Identifying key predictors of post-stroke depression and cognitive impairment in acute stroke survivors

 Predictions are useless! Both of these are solved by EXACT 100% RECOVERY PROTOCOLS! Solve the correct problem! I'd have you all fired for incompetence!

And the commentors on this need to be fired also for missing the real problem; lack of 100% recovery protocols!

Commentary: Identifying key predictors of post-stroke depression and cognitive impairment in acute stroke survivors 

The latest here:

Identifying key predictors of post-stroke depression and cognitive impairment in acute stroke survivors

• 

  Zhiwen Yan 1†

• H

  Huan Zhao 1†

• 

  Jianjun Chen 2

• F

  Fang Liu 1

• L

  Lei Gong 1

• 

  Yingli Li 1

• J

  Jie Zhang 1

• M

  Mi Xiao 1

• 

  Jun Mu 1*

• 1. Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China

• 2. Chongqing Key Laboratory of Neurobiology, Institute of Neuroscience, Chongqing Medical University, Chongqing, China

Abstract

Background: 

Post-stroke depression (PSD) and post-stroke cognitive impairment (PSCI) are prevalent complications in aging stroke survivors and are often overlooked due to the lack of early diagnostic indicators, leading to poor prognosis. Identifying reliable predictors is crucial for timely intervention.

Methods: 

This prospective cohort study followed 78 acute stroke survivors for 6 months. A composite neuropsychological outcome—defined as the development of PSD and/or PSCI—was determined using the Diagnostic and Statistical Manual of Mental Disorders-5th Edition (DSM-5) and NINDS-CSN criteria. To account for the limited sample size, multivariable Firth’s penalized logistic regression was employed to identify independent predictors, generating robust odds ratios (ORs) and 95% confidence intervals (CIs). An exploratory classification and regression tree (CART) analysis was also conducted for hypothesis generation.

Results: 

The final cohort comprised 78 acute ischemic stroke survivors with a median age of 62 years (IQR 51–71). Among these participants, 26.0% were women, and the median admission score on the National Institutes of Health Stroke Scale (NIHSS) was 3 (IQR 1–5). Within 6 months, 56 patients (71.8%) developed the composite outcome (13 experienced PSCI alone, 24 had PSD alone, and 19 had both conditions). A multivariable analysis revealed that right hemisphere lesions (OR = 9.019, 95% CI: 1.329–61.213, p = 0.016), greater baseline emotional distress (higher 9-item Patient Health Questionnaire (PHQ-9) scores; OR = 5.157, 95% CI: 1.835–14.494, p < 0.001), and pre-existing cognitive vulnerability (lower Mini–Mental State Examination (MMSE) scores; OR = 0.714, 95% CI: 0.517–0.984, p = 0.023) were independent predictors of poor neuropsychological outcomes. Advanced age (p = 0.094) and elevated urea levels (p = 0.095) showed only marginal trends. Exploratory CART modeling highlighted the hierarchical interaction of these baseline clinical scores for risk stratification.

Conclusion: 

Right hemisphere lesions, early emotional distress, and baseline cognitive vulnerability independently predicted a high risk of composite neuropsychological impairment at 6 months post-stroke. Rather than serving merely as novel biomarkers, high baseline PHQ-9 scores and low MMSE scores reflected the persistence of early distress and poor cognitive reserve, respectively. These highly accessible clinical parameters facilitate early risk stratification, emphasizing the absolute need for immediate psychological triage and integrated, long-term cognitive-emotional monitoring.

Association between complete blood count-derived hematological inflammatory ratios and nutritional risk in elderly patients with acute ischemic stroke

 

'Associations' don't get you recovered, or are you too fucking stupid to see that? What prevents nutritional risk is the needed research, not this crapola! Like EXACT DIET PROTOCOLS, starting in the hospital!

• 49% malnutrition post-stroke (1 posts to April 2025)

You've known of the risk for over a year! 

SOLVE THE GODDAMN PROBLEM!

Association between complete blood count-derived hematological inflammatory ratios and nutritional risk in elderly patients with acute ischemic stroke

• 

  Liang’e Xu 1

• 

  Wenjing Wu 2

• 

  Chao Chen 3*

• 1. Department of Neurology, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China

• 2. Department of Neurology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China

Abstract

Background and aims: 

Mounting evidence suggests CBC-derived hematological inflammatory ratios correlate with nutritional status, yet few studies explore their cross-sectional associations with GNRI-defined concurrent nutritional risk in elderly patients with acute ischemic stroke (AIS). This single-center, cross-sectional, observational study was designed to evaluate the correlation between routine admission hematological markers and nutritional risk in elderly patients with AIS. Twelve CBC-derived indices were analyzed: lymphocyte ratio (LR), red blood cell-to-lymphocyte ratio (RLR), hemoglobin-to-lymphocyte ratio (HLR), monocyte-to-lymphocyte ratio (MLR), monocyte-to-neutrophil ratio (MNR), neutrophil-to-lymphocyte ratio (NLR), NLR-to-platelet ratio (NLR/PLT100), MLR-to-platelet ratio (MLR/PLT), platelet-to-neutrophil ratio (PNR), platelet-to-lymphocyte ratio (PLR), mean platelet volume-to-lymphocyte ratio (MPVLR), serum albumin-to-lymphocyte ratio (ALBLR).

Methods: 

Between January 2022 and January 2024, 540 elderly AIS patients (≥60 years) were enrolled. All participants underwent admission GNRI assessment and were split into GNRI-defined nutritional risk group (GNRI≤98, n = 245, 45.4%) and non-nutritional risk group (GNRI>98, n = 295). Venous blood was collected within 24 h on admission. Univariate and multivariate logistic regression were applied to explore cross-sectional correlations, and an exploratory combined statistical model was built. ROC curve, DeLong’s test, likelihood ratio test and AIC were used to evaluate model discrimination and fit.

Results: 

Multiple indicators including age, hypertension, ALT, UA, TG, LR, RLR, MLR, NLR, NLR/PLT100, MLR/PLT, PLR and MPVLR showed univariate correlations with nutritional risk. Multivariate regression identified MLR and NLR/PLT100 as independent correlates within this cohort; MLR showed the strongest association in this dataset instead of robust correlative ability. Adding MLR alone or combining MLR + NLR/PLT100 to base clinical variables significantly improved C-statistic. The combined model reached an AUC of 0.735, representing only moderate discriminative capacity, and it was merely the superior exploratory model limited to the present sample without external generalizability.

Conclusion: 

Within this single-center cohort, MLR exhibited the strongest cross-sectional correlation with GNRI-defined nutritional risk among all tested CBC-derived hematological inflammatory ratios. The composite model combining baseline clinical indicators, MLR and NLR/PLT*100 demonstrated moderate discriminative ability within the study sample, but is not yet robust enough to serve as an effective tool for routine clinical risk stratification.

The association of high-sensitivity C-reactive protein-triglyceride glucose index with functional outcome in elderly patients with acute ischemic stroke undergoing intravenous thrombolysis

 

 'Associations' don't get you recovered, or are you too fucking stupid to see that? What prevents post stroke cognitive impairment is the needed research, not this crapola!

The association of high-sensitivity C-reactive protein-triglyceride glucose index with functional outcome in elderly patients with acute ischemic stroke undergoing intravenous thrombolysis

• 

  Pengyu Gong 1†

• 

  Gang Chen 2†

• 

  Shuaiyu Chen 3

• Y

  Yaya Fei 1

• Y

  Yuye Jiang 1

• Y

  Yiyang Zhang 1

• J

  Jiajie Lu 1

• J

  Jianhua Song 4

• 

• 

• Y

  Yuechun Wang 1*

• 1. Department of Neurology, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, Jiangsu, China

• 2. Department of Neurology, Haimen Hospital Affiliated to Nantong University, Nantong, Jiangsu, China

Abstract

Background and purpose: 

High-sensitivity C-reactive protein-triglyceride-glucose index (CTI) is an innovative biomarker of insulin resistance and inflammation. The objective of this study was to explore the association of high-sensitivity CTI with functional outcome in elderly patients with acute ischemic stroke (AIS) undergoing intravenous thrombolysis (IVT).

Methods: 

Elderly AIS patients treated with IVT were enrolled in three centers. Unfavorable functional outcome was defined as Modified Rankin Scale score ranging from 3–6. Logistic regression models were used to calculate the odds ratio (OR) and 95% confidence interval (95% CI) for the association between high-sensitivity CTI and 3-month functional outcome. Restricted cubic splines (RCS) were performed to explore the shape of this association. Receiver operating characteristic curve was applied to evaluate the discriminatory capacity of high-sensitivity CTI. Furthermore, subgroup and sensitivity analyses were performed to examine the consistency of the observed association.

Results: 

A total of 708 elderly patients were enrolled, among whom 231 (32.6%) developed unfavorable functional outcome at 3 month follow up. In Model 3, higher continuous high sensitivity CTI levels were independently associated with 3 month unfavorable functional outcome among elderly AIS patients receiving IVT (OR = 1.64; 95% CI, 1.28–2.11). Taking the first quartile of high sensitivity CTI as the reference group, patients in the fourth quartile exhibited the highest risk of unfavorable functional outcome in Model 3 (OR = 2.62, 95% CI, 1.48–4.64). RCS revealed a significant overall association between high sensitivity CTI and unfavorable functional outcome, with no statistically significant nonlinear component (P for overall < 0.001; P for nonlinearity = 0.743). Subgroup and sensitivity analyses demonstrated consistent directions of associations.

Conclusion: 

High-sensitivity CTI was independently associated with functional outcome at 3 months in elderly AIS patients treated with IVT.

Predictive value of blood composite biomarkers for hemorrhagic transformation following mechanical thrombectomy in acute anterior circulation large vessel occlusion stroke patients

 In what multiverse are you living that you think any predictions directly leads to survivors recovery?

Predictive value of blood composite biomarkers for hemorrhagic transformation following mechanical thrombectomy in acute anterior circulation large vessel occlusion stroke patients

• 

  Mujie Yao 1,2

• J

  Jun Li 1,2

• S

  Sen Xu 1,2

• 

  Yue Wan 2*

• 1. School of Medicine, Wuhan University of Science and Technology, Wuhan, China

• 2. Department of Neurology, Hubei No. 3 People’s Hospital of Jianghan University, Wuhan, China

Abstract

Background: 

Hemorrhagic transformation (HT) is a devastating complication of mechanical thrombectomy (MT) for acute anterior circulation large vessel occlusion (LVO), yet reliable early prediction tools remain limited. This study systematically compared nine blood composite biomarkers to identify the optimal metabolic-immune integrative predictor of HT.

Methods: 

A total of 206 patients with acute anterior circulation LVO who underwent MT were retrospectively enrolled. Nine composite biomarkers were calculated from routine admission laboratory tests: platelet-to-lymphocyte ratio (PLR), neutrophil-to-platelet ratio (NPR), systemic inflammation response index (SIRI), pan-immune inflammation value (PIV), monocyte-to-HDL ratio (MHR), neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), glucose-to-potassium ratio (GPR), and glucose-to-lymphocyte ratio (GLR). A stratified screening strategy was employed: elastic net regression for baseline variable selection, Spearman correlation for biomarker clustering, and univariate AUC with DeLong test for representative selection. Model evaluation incorporated discrimination (AUC with DeLong test and Bootstrap 1,000-iteration optimism correction), calibration (Hosmer-Lemeshow test and Brier score), and clinical net benefit (NRI, IDI, and decision curve analysis).

Results: 

HT occurred in 53 patients (25.7%). Elastic net regression identified six baseline variables: mean platelet volume, blood glucose, D-dimer, history of alcohol consumption, leukoaraiosis, and pulmonary infection. Spearman clustering yielded five representative biomarkers: GLR, SIRI, GPR, NPR, and MHR. Among these, GLR was the only biomarker that showed a trend toward improving? the baseline model’s discrimination (AUC: 0.852–0.882; △AUC = 0.030), although this difference did not reach statistical significance (P = 0.057). Bootstrap-corrected AUC for Base+GLR was 0.861. GLR also showed the most substantial calibration improvement (Hosmer-Lemeshow P = 0.858 vs. 0.081 for baseline; Brier score reduction 5.4%) and achieved significant integrated discrimination improvement (IDI = 0.0376, 95% CI: 0.002–0.078) and continuous net reclassification improvement (NRI = 0.712). Decision curve analysis revealed limited net benefit difference between GLR and the baseline model, suggesting GLR requires integration with multidimensional factors for comprehensive assessment.

Conclusion: 

Among nine composite biomarkers, GLR provides the greatest incremental predictive value for HT following MT in acute anterior circulation LVO patients. As a routinely accessible metabolic-immune integrative index, GLR may serve as an early warning layer for perioperative risk stratification, though integration with imaging and procedural information remains essential for clinical decision-making.