While advances in surgical techniques and perioperative care have improved patient outcomes, a subset of orthopaedic patients continues to experience significant perioperative complications, necessitating postoperative intensive care unit (ICU) admission. This requirement for critical care reflects the interplay between patient-specific factors, pre-existing comorbidities, intraoperative events, and the complexity of surgical and anaesthetic management.

Preoperative comorbidities such as hypertension, diabetes mellitus, chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), and ischemic heart disease (IHD) are recognized risk factors that negatively influence surgical outcomes. These conditions contribute to impaired wound healing, increased susceptibility to infections, perioperative hemodynamic instability, and delayed recovery, thereby elevating the risk of postoperative complications and ICU admission [1,2]. In particular, elderly patients and those with multiple comorbidities are more vulnerable to complications, including respiratory failure, cardiac events, and renal dysfunction, which can compromise postoperative stability [3].

Anaesthesia-related adverse events such as hypotension, hypoxia, cardiac arrhythmias, and allergic reactions also contribute significantly to the need for postoperative critical care [4]. The type of anaesthesia, especially the use of general anaesthesia over neuraxial techniques, has been associated with increased risk of postoperative cardiopulmonary complications [5]. Intraoperative factors such as prolonged surgical duration, excessive blood loss, and fluid imbalance further exacerbate postoperative risks, particularly in high-risk individuals [3,6].

Numerous studies have demonstrated that unplanned ICU admissions following orthopaedic surgery are often linked to inadequate preoperative risk assessment or unforeseen intraoperative complications. For instance, patients with high ASA physical status scores or poor functional reserve are more likely to experience perioperative instability [3,7]. Moreover, lifestyle-related factors such as smoking and obesity have been independently associated with a greater incidence of pulmonary complications, longer ICU stay, and delayed postoperative recovery [4,8].

Recognizing the need for a structured approach to perioperative care, especially in high-risk orthopaedic populations, this study aims to evaluate the demographic, clinical, and intraoperative factors contributing to postoperative ICU admissions. By identifying modifiable risk factors and high-risk profiles, the study seeks to enhance preoperative optimization, guide intraoperative vigilance, and inform postoperative monitoring protocols. Such evidence-based interventions are essential to reduce ICU utilization, lower morbidity, and improve patient safety and resource allocation.

Study Design and Setting: This retrospective observational study was conducted in the Department of Anaesthesiology at Shree Krishna Hospital, Karamsad, Gujarat. The study evaluated the clinical profiles and perioperative factors associated with intensive care unit (ICU) admission in patients undergoing orthopaedic surgery. Data were collected over a three-year period, from January 2021 to December 2023.

Study Population: The study population comprised patients who underwent orthopaedic surgical procedures and were subsequently shifted to the ICU during the postoperative period. Only patients who did not require ICU admission prior to surgery were included in the analysis. Both elective and emergency orthopaedic surgeries were considered.

Inclusion and Exclusion Criteria: The study included patients aged 18 years and above who underwent orthopaedic surgery at Shree Krishna Hospital and subsequently required postoperative admission to the intensive care unit (ICU), either directly from the operation theatre or following initial stabilization in the post-anaesthesia care unit (PACU). Patients were excluded if they had been admitted to the ICU prior to surgery or if their clinical records were incomplete or missing, thereby limiting the availability of essential data for analysis.

Data Collection: Data were retrieved from both electronic medical records and physical patient files maintained by the Medical Records Department. Each patient’s preoperative, intraoperative, and postoperative clinical parameters were thoroughly reviewed and documented in a structured data collection form. Specific focus was given to identifying comorbidities, anaesthesia and surgical events, and indications for postoperative ICU transfer.

The following variables were systematically recorded for each patient enrolled in the study. Demographic parameters included age, gender, and body mass index (BMI). Clinical history encompassed the presence of addictions such as tobacco use, alcohol consumption, and smoking, along with documentation of known comorbidities, including hypertension, diabetes mellitus, ischemic heart disease, hypothyroidism, chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), and obesity. Operative details were noted, specifying the type of surgical procedure (categorized as upper limb, lower limb, or spinal surgeries), the type of anaesthesia administered (general anaesthesia [GA], spinal anaesthesia [SA], or a combination of spinal and epidural anaesthesia [SA+EA]), and the total duration of surgery. Additionally, any intraoperative events such as cardiac, pulmonary, renal, or surgical complications, as well as anaesthetic-related adverse reactions, were documented. The American Society of Anesthesiologists (ASA) physical status classification was also recorded to assess the preoperative physical condition of the patients.

Outcome Measures: The primary outcome was postoperative admission to the ICU and its associated perioperative factors. The reasons for ICU transfer were assessed in the context of preoperative risk factors and intraoperative complications.

Statistical Analysis: Data were compiled and entered into Microsoft Excel 2016. Descriptive statistics were used to summarize patient demographics and clinical characteristics. Categorical variables were presented as frequencies and percentages. Data were visualized using bar and pie charts. Further statistical analysis was performed using STATA software version 14.2.

The demographic and baseline clinical characteristics of the study population are presented in Table 1. A majority of patients were aged 60 years or above, and the gender distribution was nearly equal. Most individuals had a body mass index (BMI) within the range of 18 to 27.5 kg/m². Regarding addiction history, over half the patients reported no addiction, while smoking was the most commonly reported form of substance use among those with addiction.

Table 1: Age, Gender, BMI, and Addiction Data

The distribution of surgical interventions and anesthesia types is summarized in Table 2. The majority of patients underwent lower limb surgeries, with a small proportion receiving upper limb or spinal procedures. General anesthesia was the most frequently administered anesthetic technique, followed by spinal anesthesia, while a combination of spinal and epidural anesthesia was less commonly employed.

Table 2: Operative Procedure and Type of Anesthesia

Operative parameters are detailed in Table 3. Most surgeries extended beyond two hours, and the majority of patients were classified under higher American Society of Anesthesiologists (ASA) grades (III–V), reflecting a significant systemic disease burden among the cohort.

Table 3: Operation Duration and ASA Grading

Pre-existing comorbidities and intraoperative complications are outlined in Table 4. Hypertension was the most prevalent comorbidity, followed by diabetes mellitus, chronic obstructive pulmonary disease (COPD), ischemic heart disease, and hypothyroidism. A notable proportion of patients also had obesity or chronic kidney disease (CKD). Intraoperative complications were frequently reported, with hypotension being the most common cardiac event, followed by electrocardiographic changes and intraoperative hypertension. Pulmonary complications such as hypoxia were observed in a substantial proportion of patients. Renal complications, though less frequent, included reduced urine output and electrolyte disturbances. Intraoperative blood loss exceeding one litre was a significant finding in half of the cases, while only a small fraction experienced intraoperative allergic reactions.

Table 4: Comorbidity and Intraoperative Complication Data

This retrospective study was conducted to assess the perioperative factors associated with postoperative ICU admission in orthopaedic surgery patients. Among the 46 patients evaluated, a substantial proportion (63%) were aged over 60 years, indicating that advanced age is a significant risk factor for postoperative critical care requirement. Similar observations were reported by Chikuda et al., who demonstrated that age above 80 years was associated with higher rates of postoperative complications and mortality in orthopaedic patients [9]. Likewise, Schoenfeld et al. found that increasing age significantly elevated the risk of mortality and complications after spinal arthrodesis [10]. The findings are also in concordance with Bhatt et al., who identified older age as a predictor for postoperative ICU admission following major surgeries [11].

Body mass index (BMI) also showed a considerable association with ICU requirement in this study. Patients with a BMI over 23 kg/m² constituted approximately half of the ICU admissions. In line with this, Childs et al. reported that obese orthopaedic trauma patients experienced more perioperative complications, longer ICU stays, and increased hospital stays compared to their non-obese counterparts [12]. These findings reinforce the need for BMI-based risk stratification and preoperative optimization.

Addiction, especially smoking and tobacco use, was another relevant factor in this cohort, with nearly 35% of patients having some form of substance use history. Møller et al. highlighted that patients with significant smoking history had higher ICU admission rates due to postoperative pulmonary complications and increased mortality, even among ex-smokers with high pack-year exposure [13].

Comorbid conditions played a central role in determining postoperative outcomes. Hypertension was present in nearly 70% of patients, followed by diabetes mellitus, COPD, IHD, and hypothyroidism. J W Roche et al. found that the presence of multiple comorbidities increased the risk of chest infections, heart failure, and perioperative mortality after hip fracture surgery [14]. Schoenfeld et al. also showed that comorbidities such as pulmonary conditions and low albumin were independent predictors of mortality, complications, and infections [10]. Similarly, Jain et al. reported that hypertension, diabetes, and obesity significantly increased the rate of complications and non-home discharge after arthroplasty procedures [15].

Intraoperative complications were prevalent in this study. Hypotension was the most frequent cardiac complication, followed by ECG changes and intraoperative hypertension. Bhatt et al. and Patel et al. emphasized that intraoperative hypotension and tachycardia requiring inotropic support were strong predictors for unplanned ICU admissions [11,16]. Pulmonary complications, particularly hypoxia, were also significant in this study. Melamed et al. noted that respiratory failure and pulmonary complications often necessitated ICU transfer and were associated with increased mortality and healthcare costs in orthopaedic patients [17].

Renal complications such as reduced urine output and electrolyte imbalance were less frequent but clinically relevant. White et al. emphasized the impact of preoperative anaemia and its correlation with renal dysfunction, postoperative infections, and unplanned ICU admissions in low-resource settings [18].

Surgical complications, notably blood loss exceeding 1 litre, were recorded in 50% of patients, underlining the need for meticulous intraoperative haemostasis. In addition, the duration of surgery and ASA grading were both found to be linked to postoperative ICU requirement. Quinn et al. reported that longer surgery durations (>4 hours) and higher ASA physical status were major contributors to ICU transfer in orthopaedic and non-orthopaedic surgical patients [19].

Finally, lifestyle and procedural factors such as the use of general anaesthesia over regional techniques and smoking history were independently linked to ICU admission. Hosam Abdel Salam et al. confirmed that older age, general anaesthesia, smoking, and cemented arthroplasty were predictors of postoperative ICU utilization [20]. Similarly, Onwochei et al., in a systematic review, identified age, ASA score, BMI, comorbidity burden, emergency surgery, and operative duration as consistent risk factors across various surgical populations [21].

The results of this study align with existing literature and emphasize the importance of preoperative risk assessment, patient optimization, vigilant intraoperative management, and tailored postoperative monitoring strategies. Addressing modifiable risk factors may significantly reduce unplanned ICU admissions and improve surgical outcomes in orthopaedic patients.

Based on the retrospective analysis, the study identified multiple perioperative factors contributing to postoperative ICU admissions in orthopaedic surgical patients. Advancing age, higher BMI, and pre-existing comorbidities such as hypertension, diabetes, and COPD were prominently associated with increased ICU requirements. Intraoperative complications including hypotension, hypoxia, and significant blood loss were major determinants necessitating critical care. The findings highlight the importance of thorough preoperative evaluation, risk stratification, and vigilant intraoperative monitoring to mitigate ICU admissions. Implementing targeted preventive strategies can improve surgical outcomes and optimize the utilization of critical care resources.

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