Comprehensive Multimorbidity Patterns in Older Patients Are Associated with Quality Indicators of Medication—MoPIM Cohort Study

Lleal, Marina; Baré, Marisa; Ortonobes, Sara; Sevilla-Sánchez, Daniel; Jordana, R.; Herranz, Susana; Gorgas, María Queralt; Espaulella-Ferrer, Mariona; Arellano, Marta; Antonio, Marta de; Nazco, Gloria Julia; Hernández-Luis, Rubén

doi:10.3390/ijerph192315902

Cited by 3 publications

(2 citation statements)

References 57 publications

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“…Thus, in recent years, evidence has been accumulating in regards to the existence of such comprehensive multimorbidity patterns [13][14][15][16][17][18]. In fact, several patterns have already been associated with outcomes such as lower function, higher presence of adverse drug reactions, higher healthcare utilisation, poor prognosis or higher mortality [19][20][21][22][23][24]. Consequently, identifying multimorbidity patterns might aid in the development of new strategies and guidelines focusing on the most appropriate actions according to each patient profile.…”

Section: Introductionmentioning

confidence: 99%

Trajectories of chronic multimorbidity patterns in older patients: MTOP study

Lleal,

Baré,

Herranz

et al. 2024

BMC Geriatr

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Background Multimorbidity is associated with negative results and poses difficulties in clinical management. New methodological approaches are emerging based on the hypothesis that chronic conditions are non-randomly associated forming multimorbidity patterns. However, there are few longitudinal studies of these patterns, which could allow for better preventive strategies and healthcare planning. The objective of the MTOP (Multimorbidity Trajectories in Older Patients) study is to identify patterns of chronic multimorbidity in a cohort of older patients and their progression and trajectories in the previous 10 years. Methods A retrospective, observational study with a cohort of 3988 patients aged > 65 was conducted, including suspected and confirmed COVID-19 patients in the reference area of Parc Taulí University Hospital. Real-world data on socio-demographic and diagnostic variables were retrieved. Multimorbidity patterns of chronic conditions were identified with fuzzy c-means cluster analysis. Trajectories of each patient were established along three time points (baseline, 5 years before, 10 years before). Descriptive statistics were performed together with a stratification by sex and age group. Results 3988 patients aged over 65 were included (58.9% females). Patients with ≥ 2 chronic conditions changed from 73.6 to 98.3% in the 10-year range of the study. Six clusters of chronic multimorbidity were identified 10 years before baseline, whereas five clusters were identified at both 5 years before and at baseline. Three clusters were consistently identified in all time points (Metabolic and vascular disease, Musculoskeletal and chronic pain syndrome, Unspecific); three clusters were only present at the earliest time point (Male-predominant diseases, Minor conditions and sensory impairment, Lipid metabolism disorders) and two clusters emerged 5 years before baseline and remained (Heart diseases and Neurocognitive). Sex and age stratification showed different distribution in cluster prevalence and trajectories. Conclusions In a cohort of older patients, we were able to identify multimorbidity patterns of chronic conditions and describe their individual trajectories in the previous 10 years. Our results suggest that taking these trajectories into consideration might improve decisions in clinical management and healthcare planning. Trial registration number NCT05717309.

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Section: Introductionmentioning

confidence: 99%

Trajectories of chronic multimorbidity patterns in older patients: MTOP study

Lleal,

Baré,

Herranz

et al. 2024

BMC Geriatr

View full text Add to dashboard Cite

show abstract

“…Remarkably, new strategies that more accurately reflect the complex, non-random association of CC in a patient-centred point of view are emerging, such as soft (or fuzzy) clustering analysis [23][24][25]. This technique has already provided relevant results in previous studies, so that several relationships between MM patterns and clinically relevant outcomes such as disability, adverse drug reactions, hospitalization, or mortality have been identified [26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Multimorbidity patterns in COVID-19 patients and their relationship with infection severity: MRisk-COVID study

Lleal,

Corral-Vazquez,

Baré

et al. 2023

PLoS ONE

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Background Several chronic conditions have been identified as risk factors for severe COVID-19 infection, yet the implications of multimorbidity need to be explored. The objective of this study was to establish multimorbidity clusters from a cohort of COVID-19 patients and assess their relationship with infection severity/mortality. Methods The MRisk-COVID Big Data study included 14 286 COVID-19 patients of the first wave in a Spanish region. The cohort was stratified by age and sex. Multimorbid individuals were subjected to a fuzzy c-means cluster analysis in order to identify multimorbidity clusters within each stratum. Bivariate analyses were performed to assess the relationship between severity/mortality and age, sex, and multimorbidity clusters. Results Severe infection was reported in 9.5% (95% CI: 9.0–9.9) of the patients, and death occurred in 3.9% (95% CI: 3.6–4.2). We identified multimorbidity clusters related to severity/mortality in most age groups from 21 to 65 years. In males, the cluster with highest percentage of severity/mortality was Heart-liver-gastrointestinal (81–90 years, 34.1% severity, 29.5% mortality). In females, the clusters with the highest percentage of severity/mortality were Diabetes-cardiovascular (81–95 years, 22.5% severity) and Psychogeriatric (81–95 years, 16.0% mortality). Conclusion This study characterized several multimorbidity clusters in COVID-19 patients based on sex and age, some of which were found to be associated with higher rates of infection severity/mortality, particularly in younger individuals. Further research is encouraged to ascertain the role of specific multimorbidity patterns on infection prognosis and identify the most vulnerable morbidity profiles in the community. Trial registration NCT04981249. Registered 4 August 2021 (retrospectively registered).

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Simultaneous Pharmacokinetic Evaluation of Pantoprazole and Vitamin B Complex for Assessing Drug–Drug Interactions in Healthy Bangladeshi Adults by a Newly Developed and Validated HPLC Method

2023

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The present study has been designed to evaluate the impact of the co-administration of pantoprazole (PNT) with vitamin B (VTB) complex (VTB comprising VTB1, VTB6, and VTB12 in this study) on pharmacokinetic behavior. In this study, HPLC-based sensitive and efficient methods for simultaneous determination in human plasma were developed per US-FDA bioanalytical standards. The pharmacokinetic parameters of PNT, VTB1, VTB6, and VTB12 were also evaluated when the medicines were administered alone and co-administered. Following linearity, it was observed that the plasma PNT, VTB1, VTB6, and VTB12 retention times were 6.8 ± 0.2, 2.7 ± 0.1, 5.5 ± 0.2, and 3.8 ± 0.1 min, respectively, over the range of 1−100 μg/mL. For all analytes at the lower limit of quantification and all other values, intra-assay and inter-assay bias were within 15% and 13.5%, respectively. They barely interacted when PNT and VTB samples were evaluated in physical combinations through in vitro tests. Moreover, in the pharmacokinetics study, treatment with VTB did not significantly alter the pharmacokinetic characteristics of PNT. Therefore, the current work’s results might help assess drug–drug interactions that may be applied to bioequivalence studies and therapeutic drug monitoring.

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Comprehensive Multimorbidity Patterns in Older Patients Are Associated with Quality Indicators of Medication—MoPIM Cohort Study

Cited by 3 publications

References 57 publications

Trajectories of chronic multimorbidity patterns in older patients: MTOP study

Trajectories of chronic multimorbidity patterns in older patients: MTOP study

Multimorbidity patterns in COVID-19 patients and their relationship with infection severity: MRisk-COVID study

Simultaneous Pharmacokinetic Evaluation of Pantoprazole and Vitamin B Complex for Assessing Drug–Drug Interactions in Healthy Bangladeshi Adults by a Newly Developed and Validated HPLC Method

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