OBJECTIVE: To clarify the relationship between the prognosis of patients with placental abruption (PA) and the healthcare delivery system using data from a large national inpatient database in Japan.
METHODS: Using the Diagnosis Procedure Combination database, we conducted a retrospective cohort study with the data of patients in almost 1000 hospitals with the primary diagnosis of PA who were hospitalized from April 2014 to March 2021. We divided the hospitals into four groups based on the number of deliveries per month. We performed multilevel logistic regression analysis to analyze the relationship between hospital case volume and maternal end-organ injury (MEOI).
RESULTS: Altogether, 8222 patients were included for analysis; among whom, 3575 (44%) were transferred by ambulance. MEOI was noted in 977 patients (12%) with no obvious difference by hospital case volume. Ambulance transfer, age, gestational weeks at admission, delivery on the first day of hospitalization, and history of eclampsia were significantly associated with a higher incidence of MEOI, but the hospital case volume was not.
CONCLUSIONS: Using a Japanese administrative database, our study shows that hospital case volume was not significantly associated with the severity of maternal illness among patients with PA.

Background Clostridioides difficile infection (CDI) recurrence is a public health concern as well as a health economic burden. Bezlotoxumab treatment is one way to prevent recurrence; however, its clinical results have not been reported in Japan. Therefore, we investigated the efficacy and safety of bezlotoxumab in patients with CDI at a university hospital in Japan and compared them with previously reported findings. Methodology We retrospectively examined all patients with some risk factors for recurrent CDI who received bezlotoxumab at the discretion of physicians at the Aichi Medical University Hospital, Aichi, Japan, between July 2018 and July 2022. The primary outcome was the three-month CDI recurrence rate. The secondary outcomes were an initial clinical cure and the six-month CDI recurrence rate. The safety of the administration was also assessed. Results A total of nine patients who received bezlotoxumab were included during the study period. The rate of CDI recurrence within three months was 28.5% (2/9). Two patients died due to other causes before their diarrhea improved. None of the patients experienced CDI recurrence between three and six months after the initial clinical cure of the baseline episode. Patients showed good tolerability to bezlotoxumab with no adverse effects. Two patients with a single episode of CDI recurrence before bezlotoxumab administration showed no recurrence. Conclusions In this Japanese case-series study, the efficacy of bezlotoxumab in preventing CDI recurrence in elderly patients with CDI and multiple underlying diseases was inferior to that reported in previous studies that analyzed real-world data. It is possible that bezlotoxumab may not be fully effective in elderly patients with CDI.

Objectives: We investigated the impact of COVID-19 on tuberculosis (TB) case notification and treatment outcomes in Eswatini. Methods: A comparative retrospective cohort study was conducted using TB data from eight facilities. An interrupted time series analysis, using segmented Poisson regression was done to assess the impact of COVID-19 on TB case notification comparing period before (December 2018-February 2020, n = 1,560) and during the pandemic (March 2020-May 2021, n = 840). Case notification was defined as number of TB cases registered in the TB treatment register. Treatment outcomes was result assigned to patients at the end of treatment according to WHO rules. Results: There was a significant decrease in TB case notification (IRR 0.71, 95% CI: 0.60-0.83) and a significant increase in death rate among registrants during the pandemic (21.3%) compared to pre-pandemic (10.8%, p < 0.01). Logistic regression indicated higher odds of unfavorable outcomes (death, lost-to-follow-up, and not evaluated) during the pandemic than pre-pandemic (aOR 2.91, 95% CI: 2.17-3.89). Conclusion: COVID-19 negatively impacted TB services in Eswatini. Eswatini should invest in strategies to safe-guard the health system against similar pandemics.

BACKGROUND: Heart failure (HF) is one of the important complications of acute myocardial infarction (AMI), but the epidemiology, associated risks and outcomes have not been well investigated in the era of broad use of fluoroscopy-guided angiographic intervention.
METHODS: We analysed 161,384 subjects who had experienced the first episode of AMI during 1 January 2000 and 31 December 2012 using the Taiwan National Health Insurance Research Database.
RESULTS: During the index AMI hospitalization, 23.6% of cases developed HF. Female, ≥65 years-old, non-ST-segment elevation type of MI, diabetes mellitus (DM), peripheral vascular occlusion disease (PAOD), chronic obstructive pulmonary disease (COPD), atrial fibrillation, and ventricular tachycardia/fibrillation (VT/VF) were associated with higher risks of developing HF. HF cases had inferior survival outcomes compared to non-HF cases in both the short and long term. Among those HF patients, ≥65 years, DM, PAOD, and VT/VF were associated with worse outcomes. On the contrary, coronary reperfusion intervention and treat-to-target pharmacologic treatment were associated with favourable survival outcomes.
CONCLUSIONS: HF remains common in the modern age and poses negative impacts in survival of AMI patients. It highlights that prudent prevention and early treatment of HF during AMI hospitalization is an important medical issue.

In the early stages of the COVID-19 global pandemic, caused by the SARS-CoV-2 virus, low- and middle-income countries (LMICs) appeared to be experiencing lower morbidity and mortality rates than high-income countries, particularly the United States. Various suggestions put forward to account for this included the possibility that LMICs might be experiencing off-target benefits of infant vaccination with BCG, intended primarily to protect against tuberculosis. A number of ecologic epidemiological studies that considered COVID-19 morbidity and mortality rates across countries appeared to support this suggestion. Ecologic studies, however, are primarily hypothesis-generating, given their well-known limitations in extrapolating to the individual-person level. The present study, which employed anonymized records of U.S. Military Veterans treated by the Department of Veterans Affairs was principally a case-control study of COVID-19 infections with a retrospective cohort study of mortality nested within the infections. Controls were a random sample of Veterans not recorded as having had COVID-19. There were 263,039 controls and 167,664 COVID-19 cases, of whom 5,016 died. The combination of country and year of birth was used as a surrogate for infant BCG vaccination. The study did not support the hypothesis that BCG in infancy was protective against COVID-19. The odds ratio for infection was 1.07 (95% confidence interval [CI]: 1.03, 1.11) and the risk ratio for mortality among the COVID-19 cases was 0.86 (95% CI: 0.63, 1.18). The potential for non-differential exposure misclassification was a concern, possibly biasing measures of association toward the null value.
PLAIN LANGUAGE SUMMARYLow- and middle-income countries (LMICs) have appeared to be much less affected by the COVID-19 pandemic, caused by the SARS-CoV-2 virus, than might have been expected from the effects of the virus in more-developed countries. It has been suggested that BCG vaccination of infants against tuberculosis in LMICs might be providing cross-protection against COVID-19. BCG has never been routinely administered in the United States and is not currently administered in most other developed countries.Some epidemiology studies, known as “ecologic” studies have provided support for the idea that BCG is protecting against COVID-19. However, ecologic studies, with group (i.e., country) measures of exposure and health outcomes, are difficult to interpret in terms of cause and effect.More interpretable are studies that use individual-person measures of exposure and health outcome. We carried out such a study using data from several hundred-thousand U.S. military Veterans, many of whom were born in LMICs and would have received BCG vaccination as infants. Many U.S. Veterans have had COVID-19, and many of those have died of it.Our study, the first of its kind, found no evidence to support the idea that infant BCG vaccination protects against infection or death from COVID-19.

BACKGROUND: Fall-risk assessment is complex. Based on current scientific evidence, a multifactorial approach, including the analysis of physical performance, gait parameters, and both extrinsic and intrinsic risk factors, is highly recommended. A smartphone-based app was designed to assess the individual risk of falling with a score that combines multiple fall-risk factors into one comprehensive metric using the previously listed determinants.
OBJECTIVE: This study provides a descriptive evaluation of the designed fall-risk score as well as an analysis of the app\'s discriminative ability based on real-world data.
METHODS: Anonymous data from 242 seniors was analyzed retrospectively. Data was collected between June 2018 and May 2019 using the fall-risk assessment app. First, we provided a descriptive statistical analysis of the underlying dataset. Subsequently, multiple learning models (Logistic Regression, Gaussian Naive Bayes, Gradient Boosting, Support Vector Classification, and Random Forest Regression) were trained on the dataset to obtain optimal decision boundaries. The receiver operating curve with its corresponding area under the curve (AUC) and sensitivity were the primary performance metrics utilized to assess the fall-risk score\'s ability to discriminate fallers from nonfallers. For the sake of completeness, specificity, precision, and overall accuracy were also provided for each model.
RESULTS: Out of 242 participants with a mean age of 84.6 years old (SD 6.7), 139 (57.4%) reported no previous falls (nonfaller), while 103 (42.5%) reported a previous fall (faller). The average fall risk was 29.5 points (SD 12.4). The performance metrics for the Logistic Regression Model were AUC=0.9, sensitivity=100%, specificity=52%, and accuracy=73%. The performance metrics for the Gaussian Naive Bayes Model were AUC=0.9, sensitivity=100%, specificity=52%, and accuracy=73%. The performance metrics for the Gradient Boosting Model were AUC=0.85, sensitivity=88%, specificity=62%, and accuracy=73%. The performance metrics for the Support Vector Classification Model were AUC=0.84, sensitivity=88%, specificity=67%, and accuracy=76%. The performance metrics for the Random Forest Model were AUC=0.84, sensitivity=88%, specificity=57%, and accuracy=70%.
CONCLUSIONS: Descriptive statistics for the dataset were provided as comparison and reference values. The fall-risk score exhibited a high discriminative ability to distinguish fallers from nonfallers, irrespective of the learning model evaluated. The models had an average AUC of 0.86, an average sensitivity of 93%, and an average specificity of 58%. Average overall accuracy was 73%. Thus, the fall-risk app has the potential to support caretakers in easily conducting a valid fall-risk assessment. The fall-risk score\'s prospective accuracy will be further validated in a prospective trial.