Tag: statistics

J Nurs Scholarsh. 2024 Mar 20. doi: 10.1111/jnu.12967. Online ahead of print.

ABSTRACT

INTRODUCTION: With the prolongation of the COVID-19 pandemic, more individuals are experiencing sequelae after COVID-19 infection, also known as post-acute COVID-19 syndrome (PCS). The aims of this study were to describe the prevalence and characteristics of PCS symptoms such as fatigue, anxiety, and depression and to compare these symptoms according to participant characteristics in patients who had been previously hospitalized due to COVID-19.

DESIGN: A descriptive cross-sectional study design was used.

METHODS: We included 114 individuals who had been hospitalized for COVID-19 and were discharged from the hospital at least 4 weeks before. Symptoms were assessed using the Fatigue Severity Scale, the Hospital Anxiety-Depression Scale, and the PCS symptom questionnaire developed by the authors. We used descriptive statistics, the Student’s t-test, the Wilcoxon rank-sum test, and the Kruskal-Wallis test for statistical analyses.

RESULTS: The most prevalent symptoms were anxiety (66.7%), fatigue (64.0%), headache (57.9%), and concentration or memory difficulties (57.9%). Concentration or memory difficulties and sleep disturbances had the highest mean frequency. Concentration or memory difficulties were rated with the highest mean severity, and cough, loss of taste, and muscle and joint pain had the highest mean distress scores. Female participants, individuals hospitalized for more than 2 weeks, individuals discharged more than 9 months ago, unvaccinated patients, and those who tried at least one symptom relief method reported higher symptom distress.

CONCLUSION: The findings of this investigation into the frequency, severity, and distress of symptoms shed light on the identification of post-COVID symptoms in detail. To objectively evaluate and comprehend the symptom trajectories of PCS, prospective studies about the development of symptom assessment tools and studies with a longitudinal design should be conducted.

CLINICAL RELEVANCE: A substantial number of respondents reported numerous symptoms and expressed symptom distress; therefore, the development of nursing interventions and treatments to alleviate PCS symptoms is crucial.

PMID:38505990 | DOI:10.1111/jnu.12967

J Forensic Sci. 2024 Mar 20. doi: 10.1111/1556-4029.15504. Online ahead of print.

ABSTRACT

As massively parallel sequencing is implemented in forensic genetics, an understanding of sequence data must accompany these advancements, that is, accurate modeling of data for proper statistical analysis. Allelic drop-out, a common stochastic effect seen in genetic data, is often modeled in statistical analysis of STR results. This proof-of-concept study sequenced several serial dilutions of a standard sample ranging from 4 ng to 7.82 pg to evaluate allelic drop-out trends on a select panel of autosomal STRs using the ForenSeq™ DNA Signature Prep Kit, Primer Set A on the Illumina MiSeq FGx. Parameters assessed included locus, profile, and run specific information. A majority of the allelic drop-out occurred in DNA concentrations less than 31.25 pg. Statistical results indicated a need for locus-specific modeling based on STR descriptors, like simple versus compound repeat patterns. No correlation was seen between average read count of scored alleles and allelic drop-out at a locus. A statistical correlation was observed between the amount of allelic drop-out and the starting amount of DNA in a sample, average read count of a sample, and total read count generated on a flow cell. This study supports using common allelic drop-out factors used in fragment length analysis on sequenced STRs while including additional locus, sample, and run specific information. Results demonstrate multiple factors that can be considered when developing probability of allelic drop-out models for sequenced autosomal STRs including locus-specific analysis, total read count of a profile, and total read count sequenced on a flow cell.

PMID:38505986 | DOI:10.1111/1556-4029.15504

Twin Res Hum Genet. 2024 Mar 20:1-8. doi: 10.1017/thg.2024.13. Online ahead of print.

ABSTRACT

Women with twin pregnancies experience greater sleep disturbance compared to women with singleton pregnancies. The aims of this study were to explore the sleep quality in women with twin pregnancies and to compare their sleep dimensions with coetaneous single pregnancies. This was an observational study in which women were enrolled at the end of pregnancy in the Obstetric Service of Hospital La Paz (Spain). The women were classified as single (n = 143) or twin pregnancy (n = 62). Pregnant women responded to the Pittsburgh Sleep Quality Index to evaluate sleep quality, latency, duration, efficiency, perturbance, use of medication, and daytime dysfunction. The higher the index, the greater the alteration of sleep quality. Without statistical differences, a poor sleep quality was higher in women with single (66.7%) than women with twin pregnancies (22.8%). The good sleeper slept 6.8 h/day in single pregnancy and 7.3 h/day in twin pregnancy. The sleep perturbation and dysfunctionality were higher in women with twin than single pregnancies. The use of medication to sleep was significantly lower in women with twin than single pregnancies. In women with twin pregnancy, the body weight gain during first trimester had a positive correlation with worse sleep quality and sleep perturbations. Twin pregnancy needed more than 7 h/day to have a high sleep quality, showing greater sleep perturbations and daytime dysfunction than single pregnancies. The control of gestational body weight can improve the sleep quality, disturbances, and duration in twin gestations. Sleep screening during pregnancy would be necessary to handle sleep issues and increase benefits in twin gestational outcomes.

PMID:38505981 | DOI:10.1017/thg.2024.13

J Appl Biomed. 2024 Mar;22(1):40-48. doi: 10.32725/jab.2024.001. Epub 2024 Jan 19.

ABSTRACT

BACKGROUND: Endoplasmic reticulum (ER) stress has been shown to play an important role in osteoarthritis (OA).

OBJECTIVE: This study was aimed at assessing the relationship of endoplasmic reticulum (ER) stress-related glucose-regulated protein 78 (GRP78) and CCAAT/enhancer-binding protein homologous protein (CHOP) concentrations in the serum/synovial fluid (SF) with disease severity of primary knee osteoarthritis (pkOA).

METHODS: Patients with pkOA together with healthy individuals were consecutively recruited from our hospital. The levels of GRP78 and CHOP in serum / SF were detected using enzyme-linked immunosorbent assay. The levels of IL-6 and MMP-3 were also examined. Radiographic progression of pkOA was evaluated based on Kellgren-Lawrence (K-L) grades. Receiver Operating Characteristic (ROC) curves were used to assess the diagnostic value of GRP78/CHOP levels with regard to K-L grades. The assessment of clinical severity was conducted using the visual analogue scale (VAS), Oxford knee score (OKS), and Lequesne algofunctional index (LAI).

RESULTS: A total of 140 pkOA patients and 140 healthy individuals were included. Serum GRP78 and CHOP levels in pkOA patients were not significantly different from those in healthy individuals. The SF GRP78 and CHOP levels in healthy controls were not detected due to ethical reasons. Compared to those with K-L grade 2 and 3, the pkOA patients with K-L grade 4 had higher GRP78 and CHOP levels in the SF with statistical significance. In addition, the pkOA patients with K-L grade 3 exhibited drastically upregulated GRP78 and CHOP concentrations in the SF compared to those with K-L grade 2. Positive correlations of GRP78 and CHOP levels with K-L grades, IL-6, and MMP-3 levels in the SF were observed. ROC curve analysis indicated that both GRP78 and CHOP levels may act as decent indicators with regard to OA. GRP78 and CHOP concentrations in the SF were positively correlated with VAS/LAI score and negatively associated with OKS score.

CONCLUSION: The study indicated that GRP78 and CHOP levels in the SF but not the serum were positively correlated with disease severity of pkOA.

PMID:38505969 | DOI:10.32725/jab.2024.001

JBI Evid Synth. 2024 Mar 20. doi: 10.11124/JBIES-23-00034. Online ahead of print.

ABSTRACT

OBJECTIVE: The objective of this mixed methods review was to examine the effectiveness and family experiences of interventions promoting partnerships between families and the multidisciplinary health care team in pediatric and neonatal intensive care units.

INTRODUCTION: Hospitalization of infants and children in neonatal intensive care units and pediatric intensive care units has a significant effect on their families, including increased stress, anxiety, and depression. Available evidence syntheses focused on specific family-centered care, but not on partnership, which is another aspect that may improve the families’ outcomes and experiences.

INCLUSION CRITERIA: This review focused on effectiveness and experiences of interventions by health professionals in partnership with families of infants or children hospitalized in an intensive care unit. The type of intervention was a partnership between the health care team and the family, and focused on outcomes of stress, anxiety, depression, quality of life, attachment, or satisfaction with family-centered care.

METHODS: The JBI methodology for convergent segregated mixed methods systematic reviews was followed using the standardized JBI critical appraisal and data extraction tools. Ten databases were searched from January 2000 to April 2022. Findings of quantitative studies were statistically pooled through meta-analyses and those that could not pooled were reported in a narrative format. Qualitative studies were pooled through meta-synthesis.

RESULTS: This review included 6 qualitative and 42 quantitative studies. There was mixed methodological quality and all studies were included regardless of methodological quality. Meta-analyses showed positive improvements in anxiety, satisfaction with family-centered care, and stress, yet no conclusive effects in attachment and depression. These results should be interpreted with caution due to high heterogeneity. Qualitative analysis resulted in 2 synthesized findings: “Interventions that incorporate partnerships between families and the health care team can improve the family’s experience and capacity to care for the child” and “Having a child in intensive care can be an experience of significant impact for families” Integration of quantitative and qualitative evidence revealed some congruence between findings; however, the paucity of qualitative evidence minimized the depth of this integration.

CONCLUSIONS: Partnership interventions can have a positive impact on parents of children in intensive care units, with improvements seen in stress, anxiety, and satisfaction with family-centered care.

REVIEW REGISTRATION: PROSPERO CRD42019137834.

PMID:38505961 | DOI:10.11124/JBIES-23-00034

Hum Vaccin Immunother. 2024 Dec 31;20(1):2326295. doi: 10.1080/21645515.2024.2326295. Epub 2024 Mar 20.

ABSTRACT

Despite the ongoing global vaccination campaign aimed at preventing human papillomavirus (HPV) related health issues, the uptake of the HPV vaccine remains unacceptably low in developing regions, particularly in sub-Saharan Africa (SSA). Therefore, this systematic review and meta-analysis aimed at determining the pooled prevalence and associated factors of HPV vaccine uptake among adolescent school girls in SSA. Electronic bio-medical databases were explored. Pooled prevalence, publication bias, meta-regression, sub-group, and sensitivity analysis were performed. The estimated pooled prevalence of HPV vaccine uptake was 28.53% [95% CI: (5.25, 51.81)]. Having good knowledge and a positive attitude was significantly associated with HPV vaccine uptake in SSA. Subgroup analysis revealed the highest uptake was 62.52% from Kenya and the lowest was 3.77% in Nigeria. The HPV vaccine uptake is low. It underscores the need for community education, school-based immunization, and education programs that promote the uptake of the vaccine to increase coverage.

PMID:38505959 | DOI:10.1080/21645515.2024.2326295

Stat Methods Med Res. 2024 Mar 20:9622802241239008. doi: 10.1177/09622802241239008. Online ahead of print.

ABSTRACT

Platform trials are randomized clinical trials that allow simultaneous comparison of multiple interventions, usually against a common control. Arms to test experimental interventions may enter and leave the platform over time. This implies that the number of experimental intervention arms in the trial may change as the trial progresses. Determining optimal allocation rates to allocate patients to the treatment and control arms in platform trials is challenging because the optimal allocation depends on the number of arms in the platform and the latter typically varies over time. In addition, the optimal allocation depends on the analysis strategy used and the optimality criteria considered. In this article, we derive optimal treatment allocation rates for platform trials with shared controls, assuming that a stratified estimation and a testing procedure based on a regression model are used to adjust for time trends. We consider both, analysis using concurrent controls only as well as analysis methods using concurrent and non-concurrent controls and assume that the total sample size is fixed. The objective function to be minimized is the maximum of the variances of the effect estimators. We show that the optimal solution depends on the entry time of the arms in the trial and, in general, does not correspond to the square root of $k$ allocation rule used in classical multi-arm trials. We illustrate the optimal allocation and evaluate the power and type 1 error rate compared to trials using one-to-one and square root of $k$ allocations by means of a case study.

PMID:38505941 | DOI:10.1177/09622802241239008

J Biosoc Sci. 2024 Mar 20:1-19. doi: 10.1017/S0021932024000063. Online ahead of print.

ABSTRACT

Increasing prevalence of non-communicable diseases (NCDs) has become the leading cause of death and disability in Bangladesh. Therefore, this study aimed to measure the prevalence of and risk factors for double and triple burden of NCDs (DBNCDs and TBNCDs), considering diabetes, hypertension, and overweight and obesity as well as establish a machine learning approach for predicting DBNCDs and TBNCDs. A total of 12,151 respondents from the 2017 to 2018 Bangladesh Demographic and Health Survey were included in this analysis, where 10%, 27.4%, and 24.3% of respondents had diabetes, hypertension, and overweight and obesity, respectively. Chi-square test and multilevel logistic regression (LR) analysis were applied to select factors associated with DBNCDs and TBNCDs. Furthermore, six classifiers including decision tree (DT), LR, naïve Bayes (NB), k-nearest neighbour (KNN), random forest (RF), and extreme gradient boosting (XGBoost) with three cross-validation protocols (K2, K5, and K10) were adopted to predict the status of DBNCDs and TBNCDs. The classification accuracy (ACC) and area under the curve (AUC) were computed for each protocol and repeated 10 times to make them more robust, and then the average ACC and AUC were computed. The prevalence of DBNCDs and TBNCDs was 14.3% and 2.3%, respectively. The findings of this study revealed that DBNCDs and TBNCDs were significantly influenced by age, sex, marital status, wealth index, education and geographic region. Compared to other classifiers, the RF-based classifier provides the highest ACC and AUC for both DBNCDs (ACC = 81.06% and AUC = 0.93) and TBNCDs (ACC = 88.61% and AUC = 0.97) for the K10 protocol. A combination of considered two-step factor selections and RF-based classifier can better predict the burden of NCDs. The findings of this study suggested that decision-makers might adopt suitable decisions to control and prevent the burden of NCDs using RF classifiers.

PMID:38505939 | DOI:10.1017/S0021932024000063

Curr Med Res Opin. 2024 Mar 20:1-13. doi: 10.1080/03007995.2024.2331159. Online ahead of print.

ABSTRACT

Objectives: To address the need for faster pain relief of over-the-counter (OTC) analgesic users, a novel drug delivery technology was developed to achieve faster absorption of orally administered acetaminophen with the goal of delivering earlier onset of pain relief. Previous development studies suggested that a 1000 mg dose of this fast-acting acetaminophen (FA-acetaminophen) formulation provided faster absorption and onset of action versus, commercially available OTC fast-acting analgesics, 1000 mg of extra-strength acetaminophen (ES-acetaminophen) or 400 mg of liquid-filled ibuprofen capsules (LG-ibuprofen). This study was designed as the definitive trial evaluating the onset of pain relief of FA-acetaminophen versus these same OTC comparators.Methods: This single-dose, randomized, double-blind, placebo- and active-controlled clinical trial compared analgesic onset, overall efficacy, and safety of FA-acetaminophen 1000 mg, ES-acetaminophen 1000 mg, LG-ibuprofen 400 mg, and placebo over 4 hours in a postsurgical dental pain model. Following removal of 3 to 4 impacted third molars, 664 subjects with moderate-to-severe pain were randomized in a 4:4:2:1 ratio to FA-acetaminophen (249), ES-acetaminophen (232), LG-ibuprofen (124), or placebo (59). Mean age was 18.9 years; 45.5% were male; 57.5% had severe baseline pain intensity. Subjects stopped a first stopwatch if/when they had perceptible pain relief and a second stopwatch if/when their pain relief became meaningful to them. Pain intensity difference (PID) and pain relief (PAR) were obtained using an 11-point numerical rating scale.Findings: FA-acetaminophen 1000 mg had faster median time to onset of pain relief (15.7 minutes) compared to ES-acetaminophen 1000 mg (20.2 minutes, p = 0.035), LG-ibuprofen 400 mg (23.2 minutes, p < 0.001), and placebo (non-estimable), statistically greater mean PAR and PID scores than other treatment groups at 15 and 30 minutes, and a statistically greater percentage of subjects with confirmed perceptible pain relief at 15 and 20 minutes. At 25 minutes, FA-acetaminophen 1000 mg had a statistically significantly greater percentage of subjects with confirmed perceptible pain relief than LG-ibuprofen 400 mg and placebo. No clinically significant adverse events were reported.Conclusions: This study supports previous studies, demonstrating faster onset of analgesia with FA-acetaminophen 1000 mg compared to OTC ES-acetaminophen 1000 mg and OTC LG-ibuprofen 400 mg.ClinicalTrials.gov Identifier: NCT03224403 https://clinicaltrials.gov/ct2/show/NCT03224403.

PMID:38505928 | DOI:10.1080/03007995.2024.2331159

Am Surg. 2024 Mar 20:31348241238323. doi: 10.1177/00031348241238323. Online ahead of print.

ABSTRACT

BACKGROUND: The 2014 expansion of Medicaid under the Affordable Care Act (ACA) reshaped healthcare delivery in the United States. This study assessed how Medicaid expansion affected in-hospital mortality in patients with extreme risk of mortality (EROM) from traumatic injuries.

METHODS: Data from inpatients aged 18-64 years, registered in the National Inpatient Sample between 2007 and 2020, and identified with trauma-related All-Patient Refined Diagnosis Related Groups (APRDRG) codes, were analyzed. Within this group, a subset of patients was selected based on the APRDRG classification identifying them as at EROM for the principal unit of analysis. The cohort was divided into high-implementation (HIR) and low-implementation (LIR) regions based on Medicaid expansion coverage. In-hospital mortality was assessed using interrupted time-series analysis. Sensitivity analyses considered seasonality, autocorrelation, and exogenous events.

RESULTS: Analysis encompassed 70 381 trauma inpatient stays, corresponding to 346 659 patients based on National Inpatient Sample weighting. There was a consistent monthly decline in in-hospital mortality of .08% (95% CI: -.103 to -.048; P < .001) prior to Medicaid expansion, a trend unaffected by expansion. This pattern persisted across both LIR and HIR Medicaid implementation regions. Although Medicaid enrollment increased in HIR, that in LIR remained unchanged.

DISCUSSION: Over the study period, the in-hospital mortality among severely injured patients consistently decreased, and this trend was not influenced by Medicaid expansion. The statistical models and results from this study can offer valuable guidance to policymakers and healthcare leaders as they formulate more efficient and effective policies.

PMID:38505915 | DOI:10.1177/00031348241238323