Bacteremic sepsis leads to higher mortality when adjusting for confounders with propensity score matching.
Ontology highlight
ABSTRACT:
SUBMITTER: Mellhammar L
PROVIDER: S-EPMC7998031 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Propensity score matching is a common tool for adjusting for observed confounding in observational studies, but is known to have limitations in the presence of unmeasured confounding. In many settings, researchers are confronted with spatially-indexed data where the relative locations of the observational units may serve as a useful proxy for unmeasured confounding that varies according to a spatial pattern. We develop a new method, termed distance adjusted propensity score matching (DAPSm) that incorporates information on units' spatial proximity into a propensity score matching procedure. We show that DAPSm can adjust for both observed and some forms of unobserved confounding and evaluate its performance relative to several other reasonable alternatives for incorporating spatial information into propensity score adjustment. The method is motivated by and applied to a comparative effectiveness investigation of power plant emission reduction technologies designed to reduce population exposure to ambient ozone pollution. Ultimately, DAPSm provides a framework for augmenting a "standard" propensity score analysis with information on spatial proximity and provides a transparent and principled way to assess the relative trade-offs of prioritizing observed confounding adjustment versus spatial proximity adjustment.
| S-EPMC6409420 | biostudies-literature
Project description:BackgroundFluid resuscitation is necessary to correct the sepsis-induced hypoperfusion, which is contradictory to the treatment of heart failure. This study explored the association between fluid balance (FB) of the first 24 h after ICU admission and mortality in critically ill patients with heart failure and sepsis.MethodsData were extracted from the Medical Information Mart for Intensive Care database. The locally weighted scatterplot smoothing (Lowess) method was used to demonstrate the relationship between FB and in-hospital mortality. Groups were divided into high FB (≥ 55.85 ml/kg) and low FB (< 55.85 ml/kg) according to the cut-off value of FB using Receiver operating characteristic analysis and Youden index method. The primary outcome was in-hospital mortality. Subgroup analyses, multivariable logistic regression analyses, and Kaplan-Meier curves were used to detect the association and survival difference between groups. Inverse probability treatment weighting (IPTW) and propensity score matching (PSM) were performed to minimize the bias of confounding factors and facilitate the comparability between groups.ResultsA total of 936 patients were included. The Lowess curve showed an approximate positive linear relationship for FB and in-hospital mortality. In the multivariable logistic regression adjusted model, high FB showed strong associations with in-hospital mortality (OR 2.53, 95% CI 1.60-3.99, p < 0.001) as compared to the low FB group. In IPTW and PSM models, high FB consistently showed higher in-hospital mortality (IPTW model: OR 1.94, 95% CI 1.52-2.49, p < 0.001; PSM model: OR 2.93, 95% CI 1.75-4.90, p < 0.001) and 30-day mortality (IPTW model: OR 1.65, 95% CI 1.29-2.10, p < 0.001; PSM model: OR 2.50, 95% CI 1.51-4.15, p < 0.001), compared with the low FB group.ConclusionFor critically ill patients with heart failure and sepsis, high FB within the first 24 h after ICU admission could serve as an independent risk factor for in-hospital mortality and 30-day mortality. The avoidance of fluid overload exerts important effects on reducing mortality in such patients.
| S-EPMC9587660 | biostudies-literature
Project description:BackgroundThe diagnostic process is a key element of medicine but it is complex and prone to errors. Infectious diseases are one of the three categories of diseases in which diagnostic errors can be most harmful to patients. In this study we aimed to estimate the effect of initial misdiagnosis of the source of infection in patients with bacteraemia on 14 day mortality using propensity score methods to adjust for confounding.MethodsData from a previously described longitudinal cohort of patients diagnosed with monobacterial bloodstream infection (BSI) at the Leiden University Medical Centre (LUMC) between 2013 and 2015 were used. Propensity score matching and inversed probability of treatment weighting (IPTW) were applied to correct for confounding. The average treatment effect on the treated (ATT), which in this study was the average effect of initial misdiagnosis on the misdiagnosed (AEMM), was estimated. Methodological issues that were encountered when applying propensity score methods were addressed by performing additional sensitivity analyses. Sensitivity analyses consisted of varying caliper in propensity score matching and using different truncated weights in inversed probability of treatment weighting.ResultsData of 887 patients were included in the study. Propensity scores ranged between 0.015 and 0.999 and 80 patients (9.9%) had a propensity score > 0.95. In the matched analyses, 35 of the 171 misdiagnosed patients died within 14 days (20.5%), versus 10 of the 171 correctly diagnosed patients (5.8%), yielding a difference of 14.6% (7.6%; 21.6%). In the total group of patients, the observed percentage of patients with an incorrect initial diagnosis that died within 14 days was 19.8% while propensity score reweighting estimated that their probability of dying would have been 6.5%, if they had been correctly diagnosed (difference 13.3% (95% CI 6.9%;19.6%)). After adjustment for all variables that showed disbalance in the propensity score a difference of 13.7% (7.4%; 19.9%) was estimated. Sensitivity analyses yielded similar results. However, performing weighted analyses without truncation yielded unstable results.ConclusionThus, we observed a substantial increase of 14 day mortality in initially misdiagnosed patients. Furthermore, several patients received propensity scores extremely close to one and were almost sure to be initially misdiagnosed.
| S-EPMC11007998 | biostudies-literature
Project description:BackgroundAlbumin may be beneficial in patients with septic shock but availability is limited and cost is high. The objective of the present study was to investigate if the use of dextran-70 in addition to albumin and crystalloids influences organ failure or mortality in patients with severe sepsis or septic shock.MethodsPatients with severe sepsis or septic shock (n = 778) admitted to a university hospital intensive care unit (ICU) between 2007 and 2015 that received dextran-70 during resuscitation were propensity score matched to controls at a 1 to 1 ratio. Outcomes were highest acute kidney injury network (AKIN) score the first 10 days in the ICU, use of renal replacement therapy, days alive and free of organ support the first 28 days after admission to ICU, mortality and events of severe bleeding. Outcomes were assessed using paired hypothesis testing.ResultsPropensity score matching resulted in two groups of patients with 245 patients in each group. The dextran group received a median volume of 1483 ml (interquartile range, 1000-2000 ml) of dextran-70 during the ICU stay. Highest AKIN score did not differ between the control- and dextran groups (1 (0-3) versus 2 (0-3), p = 0.06). Incidence of renal replacement therapy in the control- and dextran groups was similar (19% versus 22%, p = 0.42, absolute risk reduction -2.9% [95% CI: -9.9 to 4.2]). Days alive and free of renal replacement, vasopressors and mechanical ventilation did not differ between the control- and dextran groups. The 180-day mortality was 50.2% in the control group and 41.6% in the dextran group (p = 0.046, absolute risk reduction 8.6% [-0.2 to 17.4]). Fraction of patients experiencing a severe bleeding in the first 10 days in the ICU did not differ between the control and dextran groups (14% versus 18%, p = 0.21).DiscussionThere is a paucity of high quality data regarding effects of dextran solutions on outcome in sepsis. In the present study, propensity score matching was used in attempt to reduce bias.ConclusionNo evidence to support a detrimental effect of dextran-70 on mortality or on organ failures in patients with severe sepsis or septic shock could be detected.
| S-EPMC5501466 | biostudies-literature
Project description:Background and purposePatients with dementia are particularly vulnerable to coronavirus disease 2019 (COVID-19) because they tend to be older and often have concomitant diseases. Previous studies have investigated the impact of dementia on COVID-19 outcomes, but the evidence is not robust for Asian populations. We aimed to determine the relationship between dementia and COVID-19 outcomes using data from a large-scale nationwide public database.MethodsData on patients with COVID-19 who were released from quarantine between January 1, 2020 and April 30, 2020, published by the Korea Disease Control and Prevention Agency, were divided into two groups based on the dementia status. Propensity-score matching was used to adjust for multiple confounders between the dementia and no-dementia groups. Binary, ordinal logistic regression and multivariate Cox proportional-hazards models were used to compare mortality, quarantine duration, and clinical deterioration according to the dementia status in the two groups.ResultsMales and older individuals (age ≥60 years) constituted 41.5% and 32.9%, respectively, of the 5,299 patients. The prevalence of dementia was 4.2%, and 4.5% of the participants died during hospitalization. In multivariate analysis, dementia was significantly associated with increased mortality (odds ratio [OR]=2.80, 95% confidence interval [CI]=1.60-4.60), longer duration of quarantine (hazard ratio=1.69, 95% CI=1.16-2.45), and larger shift to a worse clinical severity (common OR=1.74, 95% CI=1.18-2.61).ConclusionsAfter adjusting for important clinical predictors, dementia was associated with increased in-hospital mortality, duration of quarantine, and clinical deterioration during hospitalization in COVID-19 patients.
| S-EPMC8762493 | biostudies-literature
Project description:Cluster randomization trials with relatively few clusters have been widely used in recent years for evaluation of health-care strategies. On average, randomized treatment assignment achieves balance in both known and unknown confounding factors between treatment groups, however, in practice investigators can only introduce a small amount of stratification and cannot balance on all the important variables simultaneously. The limitation arises especially when there are many confounding variables in small studies. Such is the case in the INSTINCT trial designed to investigate the effectiveness of an education program in enhancing the tPA use in stroke patients. In this article, we introduce a new randomization design, the balance match weighted (BMW) design, which applies the optimal matching with constraints technique to a prospective randomized design and aims to minimize the mean squared error (MSE) of the treatment effect estimator. A simulation study shows that, under various confounding scenarios, the BMW design can yield substantial reductions in the MSE for the treatment effect estimator compared to a completely randomized or matched-pair design. The BMW design is also compared with a model-based approach adjusting for the estimated propensity score and Robins-Mark-Newey E-estimation procedure in terms of efficiency and robustness of the treatment effect estimator. These investigations suggest that the BMW design is more robust and usually, although not always, more efficient than either of the approaches. The design is also seen to be robust against heterogeneous error. We illustrate these methods in proposing a design for the INSTINCT trial.
| S-EPMC3407414 | biostudies-literature
Project description:Background Despite the extensive use of arterial catheterization (AC), clinical effectiveness of AC to alter the outcomes among patients with sepsis and septic shock has not been evaluated. The purpose of this study is to examine the association between the use of AC and in-hospital mortality in septic patients. Methods Adult patients with sepsis from Medical Information Mart for Intensive Care database were screened to conduct this retrospective observational study. Propensity score matching (PSM) was employed to estimate the relationship between arterial catheterization (AC) and in-hospital mortality. Multivariable logistic regression and inverse probability of treatment weighing (IPTW) were used to validate our findings. Results A total of 14,509 septic patients without shock and 4,078 septic shock patients were identified. 3,489 pairs in sepsis patients without shock and 589 pairs in septic shock patients were yielded respectively after PSM. For patients in the sepsis without shock group, AC placement was associated with increased in-hospital mortality (OR, 1.34; 95% CI, 1.17–1.54; p < 0.001). In the septic shock group, there was no significant difference in hospital mortality between AC group and non-AC group. The results of logistic regression and propensity score IPTW model support our findings. Conclusions In hemodynamically stable septic patients, AC is independently associated with higher in-hospital mortality, while in patients with septic shock, AC was not associated with improvements in hospital mortality. Supplementary Information The online version contains supplementary material available at 10.1186/s12871-022-01722-5.
| S-EPMC9178844 | biostudies-literature
Project description:BackgroundPioglitazone use via the PPARγ agonist in sepsis patients is inconclusive. It was based on a great number of animal studies. However, except for information from animal studies, there are merely any data of human studies for reference.MethodsThis study was conducted by a unique database including 1.6 million diabetic patients. From 1999 to 2013, a total of 145,327 type 2 diabetic patients, first admitted for sepsis, were enrolled. Propensity score matching was conducted in a 1 : 5 ratio between pioglitazone users and nonusers. Multivariate logistic regression was conducted to evaluate the adjusted odds ratios (aORs) of hospital mortality in pioglitazone users. Further stratification analysis was done and Kaplan-Meier plot was used.ResultsA total of 9,310 sepsis pioglitazone users (defined as "ever" use of pioglitazone in any dose within 3 months prior to the first admission for sepsis) and 46,550 matched nonusers were retrieved, respectively. In the multivariate logistic regression model, the cohort of pioglitazone users (9,310) had a decreased aOR of 0.95 (95% CI, 0.89-1.02) of sepsis mortality. Further stratification analysis demonstrated that "chronic pioglitazone users" (defined as "at least" 4-week drug use within 3 months) (3,399) were more associated with significant aOR of 0.80 (95% CI, 0.72-0.89) in reducing sepsis mortality.ConclusionsThis first human cohort study demonstrated the potential protective effect of chronic pioglitazone use in type 2 diabetic sepsis patients.
| S-EPMC8363455 | biostudies-literature
Project description:A helmet is critical for preventing head injuries during motorcycle accidents. However, South Korean motorcyclists have a lower prevalence of wearing a helmet, compared to developed countries. Therefore, we aimed to evaluate whether helmet wearing was associated with the clinical outcomes in Korean motorcycle accidents. Data were obtained from the Emergency Department-based Injury In-depth Surveillance database 2011-2015. We considered the patients had experienced a motorcycle accident and were only diagnosed with a craniocerebral trauma (CCT). The primary outcome was mortality and the secondary outcomes were the severity and hospitalization duration. The patients were separated whether they were wearing a helmet and the outcomes were compared using multivariate logistic regression after propensity score matching (PSM). Among 1,254,250 patients in the database, 2,549 patients were included. After PSM, 1,016 patients in each group were matched. The univariate analyses revealed that helmet wearing was associated with lesser severity (P < 0.001) and shorter hospitalization (P < 0.001). The regression analysis revealed that mortality was also lower in a helmet-wearing group (odds ratio: 0.34, 95% confidence interval: 0.21-0.56). In conclusion, wearing a helmet may reduce the mortality from a CCT after a motorcycle accident and associated with lesser severity and shorter hospitalization.
| S-EPMC6957151 | biostudies-literature
Project description:Small area ecological studies are commonly used in epidemiology to assess the impact of area level risk factors on health outcomes when data are only available in an aggregated form. However, the resulting estimates are often biased due to unmeasured confounders, which typically are not available from the standard administrative registries used for these studies. Extra information on confounders can be provided through external data sets such as surveys or cohorts, where the data are available at the individual level rather than at the area level; however, such data typically lack the geographical coverage of administrative registries. We develop a framework of analysis which combines ecological and individual level data from different sources to provide an adjusted estimate of area level risk factors which is less biased. Our method (i) summarizes all available individual level confounders into an area level scalar variable, which we call ecological propensity score (EPS), (ii) implements a hierarchical structured approach to impute the values of EPS whenever they are missing, and (iii) includes the estimated and imputed EPS into the ecological regression linking the risk factors to the health outcome. Through a simulation study, we show that integrating individual level data into small area analyses via EPS is a promising method to reduce the bias intrinsic in ecological studies due to unmeasured confounders; we also apply the method to a real case study to evaluate the effect of air pollution on coronary heart disease hospital admissions in Greater London.
| S-EPMC6230467 | biostudies-literature