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Nevin Manimala Statistics

Manualised Attachment-Based Interventions for Improving Caregiver-Infant Relationships: A Two-Stage Systematic Review

Clin Child Fam Psychol Rev. 2024 Nov 18. doi: 10.1007/s10567-024-00497-0. Online ahead of print.

ABSTRACT

As attachment-based interventions can improve caregiver-infant relationships and their subsequent psychological outcomes, the identification of relevant and effective interventions can facilitate their implementation into clinical practice. This systematic review aimed to a) provide an overview of manualised attachment-based interventions, without video-feedback as the main component, for caregivers and infants from conception to two years, and b) determine which of these interventions were effective in demonstrating improvements in caregiver-infant relational outcomes. To identify eligible interventions and their empirical evidence base, two search stages were conducted for 1) relevant interventions and 2) studies of interventions identified in the first stage that focussed on caregiver-infant relational outcomes. All studies included in Stage 2 were quality assessed and findings analysed. Twenty-six interventions were eligible for inclusion at Stage 1 but studies reporting on relational outcomes were identified for 16 interventions only. Forty studies reporting on those 16 interventions met inclusion criteria and were synthesised at Stage 2. Most studies were of good quality. Observer-rated measures were used in 90% of studies. There was evidence for these interventions in relation to improving caregiver-infant relational outcomes: 80% of studies reported a statistically significant positive change in a relational outcome for the intervention compared to pre-intervention or control group. The most promising evidence was identified for Attachment and Biobehavioral Catch-Up (ABC), Minding the Baby (MTB) and Circle of Security (COS). This systematic review offers guidance to healthcare professionals, commissioners and policymakers within perinatal sectors in relation to the training, delivery and implementation of evidenced manualised attachment-based interventions.

PMID:39556257 | DOI:10.1007/s10567-024-00497-0

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Nevin Manimala Statistics

Deriving and validating a risk prediction model for long COVID: a population-based, retrospective cohort study in Scotland

J R Soc Med. 2024 Nov 18:1410768241297833. doi: 10.1177/01410768241297833. Online ahead of print.

ABSTRACT

OBJECTIVES: Using electronic health records, we derived and internally validated a prediction model to estimate risk factors for long COVID and predict individual risk of developing long COVID.

DESIGN: Population-based, retrospective cohort study.

SETTING: Scotland.

PARTICIPANTS: Adults (≥18 years) with a positive COVID-19 test, registered with a general medical practice between 1 March 2020 and 20 October 2022.

MAIN OUTCOME MEASURES: Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) for predictors of long COVID, and patients’ predicted probabilities of developing long COVID.

RESULTS: A total of 68,486 (5.6%) patients were identified as having long COVID. Predictors of long COVID were increasing age (aOR: 3.84; 95% CI: 3.66-4.03 and aOR: 3.66; 95% CI: 3.27-4.09 in first and second splines), increasing body mass index (BMI) (aOR: 3.17; 95% CI: 2.78-3.61 and aOR: 3.09; 95% CI: 2.13-4.49 in first and second splines), severe COVID-19 (aOR: 1.78; 95% CI: 1.72-1.84); female sex (aOR: 1.56; 95% CI: 1.53-1.60), deprivation (most versus least deprived quintile, aOR: 1.40; 95% CI: 1.36-1.44), several existing health conditions. Predictors associated with reduced long COVID risk were testing positive while Delta or Omicron variants were dominant, relative to when the Wild-type variant was dominant (aOR: 0.85; 95% CI: 0.81-0.88 and aOR: 0.64; 95% CI: 0.61-0.67, respectively) having received one or two doses of COVID-19 vaccination, relative to unvaccinated (aOR: 0.90; 95% CI: 0.86-0.95 and aOR: 0.96; 95% CI: 0.93-1.00).

CONCLUSIONS: Older age, higher BMI, severe COVID-19 infection, female sex, deprivation and comorbidities were predictors of long COVID. Vaccination against COVID-19 and testing positive while Delta or Omicron variants were dominant predicted reduced risk.

PMID:39556251 | DOI:10.1177/01410768241297833

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Nevin Manimala Statistics

Fracture events associated with GLP-1 receptor agonists in FDA adverse events reporting system

Acta Diabetol. 2024 Nov 18. doi: 10.1007/s00592-024-02415-w. Online ahead of print.

ABSTRACT

AIMS: Diabetes patients are at a higher risk of fractures, and glucagon-like peptide-1 receptor agonists (GLP-1RAs) have been suggested to positively impact on bone metabolism. We aim to provide a comprehensive assessment of fracture events associated with GLP-1RAs based on pharmacovigilance data.

METHODS: In this study, fracture-related adverse events (AEs) associated with GLP-1RAs and other commonly used glucose-lowering drugs were identified from Food and Drug Administration Adverse Event Reporting System (FAERS) database (2004-2022). The reporting odds ratio (ROR) and adjusted ROR (adj. ROR) were used to compare the reporting of fracture-related AEs associated with insulin, GLP-1RAs, and Non GLP-1RAs, in patients with diabetes through two scenarios. This involved separately comparing each glucose-lowering drug to all other medications used in diabetic patients and reiterating after excluding insulin cases.

RESULTS: A total of 490,107 AE reports for patients with diabetes were identified and 98, 625 of them were for GLP-1RAs. Among all diabetes drugs, GLP-1RAs had the lowest reporting of any fracture-related AEs [adj. ROR = 0.44 (0.40-0.47)], consistent across osteoporotic fracture [adj. ROR = 0.39 (0.34-0.45)] and hip fracture [adj. ROR = 0.34 (0.28-0.41)]. Among GLP-1RA agents, albiglutide was associated with the lowest adj. ROR [0.11 (0.05-0.21)] for any fracture-related AEs. After excluded all insulin reports, GLP-1RAs retained a significantly lower adj. ROR towards any fracture [adj. ROR = 0.45 (0.40-0.50)], osteoporotic fracture [adj. ROR = 0.44 (0.37-0.52)], and hip fracture [adj. ROR = 0.43 (0.33-0.54)].

CONCLUSION: In a real-world pharmacovigilance setting, GLP-1RAs were associated with lower reporting of fracture-related AEs, indicating the protective effect of GLP-1RAs against fractures.

PMID:39556224 | DOI:10.1007/s00592-024-02415-w

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Nevin Manimala Statistics

Association of the triglyceride glucose index with acute renal failure in diabetes mellitus: a cross-sectional study based on participants from the MIMIC-iv database

Acta Diabetol. 2024 Nov 18. doi: 10.1007/s00592-024-02412-z. Online ahead of print.

ABSTRACT

BACKGROUND: The triglyceride glucose (TyG) index serves as a dependable surrogate biomarker for evaluating insulin resistance. However, the role of the TyG index in patients with diabetes mellitus who also suffer from acute renal failure warrants further investigation. This study sought to investigate the association between the TyG index and the incidence of acute renal failure in individuals with diabetes.

METHODS: This study utilized data from the MIMIC-IV database, categorizing patients into tertiles according to their TyG index. Employing multivariate logistic regression models, we analyzed the relationship between the TyG index and the occurrence of acute renal failure among diabetic patients. To assess non-linear relationships, restricted cubic splines were utilized, and upon detection of non-linearity, a recursive algorithm was implemented to determine inflection points.

RESULTS: The study comprised a total of 1074 participants diagnosed with diabetes mellitus. In the model adjusted for all covariates, the odds ratio (OR) for the association between the TyG index and acute renal failure, accompanied by a 95% confidence interval (CI), was 1.22 (0.82, 1.82), which did not reach statistical significance. However, analysis using restricted cubic splines revealed a U-shaped relationship between the TyG index and acute renal failure, with an inflection point at 9.26. The relationship between the TyG index and acute renal failure was inverse before reaching the inflection point and became directly proportional thereafter, with an OR (95% CI) of 1.86 (1.12, 3.09) after the point.

CONCLUSION: In individuals diagnosed with diabetes mellitus, our analysis revealed a non-linear relationship between the TyG index and the incidence of acute renal failure. Beyond the inflection point, elevated TyG index levels were markedly linked to a higher prevalence of acute renal failure.

PMID:39556222 | DOI:10.1007/s00592-024-02412-z

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Nevin Manimala Statistics

Delirium after cardiac arrest: incidence, risk factors, and association with neurologic outcome-insights from the Freiburg Delirium Registry

Clin Res Cardiol. 2024 Nov 18. doi: 10.1007/s00392-024-02575-3. Online ahead of print.

ABSTRACT

AIM: Delirium in patients treated in the intensive care unit (ICU) is linked to adverse outcome, according to previous observations. However, data on patients recovering after cardiac arrest are sparse. The aim of this study was to assess incidence, risk factors, and outcome of patients with delirium after cardiac arrest in the Freiburg Delirium Registry (FDR).

METHODS: In this retrospective registry study, all patients after cardiac arrest treated in the Freiburg University Medical Center medical ICU between 08/2016 and 03/2021 were included. Delirium was diagnosed using the Nursing Delirium screening scale (NuDesc), assessed three times daily. Favorable neurological outcome was defined as cerebral performance category (CPC) score at ICU discharge ≤ 2.

RESULTS: Two hundred seventeen patients were included and among them, delirium was detected in one hundred ninety-nine (91.7%) patients. Age was independently associated with the incidence of delirium (p = 0.003), and inversely associated with the number of delirium-free days (p < 0.001). Favorable neurological outcome was present in 145/199 (72.9%) with, and 17/18 (94.4%) patients without delirium (p = 0.048). While the incidence of delirium was not independently associated with a favorable neurologic outcome, the number of delirium-free days strongly predicted the primary endpoint [OR 2.14 (1.73-2.64), p > 0.001].

CONCLUSION: Delirium complicated the ICU course in almost all patients after cardiac arrest. The number of delirium-free days was associated with favorable outcome while incidence of delirium itself was not.

PMID:39556214 | DOI:10.1007/s00392-024-02575-3

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Nevin Manimala Statistics

Genetic Parameters and Prediction of Genotypic Values for Postharvest Physiological Deterioration Tolerance and Root Traits in Cassava using REML/BLUP

Biochem Genet. 2024 Nov 18. doi: 10.1007/s10528-024-10972-6. Online ahead of print.

ABSTRACT

The study aimed to estimate the genetic parameters and predict the genotypic values of postharvest physiological deterioration and root characteristics in cassava (Manihot esculentaCrantz) using restricted maximum likelihood (REML) and the best linear unbiased prediction (BLUP). A total of 76 cassava accessions were evaluated over two growing seasons. The evaluated traits included postharvest physiological deterioration response (PPD), root length (RL), root diameter (RD), root weight (RW), dry matter content (DMC), total starch content (TS) and total sugar content (TSU). All the traits had a higher phenotypic variance component than genetic or environmental variance, with genotypic variance making up a larger portion of the total phenotypic variance. Heritability estimates ranged from low to high, with high heritability values being recorded for dry matter content, PPD, and root diameter. The study discovered high genotypic coefficients of variation (CVg) for PPD, root weight and diameter, indicating strong genotypic variability beneficial for selection. As larger genetic effects than non-genetic effects lead to increased selection gains, the highest CVr values for dry matter content and PPD suggest the biggest probability of selection gain. Postharvest Physiological deterioration (PPD) had the highest genetic advance, indicating significant gain in the following generation. Thirty eight genotypes were selected as the most promising based on BLUP index, promoting improvement and genetic gain in several traits. The genotypes selected can be included in cassava breeding programs for PPD tolerance and other tuber traits.

PMID:39556191 | DOI:10.1007/s10528-024-10972-6

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Nevin Manimala Statistics

Human papillomavirus vaccine uptake among adolescent survivors of hematopoietic stem cell transplant

J Cancer Surviv. 2024 Nov 18. doi: 10.1007/s11764-024-01709-w. Online ahead of print.

ABSTRACT

PURPOSE: To characterize the rate of human papillomavirus (HPV) vaccine uptake among adolescents after hematopoietic stem cell transplant (HSCT).

METHODS: This retrospective study evaluated the vaccine history of adolescent patients ≥ 11 years of age who underwent either auto- or allo-HSCT between 2015 and 2022 at a tertiary care medical center. Logistic regression was used to examine bivariate associations between HPV vaccine uptake and covariates including demographic factors, indication for and type of HSCT, receipt of HPV vaccine prior to transplant, and receipt of other vaccines after transplant.

RESULTS: Among 119 (n = 53 female; n = 66 male) eligible patients, 66 (55.5%) received at least one dose of the HPV vaccine after HSCT. Among those who initiated vaccination, 45/66 (68.2%) completed two or more doses. Of the 69 patients who were eligible to receive the vaccine prior to HSCT, 19/36 (52%) were vaccinated both before and after HSCT, compared to 14/33 (42%) who did not receive the vaccine before HSCT but chose to be vaccinated after HSCT. No statistically significant difference was identified between those who did and did not initiate HPV vaccination after HSCT among covariates examined.

CONCLUSIONS: Rate of HPV vaccine uptake after HSCT was lower than the rate of other recommended vaccines. Receiving HPV vaccine prior to HSCT was not associated with HPV re-uptake after HSCT.

IMPLICATIONS FOR CANCER SURVIVORS: HPV vaccination continues to be suboptimal in HSCT survivorship and should be a targeted goal for improvement in preventing secondary malignancy in this high-risk population.

PMID:39556189 | DOI:10.1007/s11764-024-01709-w

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Nevin Manimala Statistics

Analysis of the Effects of Different Chemotherapy Methods on Blood Lipid Levels in Breast Cancer Patients

Breast Cancer (Dove Med Press). 2024 Nov 11;16:745-760. doi: 10.2147/BCTT.S456422. eCollection 2024.

ABSTRACT

PURPOSE: To analyze the impacts of distinct chemotherapy methods on blood lipid levels in breast cancer patients.

METHODS: Three hundred breast cancer patients were selected as the research subjects. The inclusion time limit was from January 2021 to January 2023, and all received treatment in our hospital. Based on the therapy plan, the patients were divided into group A (epirubicin + cyclophosphamide followed by paclitaxel regimen, 103 premenopausal cases + 61 postmenopausal cases), group B (docetaxel + cyclophosphamide regimen, 41 premenopausal instances + 37 postmenopausal instances), group C (docetaxel + carboplatin regimen, 61 premenopausal instances + 24 postmenopausal instances), comparing the changes in blood lipid levels of patients in each group at pre-therapy and post-therapy, and the abnormality frequency of blood lipids in every group of patients after therapy.

RESULTS: After treatment, the triglyceride (TG) levels of the three groups of patients were clearly greater than those at pre-therapy, and the high-density lipoprotein cholesterol (HDL-C) levels were clearly less than before therapy. The levels of low-density lipoprotein cholesterol (LDL-C) in group B and C patients were clearly greater than those before therapy in the same one, while the LDL-C levels in group A were clearly less than those before therapy in the same one; after therapy, the TG levels of patients in group A were clearly less than those in group B, and LDL-C, total Cholesterol (TC) levels were clearly less than that in group B and C (P < 0.05). The proportion of dyslipidemia in patients in the group A after therapy was clearly less than in group B (P < 0.05). After treatment, the HDL-C levels of premenopausal patients in the three groups were clearly less than those at pre-therapy. The TG, TC, and LDL-C levels of premenopausal patients in groups B and C were clearly greater than those at pre-therapy. The TG levels of premenopausal patients in group A were clearly less than those before therapy. After treatment, the TG and TC levels of premenopausal patients in group A were clearly less than those in group C, and the LDL-C levels were clearly less than those in group B and C (P < 0.05). The proportion of dyslipidemia in premenopausal patients in the group A and C after therapy was clearly less than the group B (P < 0.05). After therapy, the TG levels of postmenopausal patients in the three groups were clearly greater than those at pre-therapy, and the HDL-C levels were clearly less than those at pre-therapy. The LDL-C levels of postmenopausal patients in group B and C were clearly greater than those at pre-therapy. The TC and LDL-C levels of postmenopausal patients in group A were clearly less than those at pre-therapy; after therapy, the LDL-C and TC levels of postmenopausal patients in group A were clearly less than those in group B and C (P < 0.05). It had no statistically clear distinction in dyslipidemia among the three groups of postmenopausal patients after therapy (P > 0.05).

CONCLUSION: Chemotherapy has adverse effects on the blood lipid levels of premenopausal and postmenopausal breast carcinoma patients and increases the incidence of dyslipidemia. Compared with other regimens, epirubicin+cyclophosphamide sequential paclitaxel regimen has little impact on blood lipid level of breast carcinoma.

PMID:39553240 | PMC:PMC11566600 | DOI:10.2147/BCTT.S456422

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Nevin Manimala Statistics

Identification of high-risk tumor characteristics in patients with localized prostate cancer using conventional combined with diffusion-weighted MRI imaging parameters

Am J Cancer Res. 2024 Oct 15;14(10):4909-4921. doi: 10.62347/XADT5737. eCollection 2024.

ABSTRACT

The objective of this study was to investigate the utility of conventional imaging combined with diffusion-weighted magnetic resonance imaging (MRI) in identifying high-risk tumor characteristics in patients with localized prostate cancer. A retrospective cohort study was conducted on 194 patients who underwent surgery for localized prostate cancer. Patients were categorized into low-risk and high-risk groups based on clinical criteria. Imaging data were obtained using a MRI system, and various imaging parameters were analyzed, including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI) signal intensities, diffusion-weighted MRI parameters, and their correlations with clinical characteristics. Statistical methods such as logistic regression, and receiver operating characteristic (ROC) analysis were employed to assess the diagnostic performance of the imaging parameters and to construct joint prediction models. A verification set prediction model was established and compared. The comparison of demographic and clinical characteristics between the low and high-risk groups revealed significant differences in the prostate-specific antigen (PSA) level, Gleason score, Tumor Size and prostate volume (PV). Standard imaging parameters, T1WI and T2WI signal intensities, exhibited significant differences between the low and high-risk groups. Additionally, diffusion-weighted MRI parameters, including signal intensities at different b values, apparent diffusion coefficient (ADC), Ktrans, and Kep, were notably associated with high-risk tumor characteristics in localized prostate cancer. Logistic regression analysis identified both standard imaging and diffusion-weighted MRI parameters as independent predictors of high-risk tumor characteristics. Furthermore, the ROC analysis demonstrated the diagnostic potential of T2WI signal intensity, signal intensity at 800 s/mm2, and ADC in identifying high-risk tumors. Joint prediction models combining standard imaging and diffusion-weighted MRI parameters showed high predictive accuracy for high-risk tumor characteristics in localized prostate cancer, with Area Under the Curve (AUC) values of 0.777 for standard imaging, 0.826 for diffusion-weighted MRI, and 0.892 for the combined model. The AUC value for the prediction model in validation set was 0.860. In conclusion, this study underscores the diagnostic potential of conventional imaging combined with diffusion-weighted MRI in identifying high-risk tumor characteristics in patients with localized prostate cancer. Both standard imaging and diffusion-weighted MRI parameters were identified as non-invasive biomarkers for risk assessment and prognosis. These findings have implications for precision treatment of localized prostate cancer, highlighting the potential integration of imaging-based risk assessment tools into clinical practice for tailored treatment strategies and improved patient outcomes.

PMID:39553232 | PMC:PMC11560813 | DOI:10.62347/XADT5737

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Nevin Manimala Statistics

Risk factor analysis and development of predictive models for osteoradionecrosis in patients with nasopharyngeal carcinoma after concurrent chemoradiotherapy

Am J Cancer Res. 2024 Oct 15;14(10):4760-4771. doi: 10.62347/RIWX7204. eCollection 2024.

ABSTRACT

Nasopharyngeal carcinoma (NPC) is a malignant tumor that targets the nasopharyngeal mucosal epithelium. Concurrent chemoradiotherapy (CCRT) is a pivotal treatment modality for NPC, yet it poses a risk for osteoradionecrosis (ORN), a complication that can impede further treatment. This study sought to explore the risk factors for ORN in NPC patients post-CCRT and to construct predictive models. We performed a retrospective analysis of clinical data from 417 NPC patients treated with CCRT at the Affiliated Hospital of Jiangnan University, with 204 patients from Longyan First Hospital as a validation cohort for the models. Our findings indicated that a high radiation dose, tooth extraction after radiotherapy, inadequate oral hygiene, smoking, anemia, and advanced T staging were associated with an elevated risk of ORN in NPC patients following CCRT. We formulated risk prediction models for ORN utilizing a nomogram, gradient boosting machine (GBM), and random forest (RF) algorithms. The area under the curve (AUC) was 0.813 (95% CI: 0.724-0.902) for the nomogram model in the validation cohort, 0.821 (95% CI: 0.732-0.910) for the GBM, and 0.735 (95% CI: 0.614-0.855) for the RF. Delong’s test indicated no statistically significant differences in the AUC values among the three models. The nomogram has strong performance across both the training and validation cohorts, featuring a straightforward structure that is both intuitive and comprehensible. Taking into account the model’s discriminative power, generalizability, and clinical practicability, the nomogram was proven to be highly applicable in the current study.

PMID:39553231 | PMC:PMC11560816 | DOI:10.62347/RIWX7204