scholarly journals Hospital-Acquired Dysmagnesemia and In-Hospital Mortality

2020 ◽  
Vol 8 (3) ◽  
pp. 37 ◽  
Author(s):  
Wisit Cheungpasitporn ◽  
Charat Thongprayoon ◽  
Api Chewcharat ◽  
Tananchai Petnak ◽  
Michael A. Mao ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Hospital Mortality ◽  
Serum Magnesium ◽  
Normal Serum ◽  
Hospitalized Patients ◽  
Normal Range ◽  
Multivariable Logistic Regression ◽  
Hospital Acquired

Background and Objectives: This study aimed to report the incidence of hospital-acquired dysmagnesemia and its association with in-hospital mortality in adult general hospitalized patients. Materials and Methods: We studied 26,020 adult hospitalized patients from 2009 to 2013 who had normal admission serum magnesium levels and at least two serum magnesium measurements during hospitalization. The normal range of serum magnesium was 1.7–2.3 mg/dL. We categorized in-hospital serum magnesium levels based on the occurrence of hospital-acquired hypomagnesemia and/or hypermagnesemia. We assessed the association between hospital-acquired dysmagnesemia and in-hospital mortality using multivariable logistic regression. Results: 28% of patients developed hospital-acquired dysmagnesemia. Fifteen per cent had hospital-acquired hypomagnesemia only, 10% had hospital-acquired hypermagnesemia only, and 3% had both hospital-acquired hypomagnesemia and hypermagnesemia. Compared with patients with persistently normal serum magnesium levels in hospital, those with hospital-acquired hypomagnesemia only (OR 1.77; p < 0.001), hospital-acquired hypermagnesemia only (OR 2.31; p < 0.001), and both hospital-acquired hypomagnesemia and hypermagnesemia (OR 2.14; p < 0.001) were significantly associated with higher in-hospital mortality. Conclusions: Hospital-acquired dysmagnesemia affected approximately one-fourth of hospitalized patients. Hospital-acquired hypomagnesemia and hypermagnesemia were significantly associated with increased in-hospital mortality.

scholarly journals Hospital-Acquired Serum Chloride Derangements and Associated In-Hospital Mortality

Medicines ◽  
2020 ◽  
Vol 7 (7) ◽  
pp. 38
Author(s):  
Charat Thongprayoon ◽  
Wisit Cheungpasitporn ◽  
Tananchai Petnak ◽  
Michael A. Mao ◽  
Api Chewcharat ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Hospital Mortality ◽  
Odds Ratio ◽  
Hospitalized Patients ◽  
Normal Range ◽  
Serum Chloride ◽  
Hospital Acquired

Background: We aimed to describe the incidence of hospital-acquired dyschloremia and its association with in-hospital mortality in general hospitalized patients. Methods: All hospitalized patients from 2009 to 2013 who had normal admission serum chloride and at least two serum chloride measurements in the hospital were studied. The normal range of serum chloride was defined as 100–108 mmol/L. Hospital serum chloride levels were grouped based on the occurrence of hospital-acquired hypochloremia and hyperchloremia. The association of hospital-acquired hypochloremia and hyperchloremia with in-hospital mortality was analyzed using logistic regression. Results: Among the total of 39,298 hospitalized patients, 59% had persistently normal hospital serum chloride levels, 21% had hospital-acquired hypochloremia only, 15% had hospital-acquired hyperchloremia only, and 5% had both hypochloremia and hyperchloremia. Compared with patients with persistently normal hospital serum chloride levels, hospital-acquired hyperchloremia only (odds ratio or OR 2.84; p < 0.001) and both hospital-acquired hypochloremia and hyperchloremia (OR 1.72; p = 0.004) were associated with increased in-hospital mortality, whereas hospital-acquired hypochloremia only was not (OR 0.91; p = 0.54). Conclusions: Approximately 40% of hospitalized patients developed serum chloride derangements. Hospital-acquired hyperchloremia, but not hypochloremia, was associated with increased in-hospital mortality.

scholarly journals High-Normal Serum Magnesium and Hypermagnesemia Are Associated With Increased 30-Day In-Hospital Mortality: A Retrospective Cohort Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Liao Tan ◽  
Qian Xu ◽  
Chan Li ◽  
Jie Liu ◽  
Ruizheng Shi
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Cox Regression ◽  
Serum Magnesium ◽  
Normal Serum ◽  
Magnesium Level ◽  
Serum Magnesium Level

Background: Magnesium, the fourth most abundant mineral nutrient in our body, plays a critical role in regulating ion channels and energy generation, intracardiac conduction, and myocardial contraction. In this study, we assessed the association of admission serum magnesium level with all-cause in-hospital mortality in critically ill patients with acute myocardial infarction (AMI).Methods: Clinical data were extracted from the eICU Collaborative Research Database (eICU-CRD). Only the data for the first intensive care unit (ICU) admission of each patient were used, and baseline data were extracted within 24 h after ICU admission. Logistic regression, Cox regression, and subgroup analyses were conducted to determine the relationship between admission serum magnesium level and 30-day in-hospital mortality in ICU patients with AMI.Results: A total of 9,005 eligible patients were included. In the logistic regression analysis, serum magnesium at 2.2 to ≤2.4 and &gt;2.4 mg/dl levels were both significant predictors of all-cause in-hospital mortality in AMI patients. Moreover, serum magnesium of 2.2 to ≤2.4 mg/dl showed higher risk of in-hospital mortality than magnesium of &gt;2.4 mg/dl (adjusted odds ratio, 1.63 vs. 1.39). The Cox regression analysis yielded similar results (adjusted hazard ratio, 1.36 vs. 1.25).Conclusions: High-normal serum magnesium and hypermagnesemia may be useful and easier predictors for 30-day in-hospital mortality in critically ill patients with AMI.

Hospital-acquired serum phosphate derangements and their associated in-hospital mortality

2020 ◽  
pp. postgradmedj-2020-138872
Author(s):  
Charat Thongprayoon ◽  
Wisit Cheungpasitporn ◽  
Api Chewcharat ◽  
Tananchai Petnak ◽  
Michael A Mao ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Normal Serum ◽  
Serum Phosphate ◽  
P Value ◽  
Normal Range ◽  
Referral Centre ◽  
P Values ◽  
Hospitalised Patients ◽  
Hospital Acquired ◽  
Medical Referral

BackgroundWe aimed to report the incidence of hospital-acquired hypophosphataemia and hyperphosphataemia along with their associated in-hospital mortality.MethodsWe included 15 869 adult patients hospitalised at a tertiary medical referral centre from January 2009 to December 2013, who had normal serum phosphate levels at admission and at least two serum phosphate measurements during their hospitalisation. The normal range of serum phosphate was defined as 2.5–4.2 mg/dL. In-hospital serum phosphate levels were categorised based on the occurrence of hospital-acquired hypophosphataemia and hyperphosphataemia. We analysed the association of hospital-acquired hypophosphataemia and hyperphosphataemia with in-hospital mortality using multivariable logistic regression.ResultsFifty-three per cent (n=8464) of the patients developed new serum phosphate derangements during their hospitalisation. The incidence of hospital-acquired hypophosphataemia and hyperphosphataemia was 35% and 27%, respectively. Hospital-acquired hypophosphataemia and hyperphosphataemia were associated with odds ratio (OR) of 1.56 and 2.60 for in-hospital mortality, respectively (p value<0.001 for both). Compared with patients with persistently normal in-hospital phosphate levels, patients with hospital-acquired hypophosphataemia only (OR 1.64), hospital-acquired hyperphosphataemia only (OR 2.74) and both hospital-acquired hypophosphataemia and hyperphosphataemia (ie, phosphate fluctuations; OR 4.00) were significantly associated with increased in-hospital mortality (all p values <0.001).ConclusionHospital-acquired serum phosphate derangements affect approximately half of the hospitalised patients and are associated with increased in-hospital mortality rate.

Hyperoxia is associated with adverse outcomes in the cardiac intensive care unit: insights from the Medical Information Mart for Intensive Care (MIMI-III) database

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
A.Y Lui ◽  
L Garber ◽  
M Vincent ◽  
L Celi ◽  
J Masip ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Logistic Regression ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Adverse Outcomes ◽  
Rank Test ◽  
Positive Pressure ◽  
Cardiac Intensive Care Unit ◽  
Multivariable Logistic Regression ◽  
Cardiac Intensive Care

Abstract Background Hyperoxia produces reactive oxygen species, apoptosis, and vasoconstriction, and is associated with adverse outcomes in patients with heart failure and cardiac arrest. Our aim was to evaluate the association between hyperoxia and mortality in patients (pts) receiving positive pressure ventilation (PPV) in the cardiac intensive care unit (CICU). Methods Patients admitted to our medical center CICU who received any PPV (invasive or non-invasive) from 2001 through 2012 were included. Hyperoxia was defined as time-weighted mean of PaO2 &gt;120mmHg and non-hyperoxia as PaO2 ≤120mmHg during CICU admission. Primary outcome was in-hospital mortality. Multivariable logistic regression was used to assess the association between hyperoxia and in-hospital mortality adjusted for age, female sex, Oxford Acute Severity of Illness Score, creatinine, lactate, pH, PaO2/FiO2 ratio, PCO2, PEEP, and estimated time spent on PEEP. Results Among 1493 patients, hyperoxia (median PaO2 147mmHg) during the CICU admission was observed in 702 (47.0%) pts. In-hospital mortality was 29.7% in the non-hyperoxia group and 33.9% in the hyperoxia group ((log rank test, p=0.0282, see figure). Using multivariable logistic regression, hyperoxia was independently associated with in-hospital mortality (OR 1.507, 95% CI 1.311–2.001, p=0.00508). Post-hoc analysis with PaO2 as a continuous variable was consistent with the primary analysis (OR 1.053 per 10mmHg increase in PaO2, 95% CI 1.024–1.082, p=0.0002). Conclusions In a large CICU cohort, hyperoxia was associated with increased mortality. Trials of titration of supplemental oxygen across the full spectrum of critically ill cardiac patients are warranted. Funding Acknowledgement Type of funding source: None

scholarly journals Hospital-Acquired Serum Ionized Calcium Derangements and Their Associations with In-Hospital Mortality

Medicines ◽  
2020 ◽  
Vol 7 (11) ◽  
pp. 70
Author(s):  
Charat Thongprayoon ◽  
Panupong Hansrivijit ◽  
Tananchai Petnak ◽  
Michael A. Mao ◽  
Tarun Bathini ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Reference Range ◽  
Medical Center ◽  
Normal Serum ◽  
Ionized Calcium ◽  
Normal Reference Range ◽  
Serum Ionized Calcium ◽  
Hospital Acquired ◽  
Relationship Of ◽  
The Relationship

Background: The objective of this study was to report the incidence of in-hospital serum ionized calcium derangement and its impact on mortality. Methods: We included 12,599 non-dialytic adult patients hospitalized at a tertiary medical center from January 2009 to December 2013 with normal serum ionized calcium at admission and at least 2 in-hospital serum ionized calcium values. Using serum ionized calcium of 4.60–5.40 mg/dL as the normal reference range, in-hospital serum ionized calcium levels were categorized based on the presence of hypocalcemia and hypercalcemia in hospital. We performed logistic regression to assess the relationship of in-hospital serum ionized calcium derangement with mortality. Results: Fifty-four percent of patients developed new serum ionized calcium derangements: 42% had in-hospital hypocalcemia only, 4% had in-hospital hypercalcemia only, and 8% had both in-hospital hypocalcemia and hypercalcemia. In-hospital hypocalcemia only (OR 1.28; 95% CI 1.01–1.64), in-hospital hypercalcemia only (OR 1.64; 95% CI 1.02–2.68), and both in-hospital hypocalcemia and hypercalcemia (OR 1.73; 95% CI 1.14–2.62) were all significantly associated with increased in-hospital mortality, compared with persistently normal serum ionized calcium levels. Conclusions: In-hospital serum ionized calcium derangements affect more than half of hospitalized patients and are associated with increased in-hospital mortality.

scholarly journals Infective endocarditis at a tertiary care hospital in South Korea

Heart ◽  
2020 ◽  
Vol 107 (2) ◽  
pp. 135-141 ◽  
Author(s):  
Jung Ho Kim ◽  
Hi Jae Lee ◽  
Nam Su Ku ◽  
Seung Hyun Lee ◽  
Sak Lee ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Infective Endocarditis ◽  
Mortality Rate ◽  
South Korea ◽  
Hospital Mortality ◽  
Care Hospital ◽  
Multivariable Logistic Regression ◽  
Long Term Prognosis

ObjectiveThe treatment of infective endocarditis (IE) has become more complex with the current myriad healthcare-associated factors and the regional differences in causative organisms. We aimed to investigate the overall trends, microbiological features, and outcomes of IE in South Korea.MethodsA 12-year retrospective cohort study was performed. Poisson regression was used to estimate the time trends of IE incidence and mortality rate. Risk factors for in-hospital mortality were identified with multivariable logistic regression, and model comparison was performed to evaluate the predictive performance of notable risk factors. Kaplan-Meier survival analysis and Cox regression were performed to assess long-term prognosis.ResultsWe included 419 patients with IE, the incidence of which showed an increasing trend (relative risk 1.06, p=0.005), whereas mortality demonstrated a decreasing trend (incidence rate ratio 0.93, p=0.020). The in-hospital mortality rate was 14.6%. On multivariable logistic regression analysis, aortic valve endocarditis (OR 3.18, p=0.001), IE caused by Staphylococcus aureus (OR 2.32, p=0.026), neurological complications (OR 1.98, p=0.031), high Sequential Organ Failure Assessment score (OR 1.22, p=0.023) and high Charlson Comorbidity Index (OR 1.11, p=0.019) were predictors of in-hospital mortality. Surgical intervention for IE was a protective factor against in-hospital mortality (OR 0.25, p<0.001) and was associated with improved long-term prognosis compared with medical treatment only (p<0.001).ConclusionsThe incidence of IE is increasing in South Korea. Although the mortality rate has slightly decreased, it remains high. Surgery has a protective effect with respect to both in-hospital mortality and long-term prognosis in patients with IE.

scholarly journals Risk-Predictors of Mortality in Hospitalized Patients with Thrombotic Thrombocytopenic Purpura: Nationally Representative Data from 2007-2011

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 4290-4290
Author(s):  
Ruchika Goel ◽  
Paul Ness ◽  
Clifford M. Takemoto ◽  
Karen E. King ◽  
Aaron Tobian
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Logistic Regression ◽  
Thrombotic Thrombocytopenic Purpura ◽  
Arterial Thrombosis ◽  
Hospitalized Patients ◽  
Thrombocytopenic Purpura ◽  
Plasma Infusion ◽  
Multivariable Logistic Regression

Abstract Introduction: Survivors of Thrombotic Thrombocytopenic Purpura (TTP) hospitalizations have been proposed to be at higher risk for long term poor clinical outcomes and premature death. Patients with TTP have a high risk for in-hospital morbidity and mortality as well. However, there is a paucity of data on the predictors of adverse outcomes including death in hospitalized patients with TTP. Methods: A weighted analysis of 5 years (2007-2011) using data from the Nationwide Inpatient Sample, a stratified probability sample of 20% of all hospital discharges among community hospitals in the United States (approximately 1100 hospitals/year), was performed. Hospitalizations with TTP as the primary admitting diagnoses were identified using the ICD-9 discharge code 446.6. Univariate and stepwise multivariable logistic regression analyses with elimination were used for statistical analysis. Based on results of univariate analysis, the significant variables were added in a stepwise manner in a multivariable model. All variables selected for the multivariable model were tested for interaction with a significance threshold level of p<0.2. Except for this, all hypothesis testing was two tailed and p<0.05 was considered significant. Receiver Operator Characteristics (ROC) curve was constructed using risk factors on multivariate analysis. Results: The all-cause mortality rate was 8.7% (918/10615) among admissions with primary diagnosis of TTP (0.5% pediatric, 65.9% female, 58.2% Caucasian, 27.2% African-American). Table 1 lists the risk factors by univariate analysis and includes a) factors with significantly higher odds of mortality and b) other putative factors which were not statistically significant predictors. Table 2: In stepwise multivariable logistic regression analysis: arterial thrombosis (adjOR 5.1 95%CI=1.1-31.7), acute myocardial infarction (adjOR 2.8, 95%CI=1.6-4.9), non-occurrence of either intervention: plasmapheresis or fresh frozen plasma infusion (adjOR 2.0, 95% CI=1.4-2.9) 4) requirement of platelet transfusions during hospitalization (adjOR 2.0, 95%CI= 1.3-3.2) and every ten year increase in age (OR 1.4 95%CI=1.3-1.6) were independently predictive of mortality in TTP patients (area under the curve for ROC 74%, Figure 1). Conclusion: We present a set of independent risk factors that may potentially be used in a predictive model of mortality in TTP. Early and targeted aggressive therapy based on these factors should guide the management of hospitalized patients with TTP for improved outcomes. Table 1.Unadjusted odds of in-hospital mortality.Significant predictors of mortality for TTP on univariate analysisOdds Ratio95% Confidence LimitsArterial Thrombosis 10.92.254.6AMI 3.72.16.2STROKE 4.93.07.9Platelet Transfusion 2.31.53.6Bleeding event 1.71.12.6Plasmapheresis (No vs. Yes)1.61.22.3plasmapheresis or plasma infusion (not performed)2.21.53.1Every 10 years increase in age1.51.31.6PRBC transfusion1.71.22.3Caucasian versus African American1.91.32.8Asian versus African American3.31.29.1V ariables not significant predictors of mortality for TTP on univariate analysis.Odds Ratio95% Confidence LimitsVenous Thrombosis/Thromboembolism1.90.84.4FEMALE versus male gender1.00.71.4Hypertension Yes vs. no0.90.61.2Diabetes Yes vs. no0.90.61.4Chronic Kidney Disease Yes vs. No1.40.92.2End Stage Renal Disease Yes vs. No0.90.41.9Overweight/Obese Yes vs. No0.70.41.5Variables meeting criteria for inclusion in multiple logistic regression model are in boldface type. Table 2. Multivariable Predictors for In Hospital Mortality in patients with primary diagnosis of TTP Adjusted Odds Ratio 95% Confidence Limits Arterial Thrombosis 6.0 1.2 30.5 Acute myocardial infarction 2.8 1.6 4.8 No Plasmapheresis/Plasma infusion 2.0 1.4 2.9 Platelet Transfusion 2.1 1.4 3.2 Age (per 10 year higher) 1.4 1.3 1.6 Female versus Male 1.2 0.8 1.7 TTP = Thrombotic Thrombocytopenic Purpura Step 0: Using arterial thrombosis Figure 1: Receiver- Operator-Characteristic Curve (ROC) overlay curve for the stepwise multivariable logistic regression risk prediction showing incremental AUC with addition of each risk factor for hospital patients with TTP. Figure 1:. Receiver- Operator-Characteristic Curve (ROC) overlay curve for the stepwise multivariable logistic regression risk prediction showing incremental AUC with addition of each risk factor for hospital patients with TTP. Step 1: Adding acute myocardial infarction Step 2: Adding plasmapheresis /fresh frozen plasma infusion Step 3: Adding platelet transfusions Final model: Adding every ten year increase in age. Disclosures Ness: Terumo BCT: Consultancy.

scholarly journals Higher Frequency of Hospital-Acquired Infections but Similar In-Hospital Mortality Among Admissions With Alcoholic Hepatitis at Academic vs. Non-academic Centers

2020 ◽  
Vol 11 ◽  
Author(s):  
Muhammad Waleed ◽  
Mohamed A. Abdallah ◽  
Yong-Fang Kuo ◽  
Juan P. Arab ◽  
Robert Wong ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Liver Disease ◽  
Hospital Mortality ◽  
Alcoholic Hepatitis ◽  
Academic Status ◽  
Hospital Acquired Infections ◽  
Academic Center ◽  
Hospital Acquired ◽  
The Impact ◽  
Total Charges

BackgroundAlcoholic hepatitis (AH) is a unique syndrome characterized by high short-term mortality. The impact of the academic status of a hospital (urban and teaching) on outcomes in AH is unknown.MethodsNational Inpatient Sample dataset (2006–2014) on AH admissions stratified to academic center (AC) or non-academic center (NAC) and analyzed for in-hospital mortality (IHM), hospital resource use, length of stay in days (d), and total charges (TC) in United States dollars (USD). Admission year was stratified to 2006–2008 (TMI), 2009–2011 (TM2), and 2012–2014 (TM3).ResultsOf 62,136 AH admissions, the proportion at AC increased from 46% in TM1 to 57% in TM3, Armitage trend, p &lt; 0.001. On logistic regression, TM3, younger age, black race, Medicaid and private insurance, and development of acute on chronic liver failure (ACLF) were associated with admission to an AC. Of 53,264 admissions propensity score matched for demographics, pay status, and disease severity, admissions to AC vs. NAC (26,622 each) were more likely to have liver disease complications (esophageal varices, ascites, and hepatic encephalopathy) and hospital-acquired infections (HAI), especially Clostridioides difficile and ventilator-associated pneumonia. Admissions to AC were more likely transfers from outside hospital (1.6% vs. 1.3%) and seen by palliative care (4.8% vs. 3.3%), p &lt; 0.001. Use of endoscopy, dialysis, and mechanical ventilation were similar. With similar IHM comparing AC vs. NAC (7.7% vs. 7.8%, p = 0.93), average LOS and number of procedures were higher at AC (7.7 vs. 7.1 d and 2.3 vs. 1.9, respectively, p &lt; 0.001) without difference on total charges ($52,821 vs. $52,067 USD, p = 0.28). On multivariable logistic regression model after controlling for demographics, ACLF grade, and calendar year, IHM was similar irrespective of academic status of the hospital, HR (95% CI): 1.01 (0.93–1.08, p = 0.70). IHM decreased over time, with ACLF as strongest predictor. A total of 63 and 22% were discharged to home and skilled nursing facility, respectively, without differences on academic status of the hospital.ConclusionAdmissions with AH to AC compared to NAC have higher frequency of liver disease complications and HAI, with longer duration of hospitalization. Prospective studies are needed to reduce HAI among hospitalized patients with AH.

scholarly journals Real-World Impact of Retrievable Stents for Acute Ischemic Stroke on Disability Utilizing the National Inpatient Sample

2018 ◽  
Vol 8 (1) ◽  
pp. 60-68 ◽  
Author(s):  
Anit Behera ◽  
Eric Adjei Boakye ◽  
Jahnavi Trivedi ◽  
Eric Armbrecht ◽  
Amer Alshekhlee ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Hospital Mortality ◽  
Acute Ischemic Stroke ◽  
Real World ◽  
Severe Disability ◽  
National Inpatient Sample ◽  
Multivariable Logistic Regression ◽  
Fda Approval ◽  
The Impact

Purpose: We assess the impact of retrievable stent (RS) compared to first-generation devices on in-hospital mortality and disability in patients with acute ischemic stroke (AIS). Methods: Using the National Inpatient Sample, data were obtained for patients with a primary diagnosis of AIS who underwent mechanical thrombectomy (MT) and were admitted to US hospitals between 2010 and 2014. Two time periods were compared: 2010–2012 (pre-RS Food and Drug Administration [FDA] approval) and 2013–2014 (post-RS FDA approval). Disability level was used to classify outcomes as minimal disability, moderate to severe disability, or in-hospital mortality. Weighted, multivariable logistic regression was used to assess the association between MT device type and disability. Results: A total of 2,443,713 weighted patients admitted with AIS were identified; 148,923 (4.9%) of these received intravenous tissue plasminogen activator; and 23,719 (0.8%) underwent MT. In multivariable logistic regression analysis, the odds of in-hospital mortality decreased (OR 0.69, 95% CI 0.59–0.82) in the post-RS time-period compared with pre-RS time. The odds of moderate-to-severe disability decreased (OR 0.88, 95% CI 0.73–1.06) compared with minimal disability. In-hospital mortality rates decreased successively over the 4 years in the MT-treated patients (p < 0.001). Conclusions: The FDA approval of RS technology after 2012 was associated with decreased in-hospital mortality when compared with the 3-year interval prior. These findings provide an indication that the RCT data on the efficacy of RS technology are translating into improved real-world outcomes.

scholarly journals Application of The Sepsis-3 Consensus Criteria in a Geriatric Acute Care Unit: A Prospective Study

2019 ◽  
Vol 8 (3) ◽  
pp. 359 ◽  
Author(s):  
Davide Bastoni ◽  
Andrea Ticinesi ◽  
Fulvio Lauretani ◽  
Simone Calamai ◽  
Maria Catalano ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Hospital Mortality ◽  
Acute Care ◽  
Logistic Regression Analysis ◽  
Adverse Outcomes ◽  
Multivariable Logistic Regression Analysis ◽  
Predictive Capacity ◽  
Multivariable Logistic Regression ◽  
Mortality Difference

The prognostic value of quick Sepsis-related Organ Failure Assessment (qSOFA) score in geriatric patients is uncertain. We aimed to compare qSOFA vs. Systemic Inflammatory Response Syndrome (SIRS) criteria for mortality prediction in older multimorbid subjects, admitted for suspected sepsis in a geriatric ward. We prospectively enrolled 272 patients (aged 83.7 ± 7.4). At admission, qSOFA and SIRS scores were calculated. Mortality was assessed during hospital stay and three months after discharge. The predictive capacity of qSOFA and SIRS was assessed by calculating the Area Under the Receiver Operating Characteristic Curve (AUROC), through pairwise AUROC comparison, and multivariable logistic regression analysis. Both qSOFA and SIRS exhibited a poor prognostic performance (AUROCs 0.676, 95% CI 0.609–0.738, and 0.626, 95% CI 0.558–0.691 for in-hospital mortality; 0.684, 95% CI 0.614–0.748, and 0.596, 95% CI 0.558–0.691 for pooled three-month mortality, respectively). The predictive capacity of qSOFA showed no difference to that of SIRS for in-hospital mortality (difference between AUROCs 0.05, 95% CI −0.05 to 0.14, p = 0.31), but was superior for pooled three-month mortality (difference between AUROCs 0.09, 95% CI 0.01–0.17, p = 0.029). Multivariable logistic regression analysis, accounting for possible confounders, including frailty, showed that both scores were not associated with in-hospital mortality, although qSOFA, unlike SIRS, was associated with pooled three-month mortality. In conclusion, neither qSOFA nor SIRS at admission were strong predictors of mortality in a geriatric acute-care setting. Traditional geriatric measures of frailty may be more useful for predicting adverse outcomes in this setting.

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