Although high-intensity pain has been linked to adverse outcomes, many hospitalized patients report severe pain as acceptable

Background: Contraindications and precautions to metformin have limited inpatient use, and limited evidence exists evaluating metformin in hospitalized patients. Objective: This study aimed to determine the safety and efficacy of inpatient metformin use. Methods: This study was an observational, retrospective, cohort study at an academic medical center between June 1, 2016, and May 31, 2018. Hospitalized adults with type 2 diabetes mellitus receiving at least 1 metformin dose were included. The primary endpoint was to identify hospitalized patients using metformin with at least 1 contraindication or precautionary warning against use. Secondary endpoints included assessing metformin efficacy with glycemic control, characterizing adverse outcomes of inpatient metformin, and comparing the efficacy of metformin-containing regimens. Results: Two hundred patients were included. There were 126 incidences of potentially unsafe use identified in 111 patients (55.5%). The most common reasons were age ≥65 years (47%), heart failure diagnosis (7.5%), and metformin within 48 hours of contrast (6%). Metformin was contraindicated in 2 patients (1%) with an estimated glomerular filtration rate ≤30 mL/min/1.73 m2. The overall median daily blood glucose was 146 mg/dL (interquartile range [IQR] = 122-181). Patients were divided into 3 groups: metformin monotherapy, metformin plus oral antihyperglycemic therapy, and metformin plus insulin. The median daily blood glucoses were 129 mg/dL (IQR = 110-152), 154 mg/dL (IQR = 133-178), and 174 mg/dL (IQR = 142-203; P < .001), respectively. Two patients (1%) developed acute kidney injury, and no patients developed lactic acidosis. Conclusions: Metformin was associated with goal glycemic levels in hospitalized patients with no adverse outcomes. These results suggest the potential for metformin use in hospitalized, non–critically ill patients.

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Adverse outcomes in older hospitalized patients: The role of multidimensional geriatric assessment

Aging Clinical and Experimental Research ◽

10.1007/bf03324477 ◽

2003 ◽

Vol 15 (1) ◽

pp. 32-37 ◽

Cited By ~ 18

Author(s):

Alessandra Marengoni ◽

Stefania Cossi ◽

Monica De Martinis ◽

Maria K. Ghisla ◽

Paolo A. Calabrese ◽

...

Keyword(s):

Geriatric Assessment ◽

Hospitalized Patients ◽

Adverse Outcomes

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Comparison of Two Versions of the Beers Criteria and Adverse Outcomes in Older Hospitalized Patients

The Consultant Pharmacist ◽

10.4140/tcp.n.2017.752 ◽

2017 ◽

Vol 32 (12) ◽

pp. 752-763 ◽

Cited By ~ 2

Author(s):

Stephanie M. Ozalas ◽

Victoria Huang ◽

Luigi Brunetti ◽

Timothy Reilly

Keyword(s):

Hospitalized Patients ◽

Adverse Outcomes ◽

Beers Criteria

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Association between nutritional risk and routine clinical laboratory measurements and adverse outcomes: a prospective study in hospitalized patients of wuhan tongji hospital

European Journal of Clinical Nutrition ◽

10.1038/ejcn.2014.239 ◽

2014 ◽

Vol 69 (5) ◽

pp. 552-557 ◽

Cited By ~ 6

Author(s):

Z Y Chen ◽

C Gao ◽

T Ye ◽

X Z Zuo ◽

G H Wang ◽

...

Keyword(s):

Prospective Study ◽

Clinical Laboratory ◽

Hospitalized Patients ◽

Adverse Outcomes ◽

Nutritional Risk ◽

Laboratory Measurements ◽

Routine Clinical Laboratory ◽

A Prospective Study

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Prevalence of Current Smoking and Association with Adverse Outcome in Hospitalized COVID-19 Patients: A Systematic Review and Meta-Analysis

10.20944/preprints202005.0113.v1 ◽

2020 ◽

Author(s):

Konstantinos Farsalinos ◽

Konstantinos Poulas ◽

Riccardo Polosa ◽

Anastasia Barbouni ◽

Pasquale Caponnetto ◽

...

Keyword(s):

Systematic Review ◽

Odds Ratio ◽

Adverse Outcome ◽

Smoking Status ◽

Meta Analysis ◽

Hospitalized Patients ◽

Adverse Outcomes ◽

Prevalence Odds Ratio ◽

Current Smoking ◽

Former Smokers

Background: The purpose of this study was to examine the prevalence and effects of current smoking on adverse outcomes among hospitalized COVID-19 patients. Methods: We performed a systematic review of the literature (PubMed) for studies published until April 25. Studies were included into the analysis if they satisfied all of the following criteria: 1. To present hospitalized patients with COVID-19. 2. To classify patients into less and more severe disease, irrespective of the severity definition (defined as “adverse ourtcome”). 3. To present data on the smoking status, separately for each severity classification. We identified 18 (from a total of 1398) relevant studies. Pooled current smoking prevalence was compared with the gender-adjusted, population-based expected prevalence by calculating Prevalence Odds Ratio (POR). The association between current, compared to non-current and former, smoking and adverse outcome was examined by calculating Odds Ratio (OR). All analyses were performed using random-effects meta-analysis. Results: Among 6515 patients, 440 of whom were current smokers, the pooled prevalence of current smoking was 6.8% (95%CI: 4.8-9.1%) and the POR was 0.21 (95%CI: 0.16-0.26, P < 0.001). In Chinese studies only, the POR was 0.22 (95%CI: 0.17-0.27, P < 0.001). Current smokers were more likely to have an adverse outcome compared to non-current smokers (OR: 1.53, 95%CI: 1.06-2.20, P = 0.022). However, they were less likely to have an adverse outcome compared to former smokers (OR: 0.42, 95%CI: 0.27-0.74, P = 0.003). Conclusion: An unexpectedly low prevalence of current smoking was observed among hospitalized patients with COVID-19. Hospitalized current smokers had higher odds compared to non-current smokers but lower odds compared to former smokers for an adverse outcome. The possibility that nicotine may have a protective effect in COVID-19 which may be masked by smoking-related toxicity and by the abrupt cessation of nicotine intake when smokers are hospitalized should be explored.

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Trends over time in the risk of adverse outcomes among patients with SARS-CoV-2 infection

10.1101/2021.03.08.21253090 ◽

2021 ◽

Author(s):

George N. Ioannou ◽

Ann M. O’Hare ◽

Kristin Berry ◽

Vincent S Fan ◽

Kristina Crothers ◽

...

Keyword(s):

Mechanical Ventilation ◽

Healthcare System ◽

Hospitalized Patients ◽

Adverse Outcomes ◽

Interrupted Time Series Analysis ◽

Icu Admission ◽

National Healthcare ◽

Laboratory Test Results ◽

National Healthcare System ◽

Subsequent Stabilization

AbstractObjectivesWe aimed to describe trends in the incidence of adverse outcomes among patients who tested positive for SARS-CoV-2 between February and September 2020 within a national healthcare system.SettingUS Veterans Affairs national healthcare system.ParticipantsEnrollees in the VA healthcare system who tested positive for SARS-CoV-2 between 2/28/2020 and 9/30/2020 (n=55,952).OutcomesDeath, hospitalization, intensive care unit (ICU) admission and mechanical ventilation within 30 days of testing positive.The incidence of these outcomes was examined among patients infected each month and trends were evaluated using an interrupted time-series analysis.ResultsBetween February and July 2020, during the first wave of the US pandemic, there were marked downward trends in the 30-day incidence of hospitalization (44.2% to 15.8%), ICU admission (20.3% to 5.3%), mechanical ventilation (12.7% to 2.2%), and death (12.5% to 4.4%), with subsequent stabilization between July and September 2020. These trends persisted after adjustment for sociodemographic characteristics, comorbid conditions, and documented symptoms and after additional adjustment for laboratory test results among hospitalized patients, including among subgroups admitted to the ICU and treated with mechanical ventilation. Among hospitalized patients, use of hydroxychloroquine (56.5% to 0%), azithromycin (48.3% to 16.6%) vasopressors (20.6% to 8.7%), and dialysis (11.6% to 3.8%) decreased while use of dexamethasone (3.4% to 53.1%), other corticosteroids (4.9% to 29.0%) and remdesivir (1.7% to 45.4%) increased from February to September.ConclusionsAmong patients who tested positive for SARS-CoV-2 in a large national US healthcare system, risk for a range of adverse outcomes decreased markedly between February and July, with subsequent stabilization from July to September. These trends were not explained by changes in measured baseline patient characteristics.

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