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Risk Factors for Perioperative Complications in Geriatric Surgery: A Multivariable Analysis of Physiological Reserve and Pharmacological Precision

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Annals of Medicine and Medical Sciences (2026) May 1, 2026 pp. 550 - 554
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Abstract

Background: Geriatric anesthesia is challenged by "homeostenosis"—a progressive decline in functional reserve. In resource-constrained regions like Odisha, localized audits are essential to bridge the gap between global standards and regional clinical realities. This study aims to document real-world anesthetic management, identify independent risk factors for complications, and evaluate the impact of physiological profiles on outcomes in Indian geriatric patients. Methods: A retrospective analytical study of 300 surgical patients aged 65 years or older was conducted at a tertiary care hospital in Odisha (2022–2023). Multivariable logistic regression was used to identify independent risk factors for perioperative complications. Results: The cohort showed high clinical risk, with 58% classified as ASA III/IV and 72% hypertensive. Frequent complications included hypotension (23%), excessive somnolence (21%), and postoperative delirium (14%). ASA status III/IV was the strongest predictor of adverse outcomes (aOR 3.42; p < 0.001). Other significant predictors included propofol doses > 1.5 mg/kg (aOR 2.56; p = 0.001), age > 75 years (aOR 2.14; p = 0.008), and surgery > 120 minutes (aOR 1.95; p = 0.018). Anesthesia technique (general vs. regional) was not a significant independent risk factor (p = 0.092). Complications correlated significantly with baseline anemia (10.2 vs. 11.8 g/dL) and abnormal preoperative ECG/CXR (p < 0.001). Conclusion: Geriatric outcomes are driven primarily by physiological vulnerability and pharmacological precision rather than anesthetic technique. High rates of instability and somnolence necessitate "geriatric-dose" induction protocols (propofol ≤ 1.5 mg/kg). Implementing risk-stratified care and preoperative optimization of anemia and comorbidities is vital to improving safety in resource-constrained settings.

Introduction

The clinical management of geriatric patients represents a mounting challenge due to "homeostenosis"—a progressive decline in functional organ reserve that narrows the margin of safety during surgical stress [1]. With the elderly population in Odisha projected to reach 80 lakh by 2036 and a 91.7% prevalence of chronic morbidities, the magnitude of perioperative risk is substantial [2,3]. Anesthesia-related complications, ranging from cardiovascular events (10–35%) to postoperative delirium (up to 50% in hip fractures), significantly threaten functional independence and strain socio-economic resources, especially in a region where 40% of seniors have no personal income [4,5].

Current literature establishes that aging fundamentally alters drug pharmacokinetics, requiring lower induction doses for agents like propofol (1.7 mg/kg vs. 2.2 mg/kg in younger adults) [6,7]. Most data originates from high-income Western countries, despite the validation of tools like the ASA classification and Lee Cardiac Risk Index for predicting morbidity. Locally, there is a distinct lack of data regarding the "patient experience" concerning minor complications (dry mouth, somnolence) and the long-term impact of anesthetic depth on the unique nutritional and comorbidity profiles of Indian geriatric patients [9,10].

This study is founded on the framework that evidence-based, localized audits are required to bridge the gap between "expert opinion" and the specific resource constraints of Indian government medical colleges. By utilizing a multivariable logistic regression model, the research aims to identify independent risk factors, such as the correlation between specific drug dosages and hemodynamic instability [11]. The project’s specific purpose is to document real-world anesthetic management, compare outcomes between regional and general anesthesia, and validate risk-stratification tools to develop localized clinical protocols, such as "geriatric-dose" induction cards, to improve perioperative safety [6,12].

Materials and Methods

We conducted a quantitative, observational, and retrospective descriptive-analytical study at a tertiary care government medical college in Odisha. Researchers utilized hospital records from the inpatient department and operation theater databases covering a two-year period from January 2022 to December 2023. We identified a study population consisting of all patients aged 65 years and older who underwent elective or emergency surgical procedures requiring anesthesia.

We employed a consecutive purposive sampling method, sequentially analyzing every eligible record that met our inclusion criteria.

The inclusion criteria targeted patients aged 65 or older who received general anesthesia, regional anesthesia, or monitored anesthesia care and possessed complete medical records. We excluded patients under 65, those with missing or illegible charts, and those undergoing surgery under local anesthesia without the anesthesiology team.

For the analytical phase, patients who met the age criteria but remained free of complications served as an internal comparator to identify independent risk factors. We extracted data for several independent variables, including demographic data, preoperative ASA status, comorbidities, surgical factors (type and duration), and anesthetic management details such as specific drug dosages. We monitored several dependent variables to assess clinical outcomes. These included hemodynamic complications like hypotension and bradycardia, respiratory issues such as desaturation or re-intubation, and neurocognitive markers like postoperative delirium. We also recorded minor complications, including nausea, sore throat, and somnolence, alongside broader outcomes like length of hospital stay and 30-day mortality. Finally, we retrieved and reviewed laboratory investigation parameters from the records, including hematology, biochemistry, ECG findings, and preoperative chest X-rays, to correlate clinical status with anesthetic outcomes.

Results

The study population consisted of 300 elderly patients, with a slight female majority (53%) and a primary age concentration in the 65–74 year bracket (55%). A high clinical risk profile was observed, as 58% of the cohort was classified as ASA physical status III or IV, indicating severe systemic disease. Furthermore, hypertension was the most prevalent comorbidity, affecting 72% of patients, followed by diabetes mellitus at 43%, highlighting a significant burden of cardiovascular and metabolic disease within the group (Table 1).

Table 1: Baseline Demographic and Clinical Characteristics
Variable Category Total (n=300) Percentage (%)
Age Group 65–74 years 165 55%
75–84 years 102 34%
≥ 85 years 33 11%
Gender Male 142 47%
Female 158 53%
BMI (kg/m²) Underweight (<18.5) 42 14%
Normal (18.5–24.9) 186 62%
Overweight/Obese (≥25) 72 24%
ASA Physical Status ASA I 12 4%
ASA II 114 38%
ASA III 148 49%
ASA IV 26 9%
Comorbidities Hypertension 215 72%
Diabetes Mellitus 128 43%
Coronary Artery Disease 84 28%
Chronic Obstructive Pulmonary Disease 46 15%
Renal Dysfunction 32 11%

Statistically significant differences were observed between general anesthesia (GA) and regional anesthesia (RA) across all management factors. Patients receiving RA underwent significantly shorter procedures (84.6 ± 28.5 mins) compared to those under GA (112.4 ± 34.2 mins; p < 0.001). Additionally, GA was more frequently utilized for emergency surgeries (p = 0.042) and required a higher rate of invasive monitoring (22.3% vs. 10.7%; p = 0.012), suggesting a higher level of complexity or acuity in the general anesthesia group (Table 2).

Table 2: Comparison of Anesthetic Management: General vs. Regional
Management Factor General Anesthesia (n=188) Regional Anesthesia (n=112) p-value
Surgical Priority Elective: 120 / Emer: 68 Elective: 88 / Emer: 24 0.042
Induction Agent Propofol: 1.8 ± 0.4 mg/kg N/A --
Adjuvant Opioid Fentanyl: 1.2 ± 0.3 µg/kg N/A --
Duration of Surgery 112.4 ± 34.2 mins 84.6 ± 28.5 mins <0.001
Invasive Monitoring IBP/CVP: 42 (22.3%) IBP/CVP: 12 (10.7%) 0.012

Hemodynamic instability was the most frequent complication, with hypotension occurring in 23% of cases. Neurocognitive issues were also notable, specifically postoperative delirium (14%) and excessive somnolence (21%). Minor complications were relatively common, as evidenced by an 18% incidence of postoperative nausea and vomiting and a 16% incidence of sore throat, indicating that while major respiratory events remained below 10%, subjective and hemodynamic disturbances were prevalent in the postoperative period (Table 3).

Table 3: Incidence of Major and Minor Anesthesia-Related Complications
Category Specific Complication Frequency (n) Incidence (%)
Hemodynamic Hypotension (SBP <90 mmHg) 68 23%
Bradycardia (HR <50 bpm) 34 11%
Arrhythmias 18 6%
Respiratory Desaturation (SpO2 <90%) 28 9%
Postoperative Pneumonia 12 4%
Neurocognitive Postoperative Delirium (POD) 42 14%
Delayed Emergence 16 5%
Minor/Subjective Postoperative Nausea/Vomiting 54 18%
Sore Throat 48 16%
Excessive Somnolence 62 21%

The multivariable analysis identified ASA status (III/IV) as the strongest independent predictor of adverse outcomes, with patients having more than triple the risk of complications (aOR 3.42; p < 0.001). Other significant risk factors included a propofol dose exceeding 1.5 mg/kg (aOR 2.56; p = 0.001), age ≥ 75 years (aOR 2.14; p = 0.008), and surgery duration longer than 120 minutes (aOR 1.95; p = 0.018). Notably, general anesthesia itself did not reach statistical significance as an independent risk factor when adjusted for other variables (p = 0.092) (Table 4).

Table 4: Multivariable Logistic Regression Analysis of Risk Factors
Risk Factor Adjusted Odds Ratio (aOR) 95% Confidence Interval (CI) p-value
Age ≥ 75 years 2.14 1.22–3.76 0.008
ASA Status (III/IV) 3.42 1.84–6.35 <0.001
Emergency Surgery 1.88 1.04–3.38 0.036
Propofol Dose > 1.5mg/kg 2.56 1.45–4.52 0.001
General Anesthesia 1.64 0.92–2.94 0.092
Surgery Duration > 120m 1.95 1.12–3.40 0.018

Patients who experienced complications exhibited significantly different baseline laboratory profiles compared to the non-complication group. Most notably, the complication group had significantly lower hemoglobin levels (10.2 vs. 11.8 g/dL; p < 0.001) and higher blood glucose levels (154 vs. 128 mg/dL; p < 0.001). Furthermore, the presence of abnormal preoperative ECG or CXR findings was nearly twice as common in the complication group (67.8% vs. 34.4%; p < 0.001), suggesting that preoperative physiological optimization and screening are strongly linked to clinical outcomes (Table 5).

Table 5: Correlation between Laboratory Parameters and Clinical Outcomes
Lab Parameter Complication Group (n=56) Non-Complication Group (n=244) p-value
Hemoglobin (g/dL) 10.2 ± 1.4 11.8 ± 1.2 <0.001
Serum Creatinine (mg/dL) 1.4 ± 0.5 1.1 ± 0.3 0.002
Blood Glucose (mg/dL) 154 ± 38 128 ± 26 <0.001
Serum Potassium (mEq/L) 3.8 ± 0.6 4.1 ± 0.4 0.045
Abnormal ECG/CXR 38 (67.8%) 84 (34.4%) <0.001

Discussion

The current study in Odisha confirms that geriatric patients exhibit significant systemic vulnerability, with 58% classified as ASA III/IV, validating the rationale of homeostenosis—a narrowed functional reserve against surgical stress [13]. Multivariable regression successfully addressed the primary aim by identifying ASA status (aOR 3.42) and excessive propofol dosing (>1 mg/kg; aOR 2.56) as potent independent risk factors for complications, such as the 23% incidence of hypotension observed [14,15]. A primary strength of this project lies in its "real-world" regional specificity within a resource-constrained government medical college, capturing the critical interplay between biological aging, anemia, and socio-economic constraints that Western data often overlooks [5,16]. By disentangling complex variables through regression, the study pinpointed that physiological substrate and pharmacological precision—specifically avoiding induction "overdoses"—are more critical to outcomes than the choice of general versus regional anesthesia (GA vs. RA) [14,17].

The association between anesthetic interventions and outcomes is mediated by blunted baroreceptor reflexes and reduced "cognitive reserve," where high-dose propofol precipitates hemodynamic collapse and prolonged surgery increases neuroinflammatory stress, leading to a 14% delirium rate [18]. While these findings align with international concerns regarding propofol sensitivity, the 14% delirium incidence is lower than some regional reports, likely due to the inclusion of elective cases [19]. Strategically, the project impacts the healthcare system by advocating for "geriatric-dose" induction cards and preoperative anemia optimization, shifting the focus from high-volume throughput to patient-centered "brain health" initiatives [20]. This approach addresses the economic burden on a population where 40% are financially dependent, ensuring that safer perioperative care prevents catastrophic health expenditures [5,21].

Discrepancies between anticipated and observed outcomes revealed that GA was not an independent risk factor for complications (p > 0.05), as its perceived risk was confounded by its use in more complex, urgent surgeries [22]. Furthermore, the unexpectedly high rate of somnolence (21%) likely reflects the regional nutritional context; low albumin levels in underweight patients (14%) increase the "free fraction" of drugs, turning standard doses into relative overdoses [23]. This necessitates a strategic trade-off where the time invested in "geriatric-specific" regional techniques or invasive monitoring is balanced against theater throughput [24,25]. Ultimately, the higher cost of managing a single complication like AKI or delirium justifies the opportunity cost of slower, more meticulous anesthetic induction and preoperative optimization in high-risk (ASA III/IV) seniors [18,26].

Despite its strengths, the study’s generalizability is limited by its single-center design and a small "oldest-old" (>85 years) subgroup (11%), which may require even more aggressive dose titration [5]. Internal validity was challenged by the retrospective nature of chart reviews and potential selection bias in anesthetic choice; the 14% delirium rate may also under represent hypoactive cases due to the lack of structured CAM assessments [27,28]. To mitigate these limits, multivariable regression was employed to adjust for confounders, and the use of consecutive, purposive sampling (n=300) over two years provided high statistical power [27]. Correlating clinical complications with objective laboratory data (e.g., hemoglobin and glucose) further strengthened the study’s conclusions, providing actionable evidence for localized, risk-stratified perioperative protocols in Odisha [16].

Conclusion

Geriatric perioperative care in Odisha is challenged by "homeostenosis" and a high prevalence of ASA III/IV status (58%), with adverse outcomes primarily driven by physiological vulnerability—age ≥75 years (aOR 2.14) and ASA III/IV (aOR 3.42)—rather than the choice of anesthesia. Pharmacological precision is critical, as propofol doses >1.5 mg/kg significantly increase complication risks (aOR 2.56), while high rates of hemodynamic instability (23%) and neurocognitive issues (21% somnolence, 14% delirium) highlight the need for geriatric-specific dosing over standard protocols. Furthermore, the strong correlation between complications and preoperative anemia or abnormal ECGs (p < 0.001) confirms that physiological optimization is as vital as intraoperative management. To improve safety, we recommend implementing localized "geriatric-dose" induction cards and mandatory anemia correction, shifting from high-volume throughput to risk-stratified, patient-centered care to preserve functional independence and reduce socio-economic burdens in resource-constrained settings.

Declarations

Ethics approval and consent to participate

Not required as it is a retrospective study.

Data Availability

The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare that they have no competing interests.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Acknowledgments

None

Author Contributions

All authors contributed equally to the conceptualization, data collection, drafting of the manuscript, critical revision, and final approval of the version to be published.

Section

References
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References
  1. Li D. Emergency surgical conditions in geriatric patients: current research landscape. Int J Emerg Med. 2025 Dec 29;18(1):269. doi: 10.1186/s12245-025-01074-0.
  2. Sahu PR, Pradhan SK, Munda A, Padhan SC, Behera RR, Sahu LK, et al. Morbidity Pattern Among Elderly in an Urban Area of Burla, Odisha. Cureus. 2023 Apr 6;15(4):e37189. doi: 10.7759/cureus.37189.
  3. The Hindu. Odisha prepares to build geriatric caregiver pool amid rising elderly population [Internet]. 2024 Oct 7 [cited 2026 Apr 28]. Available from: https://www.thehindu.com/news/national/odisha/odisha-prepares-to-build-geriatric-caregiver-pool-amid-rising-elderly-population/article68729054.ece.
  4. Yadav S, Jahagirdar A, Jamwal P, Mishra J, Thind GBS, Shashank C, et al. Retrospective Study of Anesthesia-Related Complications in Elderly Patients Undergoing Surgery. J Pharm Bioallied Sci. 2024 Jul;16(Suppl 3):S2572-S2575. doi: 10.4103/jpbs.jpbs_253_24.
  5. Mourougan M, Singh AK, Mishra A, Behera BK, Patro BK. The patterns and determinants of healthcare utilisation of older adults in rural Odisha, India - a cross-sectional study. BMC Geriatr. 2025 Nov 26;25(1):966. doi: 10.1186/s12877-025-06706-x.
  6. Akhtar S, Heng J, Dai F, Schonberger RB, Burg MM. A Retrospective Observational Study of Anesthetic Induction Dosing Practices in Female Elderly Surgical Patients: Are We Overdosing Older Patients? Drugs Aging. 2016 Oct;33(10):737-746. doi: 10.1007/s40266-016-0394-x.
  7. Nishimura K, Hirata K, Noriaki F, Watabe A, Morimoto Y. The Relationship Between Age and the Propofol Dose for Anesthesia Induction: A Single-Center Retrospective Study Utilizing Neural Network Model Simulation. Applied Sciences. 2025; 15(11):6052. https://doi.org/10.3390/app15116052.
  8. Chrisant EM, Khamisi RH, Muhamba F, Mwanga AH, Mbuyamba HT. Assessing the accuracy of the revised Cardiac Risk Index compared to the American Society of Anaesthesiologists physical status classification in predicting Pulmonary and Cardiac complications among non-cardiothoracic surgery patients at Muhimbili National Hospital: a prospective cohort study. BMC Surg. 2024 Sep 14;24(1):263. doi: 10.1186/s12893-024-02536-7.
  9. Osswald PM, Meier C, Schmegg B, Hartung HJ. Komplikationen der Anaesthesie bei Patienten im höheren Lebensalter [Complications of anesthesia in elderly patients]. Anaesthesist. 1987 Jun;36(6):292-300. German.
  10. American Society of Anesthesiologists. Research round-up: anesthesia and the geriatric population [Internet]. Schaumburg (IL): American Society of Anesthesiologists; [cited 2026 Apr 28]. Available from: https://www.asahq.org/brainhealthinitiative/publications-news-videos/articlesandnews/researchroundupv
  11. Abebe MM, Arefayne NR, Temesgen MM, Admass BA. Incidence and predictive factors associated with hemodynamic instability among adult surgical patients in the post-anesthesia care unit, 2021: A prospective follow up study. Ann Med Surg (Lond). 2022 Jan 29; 74:103321. doi: 10.1016/j.amsu.2022.103321.
  12. Zhong G, Huang X, Li C, Wang D, Huang D, Sun M, Zhou Q, Guo Y. A multicenter retrospective study on anesthesia methods and their impact on neurocognitive outcomes and other complications in elderly patients undergoing hemiarthroplasty. Front Med (Lausanne). 2025 Aug 11; 12:1599989. doi: 10.3389/fmed.2025.1599989.
  13. Deiner S, Silverstein JH. Long-term outcomes in elderly surgical patients. Mt Sinai J Med. 2012 Jan-Feb;79(1):95-106. doi: 10.1002/msj.21288.
  14. Phillips AT, Deiner S, Mo Lin H, Andreopoulos E, Silverstein J, Levin MA. Propofol Use in the Elderly Population: Prevalence of Overdose and Association With 30-Day Mortality. Clin Ther. 2015 Dec 1;37(12):2676-85. doi: 10.1016/j.clinthera.2015.10.005.
  15. Staheli B, Rondeau B. Anesthetic Considerations in the Geriatric Population. [Updated 2023 Aug 5]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2026 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK572137/
  16. Wubet HB, Gobezie NZ, Deress GM, Mekuriaw BY, Abuhay AG, Afework WA, et al. Preoperative anaemia and its impact on immediate surgical outcomes in elderly patients: a multicentre prospective cohort study in Ethiopia. BMJ Open. 2025 Dec 12;15(12):e107636. doi: 10.1136/bmjopen-2025-107636.
  17. Yeung J, Patel V, Champaneria R, Dretzke J. Regional versus general anaesthesia in elderly patients undergoing surgery for hip fracture: protocol for a systematic review. Syst Rev. 2016 Apr 21;5:66. doi: 10.1186/s13643-016-0246-0.
  18. Ettoumi I, Pearce D, Wingert T, Delaporte A, Alexander B, Pal R, et al. Intraoperative hypotension and postoperative delirium among older high-risk patients undergoing major noncardiac surgery: a retrospective single-centre cohort study. BJA Open. 2025 Oct 15;16:100500. doi: 10.1016/j.bjao.2025.100500.
  19. Hu Y, Tang W, Jiang X. Prevalence and risk factors for postoperative delirium after hip fracture in the elderly: A systematic review and meta-analysis. Medicine (Baltimore). 2026 Jan 23;105(4):e47296. doi: 10.1097/MD.0000000000047296.
  20. Zietlow KE, Wong S, Heflin MT, McDonald SR, Sickeler R, Devinney M, et al. Geriatric Preoperative Optimization: A Review. Am J Med. 2022 Jan;135(1):39-48. doi: 10.1016/j.amjmed.2021.07.028.
  21. Bhavar T, Khunt M, Shetti AN. Geriatric anaesthesia: Challenges and recent updates – A review. Ann Geriatr Educ Med Sci. 2024;11(2):34-38].
  22. Sjoding MW, Luo K, Miller MA, Iwashyna TJ. When do confounding by indication and inadequate risk adjustment bias critical care studies? A simulation study. Crit Care. 2015 Apr 30;19(1):195. doi: 10.1186/s13054-015-0923-8.
  23. Agarwalla R, Saikia AM, Baruah R. Assessment of the nutritional status of the elderly and its correlates. J Family Community Med. 2015 Jan-Apr;22(1):39-43. doi: 10.4103/2230-8229.149588.
  24. Yale University. A Pilot Analysis of the Association Between Anesthesia Induction Dosing and AKI in the Elderly Population. ClinicalTrials.gov identifier: NCT03699696. Updated January 24, 2019
  25. Canales C, Wann L, Blitz J, Whittington R. The older adult surgical patient: a review of optimization and gaps in clinical practice. Perioper Med (Lond). 2025 Oct 3;14(1):104. doi: 10.1186/s13741-025-00593-x.
  26. Zietlow KE, Wong S, Heflin MT, McDonald SR, Sickeler R, Devinney M, et al. Geriatric Preoperative Optimization: A Review. Am J Med. 2022 Jan;135(1):39-48. doi: 10.1016/j.amjmed.2021.07.028.
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