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Objective: Postoperative infection is a common but costly complication. The neutrophil-lymphocyte ratio is a promising marker for the identification of postsurgical infectious events. We aimed to perform this meta-analysis to assessed the accuracy of the neutrophil-lymphocyte ratio for the prediction of postsurgical infection. Methods: We searched PubMed, Embase, Web of Science, and Cochrane Library without language restriction from their inceptions to April 2022, and checked reference lists of included studies. Studies were included if they assessed predictive accuracy of neutrophil-lymphocyte ratio for postsurgical infection. We estimated its predictive value and explored the source of heterogeneity. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to assess methodological quality and the Deeks' test to evaluate publication bias. The bivariate model and hierarchical summary receiver operating characteristic (HSROC) curve were used for meta-analysis and generated a summary receiver operating characteristic space (ROC) curve. Results: Our search returned 379 reports, of which 12 fulfilled the inclusion criteria, accounting for 4375 cases. The bivariate analysis yielded a pooled sensitivity of 0.77 (95%C.I.: 0.65-0.85) and specificity of 0.78 (95%C.I.: 0.67-0.86). Pooled positive LR and negative LR were 3.48 (95%C.I.: 2.26-5.36) and 0.30 (95%C.I.: 0.20-0.46), respectively. A negative LR of 0.30 reduces the post-test probability to 2% for a negative test result. The area under of receiver operating characteristic curve was 0.84 (95%C.I.: 0.80-0.87). Subgroups comparisons revealed difference by study design, surgical site, presentence of implant, time of sampling, type of infection event and prevalence of infection. The Deeks' test showed no publication bias. The sensitivity analysis showed no study affected the robustness of combined results. Conclusions: Low-certainty evidence suggests that the neutrophil-lymphocyte ratio is a helpful marker for predicting postoperative infectious complication. The negative predictive value of the neutrophil-lymphocyte ratio enables for reliable exclusion of postoperative infection.Trial registrationPROSPERO registration number CRD42022321197. Registered on 27 April 2022.
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BACKGROUND: Acute kidney injury (AKI) is a frequent syndrome in the intensive care unit (ICU). AKI patients with kidney function recovery have better short-term and long-term prognoses compared with those with non-recovery. Numerous studies focus on biomarkers to distinguish them. To better understand the predictive performance of urinary biomarkers of renal recovery in patients with AKI, we evaluated C-C motif chemokine ligand 14 (CCL14) and two first-generation biomarkers (cell cycle arrest biomarkers and neutrophil gelatinase-associated lipocalin) in two ICU settings. METHODS: We performed a prospective study to analyze urinary biomarkers for predicting renal recovery from AKI. Patients who developed AKI after ICU admission were enrolled and urinary biomarkers including tissue inhibitor of metalloproteinase-2 (TIMP-2), insulin-like growth factor-binding protein 7 (IGFBP7), CCL14, and neutrophil gelatinase-associated lipocalin (NGAL) were detected on the day of AKI diagnosis. The primary endpoint was non-recovery from AKI within 7 days. The individual discriminative ability of CCL14, [TIMP-2] × [IGFBP7] and NGAL to predict renal non-recovery were evaluated by the area under receiver operating characteristics curve (AUC). RESULTS: Of 164 AKI patients, 64 (39.0%) failed to recover from AKI onset. CCL14 showed a fair prediction ability for renal non-recovery with an AUC of 0.71 (95% CI 0.63-0.77, p < 0.001). [TIMP-2] × [IGFBP7] showed the best prediction for renal non-recovery with an AUC of 0.78 (95% CI 0.71-0.84, p < 0.001). However, NGAL had no use in predicting non-recovery with an AUC of 0.53 (95% CI 0.45-0.60, p = 0.562). A two-parameter model (non-renal SOFA score and AKI stage) predicted renal non-recovery with an AUC of 0.77 (95% CI 0.77-0.83, p = 0.004). When [TIMP-2] × [IGFBP7] was combined with the clinical factors, the AUC was significantly improved to 0.82 (95% CI 0.74-0.87, p = 0.049). CONCLUSIONS: Urinary CCL14 and [TIMP-2] × [IGFBP7] were fair predictors of renal non-recovery from AKI. Combing urinary [TIMP-2] × [IGFBP7] with a clinical model consisting of non-renal SOFA score and AKI stage enhanced the predictive power for renal non-recovery. Urinary CCL14 showed no significant advantage in predicting renal non-recovery compared to [TIMP-2] × [IGFBP7].
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Introduction: Sepsis is a life-threatening condition, and biomarkers are needed to diagnose sepsis fast and accurately. We aimed to perform this meta-analysis to investigate the diagnostic value of calprotectin on sepsis in critically ill patients. Methods: The investigators searched MEDLINE, Embase, Web of Science and Cochrane Library. Studies were included if they assessed the diagnostic accuracy of serum calprotectin for sepsis in intensive care unit (ICU). We estimated its diagnostic value and explored the source of heterogeneity. The bivariate model and the hierarchical summary receiver operating characteristic (HSROC) curve were used in the meta-analysis. Results: Six records assessing 821 patients were included in this meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio (PLR), and diagnostic odds ratio (DOR) were separately as 0.77, 0.85, 5.20, 0.27, respectively. The Fagan's nomogram showed post-test probabilities of 91% and 35% for positive and negative outcomes, respectively. Subgroup analysis indicated that sepsis definition could be a possible source of heterogeneity, but there's no sufficient data to investigate sepsis-3 definition. Sensitivity analysis suggested that two studies could affect the stability of pooled results. Conclusion: On the basis of our meta-analysis, calprotectin is a helpful marker for early diagnosis of sepsis on ICU admission.