Psoriasis is an immune-mediated disorder which primarily affects skin and has systemic inflammatory involvement. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and monocyte-to-lymphocyte ratio (MLR) are novel complete blood count (CBC)-derived markers which can reflect systemic inflammation. This study aimed to systematically investigate the associations of NLR, PLR, SII, and MLR with psoriasis. This study was performed in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. A comprehensive search of Pubmed, Embase, Scopus, and Google Scholar was conducted for relevant studies. Observational studies evaluating the correlations of NLR, PLR, SII, or MLR with psoriasis were included. The primary outcomes were the associations of these inflammatory markers with the presence and severity of psoriasis. The random-effect model was applied for meta-analysis. 36 studies comprising 4794 psoriasis patients and 55,121 individuals in total were included in the meta-analysis. All inflammatory markers were significantly increased in psoriasis groups compared to healthy controls (NLR: MD = 0.59, 95% CI: 0.47-0.7; PLR: MD = 15.53, 95% CI: 8.48-22.58; SII: MD = 111.58, 95% CI: 61.49-161.68; MLR: MD = 0.034, 95% CI: 0.021-0.048; all p < 0.001). Between-group mean differences in NLR and PLR were positively correlated with the mean scores of Psoriasis Area Severity Index (NLR: p = 0.041; PLR: p = 0.021). NLR, PLR, SII, and MLR are associated with the presence of psoriasis. NLR and PLR serve as significant indicators of psoriasis severity. These novel CBC-derived markers constitute potential targets in the screening and monitoring of psoriasis.

Immune and inflammatory responses play an important role in tumorigenesis and metastasis. Inflammation is an important component of the tumor microenvironment, and the changes in inflammatory cells may affect the occurrence and development of tumors. Complete blood count at the time of diagnosis and treatment can reflect the inflammatory status within the tumor. Studies have shown that the number of certain inflammatory cells in peripheral blood and their ratios are important prognostic factors for many malignancies, including neutrophil, lymphocyte, monocyte, and platelet counts, as well as neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index, systemic inflammation response index and pan-immune-inflammation-value. The value of peripheral blood inflammation indexes in predicting the efficacy and prognosis of breast cancer neoadjuvant therapy is worth recognizing. This review details the application of peripheral blood inflammation indexes in the evaluation of efficacy and prediction of prognosis in neoadjuvant therapy for breast cancer, aiming to provide a more comprehensive reference for the comprehensive diagnosis and treatment of breast cancer.

The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are emerging tools that can be used in the diagnosis of deep venous thrombosis (DVT). This study aims to evaluate the diagnostic value of NLR and PLR for patients with DVT. Our meta-analysis included 11 eligible studies and extracted relevant diagnostic indicators. Of these studies, 4 focused on the NLR, 1 on the PLR, while 6 evaluated both. For the 10 studies on NLR, the pooled sensitivity, specificity, positive-likelihood ratio, and negative-likelihood ratio were 74%, 66%, 2.16, and 0.4, respectively. The estimated diagnostic odds ratio (DOR) was 5.3, and the area under the curve (AUC) of the summary receiver operating characteristic (SROC) curves was 0.74. For the 7 studies on the PLR, the pooled sensitivity, specificity, positive-likelihood ratio, and negative-likelihood ratio were 0.65, 0.77, 2.89, and 0.45, respectively. The estimated DOR was 6.64, and the SROC-AUC was 0.79. Our findings showed that the NLR and PLR exhibit moderate diagnostic accuracy and may be helpful biomarkers for the diagnosis of DVT. Future prospective, well-designed studies with large sample sizes will be required to provide additional evidence to establish cutoff values and clinical value of these indicators.

UNASSIGNED: Stroke is known as a common cause of disability all over the world. Stroke prognosis estimation has always been a topic of interest. In this study, it was tried to investigate the prognostic value of laboratory findings of complete blood count in a systematic review.
UNASSIGNED: In this systematic review, literature from Medline via (PubMed, Ovid) Embase, Scopus, Cochrane Library, and ProQuest between 1988 and 2020 were included. A combination of Mesh and free terms were included in the search strategy: \"Stroke\", \"Red Cell Distribution Width\", \"Blood Cell Count\", \"Mean corpuscular hemoglobin\", and \"Mean Corpuscular Volume\" and with the abbreviation, in all fields. Data synthesis was achieved using content analysis.
UNASSIGNED: Elevated red blood cell distribution width was associated with stroke, cardiovascular events, and all-cause deaths among patients with prior stroke. Mean platelet volume has not any prognostic significance in ischemic stroke. There was a poor association between mean corpuscular volume (MCV) and stroke prognosis. Globulin and hemoglobin level predicted short-term mortality following acute ischemic stroke.
UNASSIGNED: Complete blood count as a routine and efficient test performed in health care centers can be used to estimate the prognosis of stroke.

暂无摘要。

Cancer is concerning owing to its high mortality rate. Consequently, methods of prolonging the life of patients with cancer have become the primary focus of attention research. In recent years, immune checkpoint inhibitors (ICIs) have achieved good clinical efficacy as antitumor drugs; however, their severe adverse effects have made their use challenging. In order to clarify the predictors of adverse effects, scientists have conducted a series of studies. Blood counts can potentially monitor risk factors associated with the occurrence of immune-related adverse events (irAEs). Herein, a meta-analysis was performed to clarify further the guiding significance of blood counts in the clinical setting.
Studies that satisfied the inclusion criteria were obtained by searching the database. Included studies were those in which irAEs had been observed, and evidence of an association between blood counts and irAEs was reported. The included ones were evaluated for quality. In addition to sensitivity analysis and subgroup analysis, a meta-analysis was performed using the odds ratio (OR) and 95% confidence interval (CI) for each study.
A total of 18 articles were included in our study. The analyses were performed separately according to different blood cell count indicators. The blood cell count metrics associated with irAEs were: absolute eosinophil count, neutrophil: lymphocyte ratio, and platelet: lymphocyte ratio.
Our review and meta-analysis of studies suggest that absolute eosinophil count, neutrophil: lymphocyte ratio, and platelet: lymphocyte ratio may serve as predictors of the emergence of irAEs. Given the small number of studies focusing on the relationship between patient blood cell counts and the risk of irAEs, future studies need to further explore the mechanisms of occurrence and potential associations.

OBJECTIVE: Sudden sensorineural hearing loss is considered idiopathic in up to 90 per cent of cases. This study explored the role of blood tests as biomarkers for the diagnosis and prognosis of sudden sensorineural hearing loss.
METHODS: Two researchers filtered 34 papers into the final review. This review was pre-registered on the Prospero database and conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines.
RESULTS: Raised inflammatory markers are almost universal in sudden sensorineural hearing loss, suggesting an inflammatory or autoimmune process. The most useful biomarkers are neutrophil-lymphocyte ratio, platelet-lymphocyte ratio and fibrinogen level. Focused investigations should be deployed on a case-by-case basis to identify underlying metabolic, infective and autoimmune conditions.
CONCLUSIONS: A full blood count and coagulation screen (fibrinogen) is recommended in all cases of sudden sensorineural hearing loss. These are inexpensive, accessible and offer as much diagnostic and prognostic information as any other biomarker. There is emerging evidence regarding specific biomarkers for sudden sensorineural hearing loss prognosis, with heat shock protein-70, anti-endothelial cell antibody and prestin demonstrating potential; investigation of their validity through prospective, controlled research is recommended.

OBJECTIVE: We aimed to establish appropriate review criteria for blood cell analysis in a specialized women\'s and children\'s hospital. Also, the CellaVision DI-60, was developed as one of the automated digital cell morphology analyzer, we evaluated if it was shown to be most effective under the certain review criteria.
METHODS: A total of 2890 blood samples were detected to optimize the previously established review criteria for women and children with the Sysmex XE-2100. A total of 623 samples were used to validate the criteria.
RESULTS: The microscopic-review rate based on the initial review criteria was 51.0%. After optimization, it was reduced to 17.3% and the false-negative rate was 3.85%. There was > 80% consistency between manual review results and CellaVision DI-60 preclassification when samples triggered the platelet- or red cell-related rules. The sensitivity for abnormalities (immature granulocytes, nucleated red blood cells) of reclassification was 90% to 100% and the false-negative rate was < 5%. However, direct microscopic review was required when the \"Blasts/AbnLympho?\" and \"Atypical Lympho?\" flags were triggered.
CONCLUSIONS: Specialized review criteria are needed for women and children. An automated morphology identification system might help to improve the review criteria.

BACKGROUND: Myelodysplastic syndromes (MDS) are clonal hematopoietic diseases of the elderly characterized by chronic cytopenias, ineffective and dysplastic haematopoiesis, recurrent genetic abnormalities and increased risk of progression to acute myeloid leukemia. A challenge of routine laboratory Complete Blood Counts (CBC) is to correctly identify MDS patients while simultaneously avoiding excess smear reviews. To optimize smear review, the latest generations of hematology analyzers provide new cell population data (CPD) parameters with an increased ability to screen MDS, among which the previously described MDS-CBC Score, based on Absolute Neutrophil Count (ANC), structural neutrophil dispersion (Ne-WX) and mean corpuscular volume (MCV). Ne-WX is increased in the presence of hypogranulated/degranulated neutrophils, a hallmark of dysplasia in the context of MDS or chronic myelomonocytic leukemia. Ne-WX and MCV are CPD derived from leukocytes and red blood cells, therefore the MDS-CBC score does not include any platelet-derived CPD. We asked whether this score could be improved by adding the immature platelet fraction (IPF), a CPD used as a surrogate marker of dysplastic thrombopoiesis.
METHODS: Here, we studied a cohort of more than 500 individuals with cytopenias, including 168 MDS patients. In a first step, we used Breiman\'s random forests algorithm, a machine-learning approach, to identify the most relevant parameters for MDS prediction. We then designed Classification And Regression Trees (CART) to evaluate, using resampling, the effect of model tuning parameters on performance and choose the \"optimal\" model across these parameters.
RESULTS: Using random forests algorithm, we identified Ne-WX and IPF as the strongest discriminatory predictors, explaining 37 and 33% of diagnoses respectively. To obtain \"simplified\" trees, which could be easily implemented into laboratory middlewares, we designed CART combining MDS-CBC score and IPF. Optimal results were obtained using a MDS-CBC score threshold equal to 0.23, and an IPF threshold equal to 3%.
CONCLUSIONS: We propose an extended MDS-CBC score, including CPD from the three myeloid lineages, to improve MDS diagnosis on routine laboratory CBCs and optimize smear reviews.

BACKGROUND: Wrong blood in tube (WBIT) errors are a significant patient-safety issue encountered by clinical laboratories. This study assessed the performance of machine learning models for the identification of WBIT errors affecting complete blood count (CBC) results against the benchmark of manual review of results by laboratory staff.
METHODS: De-identified current and previous (within seven days) CBC results were used in the computer simulation of WBIT errors. 101 015 sets of samples were used to develop machine learning models using artificial neural network, extreme gradient boosting, support vector machine, random forest, logistic regression, decision trees (one complex and one simple) and k-nearest neighbours algorithms. The performance of these models, and of manual review by laboratory staff, was assessed on a separate data set of 1940 samples.
RESULTS: Volunteers manually reviewing results identified WBIT errors with an accuracy of 85.7%, sensitivity of 80.1% and specificity of 92.1%. All machine learning models exceeded human-level performance (p-values for all metrics were <.001). The artificial neural network model was the most accurate (99.1%), and the simple decision tree was the least accurate (96.8%). Sensitivity for the machine learning models varied from 95.7% to 99.3%, and specificity varied from 96.3% to 98.9%.
CONCLUSIONS: This study provides preliminary evidence supporting the value of machine learning for detecting WBIT errors affecting CBC results. Although further work addressing practical issues is required, substantial patient-safety benefits await the successful deployment of machine learning models for WBIT error detection.