Dataset Information

Differences in Clinical Outcomes between Patients with and without Hypoglycemia during Hospitalization: A Retrospective Study Using Real-World Evidence.

ABSTRACT:

Background

Some patients admitted to hospitals for glycemic control experience hypoglycemia despite regular meals and despite adhering to standard blood glucose control protocols. Different factors can have a negative impact on blood glucose control and prognosis after discharge. This study investigated risk factors for hypoglycemia and its effects on glycemic control during the hospitalization of patients in the general ward.

Methods

This retrospective study included patients who were admitted between 2009 and 2018. Patients were provided regular meals at fixed times according to ideal body weights during hospitalization. We categorized the patients into two groups: those with and those without hypoglycemia during hospitalization.

Results

Of the 3,031 patients, 379 experienced at least one episode of hypoglycemia during hospitalization (HYPO group). Hypoglycemia occurred more frequently particularly in cases of premixed insulin therapy. Compared with the control group, the HYPO group was older (61.0±16.8 years vs. 59.1±16.5 years, P=0.035), with more females (60.4% vs. 49.6%, P<0.001), lower body mass index (BMI) (23.5±4.2 kg/m² vs. 25.1±4.4 kg/m², P<0.001), and higher prevalence of type 1 diabetes mellitus (6.1% vs. 2.6%, P<0.001), They had longer hospital stay (11.1±13.5 days vs. 7.6±4.6 days, P<0.001). After discharge the HYPO group had lower glycosylated hemoglobin reduction rate (-2.0%±0.2% vs. -2.5%±0.1%, P=0.003) and tended to have more frequent cases of cardiovascular disease.

Conclusion

Hypoglycemia occurred more frequently in older female patients with lower BMI and was associated with longer hospital stay and poorer glycemic control after discharge. Therefore, clinicians must carefully ensure that patients do not experience hypoglycemia during hospitalization.

SUBMITTER: Lee J

PROVIDER: S-EPMC7453993 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Differences in Clinical Outcomes between Patients with and without Hypoglycemia during Hospitalization: A Retrospective Study Using Real-World Evidence.

Lee Jeongmin J Kim Tong Min TM Kim Hyunah H Lee Seung Hwan SH Cho Jae Hyoung JH Lee Hyunyong H Yim Hyeon Woo HW Yoon Kun Ho KH Kim Hun Sung HS

Diabetes & metabolism journal 20200508 4

<h4>Background</h4>Some patients admitted to hospitals for glycemic control experience hypoglycemia despite regular meals and despite adhering to standard blood glucose control protocols. Different factors can have a negative impact on blood glucose control and prognosis after discharge. This study investigated risk factors for hypoglycemia and its effects on glycemic control during the hospitalization of patients in the general ward.<h4>Methods</h4>This retrospective study included patients who ...[more]

PMID: 32431110

Similar Datasets

Project description:IntroductionThe purpose of this study was to identify predictors of initial hospitalization and describe the outcomes of high-risk patients hospitalized with influenza.MethodsData were taken from the 5% national US Medicare database from 2012 to 2015. Patients (aged at least 13 years) were required to have at least one diagnosis for influenza and have continuous health plan enrollment for 6 months before (baseline) and 3 months (follow-up) after the date of influenza diagnosis. Patients who died during follow-up were included. Patients were categorized as initially hospitalized if hospitalized within 0-1 day of diagnosis. High-risk initially hospitalized patients were defined as patients aged at least 65 years or those that had a diagnostic code for chronic lung disease, cardiovascular or cerebrovascular disease, or weakened immune system during baseline period. Logistic regression models were developed to determine predictors of initial hospitalization.ResultsThe study population included 8127 high-risk patients who were initially hospitalized and 16,784 who were not hospitalized. Among high-risk patients, 89.3% were diagnosed in the emergency room, whereas 7.5% and 3.2% were diagnosed in a physician's office or other Medicare settings, respectively. Chronic obstructive pulmonary disorder, congestive heart failure, chronic kidney disease, older age, being male, other comorbidities, number of comorbidities, and baseline healthcare resource use were the predictors of hospitalization. Median length of stay for the hospitalization was 5.0 days, and the 30-day readmission rate was 14%. All-cause mortality rate was 5.1% during the inpatient stay and 9.2% within 30 days of diagnosis. Hospitalized patients with influenza incurred an increase of $16,568 per patient in total all-cause healthcare costs from pre-influenza to post-influenza diagnosis.ConclusionThe study characterized the burden of hospitalization for influenza and found that hospitalized high-risk patients experience greater comorbidity burden, higher likelihood of multiple inpatient admissions, and costly medical interventions compared to patients who were not hospitalized.

Project description:Purpose To retrospectively analyze the clinical characteristics of patients undergoing surgical treatment for gastrointestinal stromal tumors (GISTs) in Ruijin Hospital and explore the relevant prognosis clinical factors after surgical treatment. Methods We screened out 1015 patients with GISTs diagnosed and treated during January 2010 to December 2019. We performed univariate analysis by the log-rank test and multivariate analysis by COX regression. The Kaplan–Meier method was used to estimate the disease-free survival (DFS) and overall survival (OS) of the whole group. Results All 1015 patients in the whole group received radical surgery, and the proportion of patients with high, intermediate, and low risk was 31.1%, 21.7%, and 47.3%, respectively. Among the 480 low-risk patients, surgery could achieve radical therapy; only the Ki-67 index was related to DFS and OS (DFS: p = 0.032, OS: p = 0.009) among the 140 intermediate-risk patients with tumors located in the stomach, whether received Tyrosine kinase inhibitors (TKIs) therapy did not affect the prognosis of patients (DFS: p = 0.716, OS: p = 0.848). Among the 331 high-risk patients, those with non-gastric tumors (those outside the stomach, duodenum, and small intestine, HR 1.55, 95% CI 1.19–2.00, p < 0.001), tumor diameter > 10 cm (hazard ratio, HR 2.63, 95% confidence interval, CI 2.09–4.03, p < 0.001), as well as high-risk patients with mitotic rate > 10/50 HPF (HR 2.74, 95% CI 2.00–3.76, p < 0.001), the overall prognosis was obviously worse than that of other patients. For some high-risk patients, prolonged postoperative imatinib therapy could significantly improve the survival of patients (HR 0.43, 95% CI 0.15–0.66, p < 0.001). Conclusions For the vast majority of GIST patients, surgery can be curative; but in intermediate-risk patients, the Ki-67 index and postoperative TKI treatment are closely related to prognosis. For intermediate-risk patients whose primary tumor is the stomach, the value of TKI-targeted therapy after surgery seem be not necessary in our study. However, for some high-risk patients, the prognosis of patients can be improved by appropriately prolonging the treatment time of TKI. Supplementary Information The online version contains supplementary material available at 10.1186/s12957-023-02897-y.

Project description:BackgroundNeutralizing monoclonal antibodies (mAbs) were authorized for the treatment of COVID-19 outpatients based on clinical trials completed early in the pandemic, which were underpowered for mortality and subgroup analyses. Real-world data studies are promising for further assessing rapidly deployed therapeutics.Research questionDid mAb treatment prevent progression to severe disease and death across pandemic phases and based on risk factors, including prior vaccination status?Study design and methodsThis observational cohort study included nonhospitalized adult patients with SARS-CoV-2 infection from November 2020 to October 2021 using electronic health records from a statewide health system plus state-level vaccine and mortality data. Using propensity matching, we selected approximately 2.5 patients not receiving mAbs for each patient who received mAb treatment under emergency use authorization. The primary outcome was 28-day hospitalization; secondary outcomes included mortality and hospitalization severity.ResultsOf 36,077 patients with SARS-CoV-2 infection, 2,675 receiving mAbs were matched to 6,677 patients not receiving mAbs. Compared with mAb-untreated patients, mAb-treated patients had lower all-cause hospitalization (4.0% vs 7.7%; adjusted OR, 0.48; 95% CI, 0.38-0.60) and all-cause mortality (0.1% vs 0.9%; adjusted OR, 0.11; 95% CI, 0.03-0.29) to day 28; differences persisted to day 90. Among hospitalized patients, mAb-treated patients had shorter hospital length of stay (5.8 vs 8.5 days) and lower risk of mechanical ventilation (4.6% vs 16.6%). Results were similar for preventing hospitalizations during the Delta variant phase (adjusted OR, 0.35; 95% CI, 0.25-0.50) and across subgroups. Number-needed-to-treat (NNT) to prevent hospitalization was lower for subgroups with higher baseline risk of hospitalization; for example, multiple comorbidities (NNT = 17) and not fully vaccinated (NNT = 24) vs no comorbidities (NNT = 88) and fully vaccinated (NNT = 81).InterpretationReal-world data revealed a strong association between receipt of mAbs and reduced hospitalization and deaths among COVID-19 outpatients across pandemic phases. Real-world data studies should be used to guide practice and policy decisions, including allocation of scarce resources.

Project description:IntroductionHypoglycemia is the most common adverse effect of diabetes therapy, particularly insulin treatment. Hypoglycemia is associated with considerable clinical and economic burden, and may be under-reported. The aim of this study was to com pare the frequency of hypoglycemic events reported in real-world settings with those reported in clinical trials.MethodsWe conducted a structured literature review in PubMed to identify hypoglycemic event rates in patients with type 1 diabetes mellitus (T1DM) and insulin-treated type 2 diabetes mellitus (T2DM) from real-world data (RWD) and randomized controlled trials (RCTs). The search was restricted to English language, full-text publications from 2010 onwards, reporting on treatment of T1DM or T2DM with basal only, basal-bolus, or premix insulin.ResultsThe final dataset included 30 studies (11 RWD studies and 19 RCTs). Six studies (RWD, n = 2; RCT, n = 4) reported hypoglycemia event rates in people with T1DM. For all reported categories of hypoglycemia (severe, non-severe, and nocturnal), rates were consistently higher in RWD studies compared with RCTs. Twenty-five studies (RWD, n = 10; RCT, n = 15) reported hypoglycemia event rates in people with insulin-treated T2DM. For T2DM basal-oral therapy; the highest rates were observed in RWD studies, although there was an overlap with RCT rates. For basal-bolus therapy, there was considerable between-study variability but higher rates of severe and non-severe hypoglycemia were generally observed in RWD studies. For T2DM premix insulin, reported rates of hypoglycemia in RWD studies and RCTs were similar.ConclusionWe found that higher rates of hypoglycemia are observed in real-world settings compared with clinical trial settings, although there is a large degree of overlap. Due to the inherent constraints of RCTs, they are likely to underestimate the burden of hypoglycemia in clinical practice. Further, high-quality RWD are needed to determine a more accurate incidence of hypoglycemia in clinical practice.

Dataset Information

Differences in Clinical Outcomes between Patients with and without Hypoglycemia during Hospitalization: A Retrospective Study Using Real-World Evidence.

Background

Methods

Results

Conclusion

Publications

Differences in Clinical Outcomes between Patients with and without Hypoglycemia during Hospitalization: A Retrospective Study Using Real-World Evidence.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets