortality with very good performance and added significant prognostic information to SOFA score.
METHODS: Fifty-one adult patients with suspected bacterial sepsis on admission to the Emergency Department (ED) of a teaching hospital were included into the study. All relevant cultures and serology tests were performed. Serum levels for Group II Secretory Phospholipase A2 (sPLA2-IIA) and CD64 were subsequently analyzed.
RESULTS AND DISCUSSION: Sepsis was confirmed in 42 patients from a total of 51 recruited subjects. Twenty-one patients had culture-confirmed bacterial infections. Both biomarkers were shown to be good in distinguishing sepsis from non-sepsis groups. CD64 and sPLA2-IIA also demonstrated a strong correlation with early sepsis diagnosis in adults. The area under the curve (AUC) of both Receiver Operating Characteristic curves showed that sPLA2-IIA was better than CD64 (AUC = 0.93, 95% confidence interval (CI) = 0.83-0.97 and AUC = 0.88, 95% CI = 0.82-0.99, respectively). The optimum cutoff value was 2.13μg/l for sPLA2-IIA (sensitivity = 91%, specificity = 78%) and 45 antigen bound cell (abc) for CD64 (sensitivity = 81%, specificity = 89%). In diagnosing bacterial infections, sPLA2-IIA showed superiority over CD64 (AUC = 0.97, 95% CI = 0.85-0.96, and AUC = 0.95, 95% CI = 0.93-1.00, respectively). The optimum cutoff value for bacterial infection was 5.63μg/l for sPLA2-IIA (sensitivity = 94%, specificity = 94%) and 46abc for CD64 (sensitivity = 94%, specificity = 83%).
CONCLUSIONS: sPLA2-IIA showed superior performance in sepsis and bacterial infection diagnosis compared to CD64. sPLA2-IIA appears to be an excellent biomarker for sepsis screening and for diagnosing bacterial infections, whereas CD64 could be used for screening bacterial infections. Both biomarkers either alone or in combination with other markers may assist in decision making for early antimicrobial administration. We recommend incorporating sPLA2-IIA and CD64 into the diagnostic algorithm of sepsis in ED.