Category: Statistics

Blood. 2022 Jan 7:blood.2021014804. doi: 10.1182/blood.2021014804. Online ahead of print.

ABSTRACT

In acute myeloid leukemia (AML), measurable residual disease (MRD) before or after allogeneic hematopoietic cell transplantation (HCT) is an established, independent indicator of poor outcome. To address how peri-HCT MRD dynamics could refine risk assessment across different conditioning intensities, we analyzed 810 adults transplanted in remission after myeloablative conditioning (MAC; n=515) or non-MAC (n=295) who underwent multiparameter flow cytometry-based MRD testing before and 20-40 days after allografting. Patients without pre- and post-HCT MRD (MRDneg/MRDneg) had the lowest risks of relapse and highest relapse-free survival (RFS) and overall survival (OS). Relative to those patients, outcomes for MRDpos/MRDpos and MRDneg/MRDpos patients were poor regardless of conditioning intensity. Outcomes for MRDpos/MRDneg patients were intermediate. Among 161 patients with MRD before HCT, MRD was cleared more commonly with a MAC (85/104 [81.7%]) than non-MAC (33/57 [57.9%]) regimen (P=0.002). Although non-MAC regimens were less likely to clear MRD, if they did the impact on outcome was greater. Thus, there was a significant interaction between conditioning intensity and “MRD conversion” for relapse (P=0.020), RFS (P=0.002), and OS (P=0.001). Similar findings were obtained in the subset of 590 patients receiving HLA-matched allografts. C-statistic values were higher (indicating higher predictive accuracy) for peri-HCT MRD dynamics compared to the isolated use of pre-HCT MRD status and post-HCT MRD status for prediction of relapse, RFS, and OS. Across conditioning intensities, peri-HCT MRD dynamics improve risk assessment over isolated pre- or post-HCT MRD assessments.

PMID:34995355 | DOI:10.1182/blood.2021014804

Rheumatology (Oxford). 2022 Jan 6:keab937. doi: 10.1093/rheumatology/keab937. Online ahead of print.

ABSTRACT

OBJECTIVE: To better understand rheumatology patient and clinician pandemic-related experiences, medical relationships and behaviours in order to help identify the persisting impacts of the Covid-19 pandemic, and inform efforts to ameliorate the negative impacts and build-upon the positive ones.

METHODS: Rheumatology patients and clinicians completed surveys (Patients N = 1,543, Clinicians N = 111) and interviews (Patients N = 41, Clinicians N = 32) between April 2021 and August 2021. A cohort (N = 139) of systemic autoimmune rheumatic disease patients was also followed-up from March 2020 to April 2021. Analyses used sequential mixed methods. Pre-specified outcome measures included the Warwick-Edinburgh Mental wellbeing score (WEMWBS), satisfaction with care, and healthcare-behaviours.

RESULTS: We identified multiple ongoing pandemic-induced/increased barriers to receiving care. The percentage of patients agreeing they were medically supported reduced from 74.4% pre-pandemic to 39.7% during-pandemic. Ratings for medical support, medical-security and trust were significantly (p< 0.001) positively correlated with patient WEMWBS and healthcare-behaviours, and decreased during the pandemic. Healthcare-seeking was reduced, potentially long-term, including from patients feeling ‘abandoned’ by clinicians, and a ‘burden’ from Government messaging to protect the NHS. Blame and distrust were frequent, particularly between primary and secondary care, and towards the UK Government, whom <10% of clinicians felt had supported clinicians during the pandemic. Clinicians’ efforts were reported to be impeded by inefficient administration systems, and chronic understaffing, suggestive of the pandemic having exposed and exacerbated existing healthcare-system weaknesses.

CONCLUSION: Without concerted action-such as rebuilding trust, improved administrative systems, and more support for clinicians-barriers to care and negative impacts of the pandemic on trust, medical relationships, medical-security and patient help-seeking may persist longer-term.

TRIAL REGISTRATION: This study is part of a pre-registered longitudinal multi-stage trial, the LISTEN study (ISRCTN-14966097), with later Covid-related additions registered in March 2021, including a pre-registered statistical analysis plan.

PMID:34995345 | DOI:10.1093/rheumatology/keab937

PLoS One. 2022 Jan 7;17(1):e0262340. doi: 10.1371/journal.pone.0262340. eCollection 2022.

ABSTRACT

BACKGROUND: Readmission to hospital is frequent among older patients and reported as a post-discharge adverse outcome. The effect of treatment in a geriatric ward for acutely admitted older patients on mortality and function is well established, but less is known about the possible influence of such treatment on the risk of readmission, particularly in the oldest and most vulnerable patients. Our aim was to assess the risk for early readmission for multimorbid patients > 75 years treated in a geriatric ward compared to medical wards and to identify risk factors for 30-day readmissions.

METHODS: Prospective cohort study of patients acutely admitted to a medical department at a Norwegian regional hospital. Eligible patients were community-dwelling, multimorbid, receiving home care services, and aged 75+. Patients were consecutively included in the period from 1 April to 31 October 2012. Clinical data were retrieved from the referral letter and medical records.

RESULTS: We included 227 patients with a mean (SD) age of 86.0 (5.7) years, 134 (59%) were female and 59 (26%) were readmitted within 30 days after discharge. We found no statistically significant difference in readmission rate between patients treated in a geriatric ward versus other medical wards. In adjusted Cox proportional hazards regression analyses, lower age (hazard ratio (95% confidence interval) 0.95 (0.91-0.99) per year), female gender (2.17 (1.15-4.00)) and higher MMSE score (1.03 (1.00-1.06) per point) were significant risk factors for readmission.

CONCLUSIONS: Lower age, female gender and higher cognitive function were the main risk factors for 30-day readmission to hospital among old patients with multimorbidity. We found no impact of geriatric care on the readmission rate.

PMID:34995327 | DOI:10.1371/journal.pone.0262340

PLoS One. 2022 Jan 7;17(1):e0262247. doi: 10.1371/journal.pone.0262247. eCollection 2022.

ABSTRACT

Currently, a significant amount of research is focused on detecting Marine Debris and assessing its spectral behaviour via remote sensing, ultimately aiming at new operational monitoring solutions. Here, we introduce a Marine Debris Archive (MARIDA), as a benchmark dataset for developing and evaluating Machine Learning (ML) algorithms capable of detecting Marine Debris. MARIDA is the first dataset based on the multispectral Sentinel-2 (S2) satellite data, which distinguishes Marine Debris from various marine features that co-exist, including Sargassum macroalgae, Ships, Natural Organic Material, Waves, Wakes, Foam, dissimilar water types (i.e., Clear, Turbid Water, Sediment-Laden Water, Shallow Water), and Clouds. We provide annotations (georeferenced polygons/ pixels) from verified plastic debris events in several geographical regions globally, during different seasons, years and sea state conditions. A detailed spectral and statistical analysis of the MARIDA dataset is presented along with well-established ML baselines for weakly supervised semantic segmentation and multi-label classification tasks. MARIDA is an open-access dataset which enables the research community to explore the spectral behaviour of certain floating materials, sea state features and water types, to develop and evaluate Marine Debris detection solutions based on artificial intelligence and deep learning architectures, as well as satellite pre-processing pipelines.

PMID:34995337 | DOI:10.1371/journal.pone.0262247

PLoS One. 2022 Jan 7;17(1):e0261895. doi: 10.1371/journal.pone.0261895. eCollection 2022.

ABSTRACT

INTRODUCTION: There is substantial body of evidence that portrays gap in the existing maternal and child health continuum of care; one is less attention given to adolescent girls and young women until they get pregnant. Besides, antenatal care is too late to reduce the harmful effects that a woman’s may have on the fetus during the critical period of organogenesis. Fortunately, preconception care can fill these gaps, enhance well-being of women and couples and improve subsequent pregnancy and child health outcomes. Therefore, the main aim of the current study was to assess preconception care utilization and associated factors among pregnant women attending antenatal care clinics of public health facilities in Hosanna town.

METHODS: A facility based cross-sectional study design was carried out from July 30, 2020 to August 30, 2020. Data were collected through face-to-face interview among 400 eligible pregnant women through systematic sampling technique. Epi-data version 3.1 and SPSS version 24 was used for data entry and analysis respectively. Both bivariable and multivariable logistic regression analysis was conducted to identify association between dependent and independent variables. Crude and adjusted odds ratio with respective 95% confidence intervals was computed and statistical significance was declared at p-value <0.05.

RESULT: This study revealed that 76 (19%, 95% Cl (15.3, 23.2) study participants had utilized preconception care. History of family planning use before the current pregnancy (AOR = 2.45; 95% Cl (1.270, 4.741), previous history of adverse birth outcomes (AOR = 3.15; 95% Cl (1.650, 6.005), poor knowledge on preconception care (AOR = 0.18; 95% Cl (0.084, 0.379) and receiving counseling on preconception care previously (AOR = 2.82; 95% Cl (1.221, 6.493) were significantly associated with preconception care utilization.

CONCLUSIONS: The present study revealed that nearly one-fifth of pregnant women have utilized preconception care services. History of family planning use before the current pregnancy, previous history of adverse birth outcomes, poor knowledge on preconception care and receiving counseling on preconception care previously were significantly associated with preconception care utilization. Integrating preconception care services with other maternal neonatal child health, improving women’s/couples knowledge & strengthening counseling services is pivotal.

PMID:34995291 | DOI:10.1371/journal.pone.0261895

PLoS One. 2022 Jan 7;17(1):e0260436. doi: 10.1371/journal.pone.0260436. eCollection 2022.

ABSTRACT

Many pathologies can occur in the periportal space and manifest as fluid accumulation, visible in Computed tomography (CT) images as a circumferential region of low attenuation around the intrahepatic portal vessels, called periportal halo (PPH). This finding is associated with different types of hepatic and extra-hepatic disease in humans and remains a non-specific sign of unknown significance in veterinary literature. The aim of this study was to investigate the prevalence of PPH in a population of patients undergoing CT examination and to assess the presence of lesions related to hepatic and extra-hepatic disease in presence of PPH. CT studies including the cranial abdomen of dogs and cats performed over a 5-year period were retrospectively reviewed. The prevalence of PPH was 15% in dogs and 1% in cats. 143 animals were included and the halo was classified as mild, moderate and severe, respectively in 51%, 34% and 15% of animals. The halo distribution was generalized in 79 cases, localized along the second generation of portal branches in 63, and along the first generation only in one. Hepatic disease was present in 58/143 and extra-hepatic disease in 110/143 of the cases. Main cause of hepatic (36%) and extra-hepatic disease (68%) was neoplasia. Associations between halo grades and neoplasia revealed to be not statistically significant (p = 0.057). In 7% of animals the CT examination was otherwise unremarkable. PPH is a non-specific finding, occurring in presence of a variety of diseases in the examined patient population.

PMID:34995282 | DOI:10.1371/journal.pone.0260436

PLoS One. 2022 Jan 7;17(1):e0260836. doi: 10.1371/journal.pone.0260836. eCollection 2022.

ABSTRACT

In the era of open data, Poisson and other count regression models are increasingly important. Still, conventional Poisson regression has remaining issues in terms of identifiability and computational efficiency. Especially, due to an identification problem, Poisson regression can be unstable for small samples with many zeros. Provided this, we develop a closed-form inference for an over-dispersed Poisson regression including Poisson additive mixed models. The approach is derived via mode-based log-Gaussian approximation. The resulting method is fast, practical, and free from the identification problem. Monte Carlo experiments demonstrate that the estimation error of the proposed method is a considerably smaller estimation error than the closed-form alternatives and as small as the usual Poisson regressions. For counts with many zeros, our approximation has better estimation accuracy than conventional Poisson regression. We obtained similar results in the case of Poisson additive mixed modeling considering spatial or group effects. The developed method was applied for analyzing COVID-19 data in Japan. This result suggests that influences of pedestrian density, age, and other factors on the number of cases change over periods.

PMID:34995283 | DOI:10.1371/journal.pone.0260836

Neurosurgery. 2021 Dec 2. doi: 10.1227/NEU.0000000000001738. Online ahead of print.

ABSTRACT

BACKGROUND: Hypothalamic hamartomas (HHs) are disabling congenital lesions, responsible for gelastic seizures frequently associated with catastrophic epilepsies, epileptogenic encephalopathy, and cognitive and psychiatric severe comorbidities. Stereotactic radiosurgery (SRS) is a well-established minimally invasive therapeutic approach.

OBJECTIVE: To assess whether pretherapeutic gray matter density (GMD) correlates with seizure outcome.

METHODS: We used voxel-based morphometry at whole-brain level, as depicted on pretherapeutic standard structural magnetic resonance neuroimaging. We examined 24 patients (10 male patients, 14 female patients; mean age, 12.7 yr; median, 9; range, 5.9-50) treated in Marseille University Hospital, France, between May 2001 and August 2018.

RESULTS: Most relevant anatomic area predicting postoperative Engel classes I and II vs III and IV after SRS for HHs was mesencephalic tegmentum. Higher pretherapeutic GMD in this area was associated with better outcomes for seizure cessation. The only other statistically significant clusters were right cerebellar lobule VIIIb and VIIIa. Lower pretherapeutic GMD in both clusters correlated with better Engel class outcomes. GMD decreased with age in the left mediodorsal thalamus.

CONCLUSION: Seizure cessation after SRS for HHs was associated with higher GMD in mesencephalic tegmental area, acknowledged to be involved in the neural control of explosive vocal behavior in animals. This area is connected by the mamillotegmental bundle to the lateral tuberal nucleus area of the hypothalamus, where HHs are known to rise. In the future, the detection of more gray matter in this “laugh” tegmental area based on pretherapeutic routine structural neuroimaging might help in patient selection for minimally invasive radiosurgery for HH.

PMID:34995238 | DOI:10.1227/NEU.0000000000001738

J Med Internet Res. 2021 Dec 21. doi: 10.2196/24787. Online ahead of print.

ABSTRACT

BACKGROUND: Innovative surveillance methods are needed to assess adherence to COVID-19 social distancing and stay-at-home order/self-quarantine recommendations, especially methods that can provide near real-time and/or highly geographically targeted data. Use of location-based social media image data is one possible approach that could be explored to address this problem.

OBJECTIVE: We sought to evaluate whether publicly-available near real-time social media images might be used to monitor COVID-19 health policy adherence.

METHODS: We collected a sample of 43,487 Instagram images in New York from February 7 to April 11, 2020 from the following location hashtags: #Centralpark (N = 20,937); #Brooklyn Bridge (N = 14,875); and #Timesquare (N = 7,675). After manually reviewing images for accuracy, we counted and recorded the frequency of valid daily posts at each of these hashtag locations over time, as well as rated and counted whether the individuals in the pictures at these location hashtags were social distancing (i.e., whether the individuals in the images appeared to be distanced from others versus next to or touching each other). We analyzed the number of images posted over time and the correlation between trends among hashtag locations.

RESULTS: We found a statistically significant decline in the number of posts over time across all regions, with an approximate decline of 17% across each site (p< .001). We found a positive correlation between hashtags (#Centralpark,#Brooklynbridge; r=.40), (#BrooklynBridge,#Timesquare; r=.41), (#Timesquare,#Centralpark; r=.33; p< .001 for all correlations). The logistic regression analysis showed a mild statistically significant increase in the proportion of posts over time with people appearing to be social distancing at Times Square (p<.05) and Brooklyn Bridge (p < .05), but not for Central Park.

CONCLUSIONS: Results suggest the potential of using location-based social media image data as a method for surveillance of COVID-19 health policy adherence. Future studies should further explore the implementation and ethical issues associated with this approach.

PMID:34995205 | DOI:10.2196/24787

J Med Internet Res. 2021 Dec 20. doi: 10.2196/33149. Online ahead of print.

ABSTRACT

In the Czech Republic, the strategic data-based and organisational support for individual regions and for providers of acute care on the nationwide level is coordinated by the Ministry of Health of the Czech Republic. At the beginning of the COVID-19 pandemic, the country needed to implement very quickly a system for monitoring, reporting and overall management of hospital capacities. This viewpoint paper aims to describe the purpose and basic functions of a web-based application entitled “Control Centre for Intensive Care”, which has been developed and made available for the needs of systematic online technical support for the management of intensive inpatient care across the Czech Republic during the first wave of pandemic in spring 2020. Two tools of key importance are described in the context of national methodology; namely one module for regular online updates and overall monitoring of currently free capacities of intensive care in real time, and a second module for online entering and overall record keeping of requirements on medications for COVID-19 patients. A total of 134 intensive care providers and 927 users from hospitals from all 14 regions of the Czech Republic were registered in the central Control Centre for Intensive Care database as of 31 March 2021. This web-based application enabled continuous monitoring and decision-making during the mass surge of critical care from autumn 2020 to spring 2021. The Control Centre for Intensive Care has become an indispensable part of a set of online tools that are employed on a regular basis for crisis management at the time of the COVID-19 pandemic.

PMID:34995207 | DOI:10.2196/33149