Home | About Us | Current Issue | Ahead of print | Archives | Search | Instructions | Subscription | Feedback | Editorial Board | e-Alerts | Login 
Journal of Indian Association of Pediatric Surgeons
     Journal of Indian Association of Pediatric Surgeons
Official journal of the Indian Association of Pediatric Surgeons         
 Users Online:1668 
  Print this page Email this page   Small font sizeDefault font sizeIncrease font size

Table of Contents   
Year : 2017  |  Volume : 22  |  Issue : 4  |  Page : 211-216

“Neo-PIRO”: Introducing a novel grading system for surgical infections of neonates

1 Department of Paediatric Surgery, Princess Esra Hospital, Deccan College of Medical Sciences, Hyderabad, Telangana, India
2 Department of Anaesthesia, Princess Esra Hospital, Deccan College of Medical Sciences, Hyderabad, Telangana, India

Date of Web Publication12-Sep-2017

Correspondence Address:
G Raghavendra Prasad
Professor of Paediatric Surgery, Princess Esra Hospital, Deccan College of Medical Sciences, Hyderabad
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0971-9261.214455

Rights and Permissions



Introduction: Quantification of surgical sepsis was never done beyond superficial, subfascial, and deep surgical site infection (SSI). Invasive surgical sepsis with systemic manifestation has not been tried to be quantified in general and pediatric surgery in particular. Hence, this attempts to develop a novel grading system to quantify neonatal surgical infections.
Materials and Methods: Predisposing factors, infection, response, and organ failure (PIRO) is being used in critical care institutions for medical sepsis; it was modified with neonate-specific surgical parameters. Authors have developed a grading of these parameters into Grade I, II, and III.
Results: A blinded statistical test was performed and results were put to test. Extended Mantel–Haenszel Chi-square test validated linear relationship with grade and outcome, hospital stay, deep SSI, and organ dysfunction. Analysis of variance also showed the significant relationship of changing trends in grade and outcome. (1) Higher the grade indicated the probability of death. (2) Grade I patients had less duration of hospital stay compared to Grade II and III (P = 0.04). (3) The requirement of organ support and SSI were also more in Grade III. (4) Grade I patients had less increase in trends compared to Grade II and III (F = 4.86). Authors therefore feel Neo-PIRO seems to be the first scoring system that shows a linear relationship between scores and grade.
Conclusion: Neo-PIRO is a novel grading system with surgical neonate-specific parameters. Future versions to include molecular parameters, as well as parameters selected by regression analysis.

Keywords: Neonatal surgical infections, neonate-specific surgical infection scoring system, “neo-predisposing factors, infection, response, and organ failure”

How to cite this article:
Prasad G R, Subba Rao J V, Aziz A, Rashmi T M. “Neo-PIRO”: Introducing a novel grading system for surgical infections of neonates. J Indian Assoc Pediatr Surg 2017;22:211-6

How to cite this URL:
Prasad G R, Subba Rao J V, Aziz A, Rashmi T M. “Neo-PIRO”: Introducing a novel grading system for surgical infections of neonates. J Indian Assoc Pediatr Surg [serial online] 2017 [cited 2022 Sep 26];22:211-6. Available from: https://www.jiaps.com/text.asp?2017/22/4/211/214455

   Introduction Top

Stratification and prognostication of neonatal sepsis remain unsolved. Many severity scoring systems were developed, modified, and remodified but without universal approval and acceptance. The scoring systems in vogue may be grouped as (a) anatomical scoring systems: Injury severity score, abbreviated injury scale.(b) Physiological scoring systems: Acute Physiology and Chronic Health Evaluation score (APACHE),[1] Simplified acute physiology score (SAPS).[2] (c) Therapeutic intervention scoring system (TISS).[3] (d) Organ-based scoring systems: Multiorgan dysfunction syndrome,[4] Sequential organ failure assessment score (SOFA),[5] and risk injury failure loss end-stage kidney disease (RIFLE).[6] (e) Disease-based scoring system: Ranson's criteria-pancreatitis,[7] Child-Pugh for liver,[8] and RIFLE for kidney.[6]

Most of these scoring systems were first developed for adult critical care units and later tried in children. Exclusive scoring systems for neonates and children include pediatric risk of mortality score (PRISM),[9] Clinical Risk Index for Babies score (CRIB),[10] Score for Neonatal Acute Physiology (SNAP), and SNAP Perinatal Extension (SNAPPE).[11] These scoring systems are not widely accepted and applied despite partially successful multi-institutional trials.[12] A consensus for an acceptable scoring system for neonatal surgical infections could not be achieved. The main disadvantage of these scoring systems was uncertainty and inability to validate.[13],[14]

Waterston scoring system [15] was age-, weight-, and comorbidity-based scoring system for prognostication of tracheoesophageal fistula and esophageal atresia. The disadvantage of these scoring systems is nonlinearity, which means the absence of linear correlation between scores and mortality rate.[16],[17],[18] There are no grading/scoring systems available for surgical infections in neonates. This prompted the author to modify predisposing factors, infection, response, and organ failure (PIRO).[19],[20] An existing system of grading that is used in adult critical care units for sepsis. PIRO is an acronym for PIRO. The author would like to call it Neo-PIRO applicable for surgical infections in neonates.

   Materials and Methods Top


The present work was based on a pilot study conducted between 2009 and 2011 on 58 surgical neonates and children. The pilot study helped to choose parameters for Neo-PIRO, the currently proposed grading system of surgical infection in neonates. The present study was a prospective observation cohort conducted from 2013 to March 2015. Forty-seven neonates with infections formed the core of the study. The following neonatal surgical infections were included:

  1. Clinically and otherwise established peritonitis
  2. Empyema thoracis (diagnosed clinically, pleural tap, and/or International Classification of Diseases or culture and sensitivity)
  3. Cellulitis and gangrene of soft tissue and culture and sensitivity
  4. Septic arthritis and osteomyelitis based on clinical, ultrasonography, and radiographical studies
  5. Invasive urinary tract infection (UTI) (defined as culture positive urine) with dilated upper tracts both obstructive, reflexive and combined
  6. Infected ventriculoperitoneal shunts with seizures, fever, and symptoms of ventriculitis.

The following conditions were excluded:

  1. Primary pneumonia
  2. Meningitis
  3. Lower UTI including pyuria on clean intermittent catheterization - (neurogenic bladder)
  4. Medically treated liver abscess (not referred to pediatric surgeon)
  5. Infant and older children with surgical infections (they formed a part of larger study under preparation)
  6. Surgical site infection (SSI) (it was taken as end point)
  7. Intensive Care Unit (ICU)-acquired infections.

The pro forma was prepared with parameters chosen for predisposition and infection, ten parameters each, twenty parameters for response, and six parameters for organ dysfunction picked up from the pilot study the following parameters were chosen.

The parameters of predisposition:

  1. Preterm baby
  2. Syndromic baby
  3. Small for gestational age/preemie/micro-preemie
  4. Premature rupture of membranes
  5. Maternal fever
  6. Bad obstetric history
  7. Inborn (0) (all inborn babies were considered clean)
  8. Outborn baby (1) (all outborn babies were considered infected)
  9. Preadmission treatment (medical)
  10. Preadmission intervention (surgical)
  11. Sick baby (defined as baby who is lethargic, pale, cutis murmurata, poor reflexes, and poor suckig reflux with a background of surgery).

Parameters for infection:

  1. Peritonitis (clinical, operative, contrast-enhanced computed tomography and culture)
  2. Empyema thoracis (clinical, chest X-ray [CXR], pleural fluid analysis and culture)
  3. Cellulitis (clinical and discharge culture)
  4. Culture positive deep SSI
  5. Osteomyelitis (clinical, radiological and needle aspiration – positive culture)
  6. UTI (urine culture with dilated upper tracts and a source like posterior urethral valves, vesicoureteral reflux, ureterocele, pelviureteric junction obstruction, and other anatomical lesions)
  7. Positive blood culture
  8. Positive pus culture
  9. Positive urine or bile culture
  10. Positive cerebrospinal fluid culture.

Parameters of response:

  1. Tachycardia (heart rate >180/min)
  2. Hypothermia (temperature below 36.5°C)
  3. Fever (temperature above 38.2°C)
  4. Tachypnea (respiratory rate >60/min)
  5. Convulsions
  6. Oliguria (<0.3/kg/h)
  7. Hypotension (mean arterial pressure [MAP] <10th percentile or <30 mmHg in first 3 days of life)
  8. Abdominal distension and intra-abdominal hypertension (>12 cm of water)
  9. Increased thin-layer chromatography (TLC) >18,500/cumm
  10. Decreased TLC < 3500/cumm
  11. Increased C-reactive protein >6 mg/L
  12. Decreased platelets <80,000/cumm
  13. Increased bilirubin >1 mg%
  14. Poor neonatal reflexes
  15. Need for vasopressors
  16. Need for support ventilation and increased oxygen supply
  17. Need for advanced ventilation and increased FiO2 on ventilator
  18. Metabolic acidosis (arterial blood gasses – pH < 7.2)
  19. Peripheral blood film with toxic granules in neutrophils and band cells >10%
  20. Increased procalcitonin (>2–3 ng/mL).

The parameters for organ dysfunction were similar to SOFA, but it was simplified as organ dysfunction present or absent. Authors called it as simplified SOFA (SSOFA). The organs with parameters included were:

  1. Lung – FiO2 need, pulmonary artery wedge pressure, CXR changes, acute respiratory distress syndrome, increased need for positive end expiratory pressure/peak inspiratory pressure
  2. Kidney – RIFLE
  3. Heart – MAP, need for vasopressors and Congestive Heart Failure (CHF)
  4. Central nervous system – Glasgow Coma Scale
  5. Liver – Child-Pugh score, prothrombin time, activated partial thromboplastin time
  6. Hematological – TLC, differential leukocytes count, platelet count, Hb.

Point system for scoring adopted in the study. Each parameter was assigned 1 point. Ten points for predisposition, ten for infection, twenty for response, and six for organ dysfunction making a total score of 46.

Authors adopted the grading system <2 points each for predisposition and infection, 4 points for response, and 3 points for organ dysfunction were considered as Grade I. Thus, Neo-PIRO was divided into three grades as follows:

  • Grade I – up to 11
  • Grade II – 12–26
  • Grade III – 27–46.

The end points selected for Neo-PIRO were as follows:

  1. Outcome
  2. Duration of hospital stay
  3. Severe SSI requiring secondary suturing
  4. Organ support
  5. Trends of Neo-PIRO were also studied at admission, at 24 h and 3 days later.

  • [Table 1] shows six preterm, 35 term babies, and six small for gestational age
  • [Table 2] shows eight with Grade I, 24 Grade II, and fifteen had Grade III
  • [Table 3] shows 33.4% with Grade III died
  • [Table 4] shows 66.7% with Grade III had more than 10 days of hospital stay
  • [Table 5] shows 33.3% with Grade III had SSI whereas only 12.5% of Grade I
  • [Table 6] shows 40% with Grade III required organ support compared to only 12.5% of Grade I
  • [Table 7] shows only 12.5% with Grade I had increase in trends compared to Grade III in which 66.7% had increasing trends
  • [Table 8] shows the trends of being alive or dead.
Table 1: Age incidence

Click here to view
Table 2: Distribution of grade

Click here to view
Table 3: Grade versus outcome

Click here to view
Table 4: Grade versus duration of stay

Click here to view
Table 5: Surgical site infection versus grade

Click here to view
Table 6: Grade versus organ support

Click here to view
Table 7: Changing trends of grades

Click here to view
Table 8: Trends of being alive or death

Click here to view

Statistical method

The statistical method used for analysis was (a) Extended Mantel–Haenszel Chi-square for linear trend, (b) Chi-square, and (c) analysis of variance (ANOVA) for predictability.

Internal Review Ethics Committee approved the project. The consent was taken at the time of admission. There were no conflicts of interest.

   Results Top

Grade and outcome [Table 3] were evaluated using the Extended Mantel–Haenszel Chi-square for linear trend, and its value was 25.01 and P < 0.05. As the grades increased the possibility of being alive decreased significantly and also as the grades increased the possibility of the being dead increased significantly.

Grade and duration of hospital stay [Table 4] correlated using Chi-square and value was 6.34 and P < 0.05. Duration of hospital stay is significantly associated with grades. Grade I patients have significantly less duration of hospital stay compared to Grade II and Grade III.

SSI [Table 5] was correlated with Grade, Extended Mantel–Haenszel Chi-square for linear trend value 12.45. As the grades increased in severity, the possibility of being infected increased from 12.5% in Grade I patients to 33.3% in Grade III patients. This is statistically significant with P < 0.05.

Grade and organ support [Table 6] were correlated using Extended Mantel–Haenszel Chi-square for linear trend. Its value was 20.47. A clear trend is seen in terms of increasing severity and the requirement of organ support from 12.5% in grade 1%–40% of patients requiring organ support in Grade III. P <0.05 and hence statistically significant.

Changing trends of Grades [Table 7] were also compared using Chi-square. Grade I patients had significantly less increase in trends compared to Grade II and III. The Chi-square value was 10.62 and P < 0.05.

Trends of being alive or dead [Table 8] were analyzed by applying the ANOVA test. The “F” value is 4.864, and the P value was 0.02. This means that patients in Grade I have more decreasing trend of being dead compared to other grades. At the same time, they are also less susceptible to increasing trend of being dead. Grade I patients also show a less number of patients when decreasing trend alive is considered compared to Grade II. All this is statistically significant.

Comparing grade and outcome most of patients with Grade II and Grade III, 5 out of 24 and 5 out of 15, respectively, died. Ten out of fifteen with Grade III had more than 10 days of hospital stay, while 7 out of 24 with Grade II and two out of eight with Grade I had a hospital stay of more than 10 days. SSI when correlated with grade showed one-third of Grade III had deep SSI. Development of new organ failure and need for organ support were correlated with grade at admission. Six out of fifteen with Grade III and 4 out of 24 with Grade II required organ support. Change in the trends of grade showed only one out of eight with Grade I increased the grade over 2–3 days, 10 out of 15 with Grade III had an increased trend. When changing trends were compared six out of eight with Grade I with decreasing trend were alive while six out of nine with Grade III and increasing trend died.

   Discussion Top

Surgical infections in general were treated empirically based on clinical appearance and some hematological data. Quantification and severity grading were not conventionally used. This led to a lack of evidence-based approach to surgical infection in general, neonatal surgical infections in particular. Infections in neonatal ICUs continue to be an impacting confounding factor for morbidity and mortality. PRISM, CRIB, SNAP, and SNAPPE are some of the neonatal scoring systems that have been used in some institutions.

Manchanda et al.[21] had tried to develop a neonatal scoring system. Adult modules like APACHE [1] and organ scoring systems like SOFA [5] although found to be useful could not quantify sepsis. PRISM III was developed in 1996 and tried in a very large number of patients in 32 ICUs all over North America.[22] Gulla and Sachdev also attempted to review illness severity and organ dysfunction in pediatric ICU.[23]

They concluded PRISM may not be applicable to India maintaining reason of source limitation, different patient characters, and inadequate training of staff. An attempt was made to quantify sepsis in by way of PIRO.[19],[20] Adult PIRO was projected as a staging model like TNM for tumors.

Lack of scoring systems for neonatal surgical infections was the basis to develop “Neo-PIRO” specific to neonatal surgical infections. The difference between adult PIRO and the modified parameters in Neo-PIRO [Table 9] clearly shows that parameter chosen for Neo-PIRO was neonate specific. The author consolidated the parameter for PIRO based on a pilot study done in the same institution. PIRO was graded for community-acquired pneumonia for adult's surgical infections. Author has tried to develop a scoring system and grading system adaptable to surgical neonates. Due to nonavailability, Neo-PIRO was compared with APACHE II and SOFA scoring system. SNAPPE2, PRISM, and TISS all have tried to predict outcome in neonatal ICUs. Extrapolation to Neo-PIRO could not be performed due to change in parameters selected. Neo-PIRO can be compared by a combination of various scoring system together, and the statistical variety indirectly confirms that the Neo-PIRO grading system validates a linear relationship to prognosis. Outcome, organ dysfunction, hospital stay, SSI linearly correlated with the scoring and grading system. An upward trend also predicted the poor outcome or prolonged hospital stay. The authors concluded that Neo-PIRO as a novel grading system to stratify neonatal surgical infections.
Table 9: Differences between predisposing factors infection response and organ failure and Neo-predisposing factors, infection, response, and organ failure

Click here to view


Authors conceded that the sample size was too small and needs to be studied in larger numbers and tried at more number of institutions. Not calculating the power of the study was yet another limitation. Authors also conceded that the predisposing factors particularly genetic background like tumor necrosis factor polymorphism would add more impact to predisposition. Others parameters need to be verified by regressive analysis to develop more robust statistically strong grading system.

   Conclusion Top

Neo-PIRO is a novel grading system with surgical neonate-specific parameters. Neo-PIRO statistically validated linear predictability with Neo-PIRO grading system. Future versions will have molecular parameters and others selected by regression analysis.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

   References Top

Waters M, Nightingale P, Edwards JD. A critical study of the APACHE II scoring system using earlier data collection. Arch Emerg Med 1990;7:16-20.  Back to cited text no. 1
Haq A, Patil S, Parcells AL, Chamberlain RS. The simplified acute physiology score III is superior to the simplified acute physiology score II and acute physiology and chronic health evaluation II in predicting surgical and ICU mortality in the “oldest old”. Curr Gerontol Geriatr Res 2014;2014:934852.  Back to cited text no. 2
Gray JE, Richardson DK, McCormick MC, Workman-Daniels K, Goldmann DA. Neonatal therapeutic intervention scoring system: A therapy-based severity-of-illness index. Pediatrics 1992;90:561-7.  Back to cited text no. 3
Marshall JC, Cook DJ, Christou NV, Bernard GR, Sprung CL, Sibbald WJ. Multiple organ dysfunction score: A reliable descriptor of a complex clinical outcome. Crit Care Med 1995;23:1638-52.  Back to cited text no. 4
Jones AE, Trzeciak S, Kline JA. The sequential organ failure assessment score for predicting outcome in patients with severe sepsis and evidence of hypoperfusion at the time of emergency department presentation. Crit Care Med 2009;37:1649-54.  Back to cited text no. 5
Lopes JA, Jorge S. The RIFLE and AKIN classifications for acute kidney injury: A critical and comprehensive review. Clin Kidney J 2012;6:8-14.  Back to cited text no. 6
Banks PA, Freeman ML; Practice Parameters Committee of the American College of Gastroenterology. Practice guidelines in acute pancreatitis. Am J Gastroenterol 2006;101:2379-400.  Back to cited text no. 7
Angermayr B, Cejna M, Karnel F, Gschwantler M, Koenig F, Pidlich J, et al. Child-Pugh versus MELD score in predicting survival in patients undergoing transjugular intrahepatic portosystemic shunt. Gut 2003;52:879-85.  Back to cited text no. 8
Pollack MM, Ruttimann UE, Getson PR. Pediatric risk of mortality (PRISM) score. Crit Care Med 1988;16:1110-6.  Back to cited text no. 9
Cockburn F, Cooke RW, Gamsu HR, Greenough A, Hopkins A, McIntosh N. The CRIB (Clinical Risk Index for Babies) score: A tool for assessing initial neonatal risk and comparing performance of neonatal intensive-care units. Lancet 1993;342:193-8.  Back to cited text no. 10
Mesquita Ramirez MN, Godoy LE, Alvarez Barrientos E. SNAP II and SNAPPE II as predictors of neonatal mortality in a pediatric intensive care unit: Does postnatal age play a role? Int J Pediatr 2014;2014:298198.  Back to cited text no. 11
Field D, Manktelow B, Draper ES. Bench marking and performance management in neonatal care: Easier said than done! Arch Dis Child Fetal Neonatal Ed 2002;87:F163-4.  Back to cited text no. 12
Ridley SA. Uncertainty and scoring systems. Anaesthesia 2002;57:761-7.  Back to cited text no. 13
Altman DG, Royston P. What do we mean by validating a prognostic model? Stat Med 2000;19:453-73.  Back to cited text no. 14
Teich S, Barton DP, Ginn-Pease ME, King DR. Prognostic classification for esophageal atresia and tracheoesophageal fistula: Waterston versus Montreal. J Pediatr Surg 1997;32:1075-9.  Back to cited text no. 15
Pollack MM, Koch MA, Bartel DA, Rapoport I, Dhanireddy R, El-Mohandes AA, et al. A comparison of neonatal mortality risk prediction models in very low birth weight infants. Pediatrics 2000;105:1051-7.  Back to cited text no. 16
Hariharan S, Zbar A. Risk scoring in perioperative and surgical intensive care patients: A review. Curr Surg 2006;63:226-36.  Back to cited text no. 17
Dorling JS, Field DJ, Manktelow B. Neonatal disease severity scoring systems. Arch Dis Child Fetal Neonatal Ed 2005;90:F11-6.  Back to cited text no. 18
Granja C, Póvoa P, Lobo C, Teixeira-Pinto A, Carneiro A, Costa-Pereira A. The predisposition, infection, response and organ failure (Piro) sepsis classification system: Results of hospital mortality using a novel concept and methodological approach. PLoS One 2013;8:e53885.  Back to cited text no. 19
Howell MD, Talmor D, Schuetz P, Hunziker S, Jones AE, Shapiro NI. Proof of principle: The predisposition, infection, response, organ failure sepsis staging system. Crit Care Med 2011;39:322-7.  Back to cited text no. 20
Manchanda V, Sarin YK, Ramji S. Prognostic factors determining mortality in surgical neonates. J Neonatal Surg 2012;1:3.  Back to cited text no. 21
Pollack MM, Patel KM, Ruttimann UE. PRISM III: An updated pediatric risk of mortality score. Crit Care Med 1996;24:743-52.  Back to cited text no. 22
Gulla KM, Sachdev A. Illness severity and organ dysfunction scoring in pediatric intensive care unit. Indian J Crit Care Med 2016;20:27-35.  Back to cited text no. 23
[PUBMED]  [Full text]  


  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9]


Print this article  Email this article


    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Article in PDF (461 KB)
    Citation Manager
    Access Statistics
    Reader Comments
    Email Alert *
    Add to My List *
* Registration required (free)  

    Materials and Me...
    Article Tables

 Article Access Statistics
    PDF Downloaded116    
    Comments [Add]    

Recommend this journal

Contact us | Sitemap | Advertise | What's New | Copyright and Disclaimer | Privacy Notice

  2005 - Journal of Indian Association of Pediatric Surgeons | Published by Wolters Kluwer - Medknow 

Online since 1st May '05