PractIce pattern of INtraoperative FlUid therapy in elective major gastrointeStinal cancer surgEries in India (I-INFUSE): A multicentre observational study

Abstract

Background and Aims:

Intraoperative fluid therapy is crucial in optimising outcomes after major abdominal surgeries. However, clinical practices vary widely due to uncertainty of appropriate choice of fluid, amount, rate and strategy of fluid administration, and factors like preoperative fluid deficits and intraoperative losses in major abdominal surgeries.

Methods:

Institutional ethics committee approvals were taken, and this multicentric study was registered with the Clinical Trials Registry-India. In the 3-month observation period, 810 patients undergoing major gastrointestinal (GI) cancer surgery across 30 centres in India were included. Data collected included patient demographics, surgical and anaesthetic details, types and volumes of fluids administered intraoperatively, haemodynamic monitoring, blood loss, transfusions, postoperative complications measured by Clavien–Dindo (CD) classification and Comprehensive Complication Index (CCI), and 30-day readmission. Along with the descriptive statistics, multivariate regression analyses were done to identify predictors outcomes with significance set at P < 0.05.

Results:

The mean intraoperative fluid administration was 5.34 {standard deviation(SD)}ml/kg/h, and the mean total volume administered was 2648.5 (SD: 1486.6) mL. Postoperative complication rates graded CD ≥3 were observed in 7.9% of patients. Multivariate analysis revealed that lower preoperative serum albumin, higher fluid administration rates, greater blood loss, and intraoperative blood transfusions were independently associated with increased postoperative morbidity and higher CCI scores. Minimally invasive surgery correlated with shorter hospital stays.

Conclusion:

Fluid therapy practices in major GI cancer surgeries and the mean fluid administration rate of 5.34 (SD: 2.51) mL/kg/h in the intraoperative period at Indian cancer centres align largely with recent international consensus guidelines.

INTRODUCTION

Intraoperative fluid therapy plays a major role in improving outcomes of patients undergoing major surgeries.[1] Although intraoperative fluid therapy in various settings has been widely studied, there is considerable variation among anaesthesiologists in the choice of type, quantity, timing, and strategy of fluid therapy in the perioperative period while managing major gastrointestinal (GI) surgeries.[2] Factors like intravascular fluid deficits due to preoperative fasting and bowel preparation, and intraoperative insensible losses would further add to the uncertainty in major GI surgeries. The fluid therapy practices have evolved from liberal fluid strategy to restricted fluid strategy to goal-directed fluid therapy in the perioperative settings, mainly in major GI surgeries.[3] Overzealous fluid administration, like in liberal fluid strategy, has led to bowel oedema and cardiopulmonary complications,[4] and restrictive strategy for fluid therapy has led to hypoperfusion and acute kidney injury (AKI) in the perioperative period.[5] This led to the evolution of goal-directed fluid therapy (GDFT), which has shown improved perioperative outcomes.[6,7] Currently, an individualised approach to fluid therapy has been gaining attention in practice.[8] Along with the strategy, even the choice of fluid is a topic of debate in the perioperative setting. Many trials in critically ill patients have reported potential clinical side effects with the use of intravenous (IV) fluids, especially 0.9% NaCl (normal saline), which is associated with hyperchloraemic metabolic acidosis leading to subsequent renal injury.[9] Synthetic colloids are also associated with a decrease in renal function and coagulation. Use of balanced crystalloids in resuscitation has shown improved benefits in critical care settings.[10] The same knowledge has been extrapolated onto the perioperative settings, but the results were inconsistent. We therefore planned this multicentre study to determine the practice patterns of intraoperative fluid therapy for GI cancer surgeries in major cancer centres in India.

The primary objective was to study the amount of intraoperative administration of crystalloids and colloids at different major cancer centres in India. The secondary objectives were to examine the incidence of postoperative complications and length of hospital stays in these patients and to identify perioperative factors linked with postoperative outcomes in these patients.

METHODS

This multicentric point-prevalence study was conducted as a research activity of the Society of Onco-Anaesthesia and Perioperative Care (SOAPC). A total of 33 cancer care centres across India were selected and contacted, of which 30 centres participated. Institutional ethics committee approval was obtained from all participating centres prior to the enrolment of the first patient. The primary site, Tata Memorial Centre, Mumbai, received approval on 23 March 2023 (vide approval No. OIEC/4132/2023/0002). The study was registered with the Clinical Trials Registry- India (vide registration number CTRI/2023/04/052011, accessible at www.ctri.nic.in/). This study was performed in compliance with the Declaration of Helsinki, 2013 and Good Clinical Practice guidelines. This prospective multicentre observational study was conducted over a period of 3 months enroling all eligible patients undergoing major GI cancer surgeries.

All adult patients (18 years or older) and posted for elective open, laparoscopic or robotic GI cancer surgeries and those planned for liver resection surgeries were included in the study. Cytoreductive surgeries with hyperthermic intraperitoneal chemotherapy were excluded. Data from all consecutive eligible patients during 3 months were included.

Along with demographic data of the patient, preoperative data like comorbidities, Eastern Cooperative Oncology Group (ECOG) score, haemoglobin (Hb), and albumin were collected. Intraoperative data as in type of surgery (laparoscopic/open), type of anaesthesia, haemodynamic monitoring used, target mean arterial pressure (MAP), intraoperative highest and lowest MAP values and usage of vasopressors/inotropes, duration of surgery, blood loss, lowest intraoperative Hb, arterial blood gas values during and at the end of the surgery, urine output, duration of surgery, and postoperative destination of the patients were collected. The quantity and type of blood products and IV fluids were noted. The practice pattern of intraoperative fluid therapy across all included cancer centres was also analysed. Postoperative morbidity and mortality were reported as per Clavien–Dindo (CD) classification of surgical complications, duration of hospital stay, status of the patient at discharge, and readmission within 30 days of discharge, which were collected.

The sample size was determined with reference to the surgical workload of participating cancer centres. Previous hospital-level studies of GI cancer surgery demonstrate substantial variation in annual caseloads but indicate that high-volume centres routinely undertake large numbers of major GI surgeries.[11,12,13] Collectively, the 30 participating centres perform an estimated 3000 major GI cancer operations every 3 months; therefore, we aimed to enrol up to 900 patients (≈30 patients per centre) during the 3-month study window. This per-centre target represents a pragmatic and feasible fraction of routine surgical volume in Indian cancer centres. The data collection form was shared with all the participating centres. The data were collected in a 3-month window period.

All statistical analyses were conducted using International Business Machines Statistical Package for the Social Sciences Statistics for Windows, Version 26.0 (IBM Corp., Armonk, NY, United States of America). Categorical variables such as gender, American Society of Anesthesiologists (ASA) physical status, surgical approach, type of surgery, and performed surgery were summarised as frequencies and percentages, while continuous variables such as age, preoperative Hb, and albumin levels were expressed as mean [standard deviation (SD)] depending on data distribution, assessed using the Shapiro–Wilk test and visual inspection. The normality of continuous variables was assessed using the Shapiro–Wilk test and by examining skewness, kurtosis, and Q–Q plots. Age, preoperative Hb, and serum albumin were normally distributed (P > 0.05). The amount of fluid infused at each participating centre is measured with median [interquartile range (IQR)] and range. Associations between demographic, clinical, and intraoperative variables with postoperative outcomes, CD classification, Comprehensive Complication Index (CCI), and hospital stay, were explored using multivariate linear regression. Independent predictors were reported with regression coefficients (B), 95% confidence intervals (CIs), and P values, with significance set at P < 0.05. Each centre’s median intraoperative fluid rate was correlated with CCI score using Spearman’s rank correlation. All tests were two-tailed, and complete case analysis was performed for regression models.

RESULTS

The study cohort comprised 810 patients from 30 centres across India. Details of the centres are mentioned in Supplementary Table 1. Among the cohort, 43.3% were female and 56.7% were male. The mean age of the study population was 54.7 years (SD: 13.3). Most patients were of ASA class II (79.1%), with nearly 20.9% ASA III. Mean preoperative Hb was 11.3 g/dL (SD: 1.86), and the mean preoperative albumin level was 3.75 mg/dL (SD: 0.65). Open surgery was performed in 64% of the patients, and minimally invasive surgery was done in 36% of patients. Hemicolectomy and pylorus-preserving pancreaticoduodenectomy (PPPD) were the most common procedures. Details of the surgical procedure performed are mentioned in Table 1.

Supplementary Table 1.

Details of Cancer Care Centres participated in the study (alphabetically), Institutional Ethics Committee Approval number, Primary Authors, and Collaborators

Cancer Centre Name	City of India	Institutional Ethics Committee (IEC) Approval Number	Primary Author/s	Collaborator
All India Institute of Medical Sciences	Bathinda	IEC/AIIMS/BTI/407	Jyoti Sharma	Anju Grewal
All India Institute of Medical Sciences	Bhubaneswar	T/IM-NF/Anesth/22/174	Nitasha Mishra	Prasanta Kumar Das
All India Institute of Medical Sciences	Jodhpur	AIIMS/IEC/2023/5508	Priyanka sethi	Pradeep Kumar Bhatia
All India Institute of Medical Sciences	Rishikesh	AIIMS/IEC/23/34	Praveen Talawar	Dhatri Jonna
Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham	Kochi	IEC-AIMS-2023-Anest-33	Lakshmi Kumar	Anandajith Kartha
Asian Cancer Institute & Cumballa Hills Hospital	Mumbai	IFT-GI-001	Sanjay Upadhye	Esha Kodal
Basavatarakam Indo-American Cancer Hospital	Hyderabad	IEC/2023/51	Basanth Kumar Rayani	Vibhavari Naik
Bhagwan Mahaveer Cancer Hospital and Research Centre	Jaipur	BMH/2023/3734	Anjum Joad Khan	Ravi Shanker Sharma
Cancer Institute (WIA)	Chennai	IEC/2023/April03	Kalpana Balakrishnan	Punitha Chockalingan
Chittaranjan National Cancer Institute	Kolkata	CNCI-IEC-DC-46	Deepa Chakrabarti	Sayandeep Mandal
HCG Aastha Cancer Centre	Ahmedabad	IEC/17 April/2023	Kusuma Parikh	Bankim Shah
HCG Cancer Centre	Bengaluru	HIEC/126/23/01	Ramkiran K	Sunil Kumar
Homi Bhabha Cancer Hospital & Research Centre	Chandigarh	IEC/HBCH/100/23	Sofia Jaswal	Lalita Gouri Mitra
Homi Bhabha Cancer Hospital & Research Centre	Vizag	IEC/0723/12000043/001	Koilada Shiv Kumar	--
Kalyan Singh Super Speciality Hospital	Lucknow	KSSSCI/IEC/11/68/2023	Indubala Maurya	--
Kidwai Institute of Oncology	Bengaluru	KMIO/MEC/2023/04/F/AN/25	Namrata Ranganath	Shashidhar G S
King George Medical University	Lucknow	1516/Ethics/2023	Hemlata	Tanmay Tiwari
Max Nanavati Superspeciality Hospital	Mumbai	BNH/0249/2023	Rishikesh S Bhatti	Aditi Tilak
Max Superspeciality Hospital	New Delhi	SKT/IEC/ANAES/23-07	Raj Tobin	Sunny Kumar
MPMMCC & HBCH	Varanasi	OIEC/11000625/2023/00004	Jyotirmay Kirtania	Shreyasi Ray
National Cancer Institute	Nagpur	NCI/EC/2018/047/03/2023	Anuja Jain	Radhika Nair
Nizam’s Institute of Medical Sciences	Hyderabad	EC/NIMS/3172/2023	Indira Gurajala	Nirmala Jonnavithula
PD Hinduja Hospital and Medical Research Centre	Mumbai	IRB/1618/AL/23/50	Anjali Pingle	Suzanna Varghese
Post Graduate Institute of Medical Education & Research	Chandigarh	PGI/IEC/2023/EIC/000403	Kamal Kajal	Ashish Singh Aditya
Rajiv Gandhi Cancer Institute and Research Centre	Delhi	RGCRIC/IRB-BHR/22/2023	Shagun Bhatia Shah	Rajiv Chawla
Sanjay Gandhi Post Graduate Institute of Medical Sciences	Lucknow	2023-67-IP-130	Sandeep Sahu	Chetna Shamshery
Sir HN Reliance Foundation Hospital	Mumbai	HNH/IEC/2023/OCS/ANES/115	Tapas Mandal	Deepak Koli
Tata Medical Center	Kolkata	EC/WV/TMC/07/23	Jyotsna Goswami	Suparna Mitra Barman
Tata Memorial Centre – ACTREC	Navi Mumbai	OIEC/4132/2023/0002	Reshma Ambulkar Virinchi Sanapala	Malini Joshi
Tata Memorial Hospital	Mumbai	OIEC/4132/2023/0002	Sohan Lal Solanki Jigeeshu V Divatia	Vandana Agarwal

Table 1.

Baseline Demographic and Clinical Characteristics of the Study Cohort

Characteristic	Category	n (%) (n=810)
Gender	Male	459 (56.7)
	Female	351 (43.3)
ASA physical status	I	168 (20.7)
	II	479 (59.1)
	III	163 (20.1)
Age (years)	Mean (SD)	54.7 (SD: 13.3)
	Median (IQR)	56.0 (47-65)
Preoperative Haemoglobin	Mean (SD)	11.3 (SD: 1.86)
	Median (IQR)	11.3 (10.1-12.6)
Preoperative Albumin	Mean (SD)	3.75 (0.65)
	Median (IQR)	3.87 (3.3-4.2)
Surgical approach	Open	518 (64.0)
	Minimally invasive (MIS)	292 (36.0)
Type of surgery	Open	542 (66.9)
	Laparoscopic	146 (18.0)
	Robotic	73 (9.0)
	Minimally invasive + Open	26 (3.2)
	Not applicable	23 (2.8)
Surgery performed	Hemicolectomy	129 (15.9)
	PPPD	104 (12.8)
	Gastrectomy	90 (11.1)
	Radical cholecystectomy	90 (11.1)
	Others*	397 (49.0)

Data expressed as number of patients (percentages), mean (standard deviation) or median (interquartile range). *Miscellaneous includes abdomino-pelvic resection, anterior resection, low anterior resection, pancreatoduodenectomy, oesophagectomy, cytoreductive surgery, diagnostic laparoscopy, distal pancreatectomy, gastrointestinal stromal tumour excision, jejunostomy, total colectomy, retroperitoneal excision, and subtotal colectomy, among others. ASA=American Society of Anesthesiologists; MIS=minimally invasive surgery; PPPD=pylorus-preserving pancreaticoduodenectomy; SD=standard deviation; IQR=interquartile range

Invasive arterial pressure monitoring was done in 58.3% cases, while central venous catheters were inserted in 44% of cases. The peripherally inserted central catheter (PICC) was in situ in 62 (7.6%) patients, and in 21 patients, these PICCs were utilised intraoperatively for fluid administration [Supplementary Table 1]. In 75% patients, the target MAP was more than 65 mm Hg. The lowest recorded intraoperative MAP was 62.7 mmHg (SD: 9.8), while the highest recorded intraoperative MAP was 100.5 mmHg (SD: 14.5). Various GDFT tools were employed intraoperatively across centres in a total of 299 patients (36.9%). Among these, Pulse Pressure Variation (PPV) was the most commonly used modality (86.6%, n = 259). Other tools utilised included the arterial pressure-based cardiac output monitors (4.7%), Stroke Volume Variation (SVV) (3.6%), and Plethysmography Variability Index (PVI) (1.1%).

The mean total volume of intraoperative fluid administered was 2648.5 mL (SD: 1486.6) with a mean rate of 5.34 mL/kg/h (SD: 2.51). The median estimated fluid balance was 1350 mL (IQR 750–2100). Colloids were administered in 346 patients (42.7%), with a mean volume of 733.1 mL (SD: 592.2). The mean estimated blood loss was 515.9 mL (SD: 532.8) [Table 2].

Table 2.

Intraoperative fluid administration characteristics (n=810)

Variable	n	Mean (SD)
Total intraoperative volume (mL)	810	2648.5 (1486.6)
Fluid rate (mL/kg/h)	810	5.34 (2.51)
Total colloid volume (mL)	346	733.1 (592.2)
Estimated fluid balance (mL)	810	1526 (1126.2)
Estimated Blood Loss (mL)	810	515.95 (532.75)
Total Blood and Blood Product Transfusion	170	535.25 (377.52)

Data expressed as mean (standard deviation). SD=Standard Deviation

Blood or blood products were transfused in 170 patients (21%), with a mean transfusion volume of 535.3 mL (SD: 377.5). Ringer’s Lactate was the most frequently used crystalloid (70.9%), followed by acetate-based balanced salt solutions, used in 15.5% of the patients. Among the colloids, gelatin-based solutions were most common (47.7%), followed by albumin (32.6%).

Across 30 centres, the median intraoperative fluid administration rate varied widely, ranging from 2.50 to 8.50 mL/kg/h, with the corresponding mean values spanning 2.66 mL/kg/h (SD: 0.93) to 8.43 mL/kg/h (SD: 2.28). When centre-wise median fluid rates were correlated with postoperative outcomes, no significant association was observed with either mean CCI (ρ = 0.102, P = 0.604) or median CCI (ρ =0.172, P = 0.381) [Table 3 and Figure 1].

Table 3.

Correlation between centre-level fluid administration and postoperative complications (CCIs)

Variable compared with median intraoperative fluid rate (mL/kg/h)	Spearman’s ρ	P
Mean CCI per centre (n=30)	0.102	0.604
Median CCI per centre (n=30)	0.172	0.381

Centre-level analysis was performed by aggregating patient data (n=810) into 30 centres. Each centre’s median intraoperative fluid rate was correlated with either mean CCI or median CCI score using Spearman’s rank correlation. No significant association was observed. CCI=comprehensive complication index

Figure 1.

Centre-wise distribution of intraoperative fluid administration rates (mL/kg/h). Boxplots showing the distribution of intraoperative fluid administration rates across 30 participating centres. Each box represents the interquartile range (IQR), the red line indicates the median, and the whiskers show the minimum and maximum values. Centres are anonymised and labelled 1–30 on the X-axis

No postoperative complication occurred (CD grade 0) in 44.0% of patients. Grade 1 and 2 complications accounted for 32.6% and 14.4%, respectively, while grade 3 or higher was seen in 7.9%. The mean hospital stay was 9.3 days (SD: 6.4). Thirty-day readmission occurred in 4.7%. The mean of CCI was 9.6 (SD: 14.1) [Table 4].

Table 4.

Postoperative outcome measures

Outcome measure	n (%) or Mean (SD)	Median (IQR)
Clavien–Dindo classification
Grade 0	356 (44.0)	–
Grade 1	264 (32.6)	–
Grade 2	117 (14.4)	–
Grade 3A	30 (3.7)	–
Grade 3B	18 (2.2)	–
Grade 4A	10 (1.2)	–
Grade 4B	6 (0.7)	–
Grade 5	9 (1.1)	–
Comprehensive Complication Index (CCI)	9.57 (SD: 14.08)	8.7 (0-12.4)
Hospital stay (days)	9.3 (SD: 6.4)	8.0 (5-11)
30-day readmission	38 (4.7)	–

Data expressed as mean (standard deviation) or median (interquartile range). SD=Standard deviation, IQR=interquartile range

On multivariate analysis, lower preoperative serum albumin [B = –0.304 (95% CI: –0.515; –0.093), P = 0.005], higher intraoperative fluid administration rate [B = 0.044 (95% CI: 0.005;0.083), P = 0.027], perioperative blood transfusion [B = 0.288 (95% CI: 0.037; 0.539), P = 0.025], and greater estimated blood loss [B = 2.40 × 10⁻⁴ (95% CI: 2.9 × 10⁻⁵; 4.51 × 10⁻⁴), P = 0.027] were independently associated with higher CD complication grades. Conversely, higher age [B = 0.047 (95% CI: 0.012; 0.082), P = 0.008], higher intraoperative fluid volume [B = 0.673 (95% CI: 0.485; 0.861), P < 0.001], and a minimally invasive surgical approach [B = –1.540 (95% CI: –2.507; –0.573), P = 0.002] were significantly associated with shorter hospital stay [Tables 5a and b].

Table 5a.

Multivariate Linear Regression Analysis for Factors Associated with Postoperative Outcomes (Clavien–Dindo Classification)

Variable	Clavien–Dindo Classification B (95% CI)	P	Hospital Stay (days) B (95% CI)	P
Age	0.005 (–0.002; 0.012)	0.168	0.047 (0.012; 0.082)	0.008
ASA class	0.102 (–0.052; 0.256)	0.198	–0.018 (–0.771; 0.735)	0.962
Preoperative Haemoglobin	0.046 (–0.006; 0.098)	0.083	0.079 (–0.174; 0.332)	0.541
Preoperative Albumin	–0.304 (–0.515; –0.093)	0.005	–0.776 (–1.803; 0.251)	0.139
ECOG Score	0.096 (–0.024; 0.216)	0.118	–0.098 (–0.683; 0.487)	0.742
Surgical Approach (Open vs Laparoscopic vs Robotic Assisted)	–0.046 (–0.243; 0.151)	0.649	–1.540 (–2.507; –0.573)	0.002
Estimated Blood Loss (mL)	2.40×10⁻⁴ (2.9×10⁻⁵; 4.51×10⁻⁴)	0.027	0.001 (–0.001; 0.003)	0.182
Blood Transfusion	0.288 (0.037; 0.539)	0.025	0.333 (–0.891; 1.557)	0.594
Total IV Fluid Volume (ml/kg/h)	0.044 (0.005; 0.083)	0.027	0.673 (0.485; 0.861)	<0.001

ASA=American Society of Anesthesiologists; ECOG=Eastern Co-operative Oncology Group; CI=Confidence interval; IV: Intravenous

Table 5b.

Multivariate Linear Regression Analysis of Factors Associated with Postoperative Outcomes (Comprehensive Complication Index)

Variable	Comprehensive Complication Index (CCI) Score (95% CI)	P
Age	0.069 (–0.013; 0.150)	0.098
ASA class	0.473 (–1.250; 2.195)	0.590
Pre-op Serum Albumin	–3.339 (–5.374; –1.303)	0.001
Pre-op Haemoglobin	0.535 (–0.063; 1.133)	0.079
ECOG Score	0.728 (–0.614; 2.071)	0.287
Estimated Blood Loss (ml)	0.002 (0; 0.005)	0.022
Surgical Approach	−0.455 (−2.678; 1.769)	0.688
Total IV fluid volume (mL/kg/h)	0.450 (0.005; 0.894)	0.047
Blood Transfusion	3.346 (0.536; 6.155)	0.020

ASA=American Society of Anesthesiologists; ECOG=Eastern Co-operative Oncology Group; IV=Intravenous; CI=Confidence interval; Pre-op=Preoperative

DISCUSSION

In our study, the mean intraoperative fluid administration rate was 5.33 mL/kg/h, which lies between the traditionally defined liberal and restrictive fluid administration rates. While liberal and restrictive fluid strategies have been studied extensively, a randomised controlled trial (RELIEF Trial) did not demonstrate any advantage in disability-free survival between the two methods.[5] However, it did report a higher incidence of AKI in the restrictive fluid group. Therefore, striking a balance between liberal and restrictive fluid administration appears to be ideal for optimal perioperative fluid management in major non-cardiac surgeries.

A wide variation in fluid administration rates was observed in our cohort, ranging from 2.5 ml/kg/h to 8.5 ml/kg/h across all centres. Although this variation was not significantly associated with postoperative morbidity, the variability in practice likely reflects the influence of institutional protocols, which are often tailored for different surgeries based on available resources and prior experience, both in terms of the total volume and type of fluid infused. However, the individual discretion of an anaesthesiologist cannot be overlooked.

Recent consensus guidelines on perioperative fluid administration recommend the use of buffered crystalloid solutions and advise against the routine use of synthetic colloids or albumin during intraoperative care.[14] Positive fluid balance at 24 hours post-surgery or at the end of the surgical procedure holds significant clinical relevance. It is generally recommended to aim for a positive fluid balance of 1 to 2 litres at the end of the case.[14] The findings from our study are consistent with this recommendation, showing a mean estimated positive fluid balance of 1326 mL at the end of surgery. The total amount of intraoperative fluid, fluid administration rate, and estimated positive fluid balance have been associated with adverse postoperative outcomes, including increased postoperative complications and prolonged hospital stays, as demonstrated in several studies.[15,16,17,18,19] Our findings support this association; the total rate of fluid infusion was independently linked with higher rates of severe postoperative complications and extended hospital stays.

Despite current guidelines discouraging the routine use of colloids, 42.7% (N = 346) of patients in our study received them.[11] This likely reflects clinical decisions tailored to specific intraoperative patient needs such as hypoalbuminaemia, third spacing, or the requirement for rapid volume expansion in haemodynamically unstable patients. Furthermore, the translation of guidelines into clinical practice is often adapted according to institutional protocols, which are influenced by resource availability and clinician experience. In some cases, albumin was used specifically for patients with pre-existing liver disease. The rationale behind the decision to administer colloids was not studied further in this cohort.

Misaki Takahashi et al.[20] observed similar results in patients undergoing oesophagectomy, where higher total fluid infusion volumes were associated with increased incidence of anastomotic leaks. Likewise, Piia Peltoniemi et al.[21] found that lower intraoperative fluid volumes were associated with fewer complications and shorter hospital stays after pancreaticoduodenectomy, which aligns with our findings. Additionally, Voldby et al.[22] reported that a perioperative fluid balance under 2.5 litres was associated with a lower risk of overall and cardiopulmonary complications following emergency GI surgery. Consistently, our study showed that a higher estimated positive fluid balance correlated with increased severity of postoperative complications and longer hospital stays.

Given the wide range of recommendations, such as GDFT,[23] Enhanced Recovery After Surgery (ERAS) protocols,[24] and individualised fluid management,[25] each with its own implementation challenges, an integrated approach incorporating elements of all these strategies, underpinned by institutional protocols and appropriate monitoring, may offer the best compromise.[8] This approach could optimise patient safety and surgical outcomes by minimising postoperative morbidity and length of hospital stay. Recent ERAS Society guidelines advocate for maintaining a slightly positive fluid balance on the day of surgery, moving away from earlier “near-zero” balance strategies. GDFT, particularly when integrated with inotropes or vasopressors in moderate- to high-risk patients, has consistently demonstrated reductions in postoperative morbidity, shorter hospital stay, and improved bowel recovery, especially when embedded in ERAS protocols. These findings underscore the importance of individualised, haemodynamic-guided fluid management rather than uniform liberal or restrictive strategies, highlighting fluid therapy as a key implementable target for improving outcomes in GI cancer surgery.[26]

The strengths of our study include its large, multicentre design and the use of a validated outcome measure of postoperative morbidity, such as the CD classification, as well as the CCI. The inclusion of multiple centres enhances the generalisability of our findings. Nevertheless, the study has certain limitations. As an observational study with a restricted data collection window, it does not allow for the establishment of causal relationships. The short study duration precludes the evaluation of long-term outcomes in the oncological patients. Additionally, centre-specific practices and unmeasured confounding variables may have influenced the findings. Further prospective, randomised studies are needed to confirm these associations and to define optimal intraoperative fluid management strategies in major GI cancer surgeries. In addition, long-term outcome studies are required to evaluate the impact of intraoperative fluid administration on survival, recurrence, and disease progression.

CONCLUSION

In this multicentre observational study, we evaluated the perioperative fluid administration practices across major cancer care centres in India and found them to be largely aligned with the most recent consensus guidelines on perioperative fluid management in major non-cardiac surgeries. Several perioperative factors, including preoperative serum albumin, higher intraoperative fluid administration rates, higher estimated blood loss, and intraoperative blood transfusion, were associated with increased postoperative complications.

Study data availability

De-identified data may be requested with reasonable justification from the authors (email to the corresponding author) and shall be shared after approval as per the authors’ institution’s policy.

Disclosure of use of artificial intelligence (AI)-assistive or generative tools

The AI tools or language models (LLM) have not been utilised in the manuscript, except that software has been used for grammar corrections.

Declaration of use of permitted tools

No copyrighted figure or table was used in this manuscript.

Supplementary material

This article has supplementary material and can be accessed at this link. Supplementary Material at http://links.lww.com/IJOA/A70.

Conflicts of interest

Dr. Sohan Lal Solanki, who is the first and the corresponding author of this manuscript, and Dr Indubala Maurya, who is one of the co-authors are Editorial Board members of this journal. Dr Jigeeshu V Divatia served as past Editor-in-Chief of this journal. They were not involved in the decision making process, and an independent editor handled this manuscript. The authors declare that they have no other conflicts of interest.

Funding Statement

Nil.