Mini-teams

For the process of data collection within different subspecialties, mini-teams of up to three collaborators can register from each centre. Each mini-team per subspecialty will collect data on all consecutive patients presenting in a 1 month patient recruitment period.

• Multiple mini-teams can recruit patients across different subspecialties at the same centre, irrespective of whether they recruit patients in the same or distinct 1 month patient recruitment periods.

• Multiple mini-teams can recruit patients in the same subspecialty during distinct 1 month patient recruitment periods.

• Collaborators can be part of multiple mini-teams collecting data across different subspecialties.

  • Collecting data across multiple specialties will make collaborators eligible for potentially more authorship opportunities (see the ‘Authorship’ section).

Each subspecialty must be supervised by at least one consultant who can facilitate study setup, local approvals, patient recruitment, data collection and submission.

Study duration

The patient recruitment window for PakSurg 1 will proceed from 20 September 2022 to 31 March 2023 (with the last patient followed up till 30 April 2023; figure 1). This recruitment period will include patients undergoing specific surgeries for the included subspecialties as highlighted in online supplemental appendix 1—Included Procedures. Each mini-team will recruit all consecutive patients within their scope of practice for a particular subspecialty during their selected 1 month period. All patients will be evaluated till 30 days postoperatively for outcome assessment.

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Figure 1

Study timeline for PakSurg 1

Centre inclusion criteria

• Hospitals that perform elective surgeries.

Eligibility criteria for patients

Outcomes

Operational definitions

SSI (superficial incisional, deep incisional or organ space): PakSurg 1 will use the 2023 Centre for Disease Control definitions of SSIs.15 The definitions are abridged as follows:

1. Superficial incisional SSI (must meet the following criteria):

   • Date of event occurs within 30 days following the National Healthcare Safety Network (NHSN operative procedure (where day 1=the procedure date).

   • Involves only skin and subcutaneous tissue of the incision.

   • Patient has at least one of the following:

     • Purulent drainage from the superficial incision.

     • Organism(s) identified from an aseptically obtained specimen from the superficial incision or subcutaneous tissue by a culture or non-culture-based microbiological testing method which is performed for purposes of clinical diagnosis or treatment (eg, not Active Surveillance Culture/Testing [ASC/AST]).

     • A superficial incision that is deliberately opened by a surgeon, physician* or physician designee and culture or non-culture-based testing of the superficial incision or subcutaneous tissue is not performed and patient has at least one of the following signs or symptoms: localised pain or tenderness; localised swelling; erythema or heat.

     • Diagnosis of superficial incisional SSI by a physician* or physician designee.

2. Deep incisional SSI (must meet the following criteria):

   • Date of event occurs within 30 days** following the NHSN operative procedure (where day 1=the procedure date) according to the list in Table 2 from the Centre of Disease Control’s National Healthcare Safety Network January 2023 protocol on SSI events.15

   • Involves deep soft tissues of the incision (eg, fascial and muscle layers).

   • Patient has at least one of the following:

     • Purulent drainage from the deep incision.

     • A deep incision that is deliberately opened or aspirated by a surgeon, physician* or physician designee or spontaneously dehisces.

       • Organism(s) identified from the deep soft tissues of the incision by a culture or non-culture-based microbiological testing method which is performed for purposes of clinical diagnosis or treatment (eg, not ASC/AST) or culture or non-culture-based microbiological testing method is not performed. A culture or non-culture-based test from the deep soft tissues of the incision that has a negative finding does not meet this criterion.

       • Patient has at least one of the following signs or symptoms: fever (>38°C); localised pain or tenderness.

     • An abscess or other evidence of infection involving the deep incision detected on gross anatomical examination, histopathological examination or imaging test.

3. Organ/Space SSI (must meet the following criteria):

   • Date of event occurs within 30 days** following the NHSN operative procedure (where day 1=the procedure date) according to the list in Table 2 from the Centre of Disease Control’s National Healthcare Safety Network January 2023 protocol on SSI events15 and involves any part of the body deeper than the fascial/muscle layers that is opened or manipulated during the operative procedure.

   • Patient has at least one of the following:

     • A purulent drainage from a drain placed into the organ/space (eg, closed suction drainage system, open drain, T-tube drain CT-guided drainage).

     • Organism(s) identified from fluid or tissue in the organ/space by a culture or non-culture-based microbiological testing method which is performed for purposes of clinical diagnosis or treatment (eg, not ASC/AST).

     • An abscess or other evidence of infection involving the organ/space detected on gross anatomical examination or histopathological examination or imaging test evidence definitive or equivocal for infection; meets at least one criterion for a specific organ/space infection site listed in Table 3 from the Centre of Disease Control’s National Healthcare Safety Network January 2023 protocol on SSI Events.15

*The term physician for the purpose of application of the NHSN SSI criteria may be interpreted to mean a surgeon, infectious disease physician, emergency physician, other physician on the case or physician’s designee (nurse practitioner or physician’s assistant).

**One important differentiation between the SSI criteria used in our study and that reported by the CDC is that we use a 30 day cut-off for postoperative SSI identification for all operations. This is because the 90 day surveillance required to identify SSIs after some operations is extremely unfeasible in many hospitals in Pakistan, as most of these centres do not have structured surveillance systems or electronic medical records.

1. Emergency procedures: unplanned, non-elective procedures, including reoperations following previous procedures.

2. Postoperative mortality rate: mortality till the 30th day of index surgery.

3. 30 day unexpected reintervention: operative, endoscopic or radiological reintervention after skin closure till the 30th day postoperatively. Relook surgeries planned at the time of original operation are not to be included in ‘unexpected’ reinterventions.

4. Other healthcare-associated infection: an infection that was not present or not incubating at the time of admission but occurs while the patient is receiving care in a hospital or other healthcare facility. These can also be referred to as nosocomial infections. Infections other than SSI are to be included in this category. Healthcare-associated infection was defined as infection first occurring a minimum of 48 hours after admission or within 30 days of discharge.16

5. Inpatient: refers to the hospital admission for the index surgery.

6. Antimicrobial resistance: resistance in the species presumed to be pathological to the antimicrobial used for prophylaxis.

Sample size estimation

According to existing literature, incidence rate of SSIs in Pakistan ranges from 9.3% to 33.6% across multiple subspecialties.4 10–13 Assuming an unlimited population size, we estimated a sample size of 1845 patients to estimate incidence rate of SSIs with a 95% CI, 5% precision and 20% inflation rate for loss-to-follow-up using the Sample Size Calculator by the WHO.

Consecutive patients identification

Collaborators are primarily expected to review theatre logbooks/operating lists from all potential operating theatres daily to identify all eligible patients. Additionally, they can also review handover sheets or ward lists. All consecutive patients presenting in selected 1 month periods are to be recruited.

Data collection

Follow-up and outcome assessment

1. Follow-up during the inpatient hospital stay: designated hospital staff should actively monitor each patient for signs of infection. This can be achieved by direct observation or by daily file/record review, as follows:

   1. Liaising with ward staff and reviewing medical and nursing records regularly to identify signs and symptoms related to SSIs.

   2. Reviewing microbiology reports for any positive surgical site cultures, and checking with the hospital ward to identify why cultures were taken and if there were any signs of infection.

2. Detecting hospital readmissions: collaborators should devise systems to identify patients included in the study that are subsequently readmitted to their hospital. The following measures could be taken to identify such patients:

   1. Coordinating with hospital admission services to flag identifying information (name, medical record number) for patients included in the study, so that they may be identified if readmitted within 30 days.

   2. Monitor patient electronic health records (if available) to check if patient is readmitted.

   3. Direct inquiry of the patient during telephonic follow-up (detailed below).

3. Post-discharge outpatient clinic follow-up:

   1. Identifying information (name, medical record number) for included patients should be flagged to notify collaborators of outpatient or emergency department visits.

4. Post-discharge telephonic follow-up:

   1. Patients included in this study should be contacted by collaborators telephonically on the third, 15th and 30th day of surgery.

   2. Telephonic interviews should be in accordance with the attached online supplemental appendix 5—Telephonic Follow-Up (English) and online supplemental appendix 6—Telephonic Follow-Up (Urdu), which is based on the SSI surveillance protocol by the PHE.17

Given the differences in clinical care pathways and hospital resources across different centres, follow-up assessments should be structured around the pre-existing patient follow-up pathways for each hospital. All collaborators will describe methods used for obtaining follow-up data at their respective centres.

Data submission

Data collected by the collaborators will be submitted via a secure network based on the Redcap system (http://project-redcap.org/), which will be provided by Aga Khan University (AKU), Karachi. Redcap is being employed globally to gather research-related data in a secure way.18 We will configure our questionnaire on Redcap with several quality checks to ensure data are entered correctly and avoid potential errors.

Designated collaborators at each participating site will be provided access to the Redcap project server by the steering committee. This will allow them to submit the data they have collected. Collaborators will create a record for each patient on Redcap, and each record will be automatically assigned a Redcap ID. Collaborators should maintain an encrypted Microsoft Excel sheet to link Redcap IDs to specific patient identification numbers for their own use (please see the template provided on website).

Redcap accounts will be set up using the data access groups feature. This would ensure that collaborators have access to the data submitted by their own mini-team and not to the data submitted by other mini-teams. Only members from the Writing and Analysis Team and Operations Team of the steering committee will have access to all data.

Data transmission will be anonymous, and no patient identifiers will be submitted via Redcap. Furthermore, no hospital identifiers will be published; only aggregated results will be disseminated.

Data validation

Independent data validators will be recruited for data validation. These validators may be identified by the local teams, provided they were not part of any team involved in primary data collection. Validation will be performed in two phases:

1. Case completeness: case completeness will be assessed in 50% of hospitals randomly selected from participating hospitals. Independent data validators will confirm the number of eligible cases in specified periods at the participating sites. The steering committee will cross-check this with the number of patients submitted to assess the site-specific capture rate. These case ascertainment rates will be compared between provinces, public and private hospitals, and secondary and tertiary case healthcare services. Case ascertainment rate correlations (number of patients identified by validator vs number of records entered by the collaborators) will be assessed. A case ascertainment >80% will be deemed acceptable at the level of individual hospitals. Hospitals not meeting this criterion will be excluded from analysis.

2. Data accuracy: assessment of data accuracy will be performed for 25% cases randomly selected from total cases enrolled by each hospital. An independent data validator will be provided Redcap IDs of selected patients. Each validator will be responsible for obtaining patient identifiers corresponding to Redcap IDs from local data collection teams and extracting the following variables from patient records.

   1. Patient variables: age and gender

   2. Operation variables: indication and operative approach

   3. Outcome variables: 30-day mortality and unexpected reintervention

Data extracted by validators will be compared with that extracted by local data collectors for degree of agreement. This will be assessed using Cohen’s Kappa coefficient for categorical variables and Pearson correlation for age. Data accuracy will be assessed for hospitals nationwide and individual provinces. Data accuracy ≥95% will be deemed acceptable at hospital-level, and hospitals not meeting this criterion will be excluded from analysis.

Statistical analysis

All analyses will be conducted using the IBM Statistical Package for Social Sciences (SPSS) version 26. Continuous variables will be converted to categorical variables and presented as frequencies (percentages). Differences among clinicodemographic groups will be assessed via χ² test. Fisher’s exact test will be used when conditions for χ² tests are not met. Missing data will be included in flowcharts and summary tables, allowing denominators to remain consistent in calculations.

We plan to use the National Nosocomial Infections Surveillance (NNIS) risk index, which is based on wound classification, duration of procedure and ASA score, as a composite measure of a patient’s risk for development of SSI.19 However, given that some previous studies have questioned the appropriateness of the NNIS as a composite measure in certain surgical subspecialties,20 21 we will also conduct a sensitivity analysis using wound classification, duration of procedure, and ASA score as single, independent variables.

We will employ multivariable cox regression models to assess the influence of clinicodemographic variables on various outcomes for each surgical subspecialty. Predefined clinically plausible variables which occurred prior to the outcome events will be inputted into these models to adjust the main explanatory variables. Relative risk along with their 95% CIs will be presented. All statistical analyses will be two-sided, and p value<0.05 will be considered the threshold for statistical significance.

For assessing the incidence of antibiotic-resistant SSI, we will not be standardising laboratory assessment, techniques or definitions used, since it is impractical over many centres. Thus, this will be an exploratory analysis only, with full appreciation of the limitations in this measure.

Finally, additional sensitivity analysis will be performed to ascertain the robustness and credibility of our results. This will be performed using the following approaches:22

• Outliers: outliers will be reported, and regression analysis will be performed with and without outliers.

• Missing data: missing data will be reported, and regression analysis will be performed excluding and including (using simple imputation) cases with missing data.

• Subgroup analysis: regression analysis will be in subgroups created according to province, level of medical services (secondary vs tertiary medical centre), teaching status, hospital volume and mode of 30 day outcome assessment (outpatient assessment or telephonic follow-up).