Correlation between microbiological isolates, frailty indices, delirium, and clinical outcomes in a cohort of septic geriatric patients

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Whilst management has traditionally focused on pathogen identification, baseline frailty and geriatric syndromes such as delirium may be more accurate predictors of mortality. We evaluated whether biochemical parameters (CRP, procalcitonin, N/L ratio, lactate), severity scores (SOFA, q-SOFA), and multidimensional indicators (CFS, Charlson Index, delirium) outperform microbiological positivity alone as prognostic tools. Methods We conducted a retrospective study of 195 patients (aged ≥ 65 years) consecutively admitted for sepsis to the Geriatrics Department of San Luigi University Hospital, Orbassano, in 2025. Laboratory parameters on admission and multidimensional geriatric scores after clinical stabilisation were analysed. Results The cohort (mean age 87.4 ± 6.1 years) had an in-hospital mortality rate of 22.1% and a delirium incidence of 60.5%. Microbiological positivity (52.3%, predominantly E. coli) showed no significant correlation with mortality (p > 0.05). Deceased patients had significantly higher CFS and Charlson scores (p < 0.005). The N/L ratio (p < 0.001) and lactate (p = 0.013) were more reliable predictors of poor outcome than CRP or procalcitonin. SOFA score showed the strongest association with mortality (mean 6.8 vs. 2.4 in survivors; p < 0.001). Delirium correlated with both mortality (r = 0.33) and frailty (r = 0.50). Klebsiella pneumoniae isolation was associated with significantly prolonged hospital stay (29.4 vs. 19.3 days; p < 0.001). Conclusion Prognosis in septic geriatric patients is determined by a ‘critical triangle’ of acute severity (SOFA), baseline frailty (CFS), and cognitive status (delirium), rather than pathogen identification alone. The N/L ratio emerges as the biochemical marker of choice over classic inflammatory indices. Integrated multidimensional geriatric assessment is essential for accurate risk stratification and personalised care. Geriatric sepsis Frailty Delirium SOFA score Neutrophil/Lymphocyte ratio In-hospital mortality Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Sepsis represents one of the most critical challenges for global public health, with a predominant epidemiological impact on patients over 70 years of age [ 1 ]. Defined as a potentially lethal organ dysfunction resulting from a dysregulated host response to infection, sepsis is clinically identified by a SOFA (Sequential Organ Failure Assessment) score of ≥ 2 [ 2 ]. Demographic ageing, and the phenomenon of ‘inflammaging’ (a chronic low-grade inflammatory state), drastically complicates the diagnostic picture, requiring a more profound understanding of the predisposing factors in geriatric patients [ 3 ]. Sepsis in elderly populations does not always manifest with the classic systemic signs (fever, tachycardia) [ 4 ]. Immunosenescence alters the neutrophil response, which often maintains a preserved numerical count whilst undergoing functional impairment in chemotaxis and phagocytosis [ 5 ]. In this scenario, delirium - an acute, transient state characterised by confusion and significantly reduced awareness of the surroundings - emerges as a key manifestation. Often the only initial symptom, delirium is frequently underdiagnosed, particularly in its hypoactive form. This cognitive vulnerability is not merely a complication, but an indicator of depleted functional reserve and a powerful predictor of mortality [ 6 ]. Mortality in frail patients follows a ‘trimodal’ trajectory. In addition to early and late peaks, a third peak emerges between 60 and 90 days post-event, influenced by comorbidities, antibiotic resistance, and social isolation [ 7 ]. Risk assessment, therefore, cannot be based solely on chronological age but must integrate disease severity with the patient’s potential for functional recovery [ 4 ]. Our study aims to investigate the relationship between microbiological isolates (blood and urine cultures), frailty indices (Clinical Frailty Scale and Charlson Comorbidity Index), the presence of delirium, and clinical outcomes (mortality and length of stay) in a cohort of geriatric patients hospitalised for sepsis. The primary objective is to determine whether clinical and laboratory parameters (CRP, procalcitonin, neutrophils, lymphocytes, N/L ratio, lactate, q-SOFA and SOFA scores), together with multidimensional geriatric indicators, are more accurate predictors of clinical prognosis than microbiological positivity alone. Furthermore, the study evaluates the specific impact of delirium and baseline frailty on mortality, testing the hypothesis that functional and cognitive impairment are more significant prognostic drivers than pathogen virulence. Materials and Methods The study retrospectively analysed all patients admitted to the Geriatric Unit of San Luigi University Hospital in Orbassano who presented with sepsis, identified at the time of admission or manifested during their hospital stay. Data were collected consecutively between 1 January and 31 December 2025. Prior to being transferred to the ward, all patients included in the study spent an average of 36 hours in the emergency department awaiting bed availability. The final sample consisted of 195 patients aged over 65 years, with a mean age of 87.4 ± 6.1 years (range: 69–103 years). There was a slight male predominance, with 104 men (53.3%). Consistent with a real-world clinical practice approach, all subjects were included regardless of the primary site of infectious insult, with a mean hospital stay of 21 days (range: 2–70 days) [figure 1 ]. The case series was heterogeneous and was stratified according to primary admission diagnosis: pneumonia, urinary tract infections (UTIs), exacerbated chronic obstructive pulmonary disease (COPD), non-specific sepsis, abdominal sepsis, multifocal pneumonia, soft tissue infections, and COVID-19. For each patient enrolled, blood chemistry profiles were extracted to characterise the extent of the inflammatory response and degree of organ impairment. Parameters collected and analysed included C-reactive protein (CRP), procalcitonin, absolute neutrophil and lymphocyte counts, the neutrophil/lymphocyte (N/L) ratio [ 8 ], and lactate levels. Simultaneously, q-SOFA (quick Sequential Organ Failure Assessment) and SOFA scores were calculated to stratify clinical risk and sepsis severity [ 9 ]. After stabilisation of the acute condition, each patient underwent a standardised multidimensional assessment to quantify baseline frailty status. This was conducted using the Clinical Frailty Scale (CFS) [ 10 ] and the Charlson Comorbidity Index (CCI) [ 11 ], integrating the patient’s functional reserve with data on the current infectious episode. The presence of delirium, identified both on admission and as an event arising during hospitalisation, was also actively investigated and was found in 118 patients (60.5%), representing a critical marker of cerebral vulnerability and systemic severity. To define the aetiology of the septic insult, results of microbiological investigations performed during the bacteraemic phase or on clinical suspicion were analysed. The data collected were statistically analysed to investigate correlations between biochemical variables, frailty scores, the presence of delirium, and final clinical outcomes, with the aim of verifying whether geriatric indicators and inflammatory biomarkers have greater predictive accuracy than microbiological culture positivity alone. Statistical Analysis Statistical processing and database management were performed using Python (Pandas, NumPy, and SciPy). Continuous variables were described as mean ± standard deviation (SD) and range. Categorical variables were expressed as absolute frequencies and percentages. Normality of distributions was assessed using the Shapiro–Wilk test. Given the non-parametric distribution of many biochemical parameters and the ordinal nature of clinical and frailty scores, the Mann–Whitney U test was used for continuous variables and Pearson’s chi-square test for categorical variables when comparing survivors and deceased patients. Correlations between laboratory variables (CRP, procalcitonin, neutrophils, lymphocytes, N/L ratio, and lactate), severity scores (q-SOFA and SOFA), frailty indices (CFS and CCI), and the presence of delirium were investigated using Spearman’s rank correlation coefficient (ρ). To further characterise the independent contribution of clinical predictors to in-hospital mortality, a logistic regression analysis was performed, with results expressed as odds ratios (OR) with 95% confidence intervals (95% CI). For all tests, a two-tailed p-value of < 0.05 was considered statistically significant. Results The study included 195 geriatric patients with a mean age of 87.4 ± 6.1 years. Overall in-hospital mortality was 22.1% (43 deaths), and 60.5% of patients (n = 118) presented with delirium during their hospital stay [figure 2 ]. Compared to survivors, deceased patients had a significantly higher baseline frailty status (mean CFS: 7.67 vs. 6.53; p < 0.001) and greater comorbidity burden (CCI: 10.35 vs. 9.18; p = 0.005). No statistically significant differences were observed in mean age or length of hospital stay between survivors and deceased patients. Table 1 Baseline characteristics and comparison between survivors and deceased patients. Parameter Total (n = 195) Survivors (n = 152) Deceased (n = 43) P Value Demographics Age (years) 87.3 ± 6.1 87.2 ± 5.8 87.9 ± 7.1 0.228 Male sex (%) 53.3 53.3 53.5 1.000 Geriatric & Cognitive Assessment CCI 9.4 ± 2.3 9.1 ± 2.3 10.3 ± 2.1 0.005 CFS 6.7 ± 1.5 6.5 ± 1.4 7.6 ± 1.3 < 0.001 Delirium (%) 60.5 52.0 90.7 < 0.001 Biochemical & Inflammatory Markers CRP (mg/dL) 11.2 ± 9.0 10.7 ± 8.7 12.7 ± 9.7 0.293 Procalcitonin (ng/mL) 3.5 ± 22.5 2.0 ± 8.1 8.5 ± 45.4 0.302 Neutrophils (×10³/µL) 10.8 ± 6.0 10.4 ± 6.1 12.4 ± 5.6 0.007 Lymphocytes (×10³/µL) 1.2 ± 2.2 1.3 ± 2.4 0.8 ± 0.5 < 0.001 N/L Ratio 14.8 ± 14.5 13.0 ± 13.8 20.9 ± 15.5 < 0.001 Lactate (mmol/L) 1.4 ± 1.2 1.4 ± 1.3 1.6 ± 1.0 0.013 Severity Scores q-SOFA 0.7 ± 0.7 0.6 ± 0.7 1.0 ± 0.9 0.044 SOFA 3.3 ± 2.7 2.4 ± 2.0 6.8 ± 1.9 < 0.001 Data are presented as mean ± SD or percentage (%). CCI: Charlson Comorbidity Index; CFS: Clinical Frailty Scale; CRP: C-reactive protein; N/L: Neutrophil-to-Lymphocyte ratio. Bold p-values indicate statistical significance (p < 0.05). Comparisons performed using the Mann–Whitney U test for continuous variables and Pearson’s chi-square test for categorical variables. Microbiological testing yielded a positive culture in 52.3% of the sample (102 patients). Urine culture was positive in 40.5% of cases (n = 79) and blood culture in 21.5% (n = 42); in 19 patients (9.7%), both samples were positive. The most frequently isolated pathogen at both sites was Escherichia coli (34 urinary and 16 blood isolates). No statistically significant association was found between culture positivity (blood or urine) and mortality (p > 0.05), confirming that pathogen identification, in isolation from the clinical context, was not a reliable prognostic predictor in this cohort. Comparison between the survivor and deceased groups revealed marked differences in parameters collected at admission. CRP, although higher in deceased patients (12.7 vs. 10.7 mg/dL), did not reach statistical significance (p = 0.293). Similarly, procalcitonin (PCT) levels were higher in deceased patients (8.5 vs. 2.0 ng/mL) but showed high internal variability and did not achieve significance (p = 0.302). A significant difference was observed in neutrophil count (12.4 vs. 10.4 × 10³/µL; p = 0.007), alongside a marked reduction in lymphocytes in deceased patients (0.78 vs. 1.32 × 10³/µL; p < 0.001). The N/L ratio proved to be a powerful prognostic marker, with significantly higher values in patients with a poor outcome (20.9 vs. 13.0; p < 0.001). Serum lactate levels were also significantly higher in the deceased group (1.61 vs. 1.39 mmol/L; p = 0.013). Both severity scores were significant predictors of mortality: the mean q-SOFA was 1.0 in deceased patients versus 0.69 in survivors (p = 0.044), whilst the SOFA score demonstrated the strongest association with outcome, with a mean of 6.8 in deceased patients versus 2.4 in survivors (p < 0.001) [figure 3 ] [figure 4 ]. Delirium was closely correlated with both mortality (ρ = 0.33; p < 0.001) and frailty as measured by the CFS (ρ = 0.50). A significant correlation was also identified between CFS and the severity of organ dysfunction as measured by the SOFA score. Klebsiella pneumoniae (urinary isolation) was associated with a significant prolongation of mean hospital stay (29.4 vs. 19.3 days; p < 0.001), but not with an increase in direct in-hospital mortality [figure 5 ] [figure 6 ]. Discussion The mortality observed in our sample (22.1%) is consistent with data reported for geriatric sepsis cohorts in the literature, which generally range between 20% and 45% [ 12 ]. The most notable finding, however, is the absence of a significant correlation between positive cultures (haematological or urinary) and poor outcomes. This supports an emerging trend in critical geriatrics: in very elderly patients (mean age 87 years), the virulence of the isolated pathogen appears to carry less prognostic weight than the functional reserve of the host [ 13 ]. Studies indicate that, although Gram-negative bacteria such as E. coli are prevalent, survival is dictated more by biological frailty than by circulating bacterial load [ 14 ]. The high prevalence of delirium (60.5%) and its strong association with mortality (p < 0.001) corroborate findings from recent reviews; in the elderly, delirium is not a simple neurological symptom, but a manifestation of brain organ failure in the context of a systemic inflammatory response [ 6 , 15 , 16 ]. The correlation between delirium and the CFS (ρ = 0.50) suggests that acute cognitive status directly reflects the patient’s baseline vulnerability. Studies by Inouye et al. have demonstrated that delirium dramatically increases the risk of short-term death, often representing the only ‘atypical’ sign of severe sepsis in patients in whom fever or tachycardia may be absent [ 17 ]. Our results confirm that the SOFA score is the strongest predictor of mortality (mean 6.8 in deceased patients), surpassing q-SOFA, consistent with the comparative literature indicating SOFA as the superior risk stratification tool [ 18 ]. However, the addition of CFS and CCI provides a more complete clinical picture: patients who did not survive were significantly more frail (CFS 7.67). This supports the position of Muscedere et al. and Geen et al., who argue that frailty should be systematically integrated into geriatric sepsis protocols, as SOFA alone may underestimate severity in patients with depleted functional reserve [ 19 , 20 ]. The effectiveness of the N/L ratio as a prognostic marker (p < 0.001), in contrast to CRP and procalcitonin (both non-significant), is explained by the concept of inflammaging: older patients often have elevated baseline CRP levels or blunted PCT responses [ 15 ]. The N/L ratio instead reflects the imbalance between innate immune activation (neutrophilia) and adaptive immune exhaustion (lymphopenia), a critical process in geriatric sepsis associated with worse outcomes [ 21 , 22 ]. Although E. coli was the most frequently isolated organism, the association of Klebsiella pneumoniae with prolonged hospital stay (29.4 days) highlights the management challenges posed by multidrug-resistant organisms in geriatric wards. In the literature, Klebsiella is frequently associated with multi-resistance profiles and nosocomial infections that, whilst not necessarily increasing acute mortality when adequately treated, substantially prolong hospitalisation and increase the risk of secondary complications [ 23 ]. Conclusions The management of elderly septic patients requires moving beyond a purely microbiological model. Prognosis is defined by a ‘critical triangle’: acute severity (SOFA), baseline frailty (CFS), and cognitive status (delirium). These parameters, together with the N/L ratio, offer a considerably more accurate clinical compass than pathogen identification alone. Prospective, multicentre studies are needed to validate these findings and establish integrated geriatric assessment as a standard component of sepsis risk stratification in elderly populations. Limitations Several limitations of this study warrant consideration. First, the retrospective, single-centre design limits the generalisability of our findings; the cohort reflects clinical practice at a single Italian tertiary geriatric unit, and unmeasured confounders inherent to retrospective data collection cannot be excluded. Second, whilst the CFS was applied after clinical stabilisation to reflect baseline functional status, assessment during an acute hospitalisation carries an inherent risk of acute-on-chronic misclassification, whereby frailty may be transiently overestimated in patients with reversible acute deterioration. Third, our outcome data were limited to in-hospital mortality; post-discharge outcomes, including 30-day and 90-day mortality, readmission rates, and longer-term functional trajectories, were not captured. Given the trimodal mortality trajectory described in frail septic patients, with a late peak between 60 and 90 days, this represents a significant gap in follow-up. Fourth, microbiological data were dependent on culture yield; in a cohort where only 52.3% of patients had a positive culture result, the absence of an isolated pathogen does not exclude infection and may reflect sampling limitations, prior antibiotic exposure, or fastidious organisms. Accordingly, the null finding regarding culture positivity and mortality should be interpreted cautiously rather than as definitive evidence of microbial irrelevance. Fifth, antibiotic appropriateness, defined as concordance between empirical therapy and subsequent culture sensitivities, was not systematically analysed and may represent a confounding variable in the relationship between pathogen identification and outcome. Finally, the absence of a formal delirium assessment tool (such as the Confusion Assessment Method, CAM) applied at standardised timepoints means that the reported delirium prevalence of 60.5% may reflect a composite of hyperactive, hypoactive, and mixed subtypes in proportions that cannot be disaggregated from the available data, potentially underestimating true prevalence. Prospective, multicentre studies incorporating validated delirium screening instruments and longitudinal follow-up are warranted to confirm and extend these findings. Declarations Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki. The study was submitted to the Institutional Ethics Committee of San Luigi Gonzaga University Hospital, Orbassano, Turin, Italy. As a retrospective observational study involving only fully anonymised clinical data, formal ethics committee approval was not required. All patients provided informed consent for the collection and use of their anonymised clinical data at the time of hospital admission as part of the standard clinical consent process. All data were handled and reported in fully anonymised form throughout. Consent for publication Not applicable. This study contains no individually identifiable data. Patient consent for the use of anonymised clinical data was obtained at the time of hospital admission. Availability of data and materials All data relevant to the conclusions of this study are presented within the article. No additional datasets were generated or analysed beyond those reported herein. Competing interests The authors declare that they have no competing interests. Funding No funding was received for this study. Authors’ contributions TF and LSR conceived and designed the study, led data collection and analysis, and drafted the manuscript. TF acts as guarantor of the study. All authors (TF, ADS, SO, AT, IRB, TC, GM, VR, BT, LSR, EG, JMV, SDG, DM, EB, FM, RV, RP, AM, TR, GF, GV) contributed to data acquisition, critically revised the manuscript for important intellectual content, and approved the final version for submission. All authors agree to be accountable for all aspects of the work. Acknowledgements Not applicable. Clinical trial number: not applicable. References Ibarz M, Haas LEM, Ceccato A, Artigas A. The critically ill older patient with sepsis: a narrative review. Ann Intensive Care. 2024;14(1):6. https://doi.org/10.1186/s13613-023-01233-7 Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801₁0. https://doi.org/10.1001/jama.2016.0287 Fraccalini T, Ribeiro LS, Trogolo A, Tarozzo B, Piras V, Vecchini JM, et al. 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Antibiotics. 2021;10(12):1508. https://doi.org/10.3390/antibiotics10121508 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 30 Apr, 2026 Reviewers agreed at journal 29 Apr, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviewers invited by journal 27 Apr, 2026 Editor assigned by journal 27 Apr, 2026 Editor invited by journal 17 Apr, 2026 Submission checks completed at journal 17 Apr, 2026 First submitted to journal 17 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9260844","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":632230681,"identity":"fa371986-b7ac-461f-923d-0f54ae8d080d","order_by":0,"name":"Thomas Fraccalini","email":"","orcid":"","institution":"San Luigi Gonzaga University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Fraccalini","suffix":""},{"id":632230682,"identity":"49b0fb96-9e4c-41c8-ab09-507f1760ed2b","order_by":1,"name":"Adriano Simone","email":"","orcid":"","institution":"Chief Medical Officer, San Luigi Gonzaga 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Turin","correspondingAuthor":false,"prefix":"","firstName":"Emmanuel","middleName":"","lastName":"Gialitakis","suffix":""},{"id":632230706,"identity":"0aec16c5-d6de-4443-b581-07d527b14f50","order_by":11,"name":"Julia Michelin Vecchini","email":"","orcid":"","institution":"University of Turin","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"Michelin","lastName":"Vecchini","suffix":""},{"id":632230708,"identity":"f34bf1db-0d0e-40f6-a67a-ad68a0b12445","order_by":12,"name":"Salvatore Gioia","email":"","orcid":"","institution":"Chief Medical Officer, San Luigi Gonzaga University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Salvatore","middleName":"","lastName":"Gioia","suffix":""},{"id":632230714,"identity":"ad38c07e-6e80-418a-bb4b-28934ecc4480","order_by":13,"name":"Davide Minniti","email":"","orcid":"","institution":"General Manager, San Luigi Gonzaga University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Davide","middleName":"","lastName":"Minniti","suffix":""},{"id":632230729,"identity":"3241f2b7-dada-4a8b-ba78-75dd84008562","order_by":14,"name":"Elisa Binello","email":"","orcid":"","institution":"Chief Nursing Officer, San Luigi Gonzaga University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Elisa","middleName":"","lastName":"Binello","suffix":""},{"id":632230738,"identity":"aa95076b-33b8-4a2f-b0d3-2c79ec68212c","order_by":15,"name":"Federico Mallamaci","email":"","orcid":"","institution":"Chief Nursing Officer, San Luigi Gonzaga University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Federico","middleName":"","lastName":"Mallamaci","suffix":""},{"id":632230740,"identity":"4b624cf8-9980-46ef-9ee1-19b99c4b8743","order_by":16,"name":"Roberta Vacchelli","email":"","orcid":"","institution":"Chief Nursing Officer, San Luigi Gonzaga University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Roberta","middleName":"","lastName":"Vacchelli","suffix":""},{"id":632230743,"identity":"cea8c9e2-3b3c-46db-8050-4442d702ca7a","order_by":17,"name":"Roberto Penso","email":"","orcid":"","institution":"Chief Nursing Officer, San Luigi Gonzaga University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Roberto","middleName":"","lastName":"Penso","suffix":""},{"id":632230746,"identity":"66d6f4dc-da1e-471a-bedb-704fe99e2760","order_by":18,"name":"Alessandro Maraschi","email":"","orcid":"","institution":"University College London Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Alessandro","middleName":"","lastName":"Maraschi","suffix":""},{"id":632230749,"identity":"79413084-7995-4d2e-842f-9f6f590eb0e7","order_by":19,"name":"Thomas Roberts","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYPCCAxDqQ4UNAwM7hG2ASy0PXAsbAwPjjDNpDAzMpGhh5m07TFiLPXt3AnNFxR058/ntDxh42M4n9jczMH74wXDYGKctPGc3MJ4588xY5hiPAYMEz+3EGYcZmCV7GA6b4dQikbuBsbHtcOIMNqAbDSRuJ24AOkyageGwDSEt9TPY2B8wJBicA2lh/k2MlgQJNqCHDyQcAGlhA9mC22Fnzm442HDmmeEMthyDgw0Hko1nHGZss+wxSMfpffb23o0PGyruyEswH3/4+O8/O9n+9ubDN35UWBs24NLDAI96OIOxAU+sjIJRMApGwSggBgAAOINS4NfvlPcAAAAASUVORK5CYII=","orcid":"","institution":"¹⁰ University College London Medical School, University College London","correspondingAuthor":true,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Roberts","suffix":""},{"id":632230750,"identity":"7531ecff-d655-4b39-9d85-60ba9043eaf4","order_by":20,"name":"Gianfranco Fonte","email":"","orcid":"","institution":"AOU Città della Salute e della Scienza di TorinoSSD Day Hospital and Day Service CDSS","correspondingAuthor":false,"prefix":"","firstName":"Gianfranco","middleName":"","lastName":"Fonte","suffix":""},{"id":632230756,"identity":"9b5022e7-45ad-4509-b168-1c71acb8c9c1","order_by":21,"name":"Giovanni Volpicelli","email":"","orcid":"","institution":"Università Magna Graecia di Catanzaro","correspondingAuthor":false,"prefix":"","firstName":"Giovanni","middleName":"","lastName":"Volpicelli","suffix":""}],"badges":[],"createdAt":"2026-03-29 20:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9260844/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9260844/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108632686,"identity":"7d6bb901-c054-4499-906a-c2b39cd80770","added_by":"auto","created_at":"2026-05-06 17:06:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1612104,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eCohort distribution: age, frailty, and length of hospital stay.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFrequency histograms illustrating the distribution of three key cohort characteristics. (A) Age distribution, showing a right-skewed curve with peak frequency above 85 years, consistent with an extreme longevity cohort (mean age 87.4 ± 6.1 years). (B) Clinical Frailty Scale (CFS) distribution, with most patients scoring between 6 and 8, indicating a predominantly moderately to severely frail sample. (C) Length of hospital stay, showing a mean of approximately 21 days with a right-skewed tail reflecting cases of prolonged hospitalisation, several of which were associated with Klebsiella pneumoniae isolation. CFS: Clinical Frailty Scale.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9260844/v1/f2f39644be4dd660773858b6.png"},{"id":108805588,"identity":"72697d3f-94ff-4cf9-9e33-d8195f8cc430","added_by":"auto","created_at":"2026-05-08 15:26:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":14323,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDelirium prevalence in survivors and deceased patients.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eGrouped bar chart comparing the prevalence of delirium between survivors (n = 152) and deceased patients (n = 43). Delirium occurred in 52.0% of survivors compared with 90.7% of deceased patients, a difference of overwhelming statistical significance (p \u0026lt; 0.001), confirming delirium as a critical marker of systemic severity and a powerful independent predictor of in-hospital mortality in this cohort.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9260844/v1/c68401250707f1979e2ec44b.png"},{"id":108632688,"identity":"e9192253-ce7f-48c5-a905-9caa92eecbcb","added_by":"auto","created_at":"2026-05-06 17:06:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":25552,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDistribution of clinical and laboratory parameters across the cohort.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFrequency histograms for seven clinical and biochemical parameters measured at admission. C-reactive protein (CRP) and procalcitonin (PCT) show right-skewed distributions with the majority of values at low-to-moderate levels and a tail of extreme values reflecting hyperinflammatory responses. The neutrophil count shows a peak consistent with neutrophilic leukocytosis typical of sepsis, whilst the lymphocyte distribution is concentrated at low values, reflecting the lymphopenia characteristic of severe illness. The SOFA score shows a broad distribution confirming the heterogeneity of organ dysfunction severity across the cohort. PCT: procalcitonin; CRP: C-reactive protein; N: neutrophils; L: lymphocytes; SOFA: Sequential Organ Failure Assessment; q-SOFA: quick SOFA.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9260844/v1/3f5566a2272bd651657986bf.png"},{"id":108805456,"identity":"3a749eda-a181-4616-b42c-8e4761e2ea90","added_by":"auto","created_at":"2026-05-08 15:26:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":942074,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eBetween-group comparison of key prognostic parameters: survivors versus deceased.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSide-by-side comparison of five prognostic parameters between survivors (n = 152) and deceased patients (n = 43). Asterisks denote level of statistical significance: ***p \u0026lt; 0.001; **p \u0026lt; 0.01; *p \u0026lt; 0.05. The SOFA score and N/L ratio demonstrate the greatest between-group difference, confirming their status as the strongest predictors of in-hospital mortality in this cohort. The Clinical Frailty Scale (CFS) also shows a significant difference between groups, validating the prognostic importance of baseline frailty assessment. CFS: Clinical Frailty Scale; N/L: Neutrophil-to-Lymphocyte ratio; SOFA: Sequential Organ Failure Assessment; CCI: Charlson Comorbidity Index.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9260844/v1/52eadbd0d47e176ea0c2ebf6.png"},{"id":108805795,"identity":"b57b5ba3-506b-4d02-a1b1-e9a078a95a8b","added_by":"auto","created_at":"2026-05-08 15:26:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1602213,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eForest plot of odds ratios for in-hospital mortality.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eForest plot displaying the odds ratios (OR) with 95% confidence intervals (CI) for each clinical predictor variable in the logistic regression model for in-hospital mortality. The vertical dashed red line represents OR = 1 (no effect). Variables to the right of the line increase mortality risk; those to the left are protective or neutral. Delirium demonstrates the highest OR (approximately 9.0), substantially exceeding all other predictors. SOFA score and Clinical Frailty Scale (CFS) demonstrate comparable ORs of approximately 2.2. Microbiological culture positivity (blood and urine) and classical inflammatory markers (CRP, procalcitonin) span the null line, consistent with their non-significant associations with mortality. CFS: Clinical Frailty Scale; CRP: C-reactive protein; N/L: Neutrophil-to-Lymphocyte ratio; OR: odds ratio; CI: confidence interval; SOFA: Sequential Organ Failure Assessment.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9260844/v1/2723b28adb76076ed39cd59e.png"},{"id":108632691,"identity":"c42aa3e4-8186-40d7-acfc-48b4ebcf4681","added_by":"auto","created_at":"2026-05-06 17:06:38","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":335442,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eHorizontal bar chart of odds ratios for in-hospital mortality.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAlternative representation of logistic regression results. Bar length corresponds to the magnitude of the odds ratio for each predictor. Red bars indicate statistically significant associations (95% CI does not cross OR = 1); grey bars indicate non-significant associations. The visual primacy of delirium (OR ≈ 9.0) is immediately apparent. SOFA score and Clinical Frailty Scale contribute approximately equally to mortality risk (OR ≈ 2.2). Microbiological positivity, CRP, and procalcitonin fall within the neutral zone, consistent with their absence of independent prognostic value in this cohort. CFS: Clinical Frailty Scale; CRP: C-reactive protein; N/L: Neutrophil-to-Lymphocyte ratio; OR: odds ratio; SOFA: Sequential Organ Failure Assessment.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9260844/v1/7e62bb47f473a97dc513bd46.png"},{"id":108809797,"identity":"f09562da-58e9-4cca-8786-998d7eb21814","added_by":"auto","created_at":"2026-05-08 15:55:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3406474,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9260844/v1/bdb8183e-a6be-433f-bf6a-065c18ff7f4a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Correlation between microbiological isolates, frailty indices, delirium, and clinical outcomes in a cohort of septic geriatric patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSepsis represents one of the most critical challenges for global public health, with a predominant epidemiological impact on patients over 70 years of age [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Defined as a potentially lethal organ dysfunction resulting from a dysregulated host response to infection, sepsis is clinically identified by a SOFA (Sequential Organ Failure Assessment) score of \u0026ge;\u0026thinsp;2 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Demographic ageing, and the phenomenon of \u0026lsquo;inflammaging\u0026rsquo; (a chronic low-grade inflammatory state), drastically complicates the diagnostic picture, requiring a more profound understanding of the predisposing factors in geriatric patients [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSepsis in elderly populations does not always manifest with the classic systemic signs (fever, tachycardia) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Immunosenescence alters the neutrophil response, which often maintains a preserved numerical count whilst undergoing functional impairment in chemotaxis and phagocytosis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In this scenario, delirium - an acute, transient state characterised by confusion and significantly reduced awareness of the surroundings - emerges as a key manifestation. Often the only initial symptom, delirium is frequently underdiagnosed, particularly in its hypoactive form. This cognitive vulnerability is not merely a complication, but an indicator of depleted functional reserve and a powerful predictor of mortality [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMortality in frail patients follows a \u0026lsquo;trimodal\u0026rsquo; trajectory. In addition to early and late peaks, a third peak emerges between 60 and 90 days post-event, influenced by comorbidities, antibiotic resistance, and social isolation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Risk assessment, therefore, cannot be based solely on chronological age but must integrate disease severity with the patient\u0026rsquo;s potential for functional recovery [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study aims to investigate the relationship between microbiological isolates (blood and urine cultures), frailty indices (Clinical Frailty Scale and Charlson Comorbidity Index), the presence of delirium, and clinical outcomes (mortality and length of stay) in a cohort of geriatric patients hospitalised for sepsis. The primary objective is to determine whether clinical and laboratory parameters (CRP, procalcitonin, neutrophils, lymphocytes, N/L ratio, lactate, q-SOFA and SOFA scores), together with multidimensional geriatric indicators, are more accurate predictors of clinical prognosis than microbiological positivity alone. Furthermore, the study evaluates the specific impact of delirium and baseline frailty on mortality, testing the hypothesis that functional and cognitive impairment are more significant prognostic drivers than pathogen virulence.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThe study retrospectively analysed all patients admitted to the Geriatric Unit of San Luigi University Hospital in Orbassano who presented with sepsis, identified at the time of admission or manifested during their hospital stay. Data were collected consecutively between 1 January and 31 December 2025. Prior to being transferred to the ward, all patients included in the study spent an average of 36 hours in the emergency department awaiting bed availability.\u003c/p\u003e \u003cp\u003eThe final sample consisted of 195 patients aged over 65 years, with a mean age of 87.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1 years (range: 69\u0026ndash;103 years). There was a slight male predominance, with 104 men (53.3%). Consistent with a real-world clinical practice approach, all subjects were included regardless of the primary site of infectious insult, with a mean hospital stay of 21 days (range: 2\u0026ndash;70 days) [figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e]. The case series was heterogeneous and was stratified according to primary admission diagnosis: pneumonia, urinary tract infections (UTIs), exacerbated chronic obstructive pulmonary disease (COPD), non-specific sepsis, abdominal sepsis, multifocal pneumonia, soft tissue infections, and COVID-19.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor each patient enrolled, blood chemistry profiles were extracted to characterise the extent of the inflammatory response and degree of organ impairment. Parameters collected and analysed included C-reactive protein (CRP), procalcitonin, absolute neutrophil and lymphocyte counts, the neutrophil/lymphocyte (N/L) ratio [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and lactate levels. Simultaneously, q-SOFA (quick Sequential Organ Failure Assessment) and SOFA scores were calculated to stratify clinical risk and sepsis severity [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAfter stabilisation of the acute condition, each patient underwent a standardised multidimensional assessment to quantify baseline frailty status. This was conducted using the Clinical Frailty Scale (CFS) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and the Charlson Comorbidity Index (CCI) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], integrating the patient\u0026rsquo;s functional reserve with data on the current infectious episode. The presence of delirium, identified both on admission and as an event arising during hospitalisation, was also actively investigated and was found in 118 patients (60.5%), representing a critical marker of cerebral vulnerability and systemic severity.\u003c/p\u003e \u003cp\u003eTo define the aetiology of the septic insult, results of microbiological investigations performed during the bacteraemic phase or on clinical suspicion were analysed. The data collected were statistically analysed to investigate correlations between biochemical variables, frailty scores, the presence of delirium, and final clinical outcomes, with the aim of verifying whether geriatric indicators and inflammatory biomarkers have greater predictive accuracy than microbiological culture positivity alone.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical processing and database management were performed using Python (Pandas, NumPy, and SciPy). Continuous variables were described as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) and range. Categorical variables were expressed as absolute frequencies and percentages. Normality of distributions was assessed using the Shapiro\u0026ndash;Wilk test. Given the non-parametric distribution of many biochemical parameters and the ordinal nature of clinical and frailty scores, the Mann\u0026ndash;Whitney U test was used for continuous variables and Pearson\u0026rsquo;s chi-square test for categorical variables when comparing survivors and deceased patients. Correlations between laboratory variables (CRP, procalcitonin, neutrophils, lymphocytes, N/L ratio, and lactate), severity scores (q-SOFA and SOFA), frailty indices (CFS and CCI), and the presence of delirium were investigated using Spearman\u0026rsquo;s rank correlation coefficient (ρ). To further characterise the independent contribution of clinical predictors to in-hospital mortality, a logistic regression analysis was performed, with results expressed as odds ratios (OR) with 95% confidence intervals (95% CI). For all tests, a two-tailed p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe study included 195 geriatric patients with a mean age of 87.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1 years. Overall in-hospital mortality was 22.1% (43 deaths), and 60.5% of patients (n\u0026thinsp;=\u0026thinsp;118) presented with delirium during their hospital stay [figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e]. Compared to survivors, deceased patients had a significantly higher baseline frailty status (mean CFS: 7.67 vs. 6.53; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and greater comorbidity burden (CCI: 10.35 vs. 9.18; p\u0026thinsp;=\u0026thinsp;0.005). No statistically significant differences were observed in mean age or length of hospital stay between survivors and deceased patients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eBaseline characteristics and comparison between survivors and deceased patients.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;195)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvivors (n\u0026thinsp;=\u0026thinsp;152)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDeceased (n\u0026thinsp;=\u0026thinsp;43)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDemographics\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGeriatric \u0026amp; Cognitive Assessment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelirium (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBiochemical \u0026amp; Inflammatory Markers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcalcitonin (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.5\u0026thinsp;\u0026plusmn;\u0026thinsp;45.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophils (\u0026times;10\u0026sup3;/\u0026micro;L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocytes (\u0026times;10\u0026sup3;/\u0026micro;L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN/L Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.8\u0026thinsp;\u0026plusmn;\u0026thinsp;14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.0\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.9\u0026thinsp;\u0026plusmn;\u0026thinsp;15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactate (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSeverity Scores\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eq-SOFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.044\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or percentage (%). CCI: Charlson Comorbidity Index; CFS: Clinical Frailty Scale; CRP: C-reactive protein; N/L: Neutrophil-to-Lymphocyte ratio. Bold p-values indicate statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Comparisons performed using the Mann\u0026ndash;Whitney U test for continuous variables and Pearson\u0026rsquo;s chi-square test for categorical variables.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eMicrobiological testing yielded a positive culture in 52.3% of the sample (102 patients). Urine culture was positive in 40.5% of cases (n\u0026thinsp;=\u0026thinsp;79) and blood culture in 21.5% (n\u0026thinsp;=\u0026thinsp;42); in 19 patients (9.7%), both samples were positive. The most frequently isolated pathogen at both sites was \u003cem\u003eEscherichia coli\u003c/em\u003e (34 urinary and 16 blood isolates). No statistically significant association was found between culture positivity (blood or urine) and mortality (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), confirming that pathogen identification, in isolation from the clinical context, was not a reliable prognostic predictor in this cohort.\u003c/p\u003e \u003cp\u003eComparison between the survivor and deceased groups revealed marked differences in parameters collected at admission. CRP, although higher in deceased patients (12.7 vs. 10.7 mg/dL), did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.293). Similarly, procalcitonin (PCT) levels were higher in deceased patients (8.5 vs. 2.0 ng/mL) but showed high internal variability and did not achieve significance (p\u0026thinsp;=\u0026thinsp;0.302). A significant difference was observed in neutrophil count (12.4 vs. 10.4 \u0026times; 10\u0026sup3;/\u0026micro;L; p\u0026thinsp;=\u0026thinsp;0.007), alongside a marked reduction in lymphocytes in deceased patients (0.78 vs. 1.32 \u0026times; 10\u0026sup3;/\u0026micro;L; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The N/L ratio proved to be a powerful prognostic marker, with significantly higher values in patients with a poor outcome (20.9 vs. 13.0; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Serum lactate levels were also significantly higher in the deceased group (1.61 vs. 1.39 mmol/L; p\u0026thinsp;=\u0026thinsp;0.013). Both severity scores were significant predictors of mortality: the mean q-SOFA was 1.0 in deceased patients versus 0.69 in survivors (p\u0026thinsp;=\u0026thinsp;0.044), whilst the SOFA score demonstrated the strongest association with outcome, with a mean of 6.8 in deceased patients versus 2.4 in survivors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) [figure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e] [figure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDelirium was closely correlated with both mortality (ρ\u0026thinsp;=\u0026thinsp;0.33; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and frailty as measured by the CFS (ρ\u0026thinsp;=\u0026thinsp;0.50). A significant correlation was also identified between CFS and the severity of organ dysfunction as measured by the SOFA score. \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (urinary isolation) was associated with a significant prolongation of mean hospital stay (29.4 vs. 19.3 days; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but not with an increase in direct in-hospital mortality [figure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e] [figure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe mortality observed in our sample (22.1%) is consistent with data reported for geriatric sepsis cohorts in the literature, which generally range between 20% and 45% [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The most notable finding, however, is the absence of a significant correlation between positive cultures (haematological or urinary) and poor outcomes. This supports an emerging trend in critical geriatrics: in very elderly patients (mean age 87 years), the virulence of the isolated pathogen appears to carry less prognostic weight than the functional reserve of the host [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Studies indicate that, although Gram-negative bacteria such as \u003cem\u003eE. coli\u003c/em\u003e are prevalent, survival is dictated more by biological frailty than by circulating bacterial load [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe high prevalence of delirium (60.5%) and its strong association with mortality (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) corroborate findings from recent reviews; in the elderly, delirium is not a simple neurological symptom, but a manifestation of brain organ failure in the context of a systemic inflammatory response [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The correlation between delirium and the CFS (ρ\u0026thinsp;=\u0026thinsp;0.50) suggests that acute cognitive status directly reflects the patient\u0026rsquo;s baseline vulnerability. Studies by Inouye et al. have demonstrated that delirium dramatically increases the risk of short-term death, often representing the only \u0026lsquo;atypical\u0026rsquo; sign of severe sepsis in patients in whom fever or tachycardia may be absent [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur results confirm that the SOFA score is the strongest predictor of mortality (mean 6.8 in deceased patients), surpassing q-SOFA, consistent with the comparative literature indicating SOFA as the superior risk stratification tool [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, the addition of CFS and CCI provides a more complete clinical picture: patients who did not survive were significantly more frail (CFS 7.67). This supports the position of Muscedere et al. and Geen et al., who argue that frailty should be systematically integrated into geriatric sepsis protocols, as SOFA alone may underestimate severity in patients with depleted functional reserve [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe effectiveness of the N/L ratio as a prognostic marker (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), in contrast to CRP and procalcitonin (both non-significant), is explained by the concept of inflammaging: older patients often have elevated baseline CRP levels or blunted PCT responses [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The N/L ratio instead reflects the imbalance between innate immune activation (neutrophilia) and adaptive immune exhaustion (lymphopenia), a critical process in geriatric sepsis associated with worse outcomes [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough \u003cem\u003eE. coli\u003c/em\u003e was the most frequently isolated organism, the association of \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e with prolonged hospital stay (29.4 days) highlights the management challenges posed by multidrug-resistant organisms in geriatric wards. In the literature, \u003cem\u003eKlebsiella\u003c/em\u003e is frequently associated with multi-resistance profiles and nosocomial infections that, whilst not necessarily increasing acute mortality when adequately treated, substantially prolong hospitalisation and increase the risk of secondary complications [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe management of elderly septic patients requires moving beyond a purely microbiological model. Prognosis is defined by a \u0026lsquo;critical triangle\u0026rsquo;: acute severity (SOFA), baseline frailty (CFS), and cognitive status (delirium). These parameters, together with the N/L ratio, offer a considerably more accurate clinical compass than pathogen identification alone. Prospective, multicentre studies are needed to validate these findings and establish integrated geriatric assessment as a standard component of sepsis risk stratification in elderly populations.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eSeveral limitations of this study warrant consideration. First, the retrospective, single-centre design limits the generalisability of our findings; the cohort reflects clinical practice at a single Italian tertiary geriatric unit, and unmeasured confounders inherent to retrospective data collection cannot be excluded. Second, whilst the CFS was applied after clinical stabilisation to reflect baseline functional status, assessment during an acute hospitalisation carries an inherent risk of acute-on-chronic misclassification, whereby frailty may be transiently overestimated in patients with reversible acute deterioration. Third, our outcome data were limited to in-hospital mortality; post-discharge outcomes, including 30-day and 90-day mortality, readmission rates, and longer-term functional trajectories, were not captured. Given the trimodal mortality trajectory described in frail septic patients, with a late peak between 60 and 90 days, this represents a significant gap in follow-up.\u003c/p\u003e \u003cp\u003eFourth, microbiological data were dependent on culture yield; in a cohort where only 52.3% of patients had a positive culture result, the absence of an isolated pathogen does not exclude infection and may reflect sampling limitations, prior antibiotic exposure, or fastidious organisms. Accordingly, the null finding regarding culture positivity and mortality should be interpreted cautiously rather than as definitive evidence of microbial irrelevance. Fifth, antibiotic appropriateness, defined as concordance between empirical therapy and subsequent culture sensitivities, was not systematically analysed and may represent a confounding variable in the relationship between pathogen identification and outcome. Finally, the absence of a formal delirium assessment tool (such as the Confusion Assessment Method, CAM) applied at standardised timepoints means that the reported delirium prevalence of 60.5% may reflect a composite of hyperactive, hypoactive, and mixed subtypes in proportions that cannot be disaggregated from the available data, potentially underestimating true prevalence. Prospective, multicentre studies incorporating validated delirium screening instruments and longitudinal follow-up are warranted to confirm and extend these findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki. The study was submitted to the Institutional Ethics Committee of San Luigi Gonzaga University Hospital, Orbassano, Turin, Italy. As a retrospective observational study involving only fully anonymised clinical data, formal ethics committee approval was not required. All patients provided informed consent for the collection and use of their anonymised clinical data at the time of hospital admission as part of the standard clinical consent process. All data were handled and reported in fully anonymised form throughout.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This study contains no individually identifiable data. Patient consent for the use of anonymised clinical data was obtained at the time of hospital admission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data relevant to the conclusions of this study are presented within the article. No additional datasets were generated or analysed beyond those reported herein.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTF and LSR conceived and designed the study, led data collection and analysis, and drafted the manuscript. TF acts as guarantor of the study. All authors (TF, ADS, SO, AT, IRB, TC, GM, VR, BT, LSR, EG, JMV, SDG, DM, EB, FM, RV, RP, AM, TR, GF, GV) contributed to data acquisition, critically revised the manuscript for important intellectual content, and approved the final version for submission. All authors agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number: not applicable.\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eIbarz M, Haas LEM, Ceccato A, Artigas A. The critically ill older patient with sepsis: a narrative review. Ann Intensive Care. 2024;14(1):6. https://doi.org/10.1186/s13613-023-01233-7\u003c/li\u003e\n\u003cli\u003eSinger M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801₁0. https://doi.org/10.1001/jama.2016.0287\u003c/li\u003e\n\u003cli\u003eFraccalini T, Ribeiro LS, Trogolo A, Tarozzo B, Piras V, Vecchini JM, et al. The clinical impact of sarcopenia and delirium in hospitalised elderly patients: an analysis using muscle ultrasound. J Cachexia Sarcopenia Muscle. 2026;17(1):e70202. https://doi.org/10.1002/jcsm.70202\u003c/li\u003e\n\u003cli\u003eAlhamyani AH, Alamri MS, Aljuaid NW, Aloubthani AH, Alzahrani S, Alghamdi AA, et al. Sepsis in aging populations: a review of risk factors, diagnosis, and management. Cureus. 2024;16(12):e74973. https://pmc.ncbi.nlm.nih.gov/articles/PMC11691596/\u003c/li\u003e\n\u003cli\u003eYu X, Pei W, Li B, Sun S, Li W, Wu Q. Immunosenescence, physical exercise, and their implications in tumour immunity and immunotherapy. Int J Biol Sci. 2025;21(3):910\u0026ndash;39. https://pmc.ncbi.nlm.nih.gov/articles/PMC11781184/\u003c/li\u003e\n\u003cli\u003eFraccalini T, Ricci V, Pesci NR, Tarozzo B, Cardinale L, Maina G, et al. Delirium and COVID-19: prevalence, outcomes and associated factors in a cohort of elderly inpatients. Minerva Psychiatry. 2025;66(2). https://doi.org/10.23736/s2724-6612.25.02608-9\u003c/li\u003e\n\u003cli\u003eDelano MJ, Ward PA. The immune system\u0026rsquo;s role in sepsis progression, resolution, and long-term outcome. Immunol Rev. 2016;274(1):330\u0026ndash;53. https://doi.org/10.1111/imr.12499\u003c/li\u003e\n\u003cli\u003eWu H, Cao T, Ji T, Luo Y, Huang J, Ma K. Predictive value of the neutrophil-to-lymphocyte ratio in the prognosis and risk of death for adult sepsis patients: a meta-analysis. Front Immunol. 2024;15:1336456. https://doi.org/10.3389/fimmu.2024.1336456\u003c/li\u003e\n\u003cli\u003eRaith EP, Udy AA, Bailey M, McGloughlin S, MacIsaac C, Bellomo R, et al. Prognostic accuracy of the SOFA score, SIRS criteria, and qSOFA score for in-hospital mortality among adults with suspected infection admitted to the ICU. JAMA. 2017;317(3):290\u0026ndash;0. https://doi.org/10.1001/jama.2016.20328\u003c/li\u003e\n\u003cli\u003eStille K, Temmel N, Hepp J, Herget-Rosenthal S. Validation of the Clinical Frailty Scale for retrospective use in acute care. Eur Geriatr Med. 2020;11(6):1009\u0026ndash;15. https://doi.org/10.1007/s41999-020-00370-7\u003c/li\u003e\n\u003cli\u003eCharlson ME, Carrozzino D, Guidi J, Patierno C. Charlson Comorbidity Index: a critical review of clinimetric properties. Psychother Psychosom. 2022;91(1):8\u0026ndash;35. https://doi.org/10.1159/000521288\u003c/li\u003e\n\u003cli\u003eBoonmee P, Ruangsomboon O, Limsuwat C, Chakorn T. Predictors of mortality in elderly and very elderly emergency patients with sepsis: a retrospective study. West J Emerg Med. 2020;21(6):210\u0026ndash;8. https://doi.org/10.5811/westjem.2020.7.47405\u003c/li\u003e\n\u003cli\u003eSorci G, Faivre B. Age-dependent virulence of human pathogens. PLoS Pathog. 2022;18(9):e1010866. https://doi.org/10.1371/journal.ppat.1010866\u003c/li\u003e\n\u003cli\u003eRando E, Matteini E, Guerriero S, Fantoni M. Gram-negative infections in frail patients. Infez Med. 2023;31(1). https://doi.org/10.53854/liim-3101-5\u003c/li\u003e\n\u003cli\u003eFraccalini T, Ribeiro LS, Trogolo A, Tarozzo B, Piras V, Vecchini JM, et al. The clinical impact of sarcopenia and delirium in hospitalised elderly patients: an analysis using muscle ultrasound. J Cachexia Sarcopenia Muscle. 2026;17(1):e70202. https://doi.org/10.1002/jcsm.70202\u003c/li\u003e\n\u003cli\u003eFraccalini T, Tarozzo B, Maraschi A, Cardinale L, Garofalo G, Vecchini JM, et al. Air under the skin, shadows in the mind: an enigmatic case report on hyperactive delirium or sundowning triggered by subcutaneous emphysema post-pneumothorax. Minerva Psychiatry. 2025;66(3). https://doi.org/10.23736/s2724-6612.25.02639-9\u003c/li\u003e\n\u003cli\u003eInouye SK, Westendorp RG, Saczynski JS. Delirium in elderly people. Lancet. 2014;383(9920):911\u0026ndash;22. https://doi.org/10.1016/s0140-6736(13)60688-1\u003c/li\u003e\n\u003cli\u003eBattle of the scores: SOFA vs qSOFA in forecasting critical care mortality. Eur J Cardiovasc Med. 2025. https://doi.org/10.5083/ejcm/25-05-142\u003c/li\u003e\n\u003cli\u003eMuscedere J, Waters B, Varambally A, Bagshaw SM, Boyd JG, Maslove D, et al. The impact of frailty on intensive care unit outcomes: a systematic review and meta-analysis. Intensive Care Med. 2017;43(8):1105\u0026ndash;22. https://doi.org/10.1007/s00134-017-4867-0\u003c/li\u003e\n\u003cli\u003eGeen O, Rochwerg B, Wang XM. Optimizing care for critically ill older adults. CMAJ. 2021;193(39):E1525\u0026ndash;33. https://doi.org/10.1503/cmaj.210652\u003c/li\u003e\n\u003cli\u003eDi Rosa M, Sabbatinelli J, Soraci L, Corsonello A, Bonfigli AR, Cherubini A, et al. Neutrophil-to-lymphocyte ratio (NLR) predicts mortality in hospitalised geriatric patients independent of the admission diagnosis: a multicentre prospective cohort study. J Transl Med. 2023;21(1):835. https://doi.org/10.1186/s12967-023-04717-z\u003c/li\u003e\n\u003cli\u003eHan K, Wang JH, Lu JS. Clinical significance of the neutrophil-to-lymphocyte ratio on the prognosis of critically ill elderly patients with sepsis: a retrospective study based on the MIMIC-IV database. Hong Kong J Emerg Med. 2025;32(2). https://doi.org/10.1002/hkj2.70008\u003c/li\u003e\n\u003cli\u003eAsri NAM, Ahmad S, Mohamud R, Hanafi NM, Zaidi NFM, Irekeola AA, et al. Global prevalence of nosocomial multidrug-resistant Klebsiella pneumoniae: a systematic review and meta-analysis. Antibiotics. 2021;10(12):1508. https://doi.org/10.3390/antibiotics10121508\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Geriatric sepsis, Frailty, Delirium, SOFA score, Neutrophil/Lymphocyte ratio, In-hospital mortality","lastPublishedDoi":"10.21203/rs.3.rs-9260844/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9260844/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eSepsis in geriatric patients represents a diagnostic and prognostic challenge due to immunosenescence and atypical clinical presentation. Whilst management has traditionally focused on pathogen identification, baseline frailty and geriatric syndromes such as delirium may be more accurate predictors of mortality. We evaluated whether biochemical parameters (CRP, procalcitonin, N/L ratio, lactate), severity scores (SOFA, q-SOFA), and multidimensional indicators (CFS, Charlson Index, delirium) outperform microbiological positivity alone as prognostic tools.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective study of 195 patients (aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years) consecutively admitted for sepsis to the Geriatrics Department of San Luigi University Hospital, Orbassano, in 2025. Laboratory parameters on admission and multidimensional geriatric scores after clinical stabilisation were analysed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe cohort (mean age 87.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1 years) had an in-hospital mortality rate of 22.1% and a delirium incidence of 60.5%. Microbiological positivity (52.3%, predominantly E. coli) showed no significant correlation with mortality (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Deceased patients had significantly higher CFS and Charlson scores (p\u0026thinsp;\u0026lt;\u0026thinsp;0.005). The N/L ratio (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and lactate (p\u0026thinsp;=\u0026thinsp;0.013) were more reliable predictors of poor outcome than CRP or procalcitonin. SOFA score showed the strongest association with mortality (mean 6.8 vs. 2.4 in survivors; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Delirium correlated with both mortality (r\u0026thinsp;=\u0026thinsp;0.33) and frailty (r\u0026thinsp;=\u0026thinsp;0.50). Klebsiella pneumoniae isolation was associated with significantly prolonged hospital stay (29.4 vs. 19.3 days; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePrognosis in septic geriatric patients is determined by a \u0026lsquo;critical triangle\u0026rsquo; of acute severity (SOFA), baseline frailty (CFS), and cognitive status (delirium), rather than pathogen identification alone. The N/L ratio emerges as the biochemical marker of choice over classic inflammatory indices. Integrated multidimensional geriatric assessment is essential for accurate risk stratification and personalised care.\u003c/p\u003e","manuscriptTitle":"Correlation between microbiological isolates, frailty indices, delirium, and clinical outcomes in a cohort of septic geriatric patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-06 17:06:34","doi":"10.21203/rs.3.rs-9260844/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-30T07:12:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"112471965582070035946618453311126035824","date":"2026-04-29T06:40:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187980922527155584355655781913587230188","date":"2026-04-29T01:39:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-28T02:59:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-28T02:56:20+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-17T17:02:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-17T10:17:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2026-04-17T08:50:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"89241ab4-8c53-40f0-8fd4-1a2ef927900a","owner":[],"postedDate":"May 6th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-04-30T07:12:12+00:00","index":29,"fulltext":""},{"type":"reviewerAgreed","content":"112471965582070035946618453311126035824","date":"2026-04-29T06:40:55+00:00","index":27,"fulltext":""},{"type":"reviewerAgreed","content":"187980922527155584355655781913587230188","date":"2026-04-29T01:39:44+00:00","index":26,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-06T17:06:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-06 17:06:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9260844","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9260844","identity":"rs-9260844","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}